MASARYK UNIVERSITY
FACULTY OF SCIENCE
Research Centre for Toxic Compounds in the Environment (RECETOX)
Developmental neurotoxicants
Analytical determination and their occurrence in human matrices
Dissertation thesis in Environmental Chemistry
E l i š k a Č e c h o v á
Brno, 2017
BIBLIOGRAPHIC IDENTIFICATION
Author: Eliška Cechová
Title of Dissertation: Developmental neurotoxicants: Analytical determination and
their occurrence in human matrices
Degree Program: Chemistry
Field of Study: Environmental Chemistry
Supervisor: Ing. Anton Kočan, CSc.
Academic Year: 2017
Number of Pages: 174
Keywords:
Developmental neurotoxicants; exposure; flame retardants; multi-class analysis;
pesticides; risk assessment
BIBLIOGRAFICKÝ ZÁZNAM
Autor: Eliška Cechová
Název práce: Látky s vývojovou neurotoxicitou: Analytické stanovení a jejich
výskyt v lidských matricích
Studijní program: Chemie
Studijní obor: Chemie životního prostředí
Školitel: Ing. Anton Kočan, CSc.
Akademický rok: 2017
Počet stran: 174
Klíčová slova:
Expozice; hodnocení rizik; látky s vývojovou neurotoxicitou;multireziduální analýza;
pesticidy; zpomalovače hoření
© ELIŠKA ČECHOVÁ, M A S A R Y K UNIVERSITY, 2017
Acknowledgements
I would like to acknowledge Dr. Anton Kočan for the possibility to work on DENAMIC
project and for the valuable advice in the lab provided to me during my PhD studies.
Many thanks belong also to Prof. Dr. Martin Scheringer for a big help with the papers
and his support and patience during the writing. I thank to DENAMIC colleagues (Pirn
Leonards and others) for the nice and friendly atmosphere during the project meetings
and interesting collaboration possibilities.
Big thanks belong to my colleagues from the Trace Analytical Laboratories of
RECETOX, Petra Přibylová, Iva Poláková, Eva Hloušková, Eva Krejčí, Lýdie
Tupová, Jakub Martiník, Veronika Vidová, Marcela Kadlecová, Martina Partyková
and Martina Krátká (Vykoukalová). It was fun to work with you in the lab. I also thank
all the other friends from R E C E T O X who supported me, Eva Holt, Petra Booij, Jiň
Kohoutek, Jan Kuta, Jitka Bečanová, Simon Vojta, Pavlína Karáskova, Mária
Chropeňová, Zuzana Bílková and others. You all created a very friendly atmosphere at
work. Special thanks to Petr Kukučka and Garry Codling for their comments on the
thesis.
Next, I would like to acknowledge my good friend and the closest
collaborator Marta Seifertova for her help in the lab, hours of discussions about
anything possible and impossible and a memorable time spent together at the
conferences and research stays.
Finally, finishing this thesis would not be possible without the patient support
from my family during the whole period of my studies.
ii
Abstract
The growing number of children suffering from neurodevelopmental disorders has led
to intensified research into effects of neurotoxic compounds on children's health. As
many of these compounds are transferred from mother to child during the early
development, mother milk was selected as a non-invasive matrix to assess the exposure
of both mothers and children. Since humans are exposed to the mixtures of chemicals,
the development of multi-class analytical methods is desirable.
The main aim of this thesis was to develop and validate a multi-class method for the
determination of approximately 100 developmental neurotoxicants (DNTs) in human
milk. These compounds included persistent organochlorine pesticides (OCPs),
polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), current
use pyrethroids and alternative flame retardants (AFRs) and their selected metabolites.
Complex matrix of human milk containing lipids with the similar properties to DNTs
required careful selection of the sample preparation techniques. This was realized using
a clean-up process of dialysis which was used for the first time at low temperature and
it was applied to the analysis of such a complex mixture of compounds. This method
also enabled us to detect current-use compounds in trace concentrations which provided
novel data on contamination of human matrices in Europe.
The method was subsequently used for the analysis of more than 500 human milk
samples from three European countries: Norway, the Netherlands and Slovakia.
Comparison of the concentrations and human risk assessment was performed with the
main DNT groups. Legacy compounds such as selected OCPs or PCBs have been
shown to be present in human milk at the greatest concentrations in nearly all milk
samples even though they were banned more than 30 years ago. The concentrations of
persistent compounds were shown to decline over time, but selected OCPs or PCBs can
still pose health risks, especially in Slovakia with high former production of PCBs.
PBDE concentrations were the greatest in Norway, but this could be related also to the
earlier sample collection.
Data on many AFRs were presented here for the first time giving new insights into
occurrence of these compounds in human matrices in Europe. Bis(2-ethylhexyl)
tetrabromophthalate (BEH-TEBP) used as a replacement of Penta-BDE was present in
milk samples at the greatest concentrations of all analyzed AFRs, which were similar to
or exceeding the concentrations of B D E 47 as the congener with the greatest
concentration among PBDEs. The most often detected AFRs were bromobenzenes with
the detection frequency over 50%, but their concentrations were approximately an order
of magnitude lower compared to BEH-TEBP. The infants' exposure to PBDEs and
AFRs was also calculated assuming three main pathways - breastfeeding, dust ingestion
in
and air inhalation. It was shown that intake via breastfeeding was the dominant source
for both PBDEs and AFRs, but for B D E 99 and 2-ethylhexyl-2,3,4,5-tetrabromobenzoate
(EH-TBB) the contribution from dust ingestion reached up to 30%.
The results from this study using the multi-class analytical method have provided
exposure information on a broad range of DNTs for an epidemiological evaluation. The
preliminary results showed gender-specific associations between early life exposure to
organochlorine compounds and behavioural development at the age of 18 months.
IV
Abstrakt
Vzhledem ke stále se zvyšujícímu počtu dětí s neurovývojovými poruchami roste zájem
o studium vlivu efektů neurotoxických sloučenin na zdraví dětí. Tyto látky jsou během
raného vývoje přenášeny z matky na dítě, proto bylo vybráno ke studiu mateřské mléko
jako neinvazivně odebíraná matrice. Protože jsme exponováni směsmi chemických
látek, je žádoucí vývoj multireziduálních metod.
Hlavním cílem práce bylo vyvinout a validovat metodu pro současné stanovení
přibližně 100 látek s vývojovou neurotoxicitou v mateřském mléce: persistentních
organochlorových pesticidů (OCPs), polychlorovaných bifenylů (PCBs),
polybromovaných difenyletherů (PBDEs), pyrethroidů, alternativních zpomalovačů
hoření (AFRs) a vybraných metabolitů. Vzhledem ke komplexitě matrice mateřského
mléka obsahující lipidy s podobnými vlastnostmi jako cílové látky je potřeba pečlivý
výběr metodiky přípravy vzorku. K tomuto účelu byla použita nekonvenční metoda
čištění, dialýza, která byla poprvé použita při nízkých teplotách a byla aplikována na
takto komplexní směs látek. Dialýza nám umožnila detekci i nepersistentních látek
přítomných v mateřském mléce ve stopových koncentracích.
Vyvinutá metoda byla následně použita pro analýzu více než 500 vzorků mateřského
mléka ze tří evropských zemí, Norska, Nizozemí a Slovenska. V rámci zemí byly
srovnány koncentrace hlavních skupin látek s vývojovou neurotoxicitou a byla
provedena analýza rizik pro tyto skupiny. OCPs and PCBs byly v mateřském mléce
přítomny v nejvyšších koncentracích navzdory tomu, že byly zakázány před více než
30 lety. Koncentrace persistentních látek v lidských matricích sice vykazují klesající
trend, ale i současně přítomné hladiny PCBs a vybraných OCPs mohou stále
způsobovat zdravotní rizika, zejména na Slovensku, kde se v minulosti PCBs
produkovaly. Koncentrace PBDEs byly nejvyšší v Norsku, což ale může být způsobeno
tím, že vzorky byly sbírány dříve v porovnání se vzorky ze Slovenska či Nizozemí.
Koncentrace mnoha AFRs v mateřském mléce představovala první data těchto
sloučenin detekovaných v lidských matricích vůbec. Bis(2-ethylhexyl)tetrabromoftalát
(BEH-TEBP), který se nyní používá jako náhrada za Penta-BDE, byl přítomen
v nejvyšších koncentracích ze všech analyzovaných AFRs a jeho hladiny byly
srovnatelné s hladinami PBDEs. Nej častější detekovanou skupinou AFRs byly
bromobenzeny, které se nacházely ve více než 50% všech vzorků, ale jejich
koncentrace byly přibližně o řád nižší než BEH-TEBP. Byla rovněž vypočítána
expozice kojenců zpomalovací hoření, kdy byly uvažovány tři hlavní expoziční cesty kojením,
požitím prachu a inhalací vzduchu. Jako hlavní příspěvek bylo zjištěno kojení.
v
Avšak pro B D E 99 a 2-ethylhexyl-2,3,4,5-tetrabromobenzoát (EH-TBB) byl příspěvek
z požití prachu až 30%.
Výsledky z této studie používající multireziduální metodu poskytly informace
o expozici širokou škálou látek s vývojovou neurotoxicitou pro epidemiologická
vyhodnocení. Předběžné výsledky ukazují, že existují pohlavně specifické asociace
mezi ranou expozicí organochlořovými pesticidy a chováním ve věku 18 měsíců dítěte.
VI
List of papers
This thesis is based on the following papers (further referred as papers I-IV)
Paper I
Cechová, E., Seifertova, M . , Kukučka, P., Vojta, S., Quaak, I., de Cock, M . , van de
Bor, M , Kočan, A . (2016). A n effective clean-up technique for GC/EI-HRMS
determination of developmental neurotoxicants in human breast milk. Analytical and
Bioanalytical Chemistry, http://doi.org/! 0.1007/s00216-016-0059-y.
Paper II
Cechová, E., Scheringer, M . , Seifertova, M . , Mikeš, O., Kroupová, K , Kuta, J., Forns,
J., Eggesbo, M . , Quaak, I., de Cock, M . , van de Bor, M . , Patayová, H., PalkovičováMurínová,
L., Kočan, A . (2016). Developmental neurotoxicants in human milk:
Comparison of concentrations and intakes in three European countries. The Science of
the Total Environment, http://doi.org/10.10161 \. scitotenv.2016.11.046.
Paper III
Cechová, E., Vojta, S., Kukučka, P., Kočan, A . , Trnovec, T., Palkovičová Murínová,
E., de Cock, M . , van de Bor, M . , Askevold, J., Eggesbo, M . , Scheringer, M : Legacy and
alternative halogenated flame retardants in human milk in Europe: implications for
children's health. Submitted to Environment International (17t h
April 2017).
Paper IV
Quaak, I., de Cock; M . , Cechová, E., Kočan, A., van de Bor, M . , Leonards, P., van de
Bor, M . Early life exposure to organochlorine pesticides and behavioral development in
children. Submitted to The International Journal of Environmental Research and
Public Health (May 2017).
Other publications
Seifertova, M . , Cechová, E., Llansola, M . , Felipo, V . , Vykoukalová, M . , Kočan, A.
(2017). Determination of Selected Neurotoxic Insecticides in Small Amounts of Animal
Tissue Utilizing Newly Constructed Mini-extractor. Submitted to Analytical and
Bioanalytical Chemistry (25t h
March 2017).
Cechová, E., Simek, Z. Possibilities of the quantitative determination of estrgens in
surface and waste waters by HPLC-MS/MS (in Czech). Chemické listy, Prague: Czech
Chemical Society, 2012, vol. 106, p. S3-S6. ISSN 0009-2770.
vn
Cechová, E. Determination of estrogens in wastewaters (in Czech). Students for South
Moravian region. Lipka2012. ISBN 978-80-87604-34-2.
Selected conference contributions
Cechová, E., Godoy P., Maršálkova, E., Maršálek, B., Simek, Z. (2013): Determination
of estrogens in different types of wastewaters and their removal using nanoiron and
ferrates, IEuCheMS International Conference on Chemistry and the Environment ICCE,
Barcelona (ES)2013.
Cechová, E., Seifertova, M . , Kukučka, P., Kočan, A . (2014): A multi-analyte method
for the determination of compounds with (potential) developmental neurotoxicity in
human milk, 16th International Symposium on Advances in Extraction Technologies
ExTech, Cháma (GR) 2014.
Cechová, E., Seifertova, M . , Kukučka, P., Kočan, A . , Klánová, J. (2014):
Determination of PBDEs, organochlorine pesticides and pyrethroids including their
metabolites in limited amounts of biological samples, Dioxin, Madrid (ES) 2014.
Cechová, E., Seifertova, M . , Kuta, J., Kočan, A . (2015): New tools for analytical
determination of neurotoxic compounds in human and animal samples, Final workshop
of DENAMIC project, Amsterdam (NL) 2015.
vin
Abbreviations
ABS acrylonitrile butadiene styrene
ACN acetonitrile
ADHD attention-deficit hyperactivity disorder
AFRs alternative flame retardants
AhR aryl hydrocarbon receptor
ANSES French Agency for Food, Environmental and Occupational
Health & Safety
ASD autism spectrum disorders
ATE allyl-2,4,6-tribromophenyl ether
BEH-TEBP bis(2-ethylhexyl) tetrabromophthalate
BMI body mass index
BTBPE l,2-bis(2,4,6-tribromophenoxy)ethane
CBCL child behaviour checklist
DBDPE decabromodiphenyl ethane
DBE-DBCH 1,2-dibromo-4-( 1,2-dibromoethyl)-cyclohexane
DBHCTD hexachlorocyclopentenyl-dibromocyclooctane
D C M dichloromethane
DDC-CO Dechlorane Plus
DDC-COMA Dechlorane Plus mono adduct
DDE dichlorodiphenyldichloroethylene
DDT dichlorodiphenyltrichloroethane
DDX sum of p,p -DDT + o,p '-DDT + p,p '-DDE + o,p '-DDE + p,p 'DDD
+ o,p '-DDD
dl-FCBs dioxm-like PCBs (here PCB 118)
DNT developmental neurotoxicant
EFSA European Food Safety Authority
EH-TBB 2-ethylhexyl-2,3,4,5-tetrabromobenzoate
EI electron ionization
EPA Environmental Protection Agency
ESI electrospray ionization
EU European Union
FLF freezing-lipid filtration
FRs flame retardants
GC gas chromatography
GPC gel permeation chromatography
HAc acetic acid
HBB hexabromobenzene
HBCDD hexabromocyclododecane
HCB hexachlorobenzene
H C H hexachlorocyclohexane
HPV high production volume
11 RMS high resolution mass spectrometry
IX
iPCBs indicator polychlormated brphenyls (PCB 28, 52, 101, 138, 153
and 180)
IDs intellectual disabilities
IRIS Integrated Risk Information System
KOW octanol-water partition coefficient
LC liquid chromatography
LDPE low-density polyethylene
L L E liquid liquid extraction
LOQ limit of quantification
LPV low production volume
lw lipid weight
mAChR muscarinic acetylcholine receptors
MeHg methylmercury
MeOH methanol
ndl-VCBs Non-dioxin like polychlorinated biphenyls
OH-BDEs hydroxylated polybrominated diphenyl ethers
OCPs organochlorine pesticides
PBBA pentabromobenzyl acrylate
PBBz pentabromobenzene
PBDEs polybrominated diphenyl ethers
PBEB pentabromoethylbenzene
PBT pentabromotoluene
PCBs polychlorinated biphenyls
PCDDs polychlorinated dibenzodioxins
PeCB pentachlorobenzene
PK pharmacokinetic
PLE pressurized liquid extraction
PVC polyvinyl chloride
QuEChERS Quick Easy Cheap Effective Rugged Safe (clean-up
technique)
RfD reference dose
RSD relative standard deviation
SPE solid phase extraction
TBBPA tetrabromobisphenol A
TBCO 1,2,5,6-tetrabromocyclooctane
TBCT tetrabromo-o-chlorotoluene
TBP-DBPE 2,3-dibromopropy 1-2,4,6-tribromopheny 1 ether
TBX 2,3,5,6-tetrabromo-/>xylene
TMSD trimethylsilyl diazomethane
LPV low production volume
UK United Kingdom
UPLC-MS/MS ultra performance liquid chromatography coupled to tandem mass
spectrometry
US United States
WHO World Health Organization
W W
X
whole weight
T A B L E O F C O N T E N T S
Introduction
1 Developmental neurotoxicants 4
1.1 OCPs 4
1.2 PCBs 5
1.3 Pyrethroids 6
1.4 PBDEs 7
1.5 OH-BDEs 8
1.6 AFRs 9
1.7 Methylmercury 11
Main objectives and outcomes of the thesis 13
Development of the multi-class method for the determination of DNTs in human
milk 15
2 Extraction 16
3 Clean-up procedures 18
3.1 First clean-up step 19
3.2 Second clean-up step 20
4 Instrumental methods 21
4.1 Pyrethroids+chlorpyrifos 21
4.2 OH-BDEs 22
4.2.1 LC-MS/MS 22
4.2.2 GC-HRMS 24
4.2.2.1 Derivatization with diazomethan 24
4.2.2.2 Derivatization with trimethylsilyldiazomethane 27
5 Method performance characteristics 29
6 Summary - method development 29
Exposure to DNTs in human breast milk from 3 countries 31
7 Characterisation of the samples 31
8 DNT concentrations 32
8.1 OCPs+PCBs 32
8.2 Pyrethroids+chlorpyrifos 34
8.3 PBDEs 36
8.4 OH-BDEs 37
8.5 AFRs 37
8.6 Methylmercury 39
XI
9 Human risk assessment 39
9.1 Estimation of mothers' body burden - OCPs, PCBs, MeHg 39
9.2 Estimation of the children's body burden - flame retardants 41
Epidemiological investigations 43
Conclusions and future perspectives 44
Appendices 45
Appendix 1: Previously used methods for the extraction of non-polar contaminants
from human milk 45
Appendix 2: Standard Operating Procedures (SOPs) for the determination of the
developmental neurotoxicants in human milk (in Czech) 46
Appendix 3: Concentrations of measured DNTs in human milk 54
References 63
Cumulative thesis 77
Paper I 77
Paper II 101
Paper III 117
Curriculum Vitae 155
xn
Introduction
Worldwide, every sixth child suffers from some form of developmental disorder,
such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder
(ADHD), anxiety or learning problems [ 1 ]. It was reported that in the US autism affects
nearly 1.1% of the individuals [2] and approximately 1.6% in the U K [3]; A D H D
affects 14% of 4 million children born in the US each year [4] and learning disabilities
affect up to 10% of children attending public schools [5]. Although the assessment and
reporting of these disorders have improved over the last few years, scientific evidence
suggests that the incidence of these disorders is on the increase [6]. Approximately 3%
of these disorders have been found to be associated with the exposure to toxic
chemicals and physical agents (e.g., radiation) and another 25% arise out of the
interplay of genetic and environmental factors including physical, chemical and
biological agents [7]. Developmental neurotoxicants (DNT) may also cause silent
damage, which would manifest itself only at the individual age, and may contribute to
neurodegenerative diseases such as Parkinson's or Alzheimer's diseases [8],
In assessment of the toxic behaviour of compounds there has been a growing
understanding that "children are not little adults" and the action of developmental
neurotoxic compounds to children is significantly different from the adults. Children's
metabolic pathways, especially in foetal growth and in the first months after birth, are
immature and thus developmental processes are easily disrupted during the rapid growth
and development before and after birth. Exposure to neurotoxicants in utero or in early
childhood can have a greater effect than at later life stages, such as development of
cancer or neurodegenerative diseases [9]. Compared to adults, children have also
disproportionately greater exposures to environmental agents, since they drink more
water and eat more food adjusted to their body mass, therefore they are exposed to
greater concentrations of toxic compounds. Additionally, their hand-to-mouth behaviour
and movement close to the ground expose them more to a different mixture of
compounds than adults [ 10,11 ].
From newly produced chemicals only a small fraction are tested for
neurotoxicity and even a smaller part (-200) showed neurotoxicity for humans. Since
toxicity testing is time consuming and costly, there may be many compounds in
use today with unknown effects [12]. Moreover, we are exposed not only to
a single chemical, but to complex mixtures of compounds and the final toxic effect
of exposure is often different than the individual compound.
1
Introduction
Thus the additive or synergic/antagonistic effects should be taken into account. For
example, assessment of the presence of methylmercury (MeHg) and organochlorine
compounds in a mixture showed the induction of different effects to motor activity and
coordination in rats compared to the exposure to the single compounds [13].
With the increasing number of compounds with unknown toxicological properties
and the need to develop new screening methods and procedures for the developmental
toxicity of these chemicals and mixtures, the E U set up the 7t h
Framework Project. The
project was called D E N A M I C (DEvelopmental Neurotoxicity Assessment of Mixtures
In Children) and included many partner groups including RECETOX. Pre- and
postnatal exposure to developmental neurotoxicants across European countries were
evaluated and this information was subsequently used for the epidemiological
assessment of the influence of the DNT compounds to the children's health and
development. The brief overview of the main DENAMIC's tasks is summarized in
Fig. 1.
(Miniaturized)
analytical methods
D E N A M I C
(Multi-class)
anahtical methods
Hazard
cliaractcrization
(screening tools, liming)
cell, animal models
Exposure to DNTs
in Europe
Risk
assessment
Fig.l Simplified scheme about main DENAMIC's aims (RECETOX contributions
highlighted in red)
One of the R E C E T O X aims in the project was to develop multi-analyte methods for
the determination of organochlorine pesticides (OCPs), pyrethroids, polychlorinated
biphenyls (PCBs) and legacy (polybrominated diphenyl ethers, PBDEs) and alternative
flame retardants (AFRs), DNT metabolites and MeHg in human samples. As part of
DENAMIC, the Institute of Environmental Studies (IVM) at Free University in
Amsterdam, The Netherlands determined also perfluorinated compounds and other
current use pesticides, such as organophosphates, carbamates and neonicotinoids in
human samples [14]. The main human biofluid used in D E N A M I C was mother milk as
2
Introduction
it was available in all studied cohorts, which allowed comparison between countries.
Moreover, human milk is also recommended by W H O as a non-invasive and relatively
easily available matrix and for lipophilic organic pollutants which bind to milk lipids
the concentrations are representative for whole human body [15].
Another task was to develop the miniaturized analytical tools for the determination
of four selected neurotoxic pesticides (carbaryl, chlorpyrifos, endosulfan and
Cypermethrin) in rat tissues from in vivo experiments. The in-vivo experiments are not
the focus of this thesis, the study was conducted by another PhD student at RECETOX
(M. Seifertovä).
3
Developmental neurotoxicants
1 Developmental neurotoxicants
This thesis is focused on the compounds that are proven or suspected developmental
neurotoxicants. The main psysico-chemical properties and use of the DNTs which were
determined in human milk in European countries at R E C E T O X is provided in
following chapters. Many of the compounds of interest in this study are included in the
Stockholm Convention on Persistent Organic Pollutants, so their use is now banned or
severely restricted [16]. Other compounds are used as the replacement products and are
still in current use within the EU.
1.1 OCPs
Organochlorine pesticides are a diverse range of multipurpose chlorinated hydrocarbon
chemicals. Examples include dichlorodiphenyltrichloroethane (DDT), endosulfan and
drin pesticides (Fig. 2). OCPs have drawn attention because of their persistence in the
environment, accumulation in adipose tissue of animals and humans and slow
elimination from the body. They have deleterious effects on both the environment and
humans; they can disrupt normal endocrine functions at environmentally relevant
exposure concentrations [17]. This lead to their bans or restrictions in 1970s or 1980s
and inclusion of persistent OCPs to the Stockholm Convention on Persistent Organic
Pollutants [16]. Despite this ban, they still occur in human bodies at great
concentrations compared to other environmental pollutants such as PBDEs or currentused
compounds [18,19],
(a) DDT (b) endosulfan (c) dieldrin
Fig. 2 Structures of the selected legacy pesticides with the developmental neurotoxicity
Using the animal models, the developmental neurotoxicity of DDT and its
metabolites or H C B suggested that early-life exposures are related to decrease in
4
Developmental neurotoxicants
cognitive or behavioural functions in later life. In human studies, there is still
uncertainty in the long-term neurodevelopmental risks associated with low-level earlylife
exposures to DDT/DDE and HCB [20].
For their unique physicochemical properties (structural formula in Fig. 3), such as
general inertness or thermal stability, PCBs were used predominantly in closed
applications, such as dielectric fluids in electrical equipment (transformers, capacitors,
heat transfer and hydraulic systems [21]).
Fig. 3 Generalized molecular formula of PCBs
They were also used in open applications, such as pesticide extenders, sealant,
carbonless copy paper, industrial oils, paints, adhesives, plastics, flame retardants and
to control dust on roads [22]. But due to their persistence and adverse toxic potential
including developmental, reproductive, dermal toxicity, endocrine effects or
carcinogenicity, the use and marketing of PCBs in the European Community were
heavily restricted in 1985 [23]. In 2001 they were included in the Stockholm
Convention on the Persistent Organic Pollutants [24].
The main exposure route is similar to OCPs: food consumption, especially fatty
products, such as meat, dairy products, oils and fats. From among 209 potential
congeners, only a limited number of congeners were produced in technical mixtures and
a selection of these are usually determined in food and they represent the "core group"
- indicator PCBs which are 50% of ndl-VCBs, since they are most frequently found in
food and biological samples [25]. Two main groups of PCBs having different toxic
effects relate to the position of chlorine atom substitution. First group, dioxin-like PCBs
(t/Z-PCBs) comprises non-ortho or mono-ortho substituted compounds and the
molecules have the coplanar structure which makes them to act like polychlorinated
dibenzo-/>dioxins/furans (PCDDs/PCDFs), i.e. they are agonists of AhR in organisms.
1.2 PCBs
5
Developmental neurotoxicants
The other group are non-dioxin like PCBs (ndl-PCBs) which have chlorine atoms in
or//zo-positions and do not activate AhR receptor.
Two major incidences of developmental neurotoxicity of PCBs caused by
contaminated rice oil first identified their DNT effects. The first one in 1968, the Yusho
poisoning in Japan and the YuCheng incident in 1979 in Taiwan. Babies born to
exposed women suffered from lower body weight and height, greater activity, greater
incidence of behaviour problems, and lower IQ scores [42, 43]. Recently, increased
PCB concentrations were correlated to cognitive deficits in Dutch and German cohorts
[27,28].
1.3 Pyrethroids
Pyrethroids are an important group of current-use pesticides, which are derived from
the structure of natural chemical occurring in chrysanthemum flowers. They have been
used for more than 30 years and account for approximately one-fourth of the worldwide
insecticide market [29]. Apart from their use against insects in public and commercial
buildings, animal facilities, warehouses, agricultural fields and greenhouses, they are
also applied on livestock and constitute a common part of commercial insect sprays.
They are also used as structural termicides [30]. Recently, their use has increased due to
the less toxic effects to birds or mammals compared to organophosphate pesticides [31].
Pyrethroids are divided into two groups according to their chemical structures but also
exhibit different type of toxicity [32]. The compounds in the first group, such as
allethrin, bifenthrin, permethrin, phenothrin, resmethrin, tefluthrin, tetramethrin (Fig.
4a) do not include cyano group and their effects on rats is described as aggressive
behaviour, hyperexcitation, ataxia, whole-body tremor, convulsions, and paralysis [33],
Pyrethroids from the second group including cyfluthrin, cyhalothrin, cypermethrin,
deltamethrin, fenvalerate, fenpropathrin, flucithrinate, fluvalinate, tralomethrin
(Fig. 4b) have an a-cyano moiety [34] and cause hypersensitivity, choreoathetosis,
tremors, clonic seizure and profuse salivation without shedding [35],
6
Developmental neurotoxicants
.0
CI
c N
0 H3C CH-^
(a) allethrin (b) Cypermethrin
Fig. 4 Molecular formula of (a) type I pyrehtroid and (b) type II pyrethroid
Most pyrethrins and some pyrethroid products are formulated with synergists, such
as piperonyl butoxide and ft-octyl bicycloheptene dicarboximide (MGK-264), to
increase the pesticidal properties of the product. They have no pesticidal effects of their
own but enhance the effectiveness of other chemicals [31]. The general human
exposure to pyrethroid insecticides is primarily from the ingestion of food or from
residential use. Unlike legacy pesticides, pyrethroids are rapidly metabolized in human
body and are eliminated after conjugation within several days in urine and bile [36],
The developmental neurotoxic effects of pyrethroids using animal models are
inconsistent in terms of toxic effect duration. Eriksson et al (1990, 1991) reported that
mice exposed to pyrethroids on postnatal day 10-16 exhibit increased motor activity
and a lack of habituation for up to 5 months after the end of exposure [37,38]. Other
studies showed persistent changes in behaviour and/or biochemistry, including learning
[39], motor activity [40], sexual behaviour [41], mAChR expression [42] and bloodbrain
barrier permeability [43],
Existing data indicate that human exposures to pyrethroids occur and result in
detectable concentrations in body fluids [44,45], but there is insufficient information
available to adequately evaluate the range of internal doses in humans, and the
consequences of these exposures are so far unknown [46],
PBDEs are a group of lipophilic, semivolatile halogenated flame retardants which were
widely used in a variety of consumer products, such as fabrics, automotive parts,
construction materials, printed circuit boards, television, computer housings and other
electric and electronic household equipment [47].
1.4 PBDEs
7
Developmental neurotoxicants
Brm Brn
Fig. 5 Generalized molecular formula of PBDE
PBDEs are not chemically bound to the polymeric matrix, so they can easily leach
out of these materials and volatilize into the environment, ending up in great
concentrations in biota and humans [48]. Diet and house dust appear to be the major
sources of PBDE exposure in the general population, though occupational exposure can
also occur [49]. It was shown that PBDEs can cause deleterious effects to liver, kidney
and thyroid gland and can act as endocrine disruptors [50]. Together with
environmental persistence, the PBDE adverse properties led to a restriction of Pentaand
Octa-BDE technical mixture in 2004 and Deca-BDE in 2008 in the E U [51,52].
The Penta- and Octa-BDE mixes are included in the Stockholm Convention on
Persistent Organic Pollutants [16].
Several types of animal studies support their DNT potential: animal studies
confirmed that exposure to different PBDE congeners causes long-lasting behavioural
alterations, particularly in the domains of motor activity (i.e. hyperactivity) and
cognitive behaviour with reduced learning and memory [49]. However, conclusions
from the human studies are inconsistent showing both lower birth weight and length
[53], poorer attention and fine motor coordination and cognition [54]. In the
Netherlands or in Spain no associations between elevated PBDE concentrations and
altered motor function, cognition and behaviour of the child up to age six were
observed [55,56]. It was also shown that exposure to the mixtures of PCBs and PBDEs
cause different effects than exposure to the single chemical. Neonatal mice exposed to
either B D E 99 or PCB 52 impaired spontaneous locomotor activity at 4 and 6 months of
Hydroxylated polybrominated diphenyl ethers (OH-BDEs) have been identified as
metabolites of PBDEs, but also as compounds of natural origin in the marine
environment [58]. There is increasing evidence that OH-BDEs are ubiquitous in biotic
and abiotic environments. These pollutants have been observed in abiotic compartments
such as rain, snow, and wastewater influent and effluent as well as in serum of the
age [57],
1.5 OH-BDEs
8
Developmental neurotoxicants
pregnant women [59,60]. The most important congener within the DENAMIC project
was 6-OH-BDE 47 which was selected as one of the model compounds for testing the
developmental neurotoxicity [61].
Br Br
Fig. 6 Molecular structure of 6-OH-BDE 47
Recent studies have indicated that OH-BDEs can be more toxic than PBDEs, partly
due to their ability to disrupt oxidative phosphorylation [62]. Also, due to their
structural similarities to the thyroid hormone thyroxine (T4), an increased accumulation
of OH-BDE derivatives may lead to lower vitamin A concentrations and negative
impacts on thyroid hormone function [63,64]. OH-BDEs were shown to exhibit a
greater neurotoxic potential compared to the parent compounds PBDEs. Two effects
involved in OH-BDEs and PBDEs developmental neurotoxicity have been described direct
toxic effects on the nervous system and effects of the thyroid hormone system,
which further influence the early brain development [65]. Pre- and postnatal
hypothyroidism were related to the behavioural disorders in humans and in animal
models [66],
1.6 AFRs
Halogenated flame retardants (sometimes referred to as non-PBDE FRs) represent
about 25% by volume of the global production of FRs with a growth of around 5% per
year [67]. Harju et al. listed 21 brominated FRs other than PBDEs,
hexabromocyclododecane (HBCDD) and tetrabromobisphenol A (TBBPA) and
estimated an overall annual production volume of-100,000 tons for these 21 and other
alternative BFRs [68]. So far, there are no restrictions or regulations on these
chemicals. Due to their structural diversity, they are divided here into three main
groups: (i) bromobenznes, (ii) PBDE replacements and (iii) other brominated FRs and
Dechlorane Plus (DDC-CO, Fig. 7).
9
Developmental neurotoxicants
Br
Br
Br
Br
Br
Br
hexabromobenzene
(HBB)
Br 0
Br
Br
Br
CH,
CH,
2-ethylhexyl-2,3,4,5-
tetrabromobenzoate
(EH-TBB)
Dechlorane Plus (DDC-CO)
Fig. 7 The structures of the selected compounds representing three groups of AFRs
The bromobenzenes include hexabromobenzene (HBB), pentabromobenzene
(PBBz), pentabromotoluene (PBT), pentabromoethylbenzene (PBEB) and pentabromobenzyl
acrylate (PBBA) [69]. The second group comprises 2-ethylhexyl-2,3,4,5tetrabromobenzoate
(EH-TBB) and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP)
which are the major components of Firemaster 550 [70] and which are used after the
restrictions of Penta-BDE mixture. Similarly, l,2-bis(2,4,6-tribromo-phenoxy)ethane
(BTBPE) is used as a replacement of the Octa-BDE technical mixture. The list of other
brominated FRs determined in human milk samples including the names and their
abbreviations is provided in the paper III. Dechlorane Plus was a replacement of
pesticide mirex known under a name of dechlorane which was also used as a flame
retardant after its ban in the late 1970s [71]. The general information about the
production volumes (if available) and the use of the selected AFRs is provided in the
Table 1.
Table 1: Production volumes and use of the selected halogenated FR
Compound production
volume
type of FR use
HBB naa
na paper, wood, plastic, electronic and plastic
goods[70]
PBT LPVb
na unsaturated polyesters, polyethylene,
polypropylenes, polystyrene, textiles, rubbers,
ABS [68]
PBEB LPV additive thermoset polyester resins (circuit boards,
textile, adhesives, wire and cable coatings) [72]
10
Developmental neurotoxicants
EH-TBB polyuretan foams [73],
BEH-TEBP LPV [70] additive polyurethane foams, flexible polyvinyl chloride,
adhesives, carpet backing, fabric coating, film
and sheeting, wire and cable insulation, and wall
coverings [73], PVC, neopren [68]
BTBPE LPV [70] additive thermoplastics, ABS,
high impact polystyrene [68]
TBP-AE LPV additive expandable polystyrene and PS foam [70]
DBE-DBCH na additive house insulation, extruded polystyrene,
adhesives in fabric, electrical cable coatings
[74]
DDC-CO H P V nylons, polybutylene terephthalate,
polypropylene, ABS, epoxy resins, electric wire
and cable, and synthetic elastomers [75]
" not available
b
100-1,0001peryear
c
>1,0001peryear
Many of these AFRs have physical chemical properties similar to PBDEs (e.g.,
aromatic moieties, high degree of halogenation and low aqueous solubility). The
toxicological data about this new class of flame retardants is limited, however it is
expected that due to the similar structural moieties in the molecules the toxicological
behaviour could be also similar. For example, both decabromodiphenyl ethane
(DBDPE) and B D E 209 can act as developmental neurotoxicants [76],
1.7 Methylmercury
Mercury is a naturally occurring element, but has been directly mobilized by humans
for thousands of years into aquatic and terrestrial ecosystems through mining. The use
of Hg in precious metal extraction, its presence as a trace contaminant in many
materials (e.g., coal, metal ores), and its use in products (e.g., paint, electronic devices)
and by industry (chlor-alkali plants; as a catalyst) has led to global concerns [77,78],
The atmosphere represents the major transport pathway of Hg emissions, whereas land
and ocean processes play an important role in the redistribution of Hg in terrestrial,
freshwater, and marine ecosystems and the production of MeHg that drives the major
human exposure route, consumption of (marine) fish [79],
Methylmercury is nowadays recognized as an important developmental
neurotoxicant, though this insight developed slowly over many decades. Developmental
neurotoxicity was first reported in a Swedish case report in 1952, and from a serious
11
Developmental neurotoxicants
outbreak in Minamata, owing to a drainage from a chemical plant in Japan a few years
later. In Sweden the cause of toxicity came from eating MeHg contaminated porridge
that contained flour from seeds treated with MeHg. While the infants suffered from
congenital poisoning, the mothers were barely harmed. This reflected a unique
vulnerability of the child developing nervous system. In Japan between 1932 and 1968
industrial wastewater contaminated an entire bay with methylmercury. Subsequent
dietary intake of fish and shellfish from the bay caused a range of symptoms from
nervous system damage. Nonetheless, exposure limits were based upon adult exposure
and treated the child as a 'small adult' until 50 years after the first report on
developmental neurotoxicity [80],
Bellinger et al (2016) estimated incidence of mild forms of intellectual disabilities
(IDs) in individual countries related to MeHg exposure. In this modelling study, the
data from MeHg measurements in hair, blood and cord blood were used and a loss of
0.18 IQ points was found with each ^g g"1
increase in maternal MeHg hair
concentration [81]. The distribution of IQ points in each country had a mean of 100 and
a standard deviation of 15. It was shown that the largest incidences of IDs occur in
island and coastal countries with the high consumption of seafood. In Finland, Sweden,
and Norway there was the highest incidence of these disabilities of approximately 1.07
infants per 1000 newborns and in the rest of Europe approximately 0.5 infants per 1000
newborns [82],
Concentrations of MeHg were determined within the project due to its significant
developmental neurotoxic action (J. Kuta) but the method development and the
measured concentrations in mother milk are not included in this thesis. However, in
paper II the findings on MeHg in milk were used hence the inclusion of this compound
in the introduction.
12
Main objectives and outcomes of the thesis
Main objectives and outcomes of the thesis
The thesis is divided into three main sections and it is based on the three first-author
publications, from which two are published in peer-reviewed journals and the third was
submitted in April 2017. The fourth co-author paper was submitted in May 2017
(Fig. 8).
Multi-class method
development
Human milk
LEGACY
PBDEs OH-BDEs OCRs
Me-Hg
/ \
\-Rs pyrethroids
CURRENT-USE
Paper i:
\* rflVahrílc#.npp irchnlqM fm UCTI HlrM'i ililni^rtha
DNT concentrations +
exposure assessment
N o r w a y (n=360)
T h e N e t h e r l a n d s [n=i20]
Slovakia (n=37)
Paper II:
V h---1- :•• II* la Jl I-1 i a::.- -I
" • • •Mr] UK M m ln^tt'.|B Ii
Epidemiological
evaluation
'Vi » T
Paper IV:
Quaak, I., de Cock; M..,
Čechová, E. et al.
Early life exposure to
organochlorine pesticides and
behavioral development in
children.
Standard Operating Procedure
(SOP-LSA) (in Czech)
Method for determination of (non-polar)
contaminants in human milk
Poper III:
Čechová e1 al.
Legacy and alternative halogenated
flame refardanfs in human milkin
Europe: implications forchildren's
health
Fig. 8 Outcomes of the thesis
The first part of the thesis is focused on the multi-class method development, where
the sensitive method for the determination of trace concentrations of DNT compounds
was presented in a paper entitled "An effective clean-up technique for GC/EI-HRMS
determination of developmental neurotoxicants in human breast milk". The unique
contribution of this work was the concurrent determination of both legacy and current
13
Main objectives and outcomes of the thesis
use compounds which require non-destructive clean-up procedures. For that purpose,
the dialysis clean-up step at 10°C showed to be more efficient compared to the
conventionally used gel permeation chromatography or other techniques. Also, the
Standard Operating Procedures (in Czech) are enclosed to the thesis (Appendix 2).
The second part is an exposure study, where the concentrations of the selected
groups of legacy DNT compounds were determined and compared in three European
countries - Norway, the Netherlands and Slovakia in more than 500 human milk
samples. Additionally, temporal trends and human risk assessment were a part of data
evaluation. The results are described in the two papers - first one, entitled
"Developmental neurotoxicants in human milk: Comparison of concentrations and
intakes in three European countries" is focused on the legacy compounds, such as
selected organochlorine pesticides, iPCBs and also MeHg. In the paper, comparison of
the DNT concentrations and temporal trends were assessed as these compounds were
banned in 1980s. Additionally, the evaluation of their presence in human bodies was
made through an estimation of the mothers' body burden using the pharmacokinetic
modelling. These values were subsequently compared to the body burden obtained from
the analysis of food and the differences between the two approaches were discussed.
The second paper "Legacy and alternative halogenated flame retardants in human milk
in Europe: implications for children's health''' which is currently being finalized is
focused on both legacy (PBDEs) and alternative halogenated flame retardants. The
concentrations of AFRs in milk samples present the first information on some of the
AFRs in human matrices. The part of data evaluation include the infants exposure
assessment integrating both data from human matrices and F R concentrations detected
in indoor environment, which was shown to be an important exposure pathway.
The last part of the thesis is focused on the preliminary epidemiological outcomes
where the DNT concentrations were linked to the children's health. Separate regression
models were composed for each compound-outcome combination. The behavioural
disorders discussed here included A D H D , Oppositional Defiant Behavior, Aggressive
Behavior and Externalizing Behavior. The results are presented in the short
summary from the epidemiological paper 'Early life exposure to
organochlorine pesticides and behavioural development in children" by Quaak et
al.
14
DNT method development
Development of the multi-class method for the
determination of DNTs in human milk
One of analytical tasks within the D E N A M I C project was to develop and optimize
a sample preparation procedure comprising suitable extraction and clean-up method for
the determination of six groups of the developmental neurotoxicants (OCPs, PCBs,
PBDEs, pyrethroids, AFRs and OH-BDEs) in human milk.
The R E C E T O X Trace Analytical Laboratories have validated GC-MS
instrumental methods for the determination of OCPs, PCBs, PBDEs and AFRs.
However, the instrumental methods for the compounds which are not routinely
measured at RECETOX, i.e. pyrethroids and OH-BDEs, had to be developed and
validated as part of this project. The method development for the determination
of five groups of developmental neurotoxicants (excluding the OH-BDEs) and
analytical performance characteristics are presented in the Paper I.
The compounds determined in human milk samples for this study included:
OCPs: PeCB, HCB, a-, (3-, y-, S-HCH, heptachlor, heptachlor epoxide, a-, ycrordane,
a-, (3-endosulfan, endosulfan sulfate, aldrin, dieldrin, endrin, endrin
aldehyde, endrin ketone, o,p '-DDE, p,p '-DDE, o,p '-DDD, p,p '-DDD, p,p '-DDT, o,p 'DDT,
methoxychlor, mirex, chlordecone
PCBs: mdicator PCBs 28, P C B 52, PCB 101, P C B 138, P C B 153, P C B 180 +
dioxin-like PCB 118
pyrethroids: empenthrin, tefluthrin, transfluthrin, resmethrin, bifenthrin,
tetramethrin, fenpropathrin, phenothrin, cyhalothrin, acrinathrin, cyphenothrin,
fenvalerate, deltamethrin, cis-, /rafts-permethrin, cypermethrin, cyfluthrin, piperonyl-
butoxide
PBDEs: B D E 28, B D E 47, B D E 66, B D E 85, B D E 100, B D E 99, B D E 154,
B D E 153, B D E 183, B D E 209
OH-BDEs: 2'-OH-BDE 28, 3'-OH-BDE 28, 6-OH-BDE 47, 4'-OH-BDE 49, 2'OH-BDE
68, 4-OH-BDE 42, 3-OH-BDE 47, 5-OH-BDE 47, 6-OH-BDE 85, 4-OHB
D E 90, 6'-OH-BDE 99, 5'-OH-BDE 99, 4'-OH-BDE 99, 3-OH-BDE 100, 6-OH-BDE
137, 3'-MeOH-BDE 154
15
DNT method development
AFRs: allyl-2,4,6-tribromophenyl ether (TBP-AE), l,2-dibromo-4-(l,2-dibromoethyl)-cyclohexane
(DBE-DBCH), 2,3,5,6-tetrabromo-p-xylene (TBX), 2-bromoallyl-
2,4,6-tribromophenyl ether (TBP-BAE), 1,2,5,6-tetrabromocyclooctane (TBCO),
pentabromobenzene (PBBz), tetrabromo-o-chlorotoluene (TBCT), dechlorane Plus
Mono adduct (DDC-COMA), pentabromotoluene (PBT), pentabromoethylbenzene
(PBEB), 2,3-dibromopropyl-2,4,6-tribromophenyl ether (TBP-DBPE), hexabromobenzene
(HBB), pentabromobenzyl acrylate (PBBA), hexachlorocyclopentenyldibromocyclooctane
(DBHCTD), 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB),
l,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), Dechlorane Plus (syn- and anti-DDCCO),
bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP)
The following section provides a comprehensive summary of the extraction
technique selection. Also, several changes in the final clean-up step and the
instrumental method optimizations are described here since the Paper I does not deal
with the determination of OH-BDEs.
2 Extraction
The extraction technique has been selected taking into account the nature of the
analytes. The summary of the most often used extraction techniques for the non-polar
environmental contaminants is provided in Table SI (Appendix 1). The majority of the
determined DNT compounds including OH-BDE metabolites are non-polar with
a K0 w>3 (Table 2) and they accumulate in lipids. Lipid content thus constitutes an
important information and we included this determination to our procedure.
Table 2: Ranges of KQw of determined compounds
puliir 3 4 5 6
< —
7 H l
) 10 lion polar
— >
OCPs
iPCHs
PBDEs"
OH-BDEsb
Al-'Rs
a
tri-deca-BDEs
b
tri-hexa-OH-BDEs
16
DNT method development
For the lipid normalization, the quantitative extraction of lipids together with
compounds of interest is essential. A range of lipid determination methods were tested
(Table 4). The lipid content obtained from different extraction methods tested in this
study was compared to the reference Rose-Gottlieb method. In this method 1.5 ml of
25% N H 3 in water, 10 ml of ethanol, 25 ml of diethyl ether and 25 ml of ft-hexane are
used for 10 ml of liquid milk [83]. After 15 min of shaking in the separation funnel
followed by equilibration of the two layers, the upper organic layer was collected. The
procedure was repeated twice with the fresh organic solvents. The lipid content in
the purchased bovine milk was found to be 3.4% ± 0.3% (Table 4), which
corresponds to the declared lipid content in full-fat milk in the Czech Republic.
However, owing to the use of volatile and flammable diethyl ether and high volume
of solvents (150 ml for 3 extraction cycles), an alternative liquid-liquid "Smedes"
extraction method which uses non-chlorinated organic solvents was tested [84]. One ml
of 25% N H 3 in water, 6 ml of isopropanol and 40 ml of 13% isopropanol in w-hexane
were used. The volume of isopropanol :«-hexane mixture was optimized and 40 ml were
found as the minimum volume giving the fat content comparable to the reference
method (Table 4). The mixture was shaken for 15 min and after the equilibration
period, upper organic layer was collected. This process was repeated twice. As the
solvent consumption was still over 120 ml and long time was required for a separation
of the two layers, Smedes extraction was not found to be the most favourable method.
A pressurized liquid extraction (PLE) method was then tested. In this method the
milk samples were be freeze-dried prior to the extraction. Different solvent mixtures
and temperatures were tested in order to obtain the lipid content comparable to the
reference method (Table 4). Finally, three-cycled extraction programme using nhexane:DCM:MeOH=5:2:l
(v/v/v), the temperature of 65 °C and pressure of 100 bar
showed the best and reproducible lipid recovery. The P L E extraction cells were filled
with approximately 2 cm layer of cleaned Ottawa sand and 1 cm of baked anhydrous
Na2 S04 , followed by the freeze-dried milk samples ground with 15 g of Na2 S04 .
Fifty ul of the mixture of labelled internal standards were added followed by the
additional layer of Na2S04 and sand to fill the cell approximately 1.5 cm below the
upper part of the cell. A paper filter was placed on the top of the cell. The extracts were
collected to glass Biichi Syncore Analyst tubes (the final volume was approximately
40-50 ml).
17
DNT method development
Table 4: Comparison of thefat content obtained with different extraction method
Extraction Solvent mixture Temperature, % offat Solvent
method (v/v or v/v/v) °C (RSD, volume
n=4) (ml)
LLE ethanol, NH3 Et2 0, hex ambient 3.38 (10) 150
(RGa
)
LLE H20:2-PrOH: cyclohex= ambient 3.67(12) 120
(Smedes) =11:8:10
PLE hex:DCM:MeOH=5:2:1 65 3.40 (8) 50
hex:DCM:MeOH=5:2:l 30 3.18 (7) 50
hex:DCM:MeOH=67:29:4 65 2.35 (7) 50
hex:DCM=l:l 65 2.09 (5) 50
hex:DCM:MeOH=3 5:3 5:3 0 65 5.66 (8) 50
hex:2-PrOH=3:2 65 4.04(10) 50
" Rose-Gottlieb
After the solvent reduction using Syncore Analyst evaporator (Biichi, Switzerland),
the upper organic layer was quantitatively transferred to a 22-ml vial. The presence of
a bottom water layer (-1-1.5 ml) was attributed to the presence of water residues in the
solvents used (MeOH). This layer was formed also in procedural blank samples where
no freeze-dried milk was added.
The solvent in the 22-ml vial was evaporated under a stream of nitrogen and the
tubes were placed in an oven at 60 °C for 1 hour to remove residual liquids. The higher
temperature recommended in Rose-Gottlieb method protocol was not used due to
the risk of lipid oxidation at 100 °C. After a cool-down to ambient temperature, the
lipids were determined gravimetrically.
3 Clean-up procedures
After lipid determination, a clean-up step was necessary to remove interferences that
would negatively influence the accuracy of the GC-HRMS quantification. For PCBs,
PBDEs and part of OCPs and AFRs, a destructive clean-up with sulphuric acid is an
efficient and effective way for removal of lipids [85-89]. However, the inclusion of
non-persistent compounds, such as pyrethroids, drin-pesticides or selected AFRs, calls
for the use of less harsh and often multiple clean-up processes. The number of methods
18
DNT method development
suitable for the non-destructive multi-class analysis of DNTs in human breast milk is
currently limited [90],
3.1 First clean-up step
Three non-destructive clean-up steps for lipid removal were trialled; gel permeation
chromatography (GPC), freezing-lipid filtration (FLF) and dialysis. For GPC we used
two styrene-divinylbenzene GPC columns (19 x 150 mm and 19 x 300 mm, 15 |j.m
particles, Envirogel, Waters) connected in series and D C M as a mobile phase with
a flow rate of 5 ml min"1
. For FLF, 2x40 ml of A C N were used for 2 hours in the -24 °C
and for dialysis, a low-density polyethylene tubing (5 cm x 10 cm, nominal thickness of
85 |^m, Brentwood Plastics, Missouri,USA). More details regarding the clean-up
methods are provided in paper I.
High recovery of target analytes (60-120%) and sufficient lipid removal were the
two essential criteria for our method. The advantages and disadvantages of the
individual techniques are summarized in Table 5.
Table 5 Comparison of three different clean-up techniquesfor processing milk fat
GPC FLF
10 °C
Dialysis
25 °C
lipid carryover, %a
15 (8) 19(13) 4-6 (12) 6-8 (15)
(RSD, n=4) limited column
capacity of«250
mg of lipid
additional clean-up b
yes yes no no
solvent consumption 150 ml DCM 100 ml ACN 40 ml n- 40 ml nhexane
hexane
risk of cross- yes no no no
contamination
automatization yes no no no
cost high low low low
a
350 mg of milkfat was used
b
apartfrom the sorption column chromatography which was used after all three clean-up techniques
The significant advantage of the dialysis at 10 °C was the low cost and low nonchlorinated
solvent consumption (40 ml per sample) which plays an important role
when processing large amounts of samples. Despite the longer total time (48 h), many
parallel samples could be processed at the same time. This technique was the most
19
DNT method development
efficient non-destructive clean-up step for the trace analysis of fatty samples where the
fat amount exceeds 250 mg. Good removal of interfering compounds by the dialysis
compared to GPC is demonstrated in Fig. 9. The presence of the interfering
matrix caused the decline in lock and calibration masses which further leads to
inaccurate quantification.
m/z=167.0628
m/z=169.059B
LOCK MASS
m/z=168.9888
CALIBRATION
MASS „ „ „ „ „ „ , . „ „ „ „ „ „ „ „
m/z=180.9888 ' ' ' ' ' ' '.'i ' ' '.V ' ' ' ' ' ' 31 7. » « Z Z Z Z I 3 " i d • i. « « d u a t i H a d h «
a) b) c)
Fig. 9 GC-HRMS chromatograms of fenvalerate peaks in (a) standard solution, (b) milk
sample after the use of GPC clean-up and (c) milk sample after dialysis clean-up
The use of dialysis ensured the maximal removal of lipids during the clean-up
procedure. However, since the final volume prior to GC-HRMS analysis should be as
low as possible in order to obtain low LOQs, the rest of the lipids (on average 20-
40 mg per sample) were removed by an additional column chromatography step.
3.2 Second clean-up step
In the paper I, a combination of C18-reversed phase silica gel and basic alumina
sorbents were described as the last clean-up step for the removal of residual lipids and
other interferences [91]. These sorbents were used for the determination of the nonpolar
contaminants excluding OH-BDEs. The addition of the hydroxylated compounds
required the change in sorbents as basic alumina retained hydroxylated compounds
which would be eluted only with strong acidic solution. However, this acid would then
20
DNT method development
react with the derivatization agent (details about derivatization of OH-BDEs are
provided in the chapters 4.2.2.1 and 4.2.2.2). Esteve-Turrillas et al (2005) published
a list of tested sorbents for removal of fat from olive oil matrix and showed that the
lipid removal with a combination of CI 8 and acidic alumina was very similar to the use
of CI8 and basic alumina [91]. OH-BDEs were eluted with a weak acidic solution of
5% H A c in A C N , which was then easily evaporated under a stream of nitrogen and did
not interfere with the derivatization agent.
Another difference from the method described in the paper I was the separation of
the sorbents into two separate columns and after elution of non-polar fraction
containing OCPs, pyrethroids, PBDEs, AFRs and PCBs, the upper CI8 column was
discarded and thus we did not elute the interfering fatty acids into the "polar" fraction.
The OH-BDEs were eluted from the acidic alumina deactivated by 10% of water with
two times 3.5 ml of 5% H A c in A C N .
4 Instrumental methods
As the compounds of interest in this study have a wide range of physical and chemical
properties and the objective was to identify chemicals at the lowest concentrations, the
use of different compound-specific methods for identification was needed.
4.1 Pyrethroids+chlorpyrifos
Instrumental analysis of pyrethroid insecticides can be performed with LC-MS or G C MS
separation and detection/quantification techniqes [92,93]. Chlorpyrifos as an
organophosphate pesticide was also added to the method due to its strong suspected
developmental neurotoxic action [94,95]. Initial trials by UPLC-MS/MS showed low
separation efficiency and low sensitivity (Xevo TQ-S, Waters, work of M . Seifertova),
GC-EI-HRMS (Trace 1310 GC, coupled to a double-focusing magnetic sector DFS,
both from Thermo Scientific, US) was used for the further optimization. A 60-m x
0.25-mm x 0.25-(im Agilent DB-5MS Ultra Inert separation column was used with the
following temperature program: 120 °C (1.5 min hold), followed by 30 °C mm"1
to
150 °C, then 4.5 °C min"1
to 330 °C (10 mm hold). Electron ionization in positive
mode (EI+
) was used with electron energy of 48 eV. The M S was set at > 10,000
(10% valley). The GC-MS transfer line temperature was 280 °C for all analyses.
21
DNT method development
The major difficulty in analysis of pyrethroids was their in-source fragmentation, so
the most abundant ions were in the low-mass range (<200 Da) (Fig. 11). This caused
problems especially in the complex matrices of mother milk, where the samples after
insufficient clean-up significantly influenced the accurate quantification as can be
seen in Fig. 9b. The selection of proper clean-up method was therefore essential and
played a key role in the accurate quantification of pyrethroids.
Fig. 10 EF-MS spectrum of cypermethrin and proposed fragmentation pattern
4.2 OH-BDEs
Both LC-MS or GC-MS methods have been reported for the determination of OHBDEs
[96-98]. Since the disadvantage of GC-MS is a derivatization step which has to
be performed prior to the measurement, our primary option was LC-MS/MS
(Xevo TQ-S, Waters).
4.2.1 LC-MS/MS
The development of the L C separation method posed a great challenge because of the
presence of six isomers of hydroxylated tetra- and penta-BDEs (Table 6) which had to
be separated chromatographically due to the expected similar MS spectra.
22
DNT method development
Table 6: List of the OH-BDEs with differentposition of OH-group
number of 4 position of OH-BDE congeners
Br atoms OH- group
3 ortho 2'-OH-BDE-28
4 Ortho 6-OH-BDE-47, 2'-OH-BDE-68
meta 3-OH-BDE-47, 5-OH-BDE-47
para 4-OH-BDE-42, 4'-OH-BDE-49
5 ortho 6-OH-BDE-85, 6'-OH-BDE-99
meta 3-OH-BDE-100, 5'-OH-BDE-99
para 4-OH-BDE-90, 4'-OH-BDE-99
6 ortho 6-OH-BDE-137
para 3'-OH-BDE-154
Various reversed-phase L C columns with mostly non-polar CI8 or slightly polar
stationary phases were tested in order to achieve the best separation efficiency - B E H
CI8 (1.7 urn, 2.1 mm x 100 mm, Waters), X-Terra CI8 (3.5 urn, 3 mm x 100 mm,
Waters), Cortecs U P L C C18 (1.6 urn, 2 mm x 150 mm, Waters), Kmetex PFP (2.5 urn,
2.1 mm x 100 mm, Phenomenex), Ascentis RP-Amide (3 urn, 2.1 mm x 100 mm,
Sigma Aldrich) and Acclaim Surfactant (3 urn, 2.1 mm x 150 mm, Thermo Fischer
Scientific). The last column provided the best separation of the hydroxylated tetra- and
penta-BDE isomers. Mobile phase consisted of water (2 m M ammonium acetate, pH 5,
HAc, solvent A) and A C N and then MeOH (solvent B). Since A C N did not show
sufficient separation efficiency, MeOH was used instead. The final gradient was
as followed: 0-4.5 mm: 60% A , 4.5-9 mm, 9-14.5 mm 60-3% A , 14.5-15 3% A ,
15-34 mm 3% A , 34-34.2 mm 3-60% A , 34.2-40 60% A . Column temperature
was set at 30 °C, flow rate of the mobile phase was 0.115 ml min"1
. Injection volume
was 10 ul.
Contrary to our expectations, the MS/MS transitions were shown to be different
for some of the isomers with different position of OH-group (Table 7) which helped
with the quantification even when the chromatographic separation was not
perfect. Ion source parameters (ESI+
) were set as follows: Capillary voltage was
set at 1.97 kV, source offset at 100 V , cone voltage 19-40 V . Desolvatation
temperature was set at 550 °C and desolvation gas flow at 800 1 h" . Cone gas flow 160
1 h", nebulizer 6.5 bar and collision gas flow 0.14 1 h" .
23
DNT method development
Table 7: Selected MS/MS parameters used for the determination of OH-BDE
metabolites
Compound Precursor Product Cone Collision
ion, (m/z) ion, (m/z) voltage, [V] energy, [V]
OH-tn- BDEs 421.0 78.9 40 24
nie/a-OH-tetra-BDEs 500.8 250.7 19 28
para-OH-tetra-BDEs 500.8 266.0 19 40
OH-tetra-BDEs 500.8 78.9 19 15
OH-penta-BDEs 578.8 78.9 19 30
para-OH-penta-BDEs 578.8 266.0 19 28
para-OH-penta-BDEs 578.8 343.7 19 47
OH-hexa-BDEs 658.8 78.9 19 33
The separation of the individual isomers was satisfactory (Fig. 15). However,
while LOQs for OH-tetra and OH-penta-BDE ranged between 15-250 fg on
column, for OH-tri- and hexa-BDEs they were up to 850-10,400 fg on column.
Due to the low sensitivity of OH-tri- and OH-hexa-BDE isomers and requirements
to the very good column equilibration for obtaining the good separation for OHtetra
and OH-penta-BDEs, GC-HRMS method was selected as an alternative to
the LC-MS/MS method.
4.2.2 GC-HRMS
In order to increase the volatility of the analytes, methylation of the hydroxy group
was performed prior to the GC-HRMS measurement. From a range of
derivatization agents, two were tested in this study; trimethylsilyldiazomethane
(TMSD) and diazomethane (CH2 N2 ). Both agents were used following literature
established methodologies.
4.2.2.1 Derivatization with diazomethane
Methylation with diazomethane ( C H 2 N 2 ) constitutes a simple way to prepare
more volatile compounds from hydroxyl precursors as no by-products are formed
during the reaction (Fig. 11).
24
S — N — NO + KOH
+
O C H 3
CH,N,
Diazald Diazomethane
(a)
o o
y \
CH2 N2
R OH + R OCH3
+
Diazomethane (b)
Fig. 11 Reaction scheme of (a) preparation of diazomethane from diazald and (b) its
reaction with a carboxylic acid
On the other hand, diazomethane is a highly toxic and explosive gas, so preparation
and handling has to be done with caution. It is also volatile, so it has to be prepared
fresh for every use and limited storage life <1 week. Usually, a distillation apparatus is
used for a preparation of C H 2 N 2 , but we used miniaturized apparatus by Sigma Aldrich
(Fig. 12) [99] which allowed us to prepare 3 ml of 0.3 mmol C H 2 N 2 in diethyl ether.
Fig. 12 The miniaturized apparatus for preparation of CH2N2
The procedure took approximately 60 to 90 minutes and was based on the Sigma
Aldrich protocol [99]: To the outside tube of the Aldrich C H 2 N 2 generation apparatus
were added 3 ml of diethyl ether. To the inside tube 0.367 g of diazald (N-methyl-Nnitroso-4-methylbenzenesulphonamide)
and 1 ml of carbitol (2-(2-ethoxyethoxy)ethanol)
were added. Then, the two parts were assembled and the lower part of
0
25
DNT method development
the outer tube was placed in an ice bath. After equilibrating to the cooling bath
temperature, approximately 1.5 ml of aqueous K O H (37%) was slowly injected dropwise
through the septum via a syringe. The apparatus was shaken gently by hand to
ensure mixing of reactants within the inner tube, while being careful not to allow these
reactants to spill into the outer tube. The yellow colour of the solution in the outer tube
indicated the presence of diazomethane. After approximately 50 min, the yellow
solution of C H 2 N 2 in diethyl ether was transferred out of the outer tube to a 4-ml clear
vial with a solid cap and the vial was wrapped in aluminium foil to protect against light
and then stored in a refrigerator at 4 °C.
Since the amount of C H 2 N 2 and reaction times for different analytes vary among
different authors [100,101], these parameters were optimized for OH-BDEs in order to
achieve the highest reaction yield (Fig. 13a-c).
(b) OH-tetra-BDEs
26
DNT method development
4 A
0 5 10 If 20 25 30 100 200 300 JCO 500 600
Time (tod) nlofCHjNj
(c) OH-penta-BDEs
Fig. 13 Optimization of derivatization time (graphs on the left) with 100 jul CH2N2with
(a) OH-tri and OH-hexa-BDEs, (b) OH-tetra-BDEs, (c) OH-penta-BDEs and
optimization of the CH2N2 amount with 27 hours of reaction time (graphs on the right)
Based on the C H 2 N 2 amount and time optimization, the final volume for
derivatization in a standard solution was 100 d and optimum reaction time was
27 hours, when the yield was maximal.
However, when performing the derivatization in milk extracts, it was shown that
even the addition of more than 300 JLLI of diazomethane was not enough for the
complete conversion to methoxy- BDEs. The reason might have been in the presence of
the remaining fatty acids in the samples which also reacted with the diazomethane
visible as the colour change (from yellow to colourless with the release of nitrogen
bubbles). The diazomethane concentration was therefore not sufficient for the milk
samples and another method for derivatization was tested.
4.2.2.2 Derivatization with trimethylsilyldiazomethane
Trimethylsilyldiazomethane (TMSD) was reported to react more slowly than
diazomethane, but it is more convenient due to its higher stability. It is available as
more concentrated solution than diazomethan (2 M solution in w-hexane or diethyl
ether) and it is neither mutagenic, nor explosive [ 102]. The reaction scheme is shown in
Fig. 14.
27
DNT method development
R O H + C H 3 O H + N
+ R O C H'3
( C H 3 ) 3 S i C H N 2
Trimethylsilyldiazomethane C H 3 O C H 2 S i ( C H 3 ) 3
(TMSCHN2 )
Fig. 14 Scheme of the methylation reaction with TMSD
The amount of TMSD was optimized with standard solution as with diazomethane
and it was shown that 50 ul was enough for the complete reaction. The samples after
clean-up step were gently evaporated to dryness and 500 JLLI of MeOH was added
[102,103]. Then 100 |^1 of TMSD were added, the solution was gently vortexed and
heated for 15 minutes at 50 °C. In some samples the higher amount of derivatization
agent TMSD was necessary most likely due to the higher content of free fatty acids. But
for 80% of all samples 100 JLLI was enough. Afterwards, the excess of TMSD was
evaporated under a gentle stream of nitrogen and the sample was transferred
quantitatively to the GC-MS vial and recovery standard 1
C B D E 138 was added.
Methoxylated PBDEs were analyzed using a GC-HRMS (Agilent 7890 A) equipped
with a 15 m x 0.25 mm x 0.1 |j.m Restek Rtx-1614 column. A high resolution mass
spectrometer (Waters Micromass AutoSpec Premier) operated in a positive
electron ionization mode was used at a resolution >10,000. Splitless injection of 2 ul
of sample at 280 °C and He as the carrier gas at a flow of 1 ml m i n 1
were
used. The GC temperature program was as follows: Initial temperature was 80 °C
(1 mm) followed by the increase of 20 °C mm"1
to 180 °C and then of 1.5 °C mm"1
to 200 °C. The fmal increase was by 40 °C mm"1
to 325 °C (5 mm).
The differences in separation efficiencies of OH-tetra B D E isomers with the L C MS/MS
and GC-HRMS are shown in Fig. 15.
28
DNT method development
Fig. 15 Comparison of (a) LC-MS/MS chromatogram of OH-tetra-BDE isomers and (b)
GC-HRMS chromatogram ofMeO-tetra-BDE isomers
5 Method performance characteristics
Analytical performance characteristics of the method were based on validation
guidelines included in the E U Commission Decision 2002/657/EC [104]. Accuracy
(including trueness and precision), linearity and L O D were assessed using fortified
breast milk obtained from a volunteer mother at two known concentrations. Trueness,
evaluated as average recoveries, was calculated as the ratio of determined
concentrations in spiked samples to their target concentration* 100%. Recoveries for
most of the analytes ranged between 75-110%, only for selected pyrethroids and AFRs
they were between 40-121% due to the deficiency of the labelled analogue.
Additionally, expanded uncertainties (U) were calculated and for most of the
compounds they ranged between 5-40%. The details are provided in the Supplementary
Material of the paper I. The LODs ranged betweed 0.001-0.97 ng g"1
lw for all
compounds.
6 Summary - method development
Multi-class method for determination of 97 mid to non-polar developmental
neurotoxicants was developed. The main advantage of the method is the simultaneous
29
DNT method development
lipid content determination and use of lower solvent amounts compared to other
conventionally used non-destructive techniques such as gel permeation
chromatography. Dialysis was shown to be very efficient clean-up procedure being
cost-effective, and it was used for the first time on the analysis of such a complex
mixture of organic contaminants, including both legacy and current use compounds.
The complete method is shown in Fig. 16. The method was applied to the analysis of
more than 500 human milk samples from three European countries. The results brought
novel insights into the human exposure to the legacy compounds as well as current-use
compounds such as pyrethroids or alternative flame retardants for which the data on
concentrations in human matrices are still limited. Furthermore, the low limits of
detection of the method provide the efficient tool for future biomonitoring. The results
are currently being used for the epidemiological evaluation of the influence of these
compounds to the child health.
internal standards
Recovery standards
£-10 ml of milk
Freeze-drying
PLE
(hex:DCM:MeOH=5:2:l)
65°C, 3 cycles
Dialysis
[LDPE membrane)
10"C, 18 hours
Column
chromatography
(CIS +a-AI2 03 )
k Gravimetric fat
y determination
HAcinACN
GC-HRMS
(OCPs, i'PCBs, pyrethroids,
PBDEs, AFRs)
Methylation with TMSD
15 mill, 50 "C
GC-HRMS
OH-BDEs
Fig. 16 A workflow diagram indicating the method established for the multi-class
determination of DNTs in human breast milk
30
DNT concentrations in human milk
Exposure to DNTs in human breast milk from three
countries
Having established a methodology for the determination of DNTs in human breast milk,
samples from three European countries were processed.
7 Characterisation of the samples
Human milk samples were obtained from three European countries - Norway (n=360,
samples collected between 2003 and 2009), the Netherlands (n=116, 2011-14) and
Slovakia (n=37, 2011-12). Written informed consent was obtained from the mothers
during their antenatal visit. The samples were collected between the weeks 4-8
postpartum into the glass prewashed and pre-treated bottles and stored at the -20 °C
before sending aliquots to the R E C E T O X Trace Analytical Laboratories. More detailed
information on the individual cohorts included in the DENAMIC project is given in
Table 8.
Table 8: General characteristics of the mothers (for continuous variables median
values and 25th
percentile and 75th
percentile ranges are presented in parentheses)
Slovakia the Netherlands Norway p-value b
(n=37) (n=120) (n=360)
age (years) 30 (27-33) 31 (29-34) 30 (26-33) 0.00
mother's height (cm) 168 (164-169) 172(169-175) 168 (163-171) 0.00
mother's weight (kg)a
62 (56-72) 70 (63-73) 66(60-74) 0.02
BMI (kg m"2
)a
21.9 (20.5- 23.2 (21.4-24.6) 23.4 (21.4- 0.08
24.0) 26.0)
lipids in human milk,
%
4.0(3.0-5.1) 3.8 (3.2-4.7) 3.0(2.3-3.8) 0.00
/o
maternal parity, %
0.30
first child 41 43 40
second child 47 38 38
third child or more 11 19 22
missing (n) 1
" before pregnancy
b
differences between three cohorts evaluated with Kruskal-Wallis test for continuous variables and chisquare
testfor categorical variables
31
DNT concentrations in human milk
8 DNT concentrations
The relative contributions of the sums of the concentrations of individual DNT groups
in the three countries are shown in Fig. 17. The detailed distributions of the
concentrations of all compounds which were measured within this study are provided in
Appendix 3. The concentrations of z'PCBs and selected OCPs and their comparison with
other countries and daily intake calculation are commented in the exposure paper II
{^Developmental neurotoxicants in human milk: Comparison of concentrations and
intakes in three European countries''') and the concentrations of PBDEs and AFRs are
discussed in paper III ^Legacy and alternative halogenatedflame retardants in human
milk in Europe: implications for children's health").
Norway the Netherlands Slovakia
UPCBs
I Ipyrehtroids
. Z A F R s
Fig. 17 Sums of the median concentrations of developmental neurotoxicants measured
in mother milk in three European cohorts, ZDDTs is a sum of p,p '-DDT, o,p '-DDT,
p,p'-DDE, o,p'-DDE, p,p'-DDD and o,p'-DDD, XOCPs include HCB, HCHs,
heptachlorepoxide, dieldrin, endosulfan sulfate and mirex, UPCBs is a sum of PCB 28,
52, 101, 138, 153 and 180, pyrethroids include piperonyl-butoxide, eis- and transpermethrin
and chlorpyrifos, ZPBDEs is a sum of BDE 28, 52, 99, 100, 153, 154 and
180 , XAFRs is a sum ofPBBz, HBB, PBT, p-TBX, EH-TBB, BEH-TEBP, BTBPE, synDDC-CO,
anti-DDC-CO, DBE-DBCH, TBP-DBPE and TBP-AE
8.1 OCPs+PCBs
In all three countries, OCPs and PCBs were the dominant DNT group determined in
this study in human milk samples despite their ban more than 30 years ago. A l l
determined PCB congeners and 15 out of 26 measured OCPs were found in more than
32
DNT concentrations in human milk
64% of all milk samples in the three countries. Other OCPs were detected at lower
detection frequencies (0-36%). Concentrations of penta- and hexa-chlorinated
biphenyls, HCBs and DDTs in Slovakia were up to 3 times higher than in Norway or
the Netherlands (Fig. 18).
Within Slovakia, the east part in Michalovce was also identified as the place with
higher human milk contamination compared to the other parts of Slovakia, mainly due
to the former production of PCBs and high pesticide usage [105]. On the contrary, yHCH,
mirex or dieldrin in Slovakia had comparable or lower concentrations compared
to the other two countries.
OCPs
SO 100 120
ng g"1
Iw
20D
I HCB
• p.p'-DDÉ
- dieldrin
• p.p'-DDT
I mirex
I heptadilor epcKide
• p.p'-DDD
lo.p'-DDT
u ß-HCH
P C B s
• PCB 28
• PCB 52
* PCB 101
• PCB 138
• PCB 153
• PCB ISO
- P C B 118
n 6 g'1
lw
Fig. 18 The median concentrations of selected organochlorine compounds and PCB
congeners detected at highest detection frequencies in human milk samples in three
European countries
33
DNT concentrations in human milk
8.2 Pyrethroids+chlorpyrifos
The detection frequencies of pyrethroids in all three countries were low - only cis and
/ram'-permethrin were present in more than 50% of all samples The comparison of the
two most often detected pyrethroids, chlorpyrifos and piperonyl-butoxide in all three
countries is shown in Fig. 19.
J cis-permethrin
• trani-permethrin
-• chlorpyrifos
• piperonvl-bLitoxide
0,0 Q.2 ISA 0.6 0.8 1.0 1,1 1,4
ng g"3
hv
Fig. 19 Median level of eis-, trans-permethrins, chlorpyrifos and pyrethroid synergist
piperonyl-butoxide with the highest detection frequencies in the human milk samples
from Norway, the Netherlands and Slovakia
The organophosphate chlorpyrifos was found in Slovakia and the Netherlands in
more than 70% of the samples, but only in 3% of the samples in Norway. Additionally,
piperonyl butoxide suggesting previous exposure to pyrethroids was identified in all
three countries in 24-86% of the milk samples. The highest detection frequency was in
the Netherlands, where it was found in more than 86% of the samples. A l l the other
pyrethroids were present in less than 10% of the samples from Norway and in Slovakia,
while in the Netherlands remarkably higher detection frequencies of deltamethrin-2,
cyhalothrin and transfluthrin were observed which were quantified in 28 to 52% of the
samples (Fig. 20).
34
DNT concentrations in human milk
N o r w a y
7
6
5
4
3
2
1
0.6
0.5
0.4
bo 0.3
C
0.2
0.1
0.0
1.4
1.2
1.0
3 0.8
oo
00
c
0.6
0.4
ß-cyfluthrin-4
•
cypermethrin-l
1 ,«—,-;
fenvalerate-1
ß-cvfluthrln-3
•
transfluthrin
I cyhalothrin
a-cypermethrir
m
+ tefluthrin
K b i f e n t h r i n
piperonyl-butoxide
X ^
trans-permethrin c i s . p e r m B t h r i n
, =,
I 30 40
Detection frequency, %
the Netherlands
chlorpyrifos
cypermethrin-2
a-cypermethrin-3
ß-cyfluthrin-3
transfluthrin deltamethrin-2
" cypermethrin-4
• p-cyfluthrin-4
bifenthrin
H cypermethrin-l
fenvalerate-1
^ tefluthrin
cyhalothrin
piperonyl-
butoxide
x
trans-permethrin
x
cis-permethrin
20
0.2
0.0
40 60
Detection frequency, %
Slovakia
80 100
• chlorpyrifos
cyhalothrin
fenvalerate-1
a-cypermethrin-3
piperonyl butoxide
trans-permethrin
cis-permethrin
20 40 60
Detection frequency, %
80 100
Fig. 20 The dependence of the median concentrations on the detection frequency of
selectedpyrethroids in Norwegian, Dutch and Slovak human milk samples, they-axis is
different in each graph
35
DNT concentrations in human milk
There are not many studies to date on the presence of pyrethroids in mother milk. In
two studies, the concentrations of selected pyrethroids were measured in Brazil,
Columbia, Spain [106] and the US [90]. While cypermethrin was detected in all
samples in Brazil, Columbia and Spain at the median concentrations of 0.31-2.59 ng g"1
lw, in the US the detection frequency and the mean concentration was comparable to
the countries from this study. Permethrin was also detected with detection frequencies
of 93-100% in Brazil, Columbia or Spain countries which was comparable to our study,
but the concentrations were up to 10-100-times greater than in our study (0.42-
4.08 ngg"1
lw). It was not detected in any sample in the US. Piperonyl butoxide or
chlorpyrifos were determined only in US study and detection frequencies and
concentrations were comparable to our study (0.02 ng ml"1
and 0.063 ng ml"1
for
piperonyl butoxide and chlorpyrifos, respectively).
8.3 PBDEs
In Norway, the median of E7 PBDEs (sum of B D E 28, 47, 99, 100, 153, 154, 183) was
2.20 ng g"1
lw, in the Netherlands 0.91 ng g"1
lw and in Slovakia 0.49 ng g"1
lw. In all
three countries, concentrations of B D E 47, 99, 100 and 153 were detected in more than
70% of the milk samples. .The concentrations of the 4 congeners are shown in Fig. 21.
PBDEs
0.0 0.2 0.4 0.5 0.8 1.0 1.2 1.4 1.6 1.8 2.0
ng g 1
lw
Fig. 21 Median concentration of PBDE congeners with the highest detection frequency
in human milk in three European countries
The highest B D E concentrations were shown to be in Norway, but the reason is
probably the sample collection year, i.e. in Norway the samples were collected up to
10 years earlier (2003-2009) compared to the Netherlands or Slovakia (2011-14 and
2011-2012, respectively). The different years of sample collection and also differences
in the elimination half-lives [107] might be also the reason for the different congener
36
DNT concentrations in human milk
distribution in the three countries, i.e. in Norway the dominant congener was BDE 47,
while in the Netherlands it was B D E 153.
Some hydroxylated metabolites of PBDEs were reported to be more toxic than the
parent compounds [61]. Nevertheless, their determination in human matrices in the
literature is currently limited to a handful of studies. Athanasiadou et al. (2008)
measured the concentrations in serum of mothers and children living or working at
municipal waste disposal sites in serum in Manague and the concentrations ranged from
0.14 to 9.5 ng g"1
lw for both groups [98]. Zota et al. (2011) and Qm et al. (2009)
reported concentrations of two hydroxylated B D E 47 isomers in California and Indiana,
US ranging from 0.2-5.2 ng g"1
lw in both studies [59,108]. To the best of our
knowledge, only one study from Spain reported concentrations of 5 OH-BDE
congeners in human milk samples, ranging from 0.02-0.56 ng g"1
lw for all congeners
[109]. However, in 24 out of 32 milk samples, no OH-BDEs were detected. In our milk
samples, all OH-BDE isomers were <LOD, i.e.0.05-0.1 ng g" lw.
The sums of the 12 most often detected AFRs (PBBz, HBB, PBT, p-TBX, EH-TBB,
BEH-TEBP, BTBPE, syn-DDC-CO, anti-DDC-CO, DBE-DBCH, TBP-DBPE and
ATE) were 0.14, 0.25 and 0.23 ng g"1
lw in Norway, the Netherlands and Slovakia,
respectively. This is 2-15 times lower compared to the Z7 PBDEs. Out of 19 AFRs
measured in the milk samples, PBBz, HBB, PBT and EH-TBB were detected in over
43% of all samples (Fig. 24). Other determined compounds were detected with lower
detection frequencies between 0-67% (Fig. 22).
8.4 OH-BDEs
8.5 AFRs
37
DNT concentrations in human milk
Norway the Netherlands
0.40
0.35
0.30
0.25
^0.20
" 0.15
0.10
0.05
0.00
B
^ D P T E
Detection frequency, %
1.00 -
0.90 -
0.80 -
0.70 -
3 0.60 "«,0.50
-
c
0.40 -
0.30 -
0.20 )Bn,0.10
- v
1 0.00
DBE-DBCH1
40 60 B
Detection frequency, %
Slovakia
0.05
0.00
Detection frequency, %
Fig. 22 The dependence of the median concentrations in human milk samples on the
detection frequency in Norway, the Netherlands and Slovakia, the y-axis is different
in each graph
In all three countries, bromobenzene AFRs including HBB, PBBz and PBT were the
most often detected compounds. However, their median concentrations in human milk
were low (0.016-0.039 ng g"1
lw). The comparison of their concentrations is shown in
Fig. 23.
AFR5
C.C0 0.05 0.10 0.15 0,20
ngg"1
lw
Fig. 23 AFRs with the highest detection freuquencies in human milk samples
From Penta-BDE mixture replacements, only EH-TBB was present in more than
50% of the samples, but the concentrations did not exceed 0.2 ng g"1
lw. The other
component of PentaBDE mixture BEH-TEBP was detected only in 15-27% of all
samples, but in great concentrations which were comparable to the B D E congeners
(medians calculated from the concentrations >LOD ranged between 0.31-0.99 ng g"1
lw
in all countries). The concentrations of the replacement of Octa-BDE commercial
mixture, BTBPE, ranged between 0.01-0.03 ng g"1
lw and they were detected in
approximately one fourth of all samples.
This study provides unique results on A F R concentrations in human milk in
European countries. To the best of our knowledge, TBP-AE, T B X , TBCO, PBBz,
38
DNT concentrations in human milk
TBCT or D D C - C O M A have never been measured in human matrices despite the fact
they were detected in indoor environments which might be a potential exposure route
for humans similarly to PBDEs [110]. For other compounds, only a limited number of
studies on the concentrations of DDC-CO in human milk or serum have been available,
mostly from China [111-114]. The detailed comparison is provided in the paper III.
8.6 Methylmercury
Methylmercury was detected in >98% of the samples in all three countries. Data on the
MeHg concentrations in mother milk are very scarce in the literature, since MeHg is
usually measured in human hair. The median concentration in Norway (39 pg g"1
ww)
was approximately twice as great as in Slovakia and the Netherlands (18 pg g"1
ww in
both countries) which corresponds to the greater fish consumption in Norway [115].
9 Human risk assessment
9.1 Estimation of mothers' body burden - OCPs,
PCBs, MeHg
Two approaches for the estimation of mothers' body burden were used and compared
here. The top-down approach was based on the use of the concentrations in human milk
from which the intakes are calculated using the pharmacokinetic (PK) models. The
bottom-up approach looks at the intake of contaminants mainly from the diet as the
most important exposure source.
In the top-down approach for OCPs and PCBs, single-box steady state P K model
using the intrinsic elimination half-lives [7,116-119] was applied. For MeHg, a novel
steady state P K model derived based on the study from Carrier et al (2001) [120] was
used (details of the models and calculations are described in the Paper II). The
estimated top-down intakes were compared to the tolerable weekly or daily values
established by EFSA or US E P A (IRIS, US EPA, 2014). For MeHg the tolerable
weekly intake of 1.3 \xg kgb w
_ 1
was exceeded by two out of 360 Norwegian samples. For
iPCBs, no reference dose was available, but the concentration of 10 ng kgb w
_ 1
day" was
reported as a tolerable daily intake by French Agency for Food, Environmental and
39
Human risk assessment
Occupational Health & Safety (ANSES); higher concentrations can cause changes in
brain development of the foetus observed in an animal study [121]. This value was
exceeded in 10 out of 360 Norwegian samples (2.8%) and 6 out of 37 Slovak mothers
(16%), but in none of 120 Dutch samples. In the case of OCPs, the calculated intakes
constituted maximum 2.7% of the RfD for dieldrin indicating that the concentrations
should not affect the human health when assessing the non-cancer risk.
In the bottom-up approach, the intakes can be obtained by the the daily consumption
of the food commodity multiplied by the concentrations of the compound in food.
However, the accessibility of the concentrations of OCPs and PCBs in the selected food
commodities from the studied countries and from the required years (comparable to the
year of milk sample collection) was limited. For Norway, we used the published values
of the iPCB intakes [122]. For the Netherlands and Slovakia, averaged iPCB
concentrations from 22 European countries reported by EFSA were used [25]. For yHCH,
H C B and DDTs in Slovakia, data from the Slovak Food Research Institute,
Global Environment System database of W H O and the State Veterinary Administration
of the Czech Republic were used. The comparison between the top-down and bottomup
approach is shown in Fig. 24.
" > "IK I)
Norway
• Top-down
• 8ottorn-up
P # # #
Fig. 24 Comparison of the intakes of selected organochlorine compounds obtained
from top-down approach (black) and bottom-up (grey) in Slovakia, the Netherlands and
Norway
40
Human risk assessment
In the ideal case, the intakes from the top-down and bottom-up intakes should be
equal. However, it was shown that the bottom-up estimates were higher in most cases
compared to the top-down intakes. The uncertainties of both approaches are also
discussed in the paper II. In the top-down approach, sources of uncertainty may be
present in the analytical method where the average expanded uncertainties were below
20%. The expanded uncertainties of the individual compounds are the part of the
Supplementary Material of the paper I. Additional sources of uncertainties could be in
the differences in the reported values of the elimination half-lives [116,118] or in
absorption factors which might differ substantially [123-125]. In the bottom-up
approach, uncertainties included differences in daily consumption data among the
various dietary surveys, fat contents for the individual food commodities [126] or the
way of food preparation for the bottom-up estimates [127,128],
Based on the results shown in Fig. 24, the maximum difference between the topdown
and the bottom-up approach was by a factor of 7 for the ZiPCBs, DDE+DDT,
H C B or y-HCH. Taken into account all the above uncertainties, it can be concluded that
the food intake can explain the actual intake presented in humans.
9.2 Estimation of the children's body burden flame
retardants
In paper III we focused on infants who are considered a more vulnerable group to to
DNT exposure compared to the adults due to their immature and developing nervous
system. The total infant's intake included the intakes via breastfeeding and indoor
environment (i.e. dust ingestion and air inhalation), which were shown to be important
sources of exposure for FRs earlier [129],
The effects of the presence of FRs in the indoor environment were investigated by
calculating the daily intakes of 5 B D E congeners and 4 AFRs which occurred in the
milk samples with the highest detection frequencies. Since the data from the indoor dust
concentrations and indoor air in the Netherlands were not available, only total intakes
for Norway and Slovakia were estimated. The results are shown in Fig. 25. For both
countries, dietary intake via breastfeeding was the most significant exposure route.
However, in the case of B D E 99 in Norway and EH-TBB in Norway and Slovakia the
contributions of dust ingestion became important as well and corresponded up to 30%
of the overall infant exposure. For the more volatile compounds, such as PBBz, PBB or
HBB, the inhalation route presented 2-10% of the total exposure.
41
Human risk assessment
Fig.25 Contribution of the individual exposure pathways to the total infant's body
burden; intakes for BDE 28 in Slovakia were not calculated due to the low detection
frequency in the milk samples. The scale ofy-axis for PBDEs andAFRs is different
42
Epidemiological investigations
Epidemiological investigations
This section is only discussed in brief as most of the results are being further evaluated
by the Dutch or Norwegian epidemiologists participating in the D E N A M I C project.
The epidemiological paper ("Early life exposure to organochlorine compounds and
behavioural development in children" by Quaak et al.) investigates the association
between early life exposure to the selected organochlorine compounds, such as iPCBs,
HCB, HCHs, heptachlor epoxide, dieldrin and behavioural disorders at 18 months of
age in the Dutch cohort LINC (Linking endocrine disruptors in maternal Nutrition to
Child health). Behavioural development was evaluated using the Child Behaviour
Checklist 1.5-5 (CBCL) and several most important confounding factors, such as
a family history of A D H D , educational level, smoking or alcohol use during pregnancy
were checked. Separate regression models were composed for each compound-outcome
combination. Variables were categorized into tertiles ( T l , T2 and T3) and the results
showed positive associations between A D H D symptoms and early life exposure to the
highest concentrations (T3) of ZiPCBs, EHCHs, dieldrin, and T2 concentrations of
HCB. Higher scores were found on the externalizing behaviour scale of the C B C L after
exposure to dieldrin (T3) and EiPCBs (T2 and T3), but only for girls.
The results confirmed the influence of presence of the neurotoxic organochlorines
on the developmental disorders in children. However, due to the small sample size (for
the statistical analyses 59 mother-child pairs was assessed) more research is needed,
especially among preschool children, in order to further explore this relationship.
43
Conclusions and future perspectives
Conclusions and future perspectives
The main aim of this study was to develop the multi-class method for the determination
of 97 compounds from the various groups of proved or potential developmental
neurotoxicants. The method including lipid determination and dialysis clean-up step
using LDPE membrane was designed for the most efficient lipid removal with the
minimal solvent consumption and the use of non-chlorinated solvents. The validation of
the method showed low limits of quantification and high analyte recoveries. This
allowed us to quantify the compounds which are often not detected in human milk
samples, such as pyrethroids or alternative flame retardants. Due to this fact, the data on
emerging contaminants in particular are unique and could contribute to better
understanding of their toxic potential in child organisms.
The method thoroughly described in the standard operating procedure is utilized by
R E C E T O X Trace Analytical Laboratories within their analytical measurement.
Moreover, an internal reference material based on spiked pork fat (lard) was prepared
in order to check the analytical quality of the measurements reqularly. The method was
subsequently used for the analysis of more than 500 human milk samples with the main
aim to determine the extent of exposure to legacy and emerging developmental
neurotoxicants in three different European countries representing Northern (Norway),
Western (the Netherlands) and Eastern Europe (Slovakia). The concentrations of these
compounds in humans are currently being evaluated by the epidemiologists of the
D E N A M I C project and new links between the presence of these compounds and the
neurotoxic disorders in children including A D H D , A S D or others are being revealed.
Multi-class method development should be strongly supported in further studies as
we are not exposed to a single chemical but to the whole mixtures of compounds which
might interact with each other. Toxicological studies could be also employed to use
concentrations from multi-analyte studies to test the effects of these mixtures.
Emerging high resolution M S instruments, such Orbitrap M S can be used in the
future for non-target analysis to reveal more toxicants present in human samples.
However, these techniques have higher detection limits, so for the current use
compounds present at low cocnentrations targeted methods will still provide useful
information on their environmental distribution and/or fate in human body.
44
Appendices
Appendix 1: Previously used methods for the extraction of
non-polar contaminants from human milk
Table SI: The extraction methods used for the extraction of non-polar contanimants
from human milk
Method usual modifications
for the non-polar
compounds
advantages disadvantages Ref
LLE ft-hexane:acetone=2:1 enables to determine lipids. time-consuming. [130-132]
(v/v), n- cheap, no special high solvent
hexane:diethyl instrumentation needed consumption
ether= 1:1 (v/v), or n-
hexane
PLE «-hexane:DCM=2:l enables to determine lipids. initial cost is high. [133,134]
(v/v), acetone:«- short extraction time, low more matrix is
hexane=l:l (v/v) solvent consumption,
automated
extracted, requires
freeze-dried
samples
QuEChERS ACN+MgS04 and
CH3 COONa
cheap, fast, also clean-up no lipid
determination
[135,136]
SPE C18 sorbent, florisil cheap, small volumes of no lipid [19,87,
or diatomaceous earth solvents, cleaner extracts
and possibility of
automatization
determination 137]
45
Appendix 2: Standard Operating Procedures (SOPs) for the
determination of the developmental neurotoxicants in
human milk (in Czech)
3 parts
SOP-LSA-054: Extraction of the non-polar organic contaminants from mother milk
and lipid determination (2 pages)
SOP-LSA-055: Clean-up of mother milk extracts after the PLE extraction (3 pages)
SOP-LSA-056: Derivatization of the polar fraction of the mother milk samples for the
GC-MS determination of OH-BDEs (1 page)
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
Standardní operační postup:
Název dokumentu:
Datum vydání:
Vypracoval:
Schválil:
SOP-LSA-054
Extrakce nepolárních organických kontaminantů
z mateřského mléka a stanovení lipidů
25.12.2016
RNDr. Eliška Čechová
Ing. Anton Kočan, CSc.
© Žádná část tohoto standardního operačního postupu, tak v tištěné jako i v elektronické
formě, nesmí být reprodukována nebo použita bez povolení Centra pro výzkum toxických
látek v prostředí, MU Brno
Aplikovatelnost metody
Uvedenou metodu lze použít k extrakci nepolárních látek (OCPs, PCBs, PBDEs, AFRs,
pyrethroidy) a mírně polárních látek (OH-PBDEs) z mateřského mléka včetně
kvantitativního stanovení lipidů
Chemikálie
N a 2 S 0 4 (vypečený), na doplnění extrakčních cel: Ottawa písek na zrychlenou tlakovou
extrakci rozpouštědlem (PSE) předem čištěný čisticím programem na PSE nejprve
toluenem, poté extrakční směsí «-hexan:dichlormethan:methanol=5:2:l, v/v/v),
organická rozpouštědla kvality pro ultrastopovou analýzu: methanol (MeOH),
dichlormethan (DCM), w-hexan
Pracovní postup
Poznámka 1: pro veškeré analýzy používat pouze sklo po umytí v myčce laboratorního
skla a následném vypečení při 400 °C (min. 4 h)
1. Příprava vzorku před extrakcí
a) dodaný vzorek mléka vložit na cca 20 min do ultrazvukové lázně pro zajištění
dokonalé homogenity
b) 8-10 ml mléka (není nutné vážit) přepipetovat do Petriho misky, přiklopit
víčkem s malým otvorem uprostřed a opatrně umísit do mrazničky vedle lyofilizátoru
na cca 2-3 hodiny
Číslo SOP: SOP-LSA-054 Číslo vydání: 1
Název SOP: Extrakce nepolárních org. kontaminantů z mat. mléka a stanovení lipidů
Vypracovala: E. Cechová SchválikA. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
c) lyofilizace vzorků 24 hodin (lze ponechat i přes víkend)
2. Tlaková extrakce rozpouštědlem (PSE)
a) důkladné rozetření lyofilozovaného vzorku s 15 g vypečeného Na2S04 ve větší
třecí misce
b) naplnění vzorku do 40 ml extrakční cely v tomto pořadí:
čistý filtr -> 1 1.5 lžičky čištěného pisku -> 1 1.5 lžičky (vypečeného) Na2S04 ->
rozetřený vzorek -> spike 50 jul značených standardů #859a + #860 a (dle Seznamu
standardů LSA) -> 1 1.5 lžičky (vypečeného) Na2S04 -> 1—1.5 lžičky čištěného pisku
(Bůchi) -> čistý filtr
c) extrakce metodou „DriedMilk-whole-3c" (65 °C), vhodné nechat extraktor cca
15 min před extrakcí vytemperovat. Extrakty jímat do označených Syncore zkumavek
d) extrakty odpařeny na Syncore metodou „hex:DCM:MeOH-KRATSi" na cca 5
8 ml, poté kvantitativní převedení hexanem do zvážené 22 ml vialky a odpaření
rozpouštědla pod dusíkem.
Poznámka 2: Opatrně při zpracovávání procesních blanku, aby nedošlo k jej ich
odpaření úplně do sucha, nedávat do sušárny!!
e) 22 ml vialky s vyextrahovaným mléčným tukem (NE procesní blank!) umístit
na 1 hod do vyhřáté sušárny na biologické vzorky (60 °C), poté nechat 20 min
ekvilibrovat při laboratorní teplotě a zvážit - z rozdílu získána hmotnost lipidů.
f) vyextrahovaný mléčný tuk rozpustit ve 400 ul hexanu (lze takto uchovat
v mrazničce před dalším zpracováváním extraktu).
Následuje dvoukrokové čištění extraktů popsané v SOP-LSA-055.
Číslo SOP: SOP-LSA-054 Číslo vydání: 1
Název SOP: Extrakce nepolárních org. kontaminantů z mat. mléka a stanovení lipidů
Vypracovala: E. Cechová Schválil:A. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
Standardní operační postup:
Název dokumentu:
Datum vydání:
Vypracoval:
Schválil:
SOP-LSA-055
Čištění extraktů mateřského mléka po PSE extrakci
25.12.2016
RNDr. Eliška Čechová
Ing. Anton Kočan, CSc.
© Žádná část tohoto standardního operačního postupu, tak v tištěné jako i v elektronické
formě, nesmí být reprodukována nebo použita bez povolení Centra pro výzkum
toxických látek v prostředí, MU Brno
Shrnutí metody
Dva čisticí kroky, které následují za SOP-LSA-054, slouží k odstranění lipidů z
extraktů mateřského mléka. Po dialýze následuje kombinované "SPE", které umožňuje
frakcionací zvlášť stanovit nepolární environmentálni kontaminanty a mírně polární
OH-PBDE metabolity
Aplikovatelnost metody
Stejné nebo obdobné čisticí kroky lze aplikovat i na jiné lipidické (biologické) vzorky,
kde je nutné s velkou účinností odstranit tuk před instrumentální analýzou. Maximální
hmotnost tuku použitelná pro dialýzu není omezena.
Chemikálie
LDPE membrána (5 cm x 10 cm, Polymer Institut Brno), SPE kolonky Agilent C l 8
Bond Elut (500 mg), skleněné prázdné SPE kolonky a papírové filtry, teflonové spojky
pro spojení SPE kolonek, kyselá alumina (vypečená na 400 °C, 12 hod), kyselina
octová (HAc, 100%, Sigma Aldrich), miliQ H 2 0 , organická rozpouštědla kvality pro
ultrastopovou analýzu: w-hexan, acetonitril.
Číslo SOP: SOP-LSA-055 Číslo vydání: 1
Název SOP: Čištění extraktů mateřského mléka po PSE extrakci
Vypracovala: E. Čechová Schválil: A. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
Pracovní postup
Dialýza
a) LDPE membrány před plněním 2 dny macerovat v^-hexanu pro odstranění
možných interferentů.
b) vyextrahovaný mléčný tuk doplnit rozpuštěný ve 400 ^1 hexanu naplnit do 10 cm
dlouhé na obou stranách zatavené dialyzační membrány plastovou injekční
stříkačkou s tenkou jehlou proplach vialky 250 JLLI hexanu. Z membrány odstranit
maximum bublin a nahoře opatrně zatavit tavičkou.
c) membránu vložit do 40 ml tmavé vialky naplnenej 20 ml hexanu. Vialku umístit do
ledničky (10 °C) a po 24 hod vyměnit rozpouštědlo (slévat do 60 ml vialky).
Celkem v ledničce 48 hod
d) vzorek odpařit pod dusíkem do sucha a rozpustit ve 4 ml A C N
"Kombinované SPE"
Příprava absorbentu - kyselá alumina (AI2O3) deakt. 10% H2 0
a) pro 16 vzorků za den pomocí malé nálevky s tenkou stopkou navážit do 60 ml
vialky 45 g čerstvě vypečené kyselé aluminy (používat max. týden starou
vypečenou kyselou aluminu) a přidat pasteurkou 5 g miliQ vody
b) důkladně třepat, aby byl sorbent homogenní, bez hrudek
Příprava skleněných SPE kolonek
a) do vypečených kolonek opatrně pinzetou vložit papírový filtr a hrubší skleněnou
tyčinkou jej „utěsnit"
b) pomocí nálevky navážit do každé kolonky 3 g kyselé A12 03 deakt. 10% H 2 0
Příprava SPE manifoldu
a) do víka manifoldu (Supelco) do jednotlivých pozic vsunout jednorázové linery
(PTFE, Sigma Aldrich)
b) do linerů umístit označené skleněné kolonky s 3 g kyselé AI2O3 deakt. 10% H 2 0
c) na skleněnou kolonku pomocí teflonových spojek (předem vyčištěných 10 min
v hexanu v ultrazvuku) umístit SPE kolonky C l 8 Bond Elut (500 mg)
d) proplach sorbentů 4+4 ml A C N (jímat do plastové vaničky umístěné v manifoldu)
Číslo SOP: SOP-LSA-055 Číslo vydání: 1
Název SOP: Čištění extraktů mateřského mléka po PSE extrakci
Vypracovala: E. Cechová Schválil: A. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
SPE - sběr frakce 1 - NON-POLAR (vyměnit vaničku v manifoldu za vialky „non-
polar")
a) vzorky v 60 ml vialkách rozpuštěné ve 4 ml A C N dát na 5 min do ultrazvukové
lázně
b) nanesení vzorku dlouhou pasteurkou na kondiciovaný sorbent
c) proplach vialek 3 ml A C N (oplach 64^rát pasteurkou) a znovu nanesení na sorbent
d) proplach vialek 2.5 ml A C N (oplach 64^rát pasteurkou) a nanesení na sorbent
e) po posledním nanesení vysát zbytky A C N opatrně pod vakuem
SPE - sběr frakce 2 - METABOLITES (vyměnit vialky „non-polar" za
„metabolites")
a) příprava 120 ml 5% HAc (v/v) v A C N : tj. 6 ml HAc +114 ml A C N v odměrném
válci do kádinky
b) z manifoldu odebrat vrchní kolonky (Cl 8) a teflonové spojky
c) pomalu eluovat 3.5 + 3.5 ml 5% HAc v A C N ze skleněných kolonek
d) zbytky rozpouštědla opatrně vysát pod vakuem
Postup derivatizace je popsán v SOP-LSA-056.
Číslo SOP: SOP-LSA-055 Číslo vydání: 1
Název SOP: Čištění extraktů mateřského mléka po PSE extrakci
Vypracovala: E. Cechová Schválil: A. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
Standardní operační postup:
Název dokumentu:
Datum vydání:
Vypracoval:
Schválil:
SOP-LSA-056
Derivatizace polární frakce vzorků mateřského mléka
pro GC-MS kvantifikaci OH-PBDEs
25.12.2016
RNDr. Eliška Čechová
Ing. Anton Kočan, CSc.
© Žádná část tohoto standardního operačního postupu, tak v tištěné jako i v
elektronické formě, nesmí být reprodukována nebo použita bez povolení Centra pro
výzkum toxických látek v prostředí, MU Brno
Shrnutí metody
Následující krok navazuje na SOP-LSA-054 a SOP-LSA-055, kdy je v posledním
čisticím kroku ("kombinované SPE") zvlášť jímána nepolární a polární frakce. Tato
polární frakce je dále derivatizována (methylace) dle níže uvedeného návodu pro
stanovení OH-PBDEs.
Aplikovatelnost metody
Uvedený postup lze použít i na jiné OH-substituované metabolity, např. OH-PCBs.
Použité chemikálie
2 M roztok trimethylsilyldiazomethanu (TMSD) v hexanu (Sigma Aldrich, Německo),
methanol Chromasolv gradient grade (Sigma Aldrich, Německo)
POZN. Pracovat v uzavřené digestoři!
Postup derivatizace
a) vzorky z polární frakce po "SPE" čisticím kroku jemně odpařit do sucha (do
vymizení octového zápachu po HAc) - lze ponechat přes noc v digestoři v
otevřených vialkách mírně přikrytých alobalem
b) přídavek 500 \ú MeOH a 100 nl roztoku TMSD, vortex vzorků
c) zahřívání vialek v předem vytemperované Labevě na 50 °C (15 min), musí přetrvat
žluté zabarvení vzorku, pokud vymizí, je nutné přidat derivatizační činidlo (TMSD)
Číslo SOP: SOP-LSA-056 Číslo vydání: 1
Název SOP: Čištění extraktů mateřského mléka po PSE extrakci
Vypracovala: E. Čechová Schválil: A. Kočan
Masarykova univerzita
RECETOX: Laboratoře stopové analýzy
Kamenice 753/5, pavilon A29, 625 00 Brno
d) odpaření vzorků pod mírným proudem N 2 a kvantitativní převedení MeOH do
minivialky
e) před měřením GC-HRMS přídavek syrmge-standardu 1 3
C B D E 138
Číslo SOP: SOP-LSA-056 Číslo vydání: 1
Název SOP: Derivatizace polární frakce vzorků mateřského mléka
Vypracovala: E. Cechová Schválil: A. Kočan
Appendices
Appendix 3: Concentrations of measured DNTs in human
milk
Norway
Table la Distribution of OCP concentrations in Norwegian human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
PeCB 8 14.63 16.05
HCB 100 5.61 6.00 7.67 11.78 13.50 21.49
a-HCH 68 0.06 0.17 0.21 0.25
p-HCH 96 1.60 2.50 5.72 12.88 17.00 31.77
y-HCH 66 0.31 0.68 1.10 1.81
5-HCH 5 0.05 0.05
O,/J'-DDE 83 0.04 0.09 0.11 0.13
/7,/7'DDE 100 16.99 22.04 51.61 143.63 187.73 224.97
O,/J'-DDD 36 0.04 0.07 0.08
W ' - D D D 97 0.04 0.06 0.19 0.51 0.67 0.89
O,/J'-DDT 97 0.08 0.09 0.20 0.44 0.52 0.62
p,p'-DDT 99 0.74 0.90 1.79 4.49 5.54 7.47
heptachlor 1
heptachlor epoxide 98 0.33 0.41 0.92 2.13 2.77 3.44
aldrin 0 0.29 0.29 0.29 0.29 0.29 0.29
dieldrin 100 0.92 1.13 2.05 4.05 5.51 7.30
endrin 0
endrin aldehyde 4 3.99
endrin ketone 0 1.53 1.53 1.53 1.53 1.53 1.53
a-chlordane 3 7.11
y-chlordane 8 5.86 6.67
a-endosultan 5 0.35 2.98 8.39
P-endosulfan 3 2.48 2.83
endosulfan sulfate 64 0.40 0.56 0.60
methoxychlor 8 0.24 12.04
mirex 99 0.08 0.10 0.23 0.54 0.75 1.07
54
Appendices
Table lb Distribution of pyrethroid concentrations in Norwegian human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
tefluthrin 11 1.07 1.14 1.27
transfluthrin 2
chlorpyrifos 3 2.41
piperonyl-butoxide 29 1.55 2.86 16.28
bifenthrin 7 3.18 6.00
tetramethrin-2 1
cyhalothrin 2
acrinathrin 1
c/s-permethrin 69 0.07 0.21 0.39 0.60
fraws-permethrin 51 0.12 0.36 0.53 0.71
ß-cyfluthrin-3 2
ß-cyfluthrin-4 1
Cypermethrin-1 1
cypermethrin-2 0
a-cypermethrin-3 2
cypermethrin-4 0
fenvalerate-1 1 0.15 0.15 0.15 0.15 0.15 0.15
deltamethrin-2 0
Table lc Distribution of PCB concentrations in Norwegian human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
PCB 28 99 0.84 0.97 1.56 2.79 3.43 4.16
PCB 52 99 0.24 0.29 0.51 1.10 1.53 1.97
PCB 101 96 0.27 0.31 0.58 1.26 1.81 2.40
PCB 138 100 7.58 8.81 17.43 35.62 43.35 62.32
PCB 153 100 12.64 14.77 27.44 55.06 67.25 98.83
PCB 180 100 5.94 7.75 13.93 27.87 36.12 48.05
PCB 118 98 2.14 2.60 5.22 10.67 14.21 20.27
55
Appendices
Table Id Distribution of BDE concentrations in Norwegian human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
BDE 28 59 0.08 0.29 0.46 0.91
BDE 47 82 1.01 3.48 6.18 10.14
BDE 66 18 0.13 0.24 0.37
BDE 100 83 0.26 0.72 1.13 1.51
BDE 99 81 0.27 0.84 1.33 1.99
BDE 85 25 0.05 0.18 0.32 0.40
BDE 154 40 0.09 0.11 0.14
BDE 153 81 0.22 0.27 0.48 1.02 1.35 1.87
BDE 183 28 0.12 0.18 0.25
BDE 209 1
Table le Distribution of AFR concentrations in Norwegian human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
TBP-AE 6 0.15 0.15
DBE-DBCH 25 0.07 0.08 0.09
TBX 14 0.03 0.04 0.04
TBP-BAE 0
TBCO 0
PBBz 97 0.00 0.01 0.02 0.05 0.06 0.07
TBCT 0
DDC-COMA 1
PBT 83 0.01 0.01 0.03 0.05 0.06 0.09
PBEB 2
DPTE 10 0.12 0.25 0.43
HBB 41 0.03 0.06 0.08 0.11
PBBA 3 0.02
DBHCTD 0
EH-TBB 46 0.02 0.07 0.12 1.17
BTBPE 23 0.10 0.14 0.29
syn-DDC-CO 7 0.88 1.70
anti-DDC-CO 26 0.09 0.18 0.20
BEH-TEBP 27 1.09 1.61 2.99
56
Appendices
The Netherlands
Table 2a Distribution of OCP concentrations in Dutch human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
PeCB 5 0.47 0.49
HCB 100 4.29 4.39 6.22 8.56 9.67 11.14
a-HCH 97 0.04 0.04 0.06 0.08 0.10 0.10
p-HCH 100 2.10 2.42 3.98 7.56 8.03 8.57
y-HCH 97 0.07 0.09 0.18 0.35 0.47 0.60
5-HCH 14 0.04 0.06 0.07
O,/J'-DDE 100 0.03 0.04 0.06 0.11 0.13 0.17
/7,/7'DDE 99 24.42 27.38 49.46 92.33 121.62 333.43
o,p'-DDD 97 0.01 0.01 0.02 0.03 0.05 0.06
p,p'-DDD 93 0.04 0.14 0.29 0.38 0.62
O,/J'-DDT 97 0.07 0.09 0.15 0.28 0.32 0.38
/7,/7'DDT 100 0.88 0.97 1.54 2.89 3.87 5.14
heptachlor 76 0.01 0.01 0.01 0.02
heptachlor epoxide 99 1.08 1.22 2.09 3.12 3.34 3.51
aldrin 1
dieldrin 99 1.24 1.38 2.27 3.54 4.01 4.82
endrin 0
endrin aldehyde 0
endrin ketone 0
a-chlordane 0
y-chlordane 0
a-endosultan 3 0.20
P-endosulfan 2
endosulfan sulfate 97 0.03 0.04 0.09 0.29 0.45 0.65
methoxychlor 5 0.03 0.03
mirex 99 0.05 0.06 0.12 0.25 0.30 0.36
Table 2b Distribution of pyrethroid concentrations in Dutch human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
tefluthrin 22 0.12 0.25 0.43
transfluthrin 12 0.77 0.97 1.07
chlorpyrifos 74 0.55 0.96 1.16 1.71
piperonyl-butoxide 86 0.26 1.27 2.13 2.70
57
Appendices
bifenthrin 9 0.15 0.29 0.31 0.31
tetramethrin-2 0
cyhalothrin 52 0.09 0.27 0.53 0.63
acrinathrin 0
c/s-permethrin 88 0.06 0.38 0.69 1.02
fraws-permethrin 88 0.08 0.40 0.76 1.27
P-cyfluthrin-3 8 0.42 0.42
P-cyfluthrin-4 8 0.23 0.23
cypermethrin-1 18 0.22 0.24 0.24
cypermethrin-2 8 0.62 0.63
a-cypermethrin-3 31 0.54 0.56 0.58
cypermethrin-4 11 0.51 0.58 0.62
fenvalerate-1 12 0.14 0.16 0.17
deltamethrin-2 28 0.74 0.84 0.89
Table 2c Distribution of PCB concentrations in Dutch human milk samples
Analyte DF, % P5 P10 P50 P90 P95 P97.5
PCB 28 100 0.49 0.53 0.79 1.39 1.68 2.05
PCB 52 100 0.09 0.10 0.17 0.47 0.69 0.81
PCB 101 100 0.09 0.11 0.19 0.36 0.45 0.54
PCB 138 100 5.38 6.30 10.68 17.69 23.42 29.17
PCB 153 100 7.55 8.95 15.95 25.94 30.87 35.03
PCB 180 100 4.54 5.24 10.72 17.71 22.13 24.13
PCB 118 97 1.79 2.04 3.59 6.48 7.35 8.92
Table 2d Distribution of BDE concentrations in Dutch human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
BDE 28 97 0.01 0.01 0.02 0.05 0.06 0.07
BDE 47 100 0.06 0.07 0.20 0.55 1.05 1.66
BDE 66 43 0.02 0.02 0.03
BDE 100 100 0.02 0.02 0.06 0.15 0.18 0.26
58
Appendices
BDE 99 100 0.02 0.03 0.08 0.18 0.23 0.35
BDE 85 24 0.03 0.05 0.10
BDE 154 41 0.04 0.05 0.13
BDE 153 100 0.22 0.28 0.48 0.84 0.96 1.02
BDE 183 56 0.04 0.09 0.11 0.14
BDE 209 8 20.89 24.16
Table 2e Distribution of AFR concentrations in Dutch human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
TBP-AE 0
DBE-DBCH 26 0.03 0.04 0.05
TBX 69 0.02 0.04 0.13 0.28
TBP-BAE 5 0.01 0.01
TBCO 0
PBBz 75 0.02 0.04 0.06 0.07
TBCT 0
DDC-COMA 2
PBT 85 0.02 0.05 0.07 0.12
PBEB 0
DPTE 0
HBB 88 0.04 0.08 0.10 0.14
PBBA 0
DBHCTD 0
EH-TBB 69 0.13 0.54 0.68 0.82
BTBPE 26 0.16 2.38 10.65
syn-DDC-CO 9 0.85 1.03
anti-DDC-CO 20 0.18 0.49 1.02
BEH-TEBP 15 1.95 2.75 3.84
59
Appendices
Slovakia
Table 3a Distribution of OCP concentrations in Slovak human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
PeCB 5 0.73 0.74
HCB 100 10.38 10.61 12.89 16.70 18.70 19.28
a-HCH 70 0.05 0.08 0.10 0.12
ß-HCH 100 2.95 3.63 6.98 16.39 18.76 19.75
y-HCH 62 0.15 0.24 0.32 0.34
8-HCH 0
0,/?'-DDE 100 0.01 0.01 0.05 0.14 0.25 0.27
/7,/7'DDE 100 79.48 92.07 166.78 579.15 670.32 705.83
0,/?'-DDD 57 0.03 0.08 0.08 0.22
p,p'-DDD 100 0.46 0.49 0.84 2.16 2.54 2.90
o,p'DVT 100 0.19 0.20 0.38 0.94 1.07 1.81
p,p'DVT 100 4.95 5.42 8.74 17.89 25.77 27.96
heptachlor 0
heptachlor epoxide 100 0.15 0.16 0.34 0.73 0.95 1.00
aldrin 0
dieldrin 95 0.23 0.41 0.88 1.08 1.47
endrin 0
endrin aldehyde 0
endrin ketone 0
a-chlordane 0
y-chlordane 0
a-endosultan 3 0.16
ß-endosulfan 0
endosulfan sulfate 0
methoxychlor 0
mirex 100 0.07 0.08 0.18 0.34 0.38 0.39
Table 3b Distribution of pyrethroid concentrations in Slovak human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
tefluthrin 0
transfluthrin 0
chlorpyrifos 85 1.27 2.29 2.80 5.01
piperonyl butoxide 24 0.19 0.25 0.28
60
Appendices
bifenthrin 0
tetramethrin-2 0
cyhalothrin 5 1.39 1.43
acrinathrin 0
c/s-permethrin 89 0.04 0.11 0.15 0.51
fraws-permethrin 78 0.08 0.16 0.27 0.82
ß-cyfluthrin-3 0
ß-cyfluthrin-4 0
Cypermethrin-1 0
cypermethrin-2 0
a-cypermethrin-3 5 0.36 0.37
cypermethrin-4 0
fenvalerate-1 1
deltamethrin-2 0
Table 3c Distribution of PCB concentrations in Slovak human milk samples
BF, % P5 P10 P50 P90 P95 P97.5
PCB 28 100 0.84 0.91 1.11 1.84 2.73 3.36
PCB 52 95 0.10 0.13 0.19 0.20 0.31
PCB 101 100 0.13 0.14 0.22 0.34 0.35 0.59
PCB 138 100 14.57 17.90 30.70 72.94 91.66 99.33
PCB 153 100 27.02 30.41 59.09 121.28 133.39 153.57
PCB 180 100 19.92 27.36 44.32 90.94 97.84 125.98
PCB 118 100 1.54 2.22 3.51 8.48 10.22 16.46
Table 3d Distribution of BDE concentrations in Slovak human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
BDE 28 11 0.08 0.09 0.09
BDE 47 100 0.08 0.09 0.17 0.57 1.14 1.33
BDE 66 3 0.02
BDE 100 100 0.02 0.02 0.04 0.13 0.17 0.29
BDE 99 70 0.07 0.20 0.29 0.37
BDE 85 5 0.04 0.04
BDE 154 3 0.02
61
Appendices
BDE 153 100 0.07 0.09 0.12 0.33 0.42 0.65
BDE 183 32 0.05 0.07 0.07
BDE 209 0
Table 3e Distribution of AFR concentrations in Slovak human milk samples
DF, % P5 P10 P50 P90 P95 P97.5
TBP-AE 0
DBE-DBCH 32 0.04 0.04 0.05
TBX 0
TBP-BAE 3 0.01
TBCO 0
PBBz 100 0.02 0.03 0.04 0.10 0.13 0.14
TBCT 0
DDC-COMA 0
PBT 100 0.02 0.02 0.03 0.08 0.09 0.10
PBEB 3 0.00
DPTE 46 0.12 0.14 0.16
HBB 62 0.02 0.08 0.17 0.18
PBBA 0
DBHCTD 0
EH-TBB 59 0.02 0.07 0.09 0.10
BTBPE 22 0.05 0.08 0.09
syn-DDC-CO 3 0.11
anti-DDC-CO 24 0.10 0.13 0.14
BEH-TEBP 27 0.96 1.89 2.35
62
References
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[131] M M . Frias, M.J. Torres, A G . Fremch, J.L. Martinez Vidal, F. OleaSerrano,
N . Olea, Determination of organochlorine compounds in human
biological samples by GC-MS/MS, Biomed. Chromatogr. 18 (2004) 102-
111. doi:10.1002/bmc.300.
[132] H. Bouwman, B. Sereda, H . M . Meinhardt, Simultaneous presence of
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DDT and pyrethroid residues in human breast milk from a malaria
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doi:http://dx.doi.org/10.1016/j.envpol.2006.02.002.
[133] S. Lacorte, M . Guillamon, Validation of a pressurized solvent extraction
and G C - N C I - M S method for the low level determination of 40
polybrominated diphenyl ethers in mothers' milk, Chemosphere. 73
(2008) 70-75. doi:http://dx.doi.org/10.1016/j.chemosphere.2008.05.021.
[134] G. Devanathan, A . Subramanian, A . Sudaryanto, S. Takahashi, T. Isobe,
S. Tanabe, Brominated flame retardants and polychlorinated biphenyls in
human breast milk from several locations in India: Potential contaminant
sources in a municipal dumping site, Environ. Int. 39 (2012) 87-95.
doi:http://dx.doi.org/l 0.1016/j .envint.2011.10.005.
[135] I.-S. Jeong, B.-M. Kwak, J.-H. Ahn, S.-H. Jeong, Determination of
pesticide residues in milk using a QuEChERS-based method developed
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doi:http://dx.doi.org/l 0.1016/j .foodchem.2012.01.004.
[136] O.P. Luzardo Ruiz-Suärez, N , Almeida-Gonzälez M , HenriquezHernändez
L A , Zumbado M , Boada LD., Multi-residue method for the
determination of 57 persistent organic pollutants in human milk and
colostrum using a QuEChERS-based extraction procedure., Anal Bioanal
Chem. 405 (2013) 9523-9536. doi:10.1007/s00216-013-7377-0.
[137] M A . Alawi, N . Ammari, Y . al-Shuraiki, Organochlorine pesticide
contaminations in human milk samples from women living in Amman,
Jordan., Arch. Environ. Contam. Toxicol. 23 (1992) 235-239.
76
Cumulative thesis
Paper I
An Effective Clean-up Technique for GC/EI-HRMS Determination of
Developmental Neurotoxicants in Human Breast Milk
Eliška Čechová1
, Marta Seifertova1
, Petr Kukučka1
'2
, Šimon Vojta1
, Ilona Quaak3
,
Marijke de Cock3
, Margot van de Bor3
, Anton Kočan1
1 Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science,
Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
2 Man-Technology-Environment Research Centre, Örebro University, 701 82 Örebro, Sweden
3 Department ofHealth and Life Sciences, Faculty ofEarth and Life Sciences, Vrije University
Amsterdam, De Boelelaan 1085, 1081 HVAmsterdam, The Netherlands
Reprinted with permission from
Analytical and Bioanalytical Chemistry 2017, Volume 409, Issue 5
Copyright 2017 Springer
77
78
Anal Bioanal Chem
DOI 10.1007/s00216-016-0059-y
^JJJJ^ CrossMark
R
ESEARCH PAPER
An effective clean-up technique for GC/EI-HRMS determination
of developmental neurotoxicants in human breast milk
Eliška Čechová1
• Marta Seifertova1
• Petr Kukučka1 , 1
• Šimon Vojta1
• Ilona Quaak3
•
Marijke de Cock3
• Margot van de Bor3
• Anton Kočan1
Received: 1 July 2016 /Revised: 7 October 2016 /Accepted: 25 October 2016
© Springer-Verlag Berlin Heidelberg 2016
Abstract The increasing number of children suffering from
developmental disorders has raised questions regarding their
association with the presence of environmental contaminants
in mothers and children. We therefore developed a new method
for the determination of 78 proven and potential developmental
neurotoxicants, including polychlorinated biphenyls,
legacy pesticides, pyrethroids, and old and new halogenated
flame retardants in breast milk. The essential part of sample
preparation was dialysis as a non-destructive clean-up step
which was newly used at 10 °C and showed more efficient
lipid removal (up to 96%) than the conventional methods such
as gel permeation chromatography or freezing-lipid filtration
and thus ensured low limits of detection (LOD) by reducing
the sample volume prior to injection. Next advantages were
significant solvent reduction and no risk of sample cross-contamination.
Gas chromatography coupled with high resolution
mass spectrometry (GC-HRMS) was subsequently used for
the separation and compound quantification. The method
was validated using breast milk samples fortified with the
Electronic supplementary material The online version of this article
(doi:10.1007/s00216-016-0059-y) contains supplementary material,
which is available to authorized users.
Eliška Čechová
cechová® recetox.muni.cz
Research Centre for Toxic Compounds in the Environment
(RECETOX), Faculty of Science, Masaryk University, Kamenice
753/5, 625 00 Brno, Czech Republic
Man-Technology-Environment Research Centre, Örebro University,
701 82 Örebro, Sweden
Department of Health and Life Sciences, Faculty of Earth and Life
Sciences, Vrije Universiteit, De Boelelaan 1085, 1081
HV Amsterdam, The Netherlands
analyzed compounds. Recoveries for most of the compounds
ranged from 63 to 121 % with a relative standard deviation of
2-25%, and LODs ranged between 0.001 and 0.87 ng g_ 1
lipid weight. The method was applied to breast milk samples
from a Dutch birth cohort where 35 out of the 78 compounds
were quantified in more than 60% of the samples. For novel
flame retardants, the method provides unique results regarding
their occurrence in human matrices in Europe. Overall, the
analysis of a complex mixture of developmental
neurotoxicants could be useful for the assessment of the influence
of the studied compounds to child health and
development.
Keywords Developmental neurotoxicants - Dialysis •
GC-MS • Human breast milk • Non-destructive clean-up
Introduction
Worldwide, up to 15% of all children are affected by developmental
disorders such as attention deficit hyperactivity disorder
(ADHD), autism spectrum disorders (ASD), or learning
problems [1]. A possible link has been revealed between these
disorders and early life exposure to several environmental
pollutants, which include polychlorinated biphenyls (PCBs),
selected organochlorine pesticides (OCPs), pyrethroids, organophosphate
pesticides, polybrominated diphenyl ethers
(PBDEs), and novel flame retardants (NFRs) [2-6]. The toxic
effects of NFRs are still mostly unknown, but some NFRs can
due to structural similarities also act as developmental
neurotoxicants, such as decabromodiphenyl ethane
(DBDPE) and BDE-209 [7]. PCBs, OCPs, and PBDEs are
persistent compounds, which are still present in both the environment
(including the food chain) and humans despite bans
and restrictions; pyrethroids and NFRs are currently used as
Published online: 09 November 2016
Springer
E. Čechová et al.
alternatives to these legacy pesticides and flame retardants.
While research has focused on testing toxic effects of various
classes of environmental contaminants, there is still a lack of
data regarding the levels of some of these compounds in the
human body. The monitoring of compounds, such as NFRs, in
human matrices would thus contribute to a better understanding
of the impact of these chemicals on human health and fill
one of the gaps identified in recent research [8].
Newborns are a susceptible group in terms of exposure to
DNTs, and breast milk constitutes a significant exposure pathway
for them. Due to the limited amount of breast milk samples
usually obtained from cohort studies, multi-class analyses
are a desirable approach. Two different approaches to milk
sample preparation/extraction are currently being used.
When solid-phase extraction (SPE), Quick, Easy, Cheap,
Effective, Rugged and Safe (QuEChERS) method or
ultrasonication of freeze-dried milk are applied, part of the
lipids are removed, which prevents us from determining lipid
content (i.e., lipid content must be determined separately)
[9-11]. In contrast, use of liquid-liquid-extraction (LLE) or
pressurized liquid extraction (PLE) allows us determining
lipids gravimetrically as they are co-extracted with the target
compounds [12-14].
Following extraction, the clean-up method must be applied
due to the removal of lipids interfering with the instrumental
analysis. In the case of determination of persistent compounds
such as PCBs, OCPs, PBDEs, or their combinations, all of
which are frequently analyzed in breast milk, a destructive
clean-up method using concentrated sulfuric acid (mostly
fixed on silica particles) is often applied [15-19]. The inclusion
of non-persistent compounds, which would be broken
down by the acid, calls for the use of different and often
multiple clean-up methods. The number of methods suitable
for the non-destructive multi-class analysis of DNTs in human
breast milk is also currently limited [20]. A frequently reported
non-destructive clean-up method for organic compounds in
breast milk is gel permeation chromatography (GPC), which
shows good separation of milk lipids from persistent pesticides
and/or PBDEs with average recoveries between 66 and
84% [21, 22]. Freezing-lipid filtration (FLF) is an alternative
method, often used for fish tissue samples when determining
endocrine disrupting phenols or OCPs with sufficient recoveries
(70-120 or 80-115%, respectively) [23, 24]. The lipid
removal efficiency of FLF may reach 88.7-93.7% [20, 23,
24]. Chen et al. applied FLF to milk samples in order to analyze
persistent as well as non-persistent pesticides with recoveries
ranging from 34 to 102% [20]. Dialysis, based on the use
of a semipermeable membrane (SPM), is another potential
lipid removal method for the analysis of persistent and nonpersistent
organic compounds in breast milk. SPM has been
used for fatty foods such as butter, egg yolk, chocolate, fish
oil, or seal blubber, providing high recoveries of PCBs,
PBDEs, polychlorinated dibenzodioxins/furans (PCDD/Fs),
5} Springer
ranging from 50 to 97%, and a very high lipid removal
effi-ciency (97-99) [25-29]. The applicability of dialysis to
milk extracts was shown with DDT where the high recovery
of this compound was reported (87 and 96% after 24 and
72 h, re-spectively). However, lipid removal (86 and 78%
after 24 and 72 h, respectively) [30] was lower than for FLF.
The aims of this study were to develop a robust method
for the determination of selected groups of 78 environmental
con-taminants such as indicator PCBs, OCPs, PBDEs,
pyrethroids, and NFRs with proven or potential
developmental neurotox-icity in human milk; to determine
the method performance characteristics; and to apply it to
breast milk samples from the Netherlands. In order to reach
the lowest achievable limits of detection (LODs) and
simultaneously suppress gas chro-matography-high
resolution mass spectrometry (GC-HRMS) analysis
interferences, the proposed method should (a) use the
maximum available volume of samples provided by cohort
studies, (b) incorporate lipid determination into sample preparation,
(c) select and optimize an efficient clean-up method
that guarantees maximum fat removal, and (d) minimize the
final sample volume, e.g., lower than 30 pX.
Materials and methods
Chemicals and reagents
Native indicator PCBs (PCB 28,52,101,138,153,180), dioxinlike
PCB 118, and selected OCPs (aldrin, a-, y-chlordane, ct-endosulfan,
chlordecone, dieldrin) were purchased from LGC
Standards (Lomianki, Poland). Other OCPs ((3-endosulfan, endosulfan-sulfate,
endrin, endrin aldehyde, endrin ketone, pentachlorobenzene,
hexachlorbenzene (HCB), a-, (3-, 7-, and 6hexachlorocyclohexane
(HCH), heptachlor, heptachlor epoxide,
methoxychlor, mirex, o,p'- and p,p'-DDE, o,p'- and p,p'-DDT,
o,pF
- and p,p'-DDD) were obtained from Supelco (Bellefonte, PA,
USA). Native PBDEs (BDE 28, 47, 66, 85, 99, 100, 153, 154,
183) were purchasedfromAccuStandard, Inc. (New Haven, CA,
USA) and native pyrethroids from Cambridge Isotope
Laboratories, Inc. (Andover, MA, USA). NFRs included allyl
2,4,6-tribromophenyl ether (ATE), 2-bromoallyl-2,4,6tribromophenyl
ether (BATE), 1,2-dibromo-4-( 1,2dibromoethyl)cyclohexane
(a- and (3-TBECH), 2,3,5,6tetrabromo-p-xylene
(p-TBX), 1,2,5,6-tetobromocyclooctane (ctand
(3-TBCO), pentabromobenzene (PBBZ), tetrabromo-ochlorotoluene
(TBCT), L2,3,4,5-pentabromo-6-methylbenzene
(PBT), pentabromoethylbenzene (PBEB), 2,3-dibromopropyl
2,4,6-tribromopheny] ether (DPTE), hexabrc>mobenzene (HBB),
hexachlorocyclopentenyl-dibromocyclooctane (HCDBCO), 2ethylhexy1-2,3,4,5-tetrabromobenzoate
(EHTBB), 1,2-bis(2,4,6tribroinophenoxy)ethane
(BTBPE), decabromodiphenylethane
(DBDPE), bis(hexachlon>cyc]opentiidieno)cyc](H)ctiine {syn- and
anti-DP), anddechloranePlus®Mono adduct(DPMA). NFRs and
An effective clean-up technique for GC/EI-HRMS determination
isotope-labeled internal standards of PBDEs were purchased from
Wellington laboratories (Ontario, Canada). Labeled standard of
PCB-7 (indicatorPCBsandPCB118), OCPs, andpyrethroidswere
purchasedfromCambridge Isotope Laboratories, Inc. (Andover,
MA, USA).
Solvents and reagents used in extraction and clean-up were
dichloromethane (DCM) and «-hexane (Pestiscan grade) obtained
from Lab-Scan (Gliwice, Poland), acetonitrile (ACN,
LC-MS grade) from Biosolve B V (Valkenswaard,
Netherlands), and «-nonane picograde from Promochem
LGC Standards (Wesel, Germany). Methanol Chromasolv
gradient grade was purchased from Sigma-Aldrich
(Steinheim, Germany) and sodium sulfate, anhydrous
(analytical-reagent grade) from Lach-Ner (Neratovice,
Czech Republic).
Samples
A total of 120 breast milk samples from the mother-child
cohort Linking endocrine disruptive compounds in maternal
Nutrition to Child health (LINC) were used [31]. Samples
were collected between 2011 and 2015 in the area of Zwolle
and den Helder in the Netherlands. Women were recruited
during their first antenatal visit to the midwife and written
informed consent was obtained. Breast milk samples were
collected by mothers during weeks 4 to 8 after delivery in
pre-treated (prewashed and solvent rinsed) bottles and stored
at -20 °C until analysis.
Extraction
Prior to extraction, 8-10 mL of liquid milk werefreezedried
for 36 h using ScanVac CoolSafe Pro freeze-dryer
(Copenhagen, Denmark). Approximately 1.2 g of obtained
freeze-dried milk were ground with 15 g of sodium sulfate
in a mortar and quantitatively transferred into a 40-mL PLE
cell between two layers of cleaned Ottawa sand. Known
amounts of labeled internal standards were added. PLE was
performed on a Speed Extractor E-914 from Biichi
(Switzerland). A three-cycle extraction programme with nhexane:DCM:methanol
(5:2:1; v.v.v) at 65 °C and 100 bar
was used. Following solvent reduction using a Syncore
Analyst concentrator Biichi (Switzerland), the lipid extract
was placed into an oven at 60 °C for 1 h to evaporate the
residual solvent. After the PLE step, lipids were determined
gravimetrically.
Gel permeation chromatography
GPC was conducted on an automated system Gilson
(Middleton USA) equipped with a 402 syringe pump, 231
XL Sampling Injector, 307 binary pump, and was coupled to
a variable wavelength detector (UVD 200, Deltachrom,
Watrex, Czech Republic). Two styrene-divinylbenzene GPC
columns (19 x 150 mm and 19x
300 mm, 15 \\m particles,
Envirogel, Waters) were connected in series. DCM was used
as a mobile phase with the flow rate of 5 mL min- 1
. Milk fat
was dissolved in DCM to obtain a total volume of 2 mL which
was then injected into the GPC system.
Freezing-lipid filtration
Forty milliliters of ACN were added to milk fat and sonicated
for 15 min. The extract was placed into a freezer (-24 °C) for
2 h. Suspended frozen lipids were removed via filtration performed
inside the freezer through folded cellulose filter
(Munktell, Germany). The process was repeated twice.
Dialysis
A portion of low-density polyethylene tubing (5 cm x 10 cm,
nominal thickness of 85 \\m, Brentwood Plastics, Missouri,
USA) was macerated in w-hexane for 48 h prior to use. The
tubing was heat-sealed on both ends and PLE extracted milk
fat dissolved in 400 \\L of w-hexane was carefully injected into
the tubing at the upper sealed end using a syringe and a needle.
The vial previously containing the milk fat was then rinsed
with another 300 \\L of w-hexane and the rinsate was added to
the sample. Once the needle was removed, excess air was
mechanically squeezed out from the tubing and the puncture
was carefully heat-sealed again. The tubing was subsequently
rolled into an amber vial containing 20 mL of w-hexane. After
24 h, «-hexane was poured into a 40-mL vial and 20 mL of
fresh w-hexane were added to the original vial containing the
membrane. Total dialysis time was 48 h. After dialysis, nhexane
was evaporated under a stream of nitrogen and the
solvent was exchanged to ACN.
Column chromatography
Column chromatography was necessary in order to remove
remaining lipids following each of the GPC/FLF/dialysis
methods outlined above. Into a commercially available 6-mL
column with 500 mg of CI 8 sorbent (Agilent Technologies,
Lake Forest, CA, USA), 3 g of 90 active basic alumina
(Merck, Darmstadt, Germany) deactivated by 5% of water
were added for capturing mainly free fatty acids [32]. After
loading the sample in 4 mL ofACN to the column, the original
vial containing the sample was rinsed twice with 3 mL and
2.5 mL of ACN and the rinsate was added to the column. The
ACN volume was optimized to elute the target compounds
before lipids start eluting. The column eluent was collected
and after reducing ACN to approximately 200 \\L under the
stream of nitrogen, it was quantitatively transferred to a conical
1.2-mL vial and evaporated nearly to dryness. Twentyfive
microliters of 1 3
C , 2 PCB 162 (20 ng mL- 1
) recovery
Springer
E. Čechová et al.
standard in «-nonane were added to the sample to be analyzed
for OCPs + PCBs-7 and pyrethroids. Subsequently, 10 \iL of
1 3
Ci2 BDE 77 and 1 3
C i 2 BDE 138 [32] (100 ng niL- 1
) were
added for analysis of PBDEs and NFRs.
Instrumental analysis
Four instrumental GC-HRMS methods were used to
measure five groups of compounds. Two GC-HRMS
instruments were used for the measurement. The instrumental
analyses of OCPs, PCBs-7, and pyrethroids were
carried out using a Trace 1310 GC (Thermo Scientific,
USA) coupled to a double-focusing magnetic sector
HRMS DFS (Thermo Scientific). The analyses of
PBDEs and NFRs were performed using a 7890A
(Agilent, USA) GC coupled to a double-focusing magnetic
sector HRMS AutoSpec Premier (Waters, UK).
The GC conditions for the methods are summarized in
Table 1. In both instruments, 0.6-m x 0.53-|J.m Restek
deactivated Rxi®-guard column was used. Helium was
used as the carrier gas with a constant flow rate of
1 mL min- 1
. Splitless injection of 2 | j L was used in
all methods.
In both instruments, electron impact ionization in the
positive mode (EI+
) was used with electron energy of
35 eV (AutoSpec) and 48 eV (DFS). The MS resolution
mode in both mass spectrometers was set at >10,000
(10% valley). The GC-MS transfer line temperature
was 280 °C for all analyses. Quantification was based
on the isotope dilution method if an analyte surrogate
was available, or on the use of the labeled internal
standard method or on external calibration, when no
proper internal standard was available (selected NFRs).
Detailed information regarding individual compounds,
their masses, and used internal standards are provided
in the Table SI in Electronic Supplementary Material
(ESM). PBDE and NFR chromatograms were processed
4 NFRs Autospec Waters 15 m x 0.25 mm x 0.10 ^m
Restek Rtx®-1614
using Waters Target Lynx software. OCP + PCBs-7 and
pyrethroids chromatograms were processed using
Thermo Scientific TargetQuan 3.2.
Method performance characteristics
Analytical performance characteristics of the method, based
on validation guidelines included in the EU Commission
Decision 2002/657/EC [33], were evaluated. The validation
parameters included linearity, accuracy (comprising both triteness
and precision), and LOD, and they were assessed using
fortified breast milk obtained from a volunteer mother at two
known concentration levels. Linearity in a calibration range
was expressed as the relative standard deviation (RSD) of
response factors calculated from the GC-HRMS responses
of native and labeled analytes in calibration standards.
Acceptable RSD values were below 20%. Trueness, evaluated
as average recoveries, was calculated as the ratio of determined
concentrations in spiked samples to their target level*
100%. The range between 70 and 110% was considered
satisfactory [33]. Precision was expressed as intra-day RSD
for six measurements of fortified breast milk samples and
between-day RSD from an analysis of the fortified samples
analyzed weekly. Expanded uncertainties (U) were calculated
from the combined standard uncertainties (uc) including the
uncertainty from derived from precision (up) and from trueness
(Mb)- The details of the calculation are provided in ESM
(p. S4). The limits of detection were calculated as 3*standard
deviations of the levels found in procedural blanks (« = 18)
divided by the median lipid content of the analyzed milk samples
(0.038 g) to adjust the LOD to the lipid weight. LODs of
compounds which were not present in the blanks were calculated
as concentrations corresponding to S/N ratios of 3. In
order to lower the background levels of the compounds in
procedural blanks, all detergent-washed glassware was baked
at 400 °C for 5 h and rinsed with organic solvents prior to
analysis. The use of plasticware was avoided as much as
GC conditions
:, °C
120 °C (3 min), 40 °C min"1
to 210 °C (20 min),
2 °C min"1
to 286 °C, 10 °C min"1
to 330 °C
(30 min)
120 °C (1.5 min), 30 °C min"1
to 150 °C,
4.5 °C min"1
to 330 °C
80 °C (1 min), 20 °C min"1
to 250 °C, 1.5 °C
min"1
to 260 °C (2 min), 25 °C min"1
to
320 °C (4.5 min)
250 80 °C (1 min), 30 °C min"1
to 140 °C, 4 °C
min"1
to 175 °C, 8 °C min"1
to 270 °C,
15 °C to 325 °C (5 min)
Table 1 GC conditions for analysis of OCPs, PCBs-7, pyrethroids, PBDEs, and NFRs
Method Analytes HRMS
instrument
GC column Injector
temperature
OCPs + PCBs-7 DFS Thermo 60 m x 0.25 mm x 0.25 um
SGE HT8
260
2 Pyrethroids DFS Thermo 60 m x 0.25 mm x 0.25 \mi 260
Agilent DB-5MS Ultra Inert
3 PBDEs Autospec Waters 15mx0.25nmx0.10[im 280
Restek Rtx®-1614
Ö Springer
An effective clean-up technique for GC/EI-HRMS determination
possible in order to reduce the background levels of PBDEs/
NFRs.
Results and discussion
Extraction
A pressurized solvent extraction was used due to the lower
solvent consumption and shorter extraction time in comparison
with the traditionally used liquid-liquid extraction. The
choice of solvent mixture, temperature, and pressure used here
(«-hexane:DCM:MeOH (5:2:1; v/v/v) 65 °C, 100 bar [34])
allowed us to quantitatively co-extract all target lipophilic
compounds together with milk lipids. The lipid content constitutes
important information in the analysis of non-polar organic
compounds owing since their levels are of adjusted to
lipid weight. The fat content obtained after PLE in this study
(3.40 ± 0.15 % of fat in whole cow's milk, n = 4) was in a good
agreement with the LLE Rose-Gottlieb reference method [35]
for fat determination in milk (3.38 ±0.18% of fat in whole
cow's cow milk, n = 4).
Dutch breast milk samples analyzed in this study contained
a varying amount of fat (from 0.06 to 1.2 g in 10 mL of milk).
A robust clean-up technique had to be optimized for sufficient
lipid removal. The results from the three different clean-up
methods utilized in the present study are discussed in section
below.
Clean-up
Three clean-up techniques, i.e., FLF, GPC, and dialysis, were
compared in order to obtain the lowest lipid carryover and
highest analytes recoveries. Lipid removal was tested using
350 mg of milk fat, which corresponds to 10 mL of milk
sample with average fat content of 3.5%. In order to compare
the recoveries of individual clean-up techniques, standard solutions
were used because the lipid presence would require
additional clean-up step.
Gel permeation chromatography
A GPC column system consisting of two Envirogel columns
connected in series were tested in order to establish the most
efficient separation of lipids and analytes. The elution profile
of fat was visualized by measuring absorbance using a UV
detector (254 nm) and analyte content was determined by GCHRMS
in the individualfractionscollected every 30 s (Fig. 1).
Since pyrethroids (mainly cyhalothrin, permethrins,
cyfluthrin, tetramethrin) elute early, in order to obtain recoveries
higher than 70%, the fraction between minute
13.8 and 25 for the assessment of the total fat removal
was collected. The lipid carryover from 350 mg of the
milk fat in this fraction was 15%, i.e., approximately
50 mg of fat. The recoveries of all groups of analytes are
provided in Fig. 2. Additionally, Envirogel column capacity
was tested. Taking into account varying fat amount in
breast milk samples, we tested the lipid elution profile
with 650 mg of milk lipids. Significant broadening of the
lipid peak was observed, suggesting that the GPC column
capacity was exceeded. Lipid carryover increased to 30-
35%. However, when the lipid amount was lowered to
approximately 130 mg, the lipid peak was sharp and
showed a good separation from pyrethroids. The optimum
milk fat amount for the satisfactory separation of fat from
early eluting pyrethroids was thus determined as approximately
250 mg. More fatty milk samples would require
repeated GPC runs, which would constitute a time- and
solvent-consuming process.
Fig. 1 Elution profiles of 130,
350, and 650 mg of milk fat with
Envirogel GPC column and
elution of pyrethroids, OCPs,
PCBs, PBDE, and NFRs
time (min)
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E. Cechovä et al.
Fig. 2 Recoveries and standard deviations (n = 4) of a OCPs, where SDDX = DDTs + DDEs + DDDs, b pyrethroids, c PCBs and PBDEs, and d
AFRs using different clean-up techniques
Ö Springer
An effective clean-up technique for GC/EI-HRMS determination
I'tvezing-lipidfiltration
After two freezing-lipid filtration (FLF) cycles, mean lipid
carryover was 19% (n = 4), Lc., approximately 66 mg out of
350 mg fat remained in the extract. This amount of lipids was
still too high to be removed by the CI K/b-AUO-? column,
which is able to retain max, 20-40 mg of fat. An additional
clcan-up step such as GPC would be therefore necessary for
total fat removal. The recoveries of most of the analytcs were
higher than 75% (Fig. 2), but for some compounds (BDE 153,
B D R 154, B D E 183, EHTBB, BTBPE, DBDPE, s-DP, and aDP)
the recoveries were 23.5 54.6%. This could be explained
by their higher partitioning Iipid-acctonitrile coefficients or by
an occlusion of analytcs in the precipitated matrix and by
adsorption in the 111[ration process [36].
Dialysis
In the case of dialysis, several basic parameters affect compound
recovery and lipid carryover, including LDPE membrane
length, dialytic solvent selection and its volume, and
dialytic time and temperature. Cyclopcntanc, n-hcxanc, or an
n-hcxanc:DCM mixture were recommended previously [29].
Since cyclopcntanc has limited availability and high cost and
the presence of DCM in n hcxanc increases lipid carryover,
we chose n-hcxanc, which showed recoveries ofover 80% for
labeled PCB 52 when the solvent volume was 40 limes higher
than the volume inside the membrane [25]. Thus, for approximately
400 pL of the milk fat dissolved in 700 pL of «hcxanc
(equal to the approximate total inside volume 1 ml),
we used twice 20 ml. of w-hcxanc with one solvent exchange
after 24 h. A 48-h dialysis period was shown to be sufficient
for recoveries higher than 80% for all the analytcs. The effect
of dialysis temperature on both lipid carryover and analytc
recoveries was also studied. There is clear evidence of the
decrease of lipid carryover with decreasing temperature [25,
29], but information regarding recoveries under different temperatures
is inconsistent. While Roszko et al. showed a
significant decrease of the average recovery of indicator
PCBs in the range of 20-40 °C [29], Meadows ct al reported
that the changes in temperature within the range of 15 30 °C
do not afreet the recovery of the labeled P C B 52 [25].
Exploring recoveries of other DNTs from this study at differenttemperaturesand
taking into account a lower transfer of,
lipids at lower temperatures, wo selected two different temperatures:
10 and 25 "C. The lipid carryover was 4 6 and K 10%
at 10 °C {ft = 4) and 25 °C (« = 4), respectively. Analytc recoveries
provided in Fig. 2 indicate that the majority of the
compounds fall within the 70-110% interval with the use Of
10 or 25 ° C which confirmed (hat there were no significant
differences in analytc recoveries, but the use of lower temperature
provided IOWCT lipid carryover compared to 25 °C.
The comparison of dialysis with GPC and FLF .showed that
dialysis al 10 °C provided the lowest lipid earryover and high
recoveries for all the compounds within the range of 70-
120%. Due to the low lipid carryover (approximately 14 mg
from 10 mL of 3.5% milk up to 40 mg from 10% milk), no
othcT clean-up Step had to be used prior to column chromatography.
While the duration of the dialysis (48 h) may be viewed
as a disadvantage, many parallel samples can be processed at
the same time. Moreover, the procedure presents no risk of
cross-contamination and constitutes a cost-effective Solution.
An additional advantage ofdialysis is the significant reduction
of matrix effects during instrumental analysis compared to
GPC or FLF clcan-up methods. The summary of three used
clean-up methods discussed hcTe is shown in Table 2.
Instrumental method
Several GC-MS instruments with electron ionization available
in our center were tested (GC-MS/MS, GC-HRMS) for the
five analyzed groups of compounds. GC-HRMS showed the
highest sensitivity (optimization not shown here). Since the
injection volume was 2 pL in each of four instrumental
methods, the final sample volume prior to instrumental analysis
was 25 pL, The accuracy of quantification was
Tahle 2 Comparison of three different l L c e u i - up techniques for processing of milk fal
GPC FLF Dialysis
10 °C 25 °C
Lipid carryover, %a
15 (8); limited column capacity of -250 mg of fat 19(13) 4-6(12) 6-8 (15)
(RSD, n = 4)
Additional clean-upb
Yes Yes No No
Solvent consumption 150 mL DCM 100 mL ACN 40 mL n-hexane 40 mL n-hexane
Risk of cross-contamination Yes No No No
Automatization Yes No No No
Cost High Low Low Low
a
350 mg of milk fat was used
b
Apart from the column chromatography which was used after all three clean-up techniques
4y Springer
E. Čechová et al.
sporadically influenced by increased levels of interfering compounds
eluting in the analyte retention time which caused
suppressions ofthe MS signal of pyrethroids, especially when
their lower mass fragments were monitored. That could be
observed as a decrease of otherwise stable lock and calibration
mass signals. However, after the use ofdialysis clean-up, most
of the matrix interferients were suppressed, and no significant
decreases of MS responses during elution of analyte peaks
were recorded. The final method scheme including the
clcan-up steps is shown in Fig. 3.
Method performance characteristics
As a part of a validation procedure, the following parameters
were evaluated. Linearity expressed as RSD of the response
factors for all compounds ranged from 1 to 20%. Analysis of
breast milk samples spiked at two different levels (n = 6) provided
recoveries ranging between 81 and 121% for OCPs,
PCBs-7, and PBDEs while recoveries of pyrethroids and
NFRs were lower, 58-120 and 40-121 %, respectively, which
could be caused by the deficiency of the isotope-labeled analogues
for some compounds. For several NFRs (p-TBX,
TBECH, a-TBCO, DPMA, DPTE, HCDBCO, EHTBP), no
proper internal standard used within the method was found;
therefore, their results were not corrected to the losses within
the sample preparation. Labeled standards for analyzed compounds
are shown in Table SI in ESM. Intra-day precisions
expressed as RSDs ranged from 2 to 22% for all compounds,
but for p-cyfluthrin-3, the RSD was 28% and for endosulfansulfate
intra-day precision was 36% what can be caused by the
deficiency of the isotope-labeled standard Between-day precisions
ranged from 5 to 29% for all compounds. LODs
ranged from 0.001 to 0.731 ng g_ 1
lw for all analytes which
allowed us to determine compounds with trace levels in the
8-10 nil. of breast milk
Internal labelled
standards
Freeze-drying
36 hours
PLE
(hex:DCM:Me0H=5:2:1)
65 °C, 100 bar, 3 cycles
>=>
Gravimetricfat
determination
Dialysis at 10 °C,
48 hours, /i-hexane
Recovery labelled
standards
Column
chromatography
(C18 +b-Al203)
ACN
OCPs+PCBs-7 Pyrethroids PBDEs NFRs
GC-HRMS GC-HRMS GC-HRMS GC-HRMS
Fig. 3 Method procedure flow diagram
milk samples such as BDE 66 or BDE 154 or selected AFRs
such as TBP-BAE or TBP-AE. The expanded uncertainties
for all compounds ranged from 5 to 57% for the spiking level
1 and from 11 to 48% for the spiking level 2, respectively.
The highest uncertainties were for pyrethroids and NFRs, for
many of which no labeled standard were available. Detailed
infor-mation regarding all validation parameters can be found
in Table S2 in ESM. Blank samples contained PeCB, HCB,
y-HCH, p,p'-DDE, endosulfan-sulfate, PCB 28, BDE 47,
and BDE 99, but their levels were low in comparison with
levels present in milk samples. Qiu et al. also observed the
presence of BDE 47 and BDE 99 in the blanks and reported
their con-tribution to 2 and 9% of the sample levels,
respectively [37]. In this study, their contribution was below
1.5% of the median levels in the samples for both congeners.
Application to Dutch breast milk samples
In order to demonstrate the applicability of the method, 120
breast milk samples with various fat contents were analyzed
(Table 3). p,p'-DDE was the neurotoxicant present at the
highest concentrations in Dutch samples (median 49 ng g_ 1
lw) followed by PCB 153 (median 16.0 ng g_ 1
lw), PCB 180,
and PCB 138 (10.7 ng g_ 1
lw for both congeners). These
compounds were found in 100% of all samples. Levels of
persistent pesticides and PCBs as well as PCB congener profile
were comparable to other European countries, such as
Sweden, Belgium, or Croatia with the sample collection between
2009 and 2012 [38-40]. However, the PCB levels in
Dutch milk samples were approximately six to eight times
lower than those collected in 2009 in the Czech Republic
which belongs to one of the most PCB-polluted countries in
the world [41, 42]. Similarly, the levels of HCB and SDDX
were approximately seven and five times lower, respectively,
than those in the Czech Republic with high former use of
persistent pesticides [42]. Median levels of PBDEs were below
0.5 ng g_ 1
lw. The highest levels were observed for BDE
153 (median 0.48 ng g_ 1
lw) followed by BDE 47 (median
0.197 ng g_ 1
lw). The PBDE 47, 99, 100, and 153 congeners
were detected in all samples. A similar congener profile and
comparable levels were found in Belgian breast milk samples
from 2006 (median 0.29 ng g_ 1
lw for BDE 153, 0.16 ng g_ 1
lw for BDE 47) [39], whereas PBDE levels were approximately
six times lower in the Netherlands compared to Great
Britain with high PBDE concentrations in Europe [43].
Median levels of non-persistent neurotoxicants measured
in this study were lower than 0.43 ng g_ 1
lw for pyrethroids
and below 0.13 ng g_ 1
lw for AFRs. The detection frequency
of pyrethroids in Dutch breast milk samples was very low.
Generally, only cis- and fraws-permethrins (median
0.127 ng g_ 1
lw) and pyrethroid synergist piperonyl butoxide
(0.26 ng g_ 1
lw), which suggests previous exposure to pyrethroids,
were found in over 80% of the samples. Unlike in the
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An effective clean-up technique for GC/EI-HRMS determination
Table 3 Detection frequency
(DF, %) and levels of
developmental neurotoxicants in
Dutch breast milk samples, n =
120 (ngg-1
lw)
DF 5th percentile Median Mean 95th percentile
PeCB 5 0.12 0.23 0.27 0.47
HCB 100 4.29 6.22 6.46 9.67
EHCHs 100 2.40 4.35 5.04 8.45
EDDX 100 24.0 51.6 71.1 123
Aldrin 0
Dieldrin 100 1.24 2.27 2.41 4.01
Endrin 0
Endrin aldehyde 0
Endrin ketone 0
Echlordanes 0
Eendosulfanes 5 0.08 0.17 0.24 0.57
Endosulfan sulfate 97 0.03 0.09 0.14 0.45
Methoxychlor 5 0.001 0.01 0.01 0.02
Mirex 99 0.05 0.12 0.15 0.30
Chlordecone 93 5.0 12.7 15.0 31.3
PCB 28 100 0.49 0.79 0.90 1.68
PCB 52 100 0.09 0.17 0.23 0.69
PCB 101 100 0.09 0.19 0.22 0.45
PCB 138 100 5.42 10.7 12.2 23.4
PCB 153 100 7.62 16.0 17.4 30.9
PCB 180 100 4.50 10.7 11.7 22.1
PCB 118 97 1.81 3.62 3.93 7.35
BDE28 97 0.01 0.02 0.03 0.06
BDE47 100 0.06 0.20 0.35 1.05
BDE66 42 0.002 0.01 0.01 0.02
BDE 100 100 0.02 0.06 0.08 0.18
BDE 99 100 0.02 0.08 0.14 0.23
BDE 85 23 0.004 0.01 0.02 0.05
BDE 154 40 0.01 0.01 0.03 0.05
BDE 153 100 0.22 0.48 0.52 0.96
BDE 183 55 0.02 0.04 0.05 0.11
BDE 209 6 0.16 0.94 5.81 20.9
Tefluthrin 16 0.02 0.04 0.08 0.25
Transfluthrin 5 0.17 0.27 0.41 0.97
Chlorpyrifos 72 0.27 0.55 0.63 1.16
Piperonyl-butoxide 85 0.09 0.26 0.65 2.13
Bifenthrin 3 0.15 0.15 0.21 0.31
Tetramethrin-2 0
Cyhalothrin 48 0.04 0.09 0.15 0.53
Acrinathrin 0
Epermethrins 90 0.06 0.13 0.57 1.41
Ecyfluthrins 2 0.22 0.43 0.43 0.63
Ecypermethrins 35 0.10 0.32 0.38 0.80
Fenvalerate-1 5 0.04 0.07 0.09 0.16
Deltamethrin-2 23 0.17 0.30 0.37 0.84
ATE 0
TBECH 26 0.01 0.04 0.04 0.08
TBX 63 0.01 0.02 0.03 0.13
BATE 5 0.002 0.004 0.01 0.01
Springer
E. Cechovä et al.
Table 3 (continued)
DF 5th percentile Median Mean 95th percentile
TBCO 0
PBBz 69 0.01 0.02 0.03 0.05
TBCT 0
DPMA PBT 2 0.09 0.09 0.09 0.09
PBEB DPTE 85 0.01 0.02 0.03 0.07
HBB 0
PBBA 0
HCDBCO 88 0.02 0.04 0.05 0.1
EHTBB 0
BTBPE 0
63 0.04 0.13 0.24 0.68
24 0.02 0.03 1.10 2.38
s-DP 13 0.05 0.11 0.21 0.63
a-DP 18 0.02 0.05 0.16 0.49
BEHTBP 0
Values below LOQ not included
Netherlands, levels of all determined pyrethroids in human
milk from Spain (tetramethrin, bifenthrin, cyhalothrin, deltamethrin,
tralomethrin, fenvalerate, permethrin, and
cypermethrin) were detected in more than 67% of all samples
[11]. The median level of Xpermethrins which were present at
highest concentrations in Spain was approximately 20 times
lower than in our study. Other pyrethroid levels in Spain
and the Netherlands were comparable. From among
NFRs, TBX, PBBz, ATE, EHTBB, and TBECH were
detected in over 50% of the Dutch samples. To the best of
our knowledge, no reference data regarding the levels of
these compounds in breast milk in Europe has been
published to date.
Conclusions
A novel method for the determination of 78 organic pollutants
such as organochlorine pesticides, polychlorinated biphenyls,
polybrominated diphenyl ethers, pyrethroids, and novel flame
retardants with proven or potential developmental neurotoxicity
in human milk (8—10 ml) was developed and validated. The
advantage of the method is the determination of a whole mixture
of persistent and non-persistent compounds together including
fat dctcrrnination. Two clean-up steps comprising dialysis and
column chromatography with CI8/basic-Al2 03 were used.
Dialysis, newly used at 10 °C, showed the removal of more than
94—96% of interfering milk lipids and high analyte recoveries
(65-121 % for most of the analytes). The thorough lipid removal
from milk samples with varying fat content (from 0.6 to 12%)
allowed us to minimize the final sample volume to 2 5 ]_iL and
thus lower the LODs to sub-ng g _ 1
lipid weight and detect the
compounds with trace levels in human milk such as pyrethroids
or novel flame retardants. The dialysis procedure used in the
current study was applied for the first time to an analysis of a
complex mixture of the DNT compounds in a milk extract and
showed several advantages over the traditionally used GPC
method such as cost-effectiveness, low amount of (nonchlorinated)
solvent, and a significant reduction of interferences
influencing on GC-HRMS measurement.
The applicability of the method was verified using 120 Dutch
milk samples with various lipid contents. Of the 78 analytes, 35
compounds were present in over 60% ofthe samples. The results
from this and following biomonitoring studies using samples obtained
from other European countries will provide useful data
regarding levels of selected current use pesticides orflameretardants
in human matrices which are still scarce in the literature and
will be additionally used foran epidemiological evaluation ofthe
influence of presence of these compounds and their mixtures in
mother's body to child health.
Acknowledgments Jakub Martinik and Marcela Kadlecova are acknowledged
for their help during sample preparation. The research was
supported by the Seventh Framework Programme of EU, Grant
Agreement No. 282957: Developmental Neurotoxicity Assessment of
Mixtures in Children (DENAMIC), by the "Employment of Best
Young Scientists for International Cooperation Empowerment"
(CZ.1.07/2.3.00/30.0037), co-fmanced by the European Social Fund,
the state budget of the Czech Republic, and by the Czech Ministry of
Education, Youth and Sports (L01214 and LM 2015051).
Compliance with ethical standards The study was approved by the
ethics committee ofthe Vrije Universiteit Medical Center Amsterdam and
has been performed in accordance with the ethical standards. Written
informed consent was obtained from each individual participant.
Conflict of interest The authors declare that they have no conflict of
interest.
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An effective clean-up technique for GC/EI-HRMS determination
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Analytical and Bioanalytical Chemistry
Electronic Supplementary Material
An effective clean-up technique for GC/EI-HRMS determination
of developmental neurotoxicants in human breast milk
Eliška Cechová, Marta Seifertova, Petr Kukučka, Simon Vojta, Ilona Quaak,
Marijke de Cock, Margot van de Bor, Anton Kočan
Sl
Table of contents
Table S1 List of analysed compounds including quantitative (QM) and confirmation (CM)
masses and internal standards (ISTD). The analytes are arranged in the order of elution from
the respective GC column S3
Expanded uncertainties S5
Table S2 Performance characteristics of the method S6
S2
Table SI List of analysed compounds including quantitative (QM) and confirmation (CM) masses and
internal standards (ISTD). The analytes are arranged in the order of elution from the respective GC
column
Group acronym CAS number QM CM ISTD
Method 1
OCPs PeCB 608-93-5 247.8521 249.8491 1 3
C 6 PeCB
OCPs a-HCH 319-84-6 216.9145 220.9086 l 3
C 6 a-HCH
OCPs HCB 118-74-1 211.8754 213.8725 I 3
C 6 HCB
OCPs Y-HCH 58-89-9 180.9379 182.9349 l 3
C 6 Y-HCH
OCPs ß-HCH 319-85-7 180.9379 182.9349 1 3
C 6 ß-HCH
OCPs 5-HCH 319-86-8 180.9379 182.9349 l 3
C 6 5-HCH
PCBs-7 PCB 28 7012-37-5 255.9613 257.9584 l 3
C 1 2 PCB 28
OCPs heptachlor 76-44-8 271.8102 273.8072 I 3
C 1 0 heptachlor
PCBs-7 PCB 52 35693-99-3 291.9194 289.9224 l 3
C 1 2 PCB 52
OCPs aldrin 309-00-2 262.8570 264.8540 l 3
C 1 2 aldrin
OCPs cw-heptachlor epoxide 1024-57-3 352.8442 354.8413 l 3
Cio cw-heptachlor
epoxide
OCPs o,p'-DDE 3424-82-6 246.0030 247.9974 l 3
C 1 2 o,p'-DDE
OCPs y-chlordane 5103-74-2 262.8570 264.8540 I 3
C 1 0 y-chlordane
PCBs-7 PCB 101 37680-73-2 255.9427 257.9398 l 3
C 1 2 PCB 101
OCPs a-endosulfan 959-98-8 262.8570 264.8540 l 3
C 9 a-endosulfan
OCPs a-chlordane 5103-71-9 262.8570 264.8540 I 3
C 1 0 y-chlordane
OCPs p,p'-DDE 72-55-9 246.0003 247.9974 l 3
C 1 2 p,p'-DDE
OCPs dieldrin 60-57-1 262.8570 264.8540 l 3
Ci2 dieldrin
OCPs o,p'-DDD 53-19-0 235.0081 237.0052 l 3
C 1 2 o,p'-DDD
OCPs endrin 72-20-8 262.8570 264.8540 13
Cio endrin
OCPs o,p'-DDT 789-02-6 235.0081 237.0052 l 3
C 1 2 o,p'-DDT
PCBs-7 PCB 118 31508-00-6 253.9457 257.9398 l 3
C 1 2 P C B 118
OCPs p,p'-DDD 72-54-8 235.0081 237.0052 1 3
C i 2 p,p'-DDD
OCPs ß-endosulfan 33213-65-9 262.8570 264.8540 l 3
C 9 ß-endosulfan
PCBs-7 PCB 153 35065-27-1 252.9379 254.9349 l 3
C 1 2 PCB 153
OCPs p,p'-DDT 50-29-3 235.0081 237.0052 l 3
C 1 2 p,p'-DDT
OCPs endrin aldehyde 7421-93-4 249.8491 251.8456 l 3
C i 2 endrin aldehyde
PCBs-7 PCB 138 35065-28-2 289.9038 291.9008 I 3
C 1 2 P C B 138
OCPs endosulfan sulfate 1031-07-8 271.8100 273.8072 l 3
C 9 ß-endosulfan
recovery STD 1 3
C1 2 PCB 264.9781 266.9751
OCPs methoxychlor 72-43-5 227.1072 228.1106 1 3
C i 2 p,p'-DDT
PCBs-7 PCB 180 35065-29-3 323.8648 325.8618 I 3
C 1 2 PCB 180
OCPs mirex 2385-85-5 271.8102 273.8072 l 3
Cio mirex
OCPs endrin ketone 53494-70-5 316.9039 318.9010
I 3
C 1 2 endrin ketone
OCPs chlordecone 143-50-0 271.8102 273.8072 13
Cio chlordecone
Method 2
pyrethroids tefluthrin(la
) 79538-32-2 177.0327 197.0354 I 3
C 6 cw-permethrin
pyrethroids transfluthrin(l) 118712-89-3 163.0081 165.0052 C(, cw-permethrin
organophosphate chlorpyrifos 2921-88-2 313.9574 315.9545
2
H 1 0 chlorpyrifos
pyrethroid piperonyl butoxide 51-03-6 176.0837 177.0916 C(, cw-permethrin
synergist
recovery STD 1 3
Ci2 PCB 162 264.9781 266.9751
pyrethroids bifenthrin (1) 82657-04-3 166.0783 181.1017 I3
C6 cw-permethrin
pyrethroids tetramethrin (2) 7696-12-0 164.0712 165.0774 I 3
C 6 cw-permethrin
pyrethroids 1-cyhalothrin (1) 91465-08-6 181.0653 183.0810 l 3
C 6 Cypermethrin
pyrethroids acrinathrin(l) 101007-06-1 181.0653 208.0762 l 3
C 6 Cypermethrin
pyrethroids cw-permethrin 61949-76-6 183.0810 184.0888 C(, cw-permethrin
pyrethroids ?ra».s-permeihrin 61949-77-7 183.0810 184.0888 1 3
C6 frawi'-permeihrin
pyrethroids cyfluthrin (2) 68359-37-5 199.0559 226.0668 1 3
C 6 cyfluthrin
S3
pyrethroids Cypermethrin (4) 52315-07-8 181.0653 182.0716 1 3
C 6 Cypermethrin
pyrethroids fenvalerate (2) 51630-58-1 167.0628 169.0589 l 3
C 6 Cypermethrin
pyrethroids deltamethrin 52918-63-5 250.9071 252.9051 l 3
C 6 Cypermethrin
+tralomethrin(l)
Method 3
PBDEs BDE 28 41318-75-6 405.8027 407.8007 l 3
C 1 2 BDE 28
PBDEs BDE 47 5436-43-1 485.7112 483.7132 I 3
C 1 2 BDE 47
PBDEs BDE 66 189084-61-5 I 3
C 1 2 BDE 47
recovery STD 1 3
C 1 2 BDE 77 497.7513 495.7533
PBDEs BDE 100 189084-64-8 563.6216 565.6197 l 3
C 1 2 BDE 100
PBDEs BDE 99 60348-60-9 563.6216 565.6197 I 3
C 1 2 BDE 99
PBDEs BDE 85 182346-21-0 I 3
C 1 2 BDE 100
PBDEs BDE 154 207122-15-4 643.5302 641.5322 I 3
C 1 2 BDE 154
PBDEs BDE 153 68631-49-2 643.5302 641.5322 l 3
C 1 2 BDE 153
PBDEs BDE 183 207122-16-5 721.4407 723.4387 I 3
C 1 2 BDE 183
recovery STD 1 3
C i 2 B D E 138 655.5703 653.5723
Method 4
NFRs ATE 3278-89-5 369.8027 371.8027 l 3
C 1 0 s-DP
NFRs a-TBECH 3322-93-8 266.9207 268.9187 l 3
C 1 0 a-DP
NFRs ß-TBECH 3322-93-8 266.9207 268.9188 l 3
C 1 0 s-DP
NFRs TBX 23488-38-2 340.7999 342.7979
NFRs BATE na" 329.7714 331.7693 l 3
C 1 0 s-DP
NFRs ß-TBCO 3194-57-8 266.9207 268.9187 l 3
C 1 0 s-DP
NFRs PBBz 608-90-2 471.5954 473.5934 l 3
C 6 PBBz
NFRs TBCT 39569-21-6 441.6614 443.6593
NFRs TBCO 3194-57-8 266.9207 268.9187
NFRs DPMA na 344.9353 379.9041
NFRs PBT 87-83-2 485.6111 487.6090 1 3
C 6 PBBz
NFRs PBEB 85-22-3 499.6266 501.6247 l 3
C 6 PBBz
NFRs DPTE 35109-60-5 531.6353 529.6372
NFRs HBB 87-82-1 551.5038 549.5059 1 3
C 6 PBBz
NFRs HCDBCO 51936-55-1 476.6983 474.7003
recovery STD 1 3
C 1 2 BDE 77 497.7513 495.7533
NFRs EHTBB 183658-27-7 420.6720 418.6740
NFRs BTBPE 37853-59-1 358.7928 356.7984 I 3
C BTBPE
NFRs s-DP 13560-89-9 271.8102 273.8072 l 3
C 1 0 s-DP
NFRs a-DP 13560-89-9 271.8103 273.8073 1 3
C 1 0 a-DP
number ofevaluated isomers
b
not available
S4
Expanded uncertainties
The expanded uncertainty (U) was calculated from the combined standard uncertainty (uc) multiplied
by the coverage factor (k=2) to obtain the result in the 95% confidence interval. The combined
uncertainty was given as the square root of the sum of the squared uncertainty derived from the
measurement of precision (up) and squared uncertainty of trueness (ub) [1]
The Ub was obtained from the Ubia s and us p jke d which includes the uncertainties of the standard
concentrations and pipetting volumes and it was estimated to be 0.9739 [2]
The Up was expressed as the relative standard deviation from six between-day measurements
x
S5
Table S2 Performance characteristics of the method
Compound Linear RSD of Spiking Average RSD, % Expanded Spiking Average RSD, % (intra- Expanded LOD
calibration relative level 1, recovery 1, % (intra-day, uncertainty level 2, recovery 2, day, between- uncertainty 2,(ng g1
range, ngrespons ngg1
Iw (n=6) between-day),1, % ngg1
Iw % (n=6) day), n=6 % Iw)
mU1
e
factor, %
n=6
PeCB 0.5-250 3.0 1.78 112 9, 15 31 8.9 106 10, 13 23 0.172
HCB 0.5-250 1.6 1.78 106 13, 17 28 8.9 97 8, 15 17 0.172
a-HCH 1.5-750 2.0 5.34 108 3, 9 17 26.7 80 7, 10 44 0.003
ß-HCH 1.5-750 2.8 5.34 114 7, 12 27 26.7 104 6, 14 15 0.038
y-HCH 1.5-750 3.9 5.34 109 5, 8 20 26.7 89 3,5 23 0.047
5-HCH 1.5-750 3.1 5.34 108 6, 10 18 26.7 95 8, 8 20 0.036
o,p'-DDE 0.5-250 3.2 1.78 108 7,7 23 8.9 76 20, 14 39 0.011
p,p'-DDE 1.5-750 3.4 5.34 109 23,25 19 26.7 101 10,9 21 0.047
o,p'-DDD 0.5-250 2.3 1.78 113 6, 15 27 8.9 84 10, 19 38 0.014
p,p'-DDD 1.5-750 8.6 5.34 112 6, 17 23 26.7 91 6, 10 22 0.016
o,p'-DDT 0.5-250 5.3 1.78 109 6, 14 23 8.9 90 7, 15 28 0.019
p,p'-DDT 1.5-750 9.9 5.34 116 9, 12 33 26.7 90 8, 10 26 0.021
heptachlor 1-500 6.7 1.78 110 5, 10 23 8.9 105 17, 15 36 0.003
heptacWor 1-500 3.9 1.78 113 4, 8 26 8.9 102 14,9 29 0.017
epoxide
aldrin 1-500 4.8 1.78 112 7,21 30 8.9 76 7, 12 24 0.017
dieldrin 1-500 4.2 1.78 116 5, 18 31 8.9 104 6, 8 16 0.034
endrin 1-500 7.0 1.78 113 4, 23 24 8.9 110 12, 15 30 0.037
endrin 1-500 4.2 1.78 81 7,6 35 8.9 80 18, 10 27 0.118
aldehyde
endrin ketone 1-500 3.4 1.78 110 5, 18 21 8.9 99 4, 12 12 0.005
ot-chlordane 1-500 5.3 1.78 121 6, 10 29 8.9 84 7, 16 34 0.066
y-chlordane 1-500 4.2 1.78 117 5, 18 31 8.9 104 8, 14 20 0.072
a-endosulfan 1-500 8.8 1.78 109 9, 12 26 8.9 109 3, 8 22 0.072
ß-endosulfan 1-500 3.0 1.78 106 5, 14 17 8.9 97 10, 11 23 0.159
endosulfan 1-500 3.3 1.78 93 36,31 33 8.9 93 9, 14 25 0.031
sulfate
methoxychlor 1-500 8.8 1.78 87 16, 20 39 8.9 80 13, 13 27 0.007
mirex 1-500 1.9 1.78 112 5, 15 28 8.9 110 15, 10 36 0.003
chlordecone 20-10000 13.7 71.2 114 7, 8 33 356 104 9, 11 23 0.710
S6
PCB 28 0.5-250 4.2 1.78 98 9, 15 19 8.9 90 2, 5 22 0.041
PCB 52 0.5-250 2.2 1.78 104 7, 12 17 8.9 85 8, 11 34 0.012
PCB 101 0.5-250 1.0 1.78 116 8, 13 32 8.9 76 10, 14 14 0.018
PCB 118 0.5-250 8.4 1.78 86 14, 19 37 8.9 80 8, 17 30 0.040
PCB 138 0.5-250 4.4 1.78 119 7, 10 41 8.9 110 6, 10 25 0.056
PCB 153 5-2500 1.3 17.8 109 6, 8 24 8.9 104 18, 14 39 0.005
PCB 180 0.5-250 5.8 1.78 115 8, 11 35 8.9 107 19, 19 42 0.004
BDE 28 1-500 5.2 1.78 101 2, 8 5 8.9 82 20, 14 15 0.007
BDE 47 1-500 2.9 1.78 95 4, 8 12 8.9 90 17, 20 41 0.027
BDE 66 1-500 8.6 1.78 103 6, 17 13 8.9 104 17, 15 37 0.006
BDE 100 1-500 7.5 1.78 91 3, 10 20 8.9 94 8, 12 24 0.009
BDE 99 1-500 11.7 1.78 106 2, 10 13 8.9 107 7, 14 23 0.029
BDE 85 1-500 16.4 1.78 92 8, 16 24 8.9 90 18,13 43 0.020
BDE 154 1-500 8.6 1.78 111 4, 14 27 8.9 97 20,8 42 0.027
BDE 153 1-500 11.6 1.78 102 10, 11 20 8.9 102 10,9 24 0.025
BDE 183 1-500 7.5 1.78 115 2, 13 30 8.9 110 13, 17 34 0.029
tefluthrin 1-50 5.4 1.78 81 12, 20 47 8.9 87 20, 24 31 0.014
transfluthrin 1-50 9.6 1.78 75 19, 20 23 8.9 69 18,21 37 0.101
cMorpyrifos 1-50 4.2 1.78 85 18, 27 48 8.9 86 19, 16 47 0.742
piperonyl 1-50 20.0 1.78 120 10, 14 41 8.9 104 14, 17 32 0.046
butoxide
bifenthrin 1-50 6.0 1.78 61 13, 11 30 8.9 62 15, 18 40 0.047
tetramethrin 2 0.5-25 15.0 1.78 70 9, 15 27 8.9 78 16, 12 25 0.011
X-cyhalothrin 0.3-15 12.4 1.78 75 9, 20 49 8.9 84 18,22 20 0.056
acrinathrin 1.5-75 6.8 1.78 96 11, 14 24 8.9 90 19, 25 25 0.87
cw-permethrin 0.2-10 5.1 1.78 90 8, 16 27 8.9 84 10, 11 38 0.019
trans- 0.3-15 5.1 1.78 91 9, 18 27 8.9 84 16, 15 48 0.032
pemiethrin
ß-cyfluthrin 3 3.5-1750 3.9 1.78 58 28, 29 32 8.9 60 20, 24 30 0.291
ß-cyfluthrin 4 3.5-1750 5.9 1.78 70 15,25 39 8.9 78 17, 23 33 0.974
Cypermethrin 1 8-400 3.2 1.78 63 15, 16 30 8.9 70 14, 25 24 0.153
Cypermethrin 2 8-400 4.2 1.78 109 2, 12 19 8.9 100 18, 14 19 0.141
a-cypermethrin 8-400 6.0 1.78 101 6, 10 12 8.9 80 10, 15 28 0.160
Cypermethrin 4 8-400 7.0 1.78 75 13, 13 57 8.9 74 9, 17 24 0.155
fenvalerate 1 0.25-12.5 8.6 1.78 88 10, 12 33 8.9 85 15,15 46 0.088
deltamethrin 5-250 14.2 1.78 96 16, 20 33 8.9 90 10, 14 32 0.265
S7
+tralomethrin
2
DPMA 0.1-1000 14.3 1.78 53 20,21 23 8.9 55 8, 10 31 0.032
TBX 0.1-1000 12.2 1.78 80 10, 15 46 8.9 87 17, 18 11 0.001
DPTE 0.1-1000 14.0 1.78 55 19, 20 45 8.9 40 14, 20 14 0.731
PBEB 0.1-1000 16.7 1.78 121 7, 10 43 8.9 120 11, 17 20 0.003
TBCT 0.1-1000 7.0 1.78 79 41,38 21 8.9 80 15, 13 46 0.002
BTBPE 0.1-1000 18.2 1.78 110 12, 12 32 8.9 114 7, 10 51 0.006
PBBz 0.1-1000 8.8 1.78 110 7, 13 26 8.9 94 14, 16 32 0.002
ATE 0.1-1000 15.8 1.78 96 19, 25 39 8.9 98 18, 26 35 0.007
BATE 0.1-1000 15.3 1.78 96 21,20 43 8.9 89 17, 14 40 0.006
EH-TBB 0.1-1000 11.3 1.78 109 18,21 41 8.9 105 12,16 45 0.006
PBT 0.1-1000 10.4 1.78 121 22,21 25 8.9 104 20, 15 31 0.003
HBB 0.1-1000 4.6 1.78 110 2, 8 22 8.9 100 14, 18 44 0.060
a-TBECH 0.1-1000 11.1 1.78 105 13,20 28 8.9 87 13,16 33 0.008
ß-TBEH 0.1-1000 10.4 1.78 69 21,24 26 8.9 64 21,24 41 0.007
a-TBCO 0.1-1000 12.3 1.78 65 11, 14 37 8.9 75 14, 17 49 0.013
ß-TBCO 0.1-1000 16.7 1.78 114 12, 10 39 8.9 79 15, 19 23 0.030
HCDBCO 0.1-1000 11.1 1.78 40 9, 12 37 8.9 52 14, 16 51 0.001
s-DP 0.1-1000 7.6 1.78 113 17, 15 45 8.9 104 15, 18 36 0.044
a-DP 0.1-1000 6.9 1.78 111 20, 24 47 8.9 113 20, 26 36 0.021
S8
References
1. S.L.R. Ellison A W (2012) Eurachem/CITAC guide: Quantifying Uncertainty in
Analytical Measurement.
2. B. Magnusson, T. Näykki, H. Hovind M K (2012) Handbook for Calculation of
Measurement Uncertainty in Environmental Laboratories.
S9
100
Paper II
Developmental neurotoxicants in human milk: comparison of concentrations and
intakes in three European countries
Eliška Čechová1
, Martin Scheringer1
'2
, Marta Seifertova1
, Ondřej Mikeš1
, Kristýna
Kroupová1
, Jan Kuta1
, Joan Forns 3
, Merete Eggesbo3
, Ilona Quaak4
, Marijke de Cock4
,
Margot van de Bor4
, Henrieta Patayová5
, Ľubica Palkovičová Murínová5
, Anton Kočan1
Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk
University, Kamenice 753/5, 625 00 Brno, Czech Republic
2
InstitutefarChemical and Bioengineering, ETH Zürich, Wolfgang-Pauli-Strasse 10, CH-8093
Zürich, Switzerland
3
Norwegian Institute of Public Health, Lovisenberggata 8, 0403 Oslo, Norway
4
Department of Earth and Life Sciences, Vrije University, De Boelelaan 1085, 1081 HV
Amsterdam, The Netherlands
5
SlovakMedical University, Faculty of Public Health, Limbová 12, 83303 Bratislava, Slovakia
Reprinted with permission from
Science of the Total Environment 2017, Volume 579, 637-645
Copyright 2017 Elsevier
101
Sdence of the Total Environment 579 (2017) 637-645
ELSEVIER
Contents lists available at ScienceDirect
Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv
Developmental neurotoxicants in human milk: Comparison of levels and /• \ C r o s s M a r k
intakes in three European countries
Eliška Čechováa
, Martin Scheringera b
* , Marta Seifertovaa
, Ondřej Mikeša
, Kristýna Kroupováa
, Jan Kutaa
,
Joan Fornsc
, Merete Eggesboc
, Ilona Quaakd
, Marijke de Cockd
, Margot van de Bord
, Henrieta Patayová e
,
Lubica Palkovičová Murínová e
, Anton Kočan a
a
Research Centre for Toxic Compounds in the Environment, Faculty ofScience, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
b
Institute for Chemical and Bioengineering, ETHZurich, Vladimir-Prelog-Weg 1, CH-8093 Zurich, Switzerland
c
Norwegian Institute ofPublic Health, Lovisenberggata 8,0403 Oslo, Norway
d
Department ofEarth and Life Sciences, Vrije University, De Boelelaan 1085, 10S1 HV Amsterdam, The Netherlands
e
Faculty ofPublic Health, Slovak Medical University, Limbová 12, 83303 Bratislava, Slovakia
H I G H L I G H T S G R A P H I C A L A B S T R A C T
• Levels of selected neurotoxicants in human
milk were compared in three European
countries.
• Levels of MeHg were highest in Norway
and of PCBs, DDE, DDT and HCB were
highest in Slovakia.
• Pharmacokinetic models were used to
estimate the daily or weekly intakes of
the neurotoxicants.
• Intakes derived from human milk were
consistent to the intakes based on the
food consumption patterns.
M 1KH IM
i '
6» 1»
...: :|4
/VV Sff
Slovakia the Netherlands Norway
A R T I C L E I N F O
Article history:
Received 21 September 2016
Received in revised form 3 November 2016
Accepted 7 November 2016
Available online 25 November 2016
Editor: Adrian Covaci
Keywords:
Developmental neurotoxicity
Daily intakes
Methylmercury
Organochlorine compounds
Pharmacokinetic model
A B S T R A C T
Developmental neurotoxicants (DNTs), such as methylmercury (MeHg), polychlorinated biphenyls (PCBs) and
selected organochlorine pesticides (OCPs), have gained increasing interest recently due to their possible relation
to developmental disorders in children, which are increasing worldwide. We analyzed levels of 14 developmental
neurotoxicants in human milk samples from Slovakia (n = 37), the Netherlands (n = 120) and Norway (n =
388). Positive identification for most target analytes was >95% in all samples. In all three countries MeHg was
measured for the first time in mother milk. The highest MeHg levels were observed in Norway (39 pg g - 1
ww) with the highest fish consumption. Levels of indicator PCBs (iPCBs, sum of PCB 28, 52,101,138,153 and
180), HCB and DDE + DDT were 2-4 times higher in Slovakia compared to the Netherlands or Norway. The levels
of MeHg and organochlorine compounds were used for calculations of weekly or daily intakes (top-down approach)
by means of pharmacokinetic modeling. The intakes ranged from 0.014 to 0.142 (rg kgb"J week- 1
for
MeHg and from 0.043 to 17.4 ng kgj^J day- 1
for organochlorine compounds in all three countries. Intakes of
iPCBs exceeded a tolerable daily intake of 10 ng kgi^J day"1
in 16% of the Slovak participants. The top-down estimates
were compared with bottom-up intakes based on national dietary estimates and the results showed good
Corresponding author at: Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Kamenice 753/5,625 00 Brno, Czech Republic.
E-mail address: martin.scheringer@chemethz.ch (M. Scheringer).
http ://dx.doi.org/l 0.1016/j.scitotenv.2016.11.046
0048-9697/© 2016 Elsevier B.V. All rights reserved.
638 E. Cechova et al / Science of the Total Environment 579 (2017) 637-645
consistency between both approaches, with the bottom-up intakes exceeding the top-down by a factor of maximum
3.8 for iPCBs in the Netherlands and 3.9 for HCB in Slovakia. This confirms that food consumption in all
three countries represents the dominant pathway of exposure to these developmental neurotoxicants.
© 2016 Elsevier B.V. All rights reserved.
1. Introduction
Worldwide, 10-15% of the children have been diagnosed with some
form of neurodevelopmental disorder, such as autism spectrum disorder
(ASD), attention deficit hyperactivity disorder (ADHD) or learning
disabilities, and the incidences are increasing (Grandjean and
Landrigan, 2016; Smirnova et al., 2014). Approximately 3% of the incidence
of these disorders have been found to be associated with the exposure
to toxic chemicals and physical agents (e.g., radiation) and
another 25% arise out of the interplay of genetic and environmental factors
including physical, chemical, and biological agents (NRC, 2000). Environmentally
attributable costs due to ASD, ADHD or conduct disorders
were estimated up to $2.49 billion in the European Union in 2008
(Bartlett and Trasande, 2014). In pregnant women, the foetus is exposed
to developmental neurotoxicants (DNTs) due to passage of the
chemicals from mother to foetus via the placenta. After birth, the
major exposure route to these chemicals in the first months of life is
human milk. Useful information regarding maternal body burden and
also potential exposure of the child can be thus obtained by analysis of
human milk as it is considered as one of the best sampling matrices
due to a good availability and non-invasive sample collection (UNEP,
2013).
Approximately 200 chemicals have been shown to be neurotoxic to
humans, but only a handful have yet been tested for developmental
neurotoxicity (Landrigan et al., 2004). Methylmercury (MeHg) is a
known neurotoxicant due to several incidents, such as in Minamata,
Japan, in the 1960s, where exposed children suffered from microcephaly,
cerebral palsy, deafness and gross impairment of motor and mental
development, while their mothers were not affected (Castoldi et al.,
2008). Bellinger etal. (2016) estimated incidence of mild forms of intellectual
disabilities (1Q 50-69) in individual countries related to MeHg
exposure. In this modeling study they used data from MeHg measurements
in hair, blood or cord blood and assumed a loss of 0.18 1Q points
with each p.g g _ 1
increase in maternal hair (Axelrad et al., 2007), while
the distribution of 10. points in each country had a mean of 100 and a
standard deviation of 15. The largest incidences were shown to occur
for island or coastal countries where seafood was a major component
of a diet. For example, in Finland, Sweden and Norway the incidence
of these disabilities was 1.07 infants per 1000 newborns, while in the
rest of Europe the incidence was 0.5 infants per 1000 newborns.
Another important group of developmental neurotoxicants are organochlorine
compounds such as polychlorinated biphenyls (PCBs)
and selected organochlorine pesticides (OCPs), for which an association
with ADHD-like behavior has been reported (Forns et al., 2016; Sagiv et
al., 2010). They were banned or restricted in the 1970/80s, but as a result
of their wide use and persistence they are still present in Europe
in both the environment and human body in relatively high concentrations
compared to other persistent neurotoxicants such as brominated
flame retardants or non-persistent current-use compounds (Croes et
al., 2012; Polder et al., 2008) and represent the dominant part of the
DNT body burden. Assessment of the presence of MeHg and organochlorine
compounds in a mixture showed the induction of different effects
to motor activity and coordination in rats compared to the
exposure to the single compounds (Cauli et al., 2013).
Measurement of MeHg and organochlorine compounds in human
samples can be used for the estimation of daily intakes by pharmacokinetic
modeling. In previous years it was shown that the dietary intakes
of indicator PCBs (iPCBs, £ PCB 28, 52,101,138,153 and 180) or MeHg
in Europe exceeded the tolerable daily intakes estimated by the
European Food Safety Authority (EFSA) or French Food Safety Agency
(ANSES, 2010; EFSA, 2005). Selected European countries with high
fish consumption, which is a major source of MeHg for humans (EFSA,
2012a), or with high former production of PCBs, such as Slovakia, have
called for information about DNT body burdens.
In the present study, levels and temporal trends of MeHg and selected
organochlorine compounds in human milk in three European cohorts
representing Central (Slovakia), Western (the Netherlands) and
Northern Europe (Norway) were investigated. In these countries, levels
of MeHg were measured for the first time in human milk. By using
steady-state pharmacokinetic models, we derived intakes of developmental
neurotoxicants from the measured concentrations (top-down
approach) and compared them to the safety limits. These top-down intakes
were subsequently compared to intakes obtained from contaminant
levels in food and daily food consumption in individual countries
(bottom-up approach).
2. Materials and methods
2.1. Human milk samples
A total number of 545 human milk samples from three European
countries were analyzed. The following mother-child cohorts were included
in the study: PRENATAL (Prospective cohort study of developmental
origins of adult diseases in the Slovak population) from
Slovakia (n = 37) with sample collection from 2010 to 2012, L1NC
(Linking endocrine disrupters in maternal Nutrition to Child health)
from the Netherlands (n = 120) collected between 2011 and 2014
(de Cock et al., 2016) and HUM1S (HUman Milk Study) from Norway
(n = 388) with sample collection between years 2001-2006 (Eggesb0
et al., 2009). Women in all cohorts were recruited during antenatal
visits to the midwife, where written informed consent was obtained.
Human milk samples were collected by mothers during weeks four to
eight after delivery manually or using breast pumps into pre-treated
(prewashed and solvent rinsed) bottles and stored at —20 °C. Sample
aliquots (10-12 ml) were sent to the Trace Laboratories of RECETOX
(Research centre for toxic compounds in the environment, Masaryk
University, Czech Republic) for the chemical analysis as part of the
DENAM1C (Developmental Neurotoxicity Assessment of Mixtures In
Children) project. Selected developmental neurotoxicants were analyzed,
such as MeHg, iPCBs, PCB 118 and several legacy OCPs including
HCB, -y-HCH (lindane), p,p'-DDE, p,p'-DDT, dieldrin and mirex. General
characteristics of mothers in individual countries are provided in Table
1. No significant differences (p < 0.01) in mothers' weight, BM1, lipid
fraction and parity were found between the three cohorts. The influence
of parity (primipara/multipara mothers) on the levels of MeHg and organochlorine
compounds was further assessed using the Mann-Whitney
U test.
22. Sample preparation and analysis
The analysis of MeHg in human milk was performed with 2 ml of liquid
milk spiked with a solution of198
Hg-enriched MeHg (EMMS-1, National
Research Council, Canada) and mixed with 2 ml of 6 M HC1. The
MeHgCl complex was extracted twice with 3 ml of toluene. The combined
organic extract was further extracted with 0.5 ml of 1% L-cysteine
aqueous solution. Instrumental analysis was performed with a liquid
chromatograph (Agilent 1100 series) using a reversed-phase C18 chromatographic
column (Synergi Hydro-RP, 150 mm x 4.6 mm, 4 p.m)
E. Čechová etaL / Science of the Total Environment 579 (2017) 637-645 639
Table 1
General characteristics of the mothers (for continuous variables median values and 25th percentile and 75th percentile ranges are presented in parentheses).
Slovakia (n = 37) The Netherlands (n = 120) Norway(n = 388) p-Valueb
Age (years) 30(27-33) 31 (29-34) 30(26-33) 0.00
Mother's height (cm) 168(164-169) 172(169-175) 168(163-171) 0.00
Mother's weight (kg)a
62 (56-72) 70 (63-73) 66 (60-74) 0.02
BMI (kg n r 2
) a
21.9 (20.5-24.0) 23.2 (21.4-24.6) 23.4 (21.4-26.0) 0.08
Lipid fraction, % 27.6 (26.0-31.3) 29.4 (27.4-31.5) 29.6 (26.9-33.0) 0.23
Lipids in human milk, % 4.0 (3.0-5.1) 3.8 (3.2-4.7) 3.0 (2.3-3.8) 0.00
Maternal parity, % 0.30
First child 41 43 40
Second child 47 38 38
Third child or more 11 19 22
Missing (n) 1
a
Before pregnancy.
b
Differences between three cohorts evaluated with Kruskal-Wallis test for continuous variables and chi-square test for categorical variables.
connected to an inductively coupled plasma mass spectrometer
(Agilent 7700x 1CP-MS).
The analytical method for the analysis of PCBs and OCPs is described
elsewhere (Čechová et al., 2016). Briefly, 8-10 ml of the liquid milk
were freeze-dried and 50 (jl of the mixture of labeled internal standards
were added. After a pressurized solvent extraction
(hexane:dichlormethane:methanol = 5:2:1, v/v/v), the lipid content
was determined gravimetrically. This value was then used for adjustment
of the levels of hydrophobic organochlorine compound to the
lipid weight. Two non-destructive clean-up steps were involved, dialysis
with 2 x 30 ml of hexane at 10 °C (2 x 24 h) and a column chromatography
(C18 + basic alumina) with the elution of 9 ml of acetonitrile.
A Trace 1310 gas chromatograph with a 60-m x 0.25-mm x 0.25-(jm
HT8 fused-silica capillary column (SGE Analytical Science) coupled to a
DFS double-focusing high resolution magnetic sector mass spectrometer
(Thermo Scientific) was used for the instrumental analysis. Detailed
information on instrumental analysis parameters and Quality assurance/Quality
control can be found in the Supplementary material
(Table SI).
2.3. intake calculations (top-down approach)
The calculation of MeHg intake /MeHg was performed with a pharmacokinetic
(Pl<) model derived from Carrier et al. (2001). The model assumes
steady-state, i.e. intake equals the sum of loss and
metabolization:
'MeHg = M b b X (/<QF + fcQI) (1)
where M b b is the mother's MeHg body burden at steady-state (|ig kgbwJ),
ko_F is the whole-body-to-faeces transfer coefficient of organic mercury
(9.0668 x 1 0 - 5
day- 1
) and /<qj is the metabolism rate constant of organic
Hg to inorganic Hg (0.01347 day"1
) (Carrier et al., 2001). M b b
was reported to be approximately 12.6 times higher than the amount
of MeHg in the whole blood, mMeHg,wB (Smith and Farris, 1996). The
amount in whole blood, in turn, was calculated as the sum of the
MeHg amount occurring in plasma (cp ia s m a , \\g g - 1
blood) and in red
blood cells (cRBc. Hg g _ 1
blood) multiplied by the total amount of
blood in the human body, mb (4480 g for a 65-kg woman (Cutnell &
Johnson, 1998; Mikhail et al.,2001)).
. . _ 12.6 x mb x (cp t o s m a + cRBC)
where mm is the average mother's body weight (kg).
If the mother's exposure to methylmercury is only via fish consumption,
the MeHg concentration in plasma has been shown to be approximately
five times higher than in mother milk, cm (Sakamoto et al.,
2002). Similarly, the amount of MeHg in red blood cells (cRBc) was reported
to be 1-8 times higher than in plasma depending on the fish
consumption (Sakamoto et al., 2002). The final intake, /MeHg (Hg kgbJ"
week- 1
), can therefore be calculated as:
i _ 1 2 . 6 x m b x 5 x ( c m + / f c x c m ) , ,
'MeHg — — X U X Keg + KQI (j)
mm
where/fc is a factor reflecting the fish consumption in the country,/fc =
8 was used for Norway as a high-fish consuming country and/fc = 1 for
Slovakia and the Netherlands as low-fish consuming countries according
to the EFSA food consumption database (EFSA, 2011), cm is the
MeHg concentration in human milk (pg g - 1
ww) and u is a unit conversion
factor (7 days/106
pg).
For organochlorine compounds, the following equation derived
from a one-box Pl< model at steady state was used to estimate oral intakes
from human milk:
In(2) x/L c0 C | H M
'oc = j x — (4)
Jabs r
l / 2
where c0 c,hm (ng g~1
lw) is the concentration measured in human milk,
/0c is the intake of organochlorine compounds (ngkgbvJ day- 1
),fL is the
fraction of lipid tissue in a mother's body (g k g b J ) , / a b s is the absorbed
fraction, where the value of 0.9 was used (Moser and McLachlan,
2001) and t1 / 2 is the intrinsic elimination half-life (day- 1
). The lipid
fraction,/L, was calculated using the mothers' age, ta g e , and body mass
index (BMI). The BMI was obtained as the ratio of a mother's weight
and height squared (Deurenberg et al., 1991) reported in the cohort
questionnaires.
/ L = 10 x (1.2 x BMI+ 0.23 x ta g e -5.4) (5)
Selected intrinsic elimination half-lives are provided in Table 3. For
mirex no data on elimination half-lives in humans were available; according
to the negligible metabolism and slow elimination of mirex
(Choudhury et al., 2003), an estimated half-life of 15 years was used.
This is the maximum value of the half-life which was recommended
to use for persistent compounds (Bu et al., 2015; Shirai and Kissel,
1996) and it also corresponds to the half-life derived from the half-life
in rats (ti/2,rat = 1-19 years) using the equation reported by Geyer et
al. (2004):
logt1/2 = 1.341ogt1/2,rat + 1.25 (6)
The obtained intakes were subsequently compared to the tolerable
weekly intake for MeHg and oral reference doses revised by the Integration
Risk Information System (IRIS, 2014) for OCPs and PCBs.
2.4. Dietary intake estimations (bottom-up approach)
The intakes obtained from the DNT levels found in the human milk
samples were compared to intakes based on the national dietary
640 E Cechová et aL / Science of the Total Environment 579 (2017) 637-645
surveys and the presence of the DNTs in food. The bottom-up intakes
were estimated for individual iPCB congeners in all three countries
and for DDE + DDT, HCB and 7-HCH intakes in Slovakia. Levels of dieldrin
and mirex measured in food were below LOD in most food commodities,
so the bottom-up intakes could not be calculated.
For all three countries we used the dietary surveys from the years
when samples were collected. For Slovakia, the Czech consumption survey
from the EFSA chronic food consumption database for adults in
2011 was used (EFSA, 2011), since the dietary habits in the Czech Republic
and Slovakia are similar. For the Netherlands, the national database
of the daily food consumption in 2011 was used (EFSA, 2011).
For Norway, the complete bottom-up estimates were already published
by Kvalem et al. (2009) and they were based on the questionnaire data
from the Norwegian Fish and Game Study (NFG) from 2000-3. A summary
of all data used for the bottom-up estimates is shown in Table
S3 in the Supplementary material.
Due to the limited availability of the PCB or OCP levels for all food
commodities from recent years, the mean values reported by EFSA
from 22 European countries from 1995 to 2008 for iPCB congeners
were used for Slovakia and the Netherlands (EFSA, 2012b). Mean levels
of 7-HCH in food in Slovakia from the years 2009-12 were obtained
from the Slovak Food Research Institute (National Agricultural and
Food Centre, Bratislava). HCB levels from 2005-11 were obtained from
the Global Environment Monitoring System database of WHO (GEMS/
WHO) and DDT + DDE levels from 2011 were obtained from the State
Veterinary Administration of the Czech Republic. Average fat contents
for those commodities where the levels were adjusted on a lipid basis
were obtained from the Slovak Food Composition Database (SFCDB,
2010) and from the Dutch Food Consumption Database from National
Institute of Public Health (R1VM, 2013). The fat content of the food commodities
and food consumption rates in Slovakia and the Netherlands
are summarized in Tables S4 a, b, c in the Supplementary material.
3. Results and discussion
3.1. DNT levels in three European countries
The levels of developmental neurotoxicants in the human milk samples
were compared among three European countries (Table 2).
3.1.1. Methylmercury
Methylmercury was detected in >98% of the samples in all three
countries. The median level in Norway (39 pg g _ 1
ww) was
approximately twice as high as in Slovakia and the Netherlands
(18 pgg- 1
ww in both countries). The median MeHglevels in the Netherlands
and Slovakia were the same, which also corresponds to the similar
dailyfishconsumption (15.7 g day- 1
in Slovakia and 14.0 g day- 1
in
the Netherlands (EFSA, 2011)). To date, MeHg levels in human milk in
other European countries are limited. In Slovenia, a median level of
70 pg g _ 1
ww in human milk was reported, which is 1.8 to 4 times
greater than in our study. However, in that study an initial screening
of human hair for 574 mothers was performed and only the 15 mothers
with total Hg content in hair higher than 1 ug g _ 1
were selected for
MeHg determination in human milk. Therefore, the MeHg levels in
human milk were biased towards mothers with potentially the highest
MeHg exposure in the Slovenian population (Miklavčič et al., 2011). The
MeHg levels reported in mother milk in the high-fish consuming population
in Amazonia showed levels of 870 pg g _ 1
ww for a traditional
community and 120 pg g _ 1
ww for an urban population (Vieira et al.,
2013). That is 3 to 20 times more than in the present study. Since fish
consumption is a major source of MeHg, this elevation might be explained
by the differences in fish consumption in Amazonia,
406 g day- 1
(Oliveira et al., 2009), compared to 56 g day- 1
reported
for Norway (Fagt et al., 2012).
3.1.2. PCBs
All six iPCB congeners and PCB 118 were detected in >95% of the
samples in all three countries (Table S2 in the Supplementary material).
The order of the levels of the PCB congeners was: PCB 153 > PCB
180 > PCB 138 > PCB 28 > PCB 101 > PCB 52 (in Norway, the median
of PCB 138 (17.4 ng g"1
lw) was higher than PCB 180 (13.9 ngg"1
lw)). This is in agreement with previous studies with similar years of
sample collection (Malisch, 2006; Polder et al., 2009).
The median sum of iPCBs in Slovakia was 144 ng g _ 1
lw and it was
the highest level from all three countries. There were some differences
between the levels of higher-chlorinated PCBs (hexa- and hepta-CB)
and lower-chlorinated PCBs, such as tri-, terra- and penra-CBs among
studied countries. The levels of hexa-CB 138,153 and hepta-CB 180 in
Slovak samples collected between 2010-12 were approximately three
to four times higher than in the Dutch samples collected in 2011-14.
This is the result of the heavy use and production of PCB technical mixtures
between 1950-1980 in Slovakia (Langer et al., 2014). The most
studied area in Slovakia was the eastern part around the Michalovce district
in the vicinity of the Chemko factory producing PCBs (Delor)
(Hovander et al., 2006; Jursa et al., 2006), where the PCB concentrations
in humans were shown to be twice or three times higher than in the rest
Table 2
Levels of DNT compounds measured in three European cohorts, levels of MeHg in p g g - 1
whole weight (ww), levels of PCBs and OCPs in n g g - 1
lipid weight (lw).
Slovakia The Netherlands Norway
5th Median Mean 95th 5th Median Mean 95th 5th Median Mean 95th
MeHg 4.00 18.00 30.19 77.60 3.00 18.00 26.23 70.10 10.00 39.00 56.07 153.25
PCB 28 0.83 1.11 1.38 2.73 0.49 0.79 0.90 1.68 0.84 1.56 1.81 3.43
PCB 52 0.09 0.13 0.15 0.20 0.09 0.17 0.23 0.69 0.24 0.51 0.64 1.53
PCB 101 0.13 0.22 0.28 0.35 0.09 0.19 0.22 0.45 0.27 0.58 0.74 1.81
PCB 138 14.57 30.70 40.70 91.66 5.38 10.68 12.24 23.41 7.58 17.43 21.19 43.35
PCB 153 27.02 59.09 68.62 133.39 7.55 15.95 17.40 30.87 12.64 27.44 32.96 67.25
PCB 180 19.92 44.32 54.45 97.84 4.54 10.72 11.68 22.13 5.94 13.93 16.86 36.12
PCB 118 1.54 3.51 4.87 10.22 1.79 3.59 3.88 7.35 2.14 5.22 6.48 14.21
iPCBs 66.68 144.10 165.57 319.41 18.56 39.08 42.68 79.75 30.32 62.07 74.00 147.98
ratio PCB 138/153 0.48 0.58 0.59 0.69 0.53 0.72 0.71 0.87 0.50 0.64 0.64 0.78
ratio PCB 180/153 0.63 0.80 0.83 1.12 0.46 0.64 0.66 0.90 0.38 0.50 0.51 0.68
HCB 10.38 12.89 13.33 18.69 4.29 6.22 6.46 9.67 5.61 7.67 8.79 13.50
7-HCH 0.08 0.15 0.17 0.32 0.07 0.18 0.20 0.47 0.17 0.31 0.42 1.10
p,p'-DDE 79.48 166.78 265.71 670.32 24.42 49.45 69.24 121.62 16.96 51.57 69.34 184.65
p,p'-DDT 4.95 8.74 10.57 25.77 0.88 1.54 1.98 3.87 0.74 1.79 2.48 5.54
DDE + DDT 84.82 170.79 276.28 693.04 25.58 51.18 71.22 125.04 17.73 53.54 71.87 192.75
Dieldrin 0.07 0.18 0.19 0.38 0.05 0.12 0.15 0.30 0.08 0.23 0.30 0.75
Mirex 0.20 0.41 0.55 1.08 1.24 2.27 2.41 4.01 0.92 2.05 2.55 5.51
E Cechová etat / Science of the Total Environment 579 (2017) 637-645 641
of Slovakia (Kocan et al, 1994). This was confirmed by the present
study, where the median of the summed iPCB from eastern Slovakia
(284 ngg- 1
lw,n= 5) was more than twice as high as in the rest ofSlovak
samples (128 ng g"1
lw, n = 32). The differences in PCB 180/PCB
153 or PCB 138/PCB 153 ratios between individual countries (Table 2)
indicate the use of different technical mixtures but also different environmental
factors in the countries. Interestingly, levels of lower-chlorinated
PCBs, i.e. tri-CB 28, tetra-CB 52, penta-CB 101 and penta-CB 118 in
Slovakia are similar to Dutch and Norwegian levels despite the heavy
use of Delor 103 in Slovakia with the high content of tri and terra-chlorinated
congeners (Frame et al., 1996). This could be caused by the
higher volatility of lower-halogenated congeners. In the Netherlands,
the median ofthe summed iPCB was 39.1 ng g - 1
lw. The Dutch samples
were collected in three different areas; Zwolle city area (n = 64), agriculture
with a rather low level of urbanization; Purmerend (n = 30)
with a high degree of urbanization, and Den Helder (n = 26), a fishery
region with a naval base (de Cock et al., 2016). Comparison of the levels
between these three areas did not show any significant differences in
PCB or OCP median levels (iPCB 40.3 ng g"1
lw and DDT + DDE
51.1 ng g - 1
lw in Zwolle, 35.9 and 47.0 ng g - 1
lw in Den Helder and
37.9 and 52.8 ng g - 1
lw in Purmerend). This would indicate that there
are no point sources in the sample regions for these compounds. In Norway
the median of summed iPCB was 62.2 ng g - 1
lw and the levels are
in good agreement to other studies from similar years (Malisch, 2006;
Polderetal., 2009).
3.7.3. OCPs
Organoehlorine pesticides, p,p'-DDE, p,p'-DDT, HCB and mirex were
detected in 100% of all milk samples. Dieldrin and 7-HCH had detection
frequencies between 62-99% (Table S2 in the Supplementary material).
In Slovakia, levels of individual OCPs were in the range of 0.18-
167 ng g - 1
lw. Forp,p'-DDE the levels were the highest from all three
countries, but also compared to other European studies where the samples
were collected in similar years, such as Sweden, Croatia or Belgium
(Croes et al., 2012; Klinčié et al., 2014; Lignell et al., 2014), which is due
to the high emissions and high use of DDT in Central and Eastern Europe
(Paeyna et al., 2003). Within Slovakia, the eastern part around
Michalovce (median Y2 DDE + DDT 541 ng g - 1
lw, n = 5) showed
more than three times higher levels than in the rest ofSlovakia (median
Y2 DDE + DDT 164 ng g - 1
lw, n = 32), since it was also an important
agricultural area with heavy use of this pesticide (Langer et al., 2014).
Additionally, DDE/DDT ratios in all three countries were compared.
Low values of the ratio indicate ongoing exposure to DDT. In the case
of countries with recent high exposure of DDT such as Mexico or selected
African countries, the DDE/DDT ratio is low and close to 1 (Jaga and
Dharmani, 2003). In our study the ratios were 19.1 for Slovakia, 32.3
for the Netherlands and 28.9 for Norway, which indicates that exposure
to DDT was more recent in Slovakia. Unlike DDTs or HCB, levels of dieldrin
in Slovakia were approximately five times lower than in Norway or
the Netherlands. There were no significant differences between mirex
levels in all three countries. In the Netherlands, OCPs levels ranged between
0.12-49.5 ng g - 1
lw. The HCB levels were shown to be similar
to Belgium (Croes et al., 2012) and p,p'-DDE levels were approximately
two times higher than in Sweden or Croatia (Klinčié et al., 2014; Lignell
et al., 2014). In the case of -y-HCH, Dutch levels were seven times lower
than in Croatia (Klinčié et al., 2014). In Norway, the OCP levels ranged
between 0.22-51.6 ng g - 1
lw and the levels of p,p'-DDE, p,p'-DDT and
dieldrin in Norway were similar to the results from the 4th WHO
study in 2006 (Malisch, 2006), but the levels of HCB and 7-HCH were
approximately two times higher in this study (Eggesb0 et al., 2009;
Malisch, 2006). A comparison of the levels in human milk in Belgium
from similar years showed that the median level ofp,p'-DDE in Norway
was approximately three times lower and of HCB two times lower than
in Belgium (Malisch, 2006).
3.1.4. Influence ofparity
The influence of parity on the levels of MeHg did not show any significant
difference between primipara and multipara mothers in any
country (p < 0.01). The influence of parity on the levels of the organoehlorine
compounds varies among different studies. While some studies
have reported higher levels in primipara mothers compared to
multiparae (Gasull et al., 2013; Porta et al., 2010; Salihovie et al.,
2012), LaKind et al. (2009) and Hooper et al. (2007) have shown that
decreases in the levels of persistent compounds during breastfeeding
were not statistically significant. In the present study no significant differences
between the levels of organoehlorine compounds of primipara
and multipara mothers were observed in Slovakia and the Netherlands
(p < 0.01). However, the number of the samples was low (37 samples
from Slovakia and 120 from the Netherlands), which might influence
the results. In Norway, median levels of PCBs 138,153, 118 and p,p'DDE,
p,p'-DDT and dieldrin were found to be higher (p < 0.01) in primipara
mothers by a maximum factor of 1.2-1.3.
32. Temporal trends oforganoehlorine compounds
The temporal trends of iPCB, p,p'-DDE or DDTs and HCB using the
milk levels from this study and data reported in previous studies from
the three countries were investigated and a decreasing trend was observed
(Fig. la, b, e), which is in agreement with other studies (Polder
et al., 2009). In Slovakia, the decrease of iPCB, p,p'-DDE and HCB levels
was 76.5, 87.8 and 98%, respectively over the previous ten years. In
the Netherlands, the decline for all the three DNT groups was in the
range from 79.9 to 85% and similarly in Norway from 74.8 to 77.6%
over the same time period. The time trends show that the levels are
much lower than twenty or thirty years ago, but the compounds are
still present in humans and will likely persist in the future and thus represent
a source of chronic exposure to DNTs.
3.3. Intake calculations (top-down approach)
Weekly intake of MeHg and daily intakes of PCBs and OCPs were derived
from the human milk data in combination with published values
of elimination rate constants for MeHg or elimination half-lives for organoehlorine
compounds. The intrinsic elimination half-lives that
were used for OCPs and PCBs and the resulting top-down intakes are
provided in Table 3. The intakes of iPCBs ranged between 2.2 to
7.4 ng kgbw day- 1
for all three countries. The fri-, tetra- and penta-ehlorinated
congeners PCB 28, PCB 52 and PCB 101 contributed the least to
the sum of iPCBs and their intakes were below 0.18 ng kgbJ day- 1
. The
intakes of OCPs ranged between 0.09-17 ng kgbJ day- 1
for Slovakia,
0.06-5 ng kgbw day- 1
for the Netherlands and 0.12-5.3 ng kgj^J day- 1
for Norway with the highest contribution from p,p'-DDE in all three
countries.
The intakes were compared to tolerable weekly intakes for MeHg or
daily intakes for organoehlorine compounds. For methylmereury, a tolerable
weekly intake of 1.3 p.g kgbw was established (EFSA, 2012a),
which was exceeded in two out of 388 Norwegian samples, but in
none of the Slovak or Dutch samples. The PCB and OCP top-down intakes
were compared with oral RfD established by the US EPA
(800 ng kg^1
day- 1
for HCB, 300 ng kgbJ day- 1
for 7-HCH, 500 ng
kgbw day- 1
for DDT, 50 ng kgbw1
day- 1
for dieldrin and 200 ng kgbw1
"
day- 1
for mirex) and the median values constituted 0.01% (7-HCH) to
2.7% (dieldrin) of the RfD. For iPCBs, no reference dose was available,
but the concentration of 10 ng kgbJ day- 1
was reported as a tolerable
daily intake by the French Food Safety Agency (ANSES, 2010); above
this concentration changes in brain development of the foetus were observed
in an animal study. This value was exceeded in 10 out of388 Norwegian
samples (2.6%) and 6 out of 37 Slovak mothers (16%), but in
none of the Dutch samples.
642 E. Cechovä et al / Science of the Total Environment 579 (2017) 637-645
1992 1997 2002
Year
Norway
1991
Year
2001
Fig. l.Time trends of selected DNT concentrations in mother milk in (a) Slovakia, data from 1992 to 2006 reported by Kocan et al. (1994), Petrik et al. (2006), Malisch (2006), (b) the
Netherlands, data from 1998 to 2001 reported by Albers et al. (1996), Ataniyazova et al. (2001) and in (c) Norway, data from 1981 to 1991 reported by Johansen et al. (1994), Skaare
et al. (1988), Clench-Aas et al. (1988); levels from 1981 and 1986 recalculated from whole weight, assuming 3.5% milk lipid content (Polder et al., 2009). Due to the differences in the
levels among the countries, the scale of they-axis differs between the graphs.
3.4. Intakes derivedfrom national food consumption data (bottom-up)
For methylmercury, the median of dietary intake estimate for the
Czech Republic, which is assumed to be similar to Slovakia and therefore
used here, was reported to be 0.2 ug kgj^J week- 1
, for the Netherlands
0.07 ug kgbJ week- 1
(EFSA, 2012a) and for Norway 1 ug kgbJ week- 1
(EFSA.2004).
Published intakes of PCBs in Norway ranged between 0.14-
1.38 ng kgbw1
day- 1
(Kvalem et al., 2009), in Slovakia between 0.75-
3.53 ngkgbJ day- 1
and in the Netherlands between 0.41-2.49 ngkgbJ"
day- 1
for individual PCB congeners. In Slovakia, the bottom-up intake
for the sum of DDE + DDT was 15.2 ngkgbJ day- 1
, for HCB 4.6 ngkgbJ"
day- 1
and for 7-HCH 3.2 ng kgbJ day- 1
.
3.5. Top-down versus bottom-up approach
Ideally, the top-down and bottom-up estimates of the weekly or
daily intakes should be equal. However, for MeHg and the majority of
the organochlorine compounds, the bottom-up intakes exceed the
top-down results (Fig. 2). In all three countries, MeHg weekly intakes
obtained from the bottom-up estimation by EFSA were approximately
2.5 to 7 times higher than intakes calculated in this study from the
top-down approach. The lower values in the top-down estimates
could be partly caused by the losses of MeHg when the samples were repeatedly
frozen and unfrozen during sample aliquoting, which might
cause losses of up to 30% as described for blood samples treated in this
manner (Horvat and Byrne, 1992).
In Slovakia and the Netherlands, the 2~2 'PCB intakes from the bottom-up
estimates were 1.3 and 3.8 times higher, respectively, than in
the top-down approach (Fig. 2). This can be explained by the fact that
the PCB levels in food, which were reported as mean concentrations
from 1995 to 2008 (EFSA, 2012b), might be too high; there has been a
gradual decrease in PCB concentrations in food over time (Baars et al.,
2004). Whereas for higher-chlorinated PCB congeners such as PCB
138,153 and 180 the bottom-up intakes exceeded the top-down by a
maximum of 3.5, for the lower-chlorinated congeners (PCB 28, 52 and
101) it was 4.6 up to 36.6 times. In Slovakia, 7-HCH and HCB intakes
from the bottom-up calculations were 1.3 and 3.9 times higher than
the top-down values, while for the Y2 DDE + DDT the top-down intake
was 1.2 times higher. The higher bottom-up estimates for HCB could be
caused by the fact that some food levels available for the calculations
were from 2005, when the levels published by the Centre for health,
Table 3
Elimination half-lives and top-down intakes of MeHg (ug k g ^ week- 1
) and of selected organochlorine compounds (ng k g ^ day- 1
) for three countries.
Slovakia The Netherlands Norway
t1 / 2 (years) Median 95th Max Mean Median 95th Max Mean Median 95th Max Mean
MeHg 0.02 0.07 0.27 0.03 0.01 0.05 0.14 0.02 0.14 0.56 1.56 0.21
PCB 28 5.5" 0.13 0.32 0.45 0.15 0.09 0.22 0.31 0.10 0.18 0.42 1.48 0.21
PCB 52 2.6" 0.03 0.05 0.20 0.03 0.04 0.17 0.22 0.06 0.13 0.37 1.14 0.16
PCB 101 2.8b
0.04 0.09 0.53 0.06 0.04 0.11 0.15 0.05 0.13 0.42 1.91 0.17
PCB 138 10.8a
1.82 5.58 8.12 2.33 0.63 1.51 2.46 0.72 1.05 3.01 6.08 1.24
PCB 153 14.4a
2.63 7.03 10.78 2.95 0.71 1.47 2.85 0.77 1.20 2.93 7.32 1.45
PCB 180 11.5a
2.59 7.19 8.52 2.92 0.58 1.24 3.82 0.65 0.75 1.83 4.49 0.92
PCB 118 9.3a
0.24 0.89 1.34 0.33 0.24 0.51 0.80 0.26 0.35 0.99 2.64 0.44
l'PCBs 7.40 20.19 28.50 8.45 2.18 4.30 9.33 2.35 3.46 8.34 17.91 4.13
HCB 4.2C
1.17 1.76 1.96 1.27 0.59 1.10 1.51 0.65 0.77 1.47 4.41 0.87
7-HCH 12 days'1
2.43 4.82 8.12 2.48 3.40 8.63 14.77 3.84 5.20 14.17 53.86 6.58
p,p'-DDE 6.2e
17.35 82.84 96.25 27.41 4.99 14.38 101.82 7.20 5.31 20.76 123.35 7.45
p,p'-DDT 2.2e
0.22 0.97 1.21 0.32 0.43 1.13 8.20 0.58 0.51 1.65 5.79 0.70
DDE + DDT 17.53 83.71 97.27 27.73 5.34 16.03 104.82 7.78 5.85 21.83 126.55 8.13
Dieldrin 1.0f
0.24 0.73 1.78 0.34 1.39 2.81 5.72 1.55 1.22 3.73 16.27 1.58
Mirex 15g
0.09 0.19 0.23 0.10 0.06 0.17 0.51 0.08 0.12 0.41 1.15 0.16
a
(Ritter etal., 2011).
b
(Schettgenetal.,2012).
c
(Buetal.,2015).
d
(WHO, 1991).
e
(Ritteretal.,2009).
r
(NRC, 1982).
8
Estimated based on slow metabolism of mirex.
E. Cechova etaL / Science of the Total Environment 579 (2017) 637-645 643
* «?<P
f # #
18.0
160
M 0
12 0
10.0
the Netherlands
<& & & &
<P <P #
Norway
i Top-down
Fig. 2. Comparison of the daily intakes of the selected organochlorine compounds obtained from the top-down (black) and bottom-up (grey) approach in Slovakia, the Netherlands and
Norway.
nutrition and food of the Czech Republic were approximately four to
five times higher (Ruprich, 2013).
In Norway, the differences between bottom-up and top-down intakes
were the smallest. The bottom-up estimates were obtained from
the Norwegian food database between the years 2000-2006 (Kvalem
et al., 2009), which corresponded to the year of the mother milk samples
collection. For iPCBs the bottom-up intake was 1.2 times higher
than the top-down. The biggest difference between the two approaches
was for PCB101, where the bottom-up exceeded the top-down by a factor
of 4.3. In the cases of PCB 28 and PCB 180, the top-down estimates
were 1.3 and 2 times higher, respectively.
3.6. Uncertainties
In the bottom-up approach, two parameters affected the total estimate.
First, daily consumption data can vary substantially among different
dietary surveys depending on the reporting technique. The data
from the Czech dietary survey were obtained from 24-hour dietary recall,
which was reported to the EFSA comprehensive database. Comparison
with the food consumption obtained from the Slovak Food
Research Institute showed that the differences in meat orfishconsumption
might reach up to 200%. The second parameter affecting the bottom-up
values is the levels in food. Here, several issues have been
observed. When the level in the primary commodity was expressed
on a lipid basis (usually for meat or dairy products), it was not specified
which type of meat or dairy products were used for measurement, thus
the estimates of lipid content may be very uncertain. For example, for
PCBs in pork meat it was not clearly indicated in which part of the
pork the levels were measured. Lipid contents may vary from 15.4% of
fat in pork leg to 33% of fat in streaky pork (SFCDB, 2010). The same
problem also occurred in the case of dairy products, where preferences
of the fattiness of the milk might affect the exposure significantly. Additionally,
the amount of fat as well as pollutant levels in all three countries
in the bottom-up estimates are influenced by the way of food
preparation. Levels of DDTs in fish might be reduced by 16% to 55%
and of PCBs by 26% to 68% depending on the cooking method (Sherer
and Price, 1993; Wilson et al., 1998). In the case of the bottom-up approach
of OCPs in Slovakia, fruit and vegetables were not included in
the calculation because no measured OCP levels in these types of food
were available. These two missing food commodities can contribute
up to 16% of total intake for DDTs (Baars et al., 2004). It is also important
to mention that in the case of the Slovak bottom-up estimates the number
of analyzed samples was small (37 mothers) and the food consumption
of these mothers can differ from the general adult Slovak
population from the EFSA consumption survey which was used for the
bottom-up estimates.
In the top-down approach, several parameters can affect the total
uncertainty. First, the uncertainty of the analytical methods, which
was in our case controlled by the analysis of a reference material with
each batch of milk samples, expressed as a relative standard deviation,
was below 20%. The second parameter is the elimination half-life,
which may vary for PCBs, p,p'-DDTs and HCB up to 30% among various
authors (Bu et al., 2015; Ritter et al., 2011). Based on the propagationof-error
relationships, the overall uncertainty in the top-down approach
was approximately 40%. The third parameter influencing the total topdown
uncertainty is the absorption factor, / a b s . The value of 0.9 was
used in this study (Moser and McLachlan, 2001). However, there is
still lack of data showing the absorption of persistent organic
644 E. Čechová etaL / Science of the Total Environment 579 (2017) 637-645
compounds in the gastro-intestinal tract from food. Xing et al. (2008)
showed that bioaccessibility of PCBs from digestion of more fatty food,
such as freshwater fish might be only 3% and for leaf spinach 25%. Similarly
for OCPs, the average bioaccessibilities for HCHs were shown to
be 3.35% and 8.73% in gastric and intestinal conditions, respectively, and
for £ DDTs were 5.48% and 17.6%, respectively (Wang et al., 2011). This
means that with a lower/abs used in the calculation, the top-down estimates
would be higher and the difference between the two approaches
would be lower.
4. Conclusions
In this study levels of several developmental neurotoxicants with
the highest abundance in European population have been assessed.
Three European countries with different dietary habits were selected
and our results indicated that Slovakia is still the country with the
highest contamination by PCBs and high levels of OCPs. Levels of
MeHg were the highest in Norway, the country with the highest fish
consumption among the studied countries. The levels of PCBs and
OCPs in all three countries have declined by 75% to 98% in the last
10 years, but all of the chemicals are still present in the human body
at levels that might be harmful to vulnerable population subgroups,
like toddlers or children, where the neurotoxic character of the measured
compounds even at low levels could cause negative effects on
the developing brain (Forns et al., 2016; Quaak et al., 2016). The tolerable
daily intakes defined by WHO and EFSA limits or reference doses by
the US EPA were exceeded by 0.5% of Norwegian samples in the case of
MeHg and by 5% of Norwegian and 16% of the Slovak samples in the case
of iPCB. Any mixture effects could not be assessed in the study, but may
be also relevant.
The estimated daily intakes of MeHg and organochlorine compounds
derived from the mother milk levels were additionally compared
to the intakes based on the analysis of food in individual
countries and there was a relatively good consistency in these two approaches
with the maximum difference of 7 times in the case of
MeHg, iPCB, HCB, DDTs and 7-HCH. This suggests that the levels measured
in milk can be explained by the intakes derived from food consumption
and no major source of intakes is missing.
Acknowledgements
We would like to acknowledge Jakub Martinik, Marcela Kadlecova
and Martina Partykova for their skilled laboratory assistance during
sample preparation and Ondrej Audy for GC-MS analysis of the samples.
The research was supported by the Seventh Framework Programme of
the EU, Grant Agreement No. 282957: Developmental Neurotoxicity Assessment
of Mixtures in Children (DENAM1C), by the Czech Ministry of
Education, Youth, and Sports (L01214, LM2015051 and LM2011028),
and Masaryk University (CETOCOEN PLUS project, CZ.02.1.01/0.0/0.0/
15.003/0000469). The PRENATAL cohort was supported by Ministry
of Health no. 2007/07-SZU-03 and Slovak Research and Development
Agency no. APW-0444-11.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.scitotenv.2016.11.046.
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S U P P L E M E N T A R Y M A T E R I A L
Developmental neurotoxicants in human milk: comparison of levels and intakes
in three European countries
Eliška Čechová, Martin Scheringer, Marta Seifertova, Ondřej Mikeš, Kristýna Kroupová, Jan Kuta,
Joan Forns Guzman, Merete Eggesbo, Ilona Quaak, Marijke de Cock, Margot van de Boer, Henrieta
Patayová, Ľubica Palkovičová, Anton Kočan
Contents
Instrumental analysis S2
Table SI: List of the compounds, internal standards (IS), quantification and confirmation
masses of native analytes S2
Quality assurance/quality control S3
Table S2: Detection frequencies, average recoveries of internal standards (IS) and their
standard deviation (SD) and LODs in milk samples S3
Table S3: Data used for the bottom-up estimation S4
Table S4a: Average fat content for individual food commodities and daily consumption (DC, g
day"1
) in the Czech Republic and the Netherlands S4
Table S4b: /PCB levels in food S5
Table S4c: Levels of selected OCPs in Slovak food S5
SI
Instrumental analysis
For the analysis of OCPs and zPCBs helium was used as the carrier gas at a constant flow of 1 ml min"
(2 ml min"1
during 1.5-min splitless injection). The injector equipped with a crosslinked siloxane
deactivated liner (VICI Metronics) to reduce breakdown of some more sensitive analytes was set at
260 °C. The initial column temperature was 120 °C and it was held for 3 min. The oven was heated to
210 °C at 40 °C min"1
and held for 20 min followed by the increase to 286 °C at 2 °C min"1
. The
temperature was then increased to 330 °C at 30 °C min"1
and held for 10 min. The GC-MS transfer line
temperature was 280 °C. The MS resolution mode was set at 10 000 as defined at 10 % valley.
Perfluorotributylamine fragments were used as lock and calibration masses.
Quantification and confirmation molecular ions or fragments of higher abundance were monitored
both for each of OCP/PCB congeners and their isotopically labeled surrogates including 1 3
Ci2 PCB
162 which was used as a recovery standard. GC/MS data were processed using TargetQuan 3.2
software (Thermo Scientific).
Table SI: List of the compounds, internal standards (IS), quantification and confirmation
masses of native analytes (the order or the compounds according to the elution from the GC column)
compound IS QM CM
HCB 13
C 6 HCB 211.8754 213.8725
y-HCH l 3
C 6 y-HCH 180.9379 182.9349
PCB 28 l 3
C 1 2 PCB 28 255.9613 257.9584
PCB 52 l 3
C 1 2 PCB 52 291.9194 289.9224
PCB 101 l 3
C 1 2 PCB 101 255.9427 257.9398
p,p''-DDE '3
Cl2/7,/7'-DDE 246.0003 247.9974
dieldrin l 3
C 1 2 dieldrin 262.8570 264.8540
PCB 118 l 3
C 1 2 P C B 118 253.9457 257.9398
PCB 153 l 3
C 1 2 PCB 153 252.9379 254.9349
p,p'-DDT l 3
C1 2 /7,//-DDT 235.0081 237.0052
PCB 138 l 3
C 1 2 P C B 138 289.9038 291.9008
l 3
C1 2 PCB 162 264.9781 266.9751
PCB 180 l 3
C 1 2 PCB 180 323.8648 325.8618
mirex I 3
C 1 0 mirex 271.8102 273.8072
S2
Quality assurance/quality control
During the analysis of MeHg, procedural blanks and in-house reference material (RM) fortified with
MeHg were analysed with every batch of 20 analysed samples. In blanks, no MeHg was present.
LODs were calculated as a concentration of the analyte corresponding to the S/N ratio of 3. Recoveries
of internal standard ranged between 80-90%.
For the analysis of organochlorine compounds, the laboratory is accredited according to EN ISO/IEC
17025:2005 and successfully participated in the Proficiency Test on Determination of PCBs in Milk
2013 (EURL-PT-DPl 302-MI) with a z-score 0.2 for the I/PCBs. Procedural blanks for analysis of
organic pollutants were processed with every 7-11 milk samples. Trace levels of all /PCBs and HCB,
y-HCH and p,p'-DDE were present in majority of blank samples, but generally they did not exceed 5%
of the sample concentration. All the results above median+3SD were blank corrected, i.e. the median
from the procedural blanks was subtracted. The LODs for compounds present in blanks were
calculated as 3*SD of the levels found in procedural blanks and the result was divided by the median
lipid content of the analysed milk samples to adjust the LOD to the lipid weight. LODs of compounds
which were not present in blanks were calculated as concentrations corresponding to S/N ratios of 3.
Isotope dilution method was used for compound quantification. Average recoveries of isotope labelled
internal standards for all samples ranged between 58-91%. The summary of the recoveries and LODs
for the samples are shown in Table S2. Lipid content after the pressurized solvent extraction was in
agreement with the results from the standardized Rose-Gottlieb method for determination of lipids in
milk. In-house reference material samples consisting of low-contaminated pork lard fortified with
analysed compounds were analysed with every 20 samples.
Table S2: Detection frequencies (DF, %), average recoveries of internal standards (IS) and their
standard deviation (SD) and LODs in milk samples
Compound DF: NL
(n=120)
DF: NO
(n=388)
DF: SK
(n=37)
Recovery of
IS (SD)
LOD
(ng g"1
lw)
PCB 28 100 99 100 91(9) 0.041
PCB 52 100 99 95 91 (12) 0.012
PCB 101 100 96 100 57(10) 0.018
PCB 138 100 100 100 81(7) 0.056
PCB 153 100 100 100 71(9) 0.005
PCB 180 100 100 100 90 (7) 0.004
PCB 118 97 98 100 62(10) 0.040
HCB 100 100 100 62(18) 0.172
y-HCH 97 66 62 58(15) 0.047
p,p'-DDE 100 100 100 67(10) 0.027
p,p'-DDT 100 100 100 91(14) 0.021
dieldrin 99 100 95 53(9) 0.034
mirex 100 100 100 62(10) 0.003
S3
Table S3: Data used for the bottom-up estimation
Slovakia The Netherlands Norway
year Data source year Data source year Data source
Human milk 2011-12 2011- 2000-6
samples 14
Food 2011 Czech Chronic food Dutch Chronic food 2000-3 National survey
consumption consumption database consumption within NFGa
study
data for adults (EFSA, database for adults (Kvalemet al.,
2011a) (EFSA, 2011a) 2009)
Levels in food 1995-2008 Average values for 22 2000-6 Norwegian Food
iPCBs European countries Safety Authority
(EFSA, 2012) (Kvalemet al.,
2009)
DDE+DDT 2011 State Veterinary
Adminstration of the
Czech Republic
HCB 2005-11 GEMSb/WHO
y-HCH 2009-12 Slovak Food Research
Institute
a
Norwegian Fish and Game Study
b
Global Environment Monitoring System
Table S4 a: Average fat content for individual food commodities (RIVM, 2013; SFCDB, 2010)
and daily consumption (DC, g day"1
) in the Czech Republic and the Netherlands (EFSA, 2011b)
CZ (SK) NL
fat, % DC fat, % DC
fish 15.71 13.97
chicken 6 36.71 6 23.06
pork 20 34.71 20 19.96
beef 15 19.78 15 20.37
milk 1.5 90.79 1.5 147.76
cheese 15 31.02 24.3 13.73
margarine 70 3.09 80 16.34
butter 83 16.81 83 2.25
eggs 11 19.51 9.1 6.71
fruit 125.89 102.36
vegetable 124.09 127.79
vegetable oils 99.7 15.18 99.7 2.9
S4
Table S4 b: /PCB levels in food (EFSA, 2012)
Unit PCB 28 PCB 52 PCB 101 PCB 138 PCB 153 PCB 180
fish ngg"1
WW 0.50 2.17 4.49 5.49 6.92 3.8
poultry ngg"1
lw 0.31 0.21 0.25 0.79 0.87 0.44
pork ngg"1
lw 0.30 0.20 0.25 0.92 1.22 0.78
beef ngg"1
lw 0.37 0.32 0.36 1.00 1.75 0.83
milk ngg"1
lw 1.27 0.05 0.78 2.51 3.17 1.42
cheese ngg"1
lw 1.27 0.05 0.78 2.51 3.17 1.42
margarine ngg"1
lw 0.20 0.21 0.39 1.03 0.95 0.42
butter ngg"1
lw 1.27 0.05 0.78 2.51 3.17 1.42
eggs ngg"1
lw 1.6 1.53 1.61 4.08 4.54 3.35
fruit+vegetable ngg"1
WW 0.01 0.01 0.01 0.02 0.02 0.01
oils (vegetable) ngg"1
lw 0.20 0.21 0.39 1.03 0.95 0.42
Table S4 c: Levels of selected OCPs in Slovak food
Unit HCB DDT+DDE y-HCH
fish ng g"1
WW 6.91 6.28 2.5
poultry ng g"' lw 2.10a
0.50a
2.16
pork ng g"' lw 1.10 34.20 1.44
beef ng g"' lw 4.30 7.10 1.99
milk ng g"' lw 4.20 0.49 1.16
cheese ng g"' lw 4.80 12.31 1.16
butter ng g"' lw 3.00 13.00a
1.2
eggs ng g"' lw 3.80 0.75a
6a
a
adjusted to the whole weight (ww)
References
EFSA, 2012. European Food Safety Authority: Update of the monitoring of dioxins and PCBs levels
in food and feed. doi:10.2903/j.efsa.2012.2832.
EFSA, 201 la. Scientific opinion on hexabromocyclododecanes (HBCDDs) in food. EFSA panel on
contaminants in the food chain (CONTAM). EFSA J. 9.
EFSA, 201 lb. European Food Safety Authority: The EFSA Comprehensive European Food
Consumption Database. Published 2.3.2011.
Kvalem, H.E., Knutsen, H.K., Thomsen, C , Haugen, M., Stigum, H., Brantsseter, A.L., Froshaug, M.,
Lohmann, N., Päpke, O., Becher, G., Alexander, J., Meitzer, H.M., 2009. Role of dietary patterns
for dioxin and PCB exposure. Mol. Nutr. Food Res. 53, 1438-1451.
doi: 10.1002/mnfr. 200800462
RIVM, 2013. NEVO-online [WWW Document], version 2013/4.0, accessed 1st Sept. 2016.
SFCDB, 2010. Online food composition database [WWW Document]. Slovak Food Compos. Data
Bank.
S5
Paper III
Legacy and alternative halogenated flame retardants in human milk in Europe:
implications for children's health
Eliška Čechová1
, Šimon Vojta1
, Petr Kukučka1
, Anton Kočan1
, Tomáš Trnovec2
,
Ľubica Palkovičová Murínová2
, Marijke de Cock3
, Margot van de Bor3
, Joakim
Askevold4
, Merete Eggesbo4
, Martin Scheringer1
'5
Research Centre for Toxic Compounds in the Environment, Faculty of Science,
Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
2
Department of Environmental Medicine, Slovak Medical University, Limbová 12,
83303 Bratislava, Slovakia
3
Department of Environment and Health, Vrije Universiteit, De Boelelaan 1085,
1081 HV Amsterdam, The Netherlands
4
Norwegian Institute of Public Health, Lovisenberggata 8, 0403 Oslo, Norway
J
Institute for Chemical and Bioengineering, ETH Zürich, Vladimir-Prelog-Weg 1,
CH-8093 Zürich, Switzerland
Submitted to Environment International, April 2017
117
118
Abstract
In this study, 10 polybrominated diphenyl ethers (PBDEs) and 19 alternative
halogenated flame retardants (AFRs) were determined in >500 human milk samples
across 3 European countries, representing northern, western and eastern Europe. This
study provides very first results on the occurrence of selected A F R s in mother milk
samples and compares them among three European countries. The median sums of the
concentrations of 7 most frequently detected PBDEs were 2.16 ng g"1
lipid weight (lw)
in Norway, 0.88 ng g"1
lw in the Netherlands and 0.45 ng g"1
lw in Slovakia. In
addition, this study provides very first results on the occurrence of selected AFRs in
mother milk samples and compares them among three European countries. The sums
of concentrations of the 12 AFRs which were detected with the highest detection
frequencies in the samples ranged from 0.14 to 0.25 ng g"1
lw in all countries, which
was 2 to 15 times lower compared to L 7 P B D E s . Four AFRs including bromobenzenes
(hexabromobenzene, pentabromobenzene, pentabromotoluene) and Penta-BDE
replacement (2-ethylhexyl-2,3,4,5-tetrabromobenzoate, E H - T B B ) were detected in
more than 42% of all human milk samples. Because of the potential developmental
neurotoxicity of the halogenated flame retardants, infant daily intakes were estimated
as the sum of dietary intake, dust ingestion and air inhalation. Dietary intake via
breastfeeding was shown to be the dominant source for both PBDEs and AFRs, though
for B D E 99 and E H - T B B dust ingestion constituted up to 40% of the overall exposure.
1
Keywords
Alternative flame retardants; developmental neurotoxicants; human milk; infant
exposure; polybrominated diphenyl ethers
2
1. Introduction
Halogenated flame retardants (FRs) are added to manufactured materials, such as
electronics, fabrics, plastics, coatings and polyurethane foams and present about 25%
of the total production of all flame retardants (Fink et al., 2008). Polybrominated
diphenyl ethers (PBDEs) constitute an important group of FRs. They were introduced
in the 1970s, but concerns over adverse health effects (EFSA, 2011) and
environmental persistence led to bans or restrictions of uses of the P B D E commercial
mixtures in the European Union ( E U 2004, 2010) and by the Stockholm Convention
(UNEP, 2009). Despite the restrictions of most PBDEs more than 10 years ago, they
are still reported to be ubiquitous in the environment and humans and a decreasing
trend in the concentrations in humans for selected congeners in some European
countries has not been clearly observed (Darnerud et al., 2015).
After the restrictions of PBDEs, the use of alternative halogenated flame retardants
(AFRs) has increased. However, the environmental behaviour and toxicological
properties of many A F R s are still not fully characterized (EFSA, 2012). Early
evidence suggests that a number of them are persistent in the environment and may
have health effects similar to PBDEs (Dodson et al., 2012). Various animal studies
have shown increased liver, thyroxine concentrations, or structural similarities to
known endocrine disruptors (Patisaul et al., 2013).
One of the most adverse effects of halogenated FRs is developmental neurotoxicity.
The most vulnerable periods of life to F R exposure for humans are prenatal and the
first few years of life because the developing brain is more sensitive to neurotoxicants
than the adult brain (Landrigan et al., 2004). For breastfed infants in the first 6 months
of development, dietary intake of contaminants should be almost exclusively from the
mother (WHO, 2015). Concentrations of FRs in mother milk thus provide important
information for the assessment of the transfer of the F R to the infant's body. However,
despite the toxic potential of the AFRs, there is still scarce information regarding A F R
concentrations in human matrices in the literature to date (Covaci et al., 2011; EFSA,
2012). Limited data on brominated A F R concentrations in human milk or serum are
3
available for two bromobenzene A F R s and Octa-BDE replacement l,2-bis(2,4,6tribromophenoxy)ethane
(BTBPE) in China and Norway (Cequier et al., 2015; Shi et
al., 2016), or Penta-BDE replacements 2-ethylhexyl-2,3,4,5-tetrabromobenzoate ( E H TBB)
and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP) in Canada (Zhou et al.,
2014a).
Apart from diet, another important exposure pathway to FRs for infants and toddlers is
the indoor environment, i.e. dust ingestion and air inhalation, especially due to their
hand-to-mouth behaviour (Moya et al., 2004). The contribution of A F R s when
compared to PBDEs could be also significant since the concentrations of selected
AFRs, such as bromobenzenes, E H - T B B , B E H - T E B P and B T B P E in dust or air were
reported to be similar to PBDEs concentrations in North America, Norway or the
Czech Republic (Cequier et al., 2014; Venier et al., 2016). Other AFRs, such as
tetrabromo-o-chlorotoluene (TBCT) or l,2-dibromo-4-(l,2-dibromoethyl)cyclohexane
( D B E - D B C H ) were also detected in indoor dust in the U K and in Norway
with 100% detection frequency at the median concentrations of 3.4 ng g"1
and 9.4-15
ng g"1
, respectively (Cequier et al., 2014; Tao et al., 2016).
The aim of this study was to determine concentrations of 10 PBDEs and 19 A F R s in
more than 500 human milk samples from 3 European countries, representing northern,
western and central Europe (Norway, the Netherlands and Slovakia). The influence of
mother's age and parity to the concentrations of FRs in all three countries was
assessed. Additionally, infant exposure to FRs considered as potential developmental
neurotoxicants was investigated showing the contributions of the individual exposure
pathways from diet and indoor environment using the data previously published for
indoor dust and air for PBDEs and AFRs.
2. Materials and Methods
2.1 Human milk samples
Human milk samples were obtained from 3 European countries: Norway (n = 360,
samples collected between years 2003-2009), the Netherlands (n = 116, 2011-14) and
4
Slovakia (n = 37, 2011-12). Written informed consent was obtained from the mothers
during their antenatal visits. The samples were collected between the weeks 4-8
postpartum into pre-treated bottles and stored at the -20 °C in the country of collection
before sending aliquots for the analysis by the R E C E T O X Trace Analytical
Laboratories.
Table 1: Demographics of the participating mothers from each group (for continuous
variables median values and 25t h
percentile and 75t h
percentile ranges are presented in
parentheses)
Slovakia the Netherlands Norway p-valueb
(n=37) (n=120) (n=360)
Years of sample collection 2011-2012 2011-2014 2003-2009
Age (years) 30 (27-33) 31 (29-34) 30 (26-33) 0.00
Body mass index (kg m"2
)a
21.9 (20.5-24.0) 23.2 (21.4-24.6) 23.4 (21.4-26.0) 0.08
% of lipids in human milk 4.0 (3.0-5.1) 3.8 Q2-A.7) 3.0 (2.3-3.8) 0.00
Number of children, % 0.30
1 41 43 40
2 47 38 38
3 or more 11 19 22
missing 1
a
before pregnancy
b
differences between three countries evaluated with Kruskal-Wallis testfor continuous variables and chi-square
testfor categorical variables
2.2 Target compounds
The ten P B D E congeners analyzed in the human milk samples, B D E 28, 47, 66, 85,
99, 100, 153, 154, 183 and B D E 209 were chosen as they are representative of the
three primary commertial mixtures, Penta-, Octa- and Deca-BDE and also represent
the congeners most commonly detected in the environment or exhibiting the greatest
known toxicity. A F R s included hexabromobenzene (HBB), pentabromobenzene
(PBBz), pentabromotoluene (PBT), E H - T B B , B E H - T E B P , B T B P E , T B C T , D B E D
B C H , allyl-2,4,6-tribromophenyl ether (TBP-AE), 2-bromoallyl-2,4,6tribromophenyl
ether (TBP-BAE), 1,2,5,6-tetrabromocyclooctane (TBCO),
pentabromobenzyl acrylate (PBBA), pentabromoethylbenzene (PBEB), 2,3dibromopropyl-2,4,6-tribromophenyl
ether (TBP-DBPE), hexachlorocyclopentenyl-
5
dibromocyclooctane (DBHCTD), 2,3,5,6-tetrabromo-p-xylene (TBX), Dechlorane
Plus (DDC-CO), and Dechlorane Plus Mono adduct ( D D C - C O M A ) .
2.3 Sample preparation and instrumental analysis
A detailed description of the method for the determination of PBDEs and A F R s has
been previously published elsewhere (Čechova et al., 2016a). In brief, 10 m L of the
sample were lyophilized and isotope labelled internal standards were added. A l l native
13
and C labelled standards were obtained from Wellington (Wellington laboratories,
Canada). Pressurized liquid extraction (PLE) followed by a two-stage clean-up:
dialysis with semipermeable membrane (2x20 ml of hexane, 48 hours duration with
the exchange of the solvent after 24 hours) followed by sorbent chromatography (basic
alumina and CI8, elution using 9 ml of acetonitrile). Prior to the instrumental analysis,
13
1 ng of the labelled recovery standards ( C12 B D E 77 and B D E 138) was added.
Concentrations were normalized to lipid content, which was determined
gravimetrically after PLE. The lipid content values obtained by P L E were comparable
to the lipid content provided by the reference Rose-Gottlieb method for determination
oflipidsinmilk(IDF, 1996).
The analyses of PBDEs and A F R s were performed using a 7890A (Agilent, U S A ) gas
chromatograph coupled to a double-focusing high resolution mass spectrometer
(HRMS, AutoSpec Premier, Waters, U K ) equipped with a 15-m x 0.25-mm x 0.10-um
Rtx-1614 column (Restek, USA). More details about the instrumental parameters are
provided in the Supplementary material.
2.4 Quality assurance/quality control
A l l measurements were performed in an ISO/IEC 17 025 accredited laboratory.
Verification of the F R method was carried out through participation in interlaboratory
tests on PBDEs in human milk and A F R measurement (Interflab; Melymuk et al.,
2015).
6
Quantification of PBDEs and selected A F R s was performed using the isotope dilution
13
method in the case labelled analyte surrogates were available ( Ci2 B D E 28, 47, 99,
100, 153, 154, 183 and 209, 1 3
C PBBz, P B E B , PBT, H B B , P B B A , B T B P E , syn- and
a«//-DDC-CO). The remaining A F R concentrations were corrected by the average
recoveries obtained from the analysis of an in-house reference material (mother milk
samples fortified with the native standards) which was regularly analysed together
with the other milk samples during sample preparation. Method recoveries for PBDEs
ranged between 91 and 115% (RSD 2-17%), for A F R s between 40 and 121% (RSD
8-21%).
Procedural blanks were analysed with every batch of 7 samples, creating 65 blank
samples in total. From among PBDEs, B D E 28, 47, 99, 100 and 209 were present in
blank samples, but their contributions were <5% of the median concentrations in milk
samples. Trace concentrations of all A F R s were present in blanks samples except of
P B B A , T B C O , T B C T and D B H C T D . Concentrations of all compounds were blank
corrected, i.e. median concentrations of the procedural blank were subtracted from
concentrations in the human milk samples in the case that the concentration was
greater than median+3xstandard deviations. The LODs were calculated as the
3 x standard deviations in blank for the compounds present in the blanks, for the other
compounds the L O D was derived from the 3 times instrumental signal to noise (S/N)
ratio. The concentrations in blanks and L O D s normalized to the 3.5% lipid amount in
mother milk samples are provided in the Supplementary Material (Table SI).
2.5 Estimation of infant's daily intakes
The estimates of an infant's body burden consisted of the dietary intake, intake via
dust ingestion and air inhalation. The intakes were estimated for the compounds with
the highest detection frequencies in milk samples, i.e. for B D E 28, 47, 99, 100, 153,
H B B , PBBz, P B T and E H - T B B .
The dietary intake assumed the mother milk as the exclusive source of food. The
following equation for the calculation of infant's daily intake (IB f, ng day"1
) was used:
7
where fa b s is the absorption factor, which was assumed here as 1 for all the compounds,
c F R is the concentration of the FRs in mother milk (ng g"1
lw), and V M (g) is the
average milk volume daily recommended for the exclusively breastfed 6-month infant
(900 ml; (Dore et al., 2015)). cF is the milk lipid content (%), which was determined
gravimetrically in all samples.
The intakes via dust ingestion (ID ) were obtained as follows:
ID =cd xft xfa b s xDI (2)
where cd is the concentration of the FRs in dust (ng g"1
dust). The mean F R
concentrations in dust published for Norway were used (Cequier et al., 2014). For
Slovakia, F R data from the Czech Republic were used as a proxy (Venier et al., 2016).
Dust and air concentrations in Norway and Czech Republic used for the intake
calculations are given in Table S2 in the Supplementary Material. No F R
concentrations in indoor dust were available for the Netherlands, therefore intakes via
dust ingestion and air inhalation were estimated only for Norway and Slovakia. ft is the
fraction of time spent at home (0.9 for 6-12-month toddler (US EPA, 2011)), fa b s is the
bioaccessible fraction from dust ingestion in the gastrointestinal tract, values of 0.41 to
0.58 were used for B D E 47, 99, 100 and 153 (Abdallah et a l , 2012) and 0.5 for B D E
28, H B B , PBBz, P B T and E H - T B B . DI is the dust ingestion rate (includes only indoor
settled dust, 30 mg day"1
(US EPA, 2011)).
For the calculation of the intakes via air inhalation (IA ), equation (3) was used:
T caxftxIR
1000 v
'
where ca is the concentration of F R in indoor air (pg m" ). The concentrations were
obtained from Cequier et al. (2014) and Venier et al. (2016). IR is the air inhalation
3 1
rate, for a 6-12 month toddler a value of 5.4 m day" has been reported (US E P A ,
2011).
8
2.6 Statistical analysis
Basic and descriptive statistics were calculated using Microsoft Excel and Statistica 12
(StatSoft). For the comparison of the concentrations, Mann Whitney and KruskalWallis
Rank tests were used since the data were not normally distributed. Spearman's
correlation analysis was used to investigate correlations between the analyzed
compounds. The statistical comparisons were performed for chemicals with detection
frequencies greater than 50%. In the case of the concentrations of these chemicals
being <LOD, the value of LOD/V2 was used. Results with a p-value <0.05 were
considered statistically significant.
3. Results and Discussion
3.1 PBDEs
In all three countries, BDEs 47, 99, 100 and 153 were detected in >70% of the milk
samples. B D E 28 was detected in 71 and 97% of milk samples in Norway and the
Netherlands, but in Slovakia the detection frequency of B D E 28 was 11%. Other
analyzed congeners, such as B D E 65, 85, 154, 183 and 209 were detected in 0-49% of
all samples. The distribution of the concentrations of all B D E congeners and their
detection frequencies is provided in the Supplementary material (Table S3). The
median concentrations of 4 most often detected congeners are shown in Fig. 1.
9
2.5
BDE 153
• BDE 100
: BDE 99
• BDE 47
BDE 28
Norway the Netherlands Slovakia
Fig. 1 Median concentrations of PBDE congeners with the highest detection frequency in
human milk in three European countries; BDE 28 in Slovakia is not shown due to the low
detection frequency (11%)
Correlations between B D E 28, 47, 99, 10 and 153 were investigated in all three
countries (Tables S4 a-c). A high correlation coefficient (r>0.7) indicates the same
source of exposure, such as the same application or from dietary exposure (Cequier et
al., 2015). In Norway, B D E 99 correlated with B D E 100, in the Netherlands B D E 47
with B D E 99 and B D E 100 and B D E 99 and B D E 100 and in Slovakia B D E 47 with
B D E 99 and B D E 100 and in Slovakia B D E 100 with B D E 153. In all three countries
high correlations indicated that B D E congeners are all part of the Penta-BDE mixture.
In Norway, the median of L 7 P B D E s (sum of B D E 28, 47, 99, 100, 153, 154, 183) was
2.20 ng g"1
lw. Concentrations of all B D E congeners were approximately 2 to 5 times
higher compared to the Netherlands or Slovakia. One of the reasons could be that the
samples were collected approximately 2 to 9 years earlier. The concentrations
measured in this study are in good agreement to the results from other studies in
Norway (Eggesbo et al., 2011; Thomsen et al., 2010). Compared to other European
countries with the sample collection between 2003-2009, the L 7 P B D E in Norway was
2 times higher than in Germany or the Czech Republic (Kazda et al., 2004; Raab et al.,
2008). On the contrary, the concentrations were approximately 2.5 times lower
compared to British milk samples collected in 2001-2003 (Kalantzi et al., 2004)
10
confirming that the concentrations of PBDEs in Great Britain are the greatest in
Europe (Fang et al., 2015). The most abundant congener in Norwegian milk samples
was B D E 47 (median 1.01 ng g"1
lw) followed by B D E 153 (median 0.48 ng g"1
lw).
The ratio of B D E 47/BDE 153 indicating the distribution of these congeners was
approximately 2.1. This value is decreasing over time as shown in samples collected
earlier in Norway where this ratio was 4.7 in pooled serum samples in 1982 (Thomsen
et al., 2007). In other European countries with similar years of a sample collection, the
ratio varied from 0.8 in Germany (Raab et al., 2008) to 4.6 in the Netherlands (Leijs et
al., 2008) showing different abundance of B D E 47 or B D E 153.
In the Netherlands, the median of L 7 P B D E s was 0.91 ng g"1
lw. Unlike in Norwegian
milk samples, the congener with the greatest median concentration was B D E 153 (0.48
ng g"1
lw) followed by B D E 47 (0.20 ng g"1
lw), which could be explained by the later
sample collection and differences in hydrophobicity and elimination of these two
congeners from the human body, also reflected in the calculated total-body elimination
half-lives (1.4 and 7.4 years for B D E 47 and B D E 153, respectively (Trudel et al.,
2011)). The same congener distribution was also observed by Croes et al. (2012);
Darnerud et al. (2015) and Raab et al. (2008). Concentrations of B D E 47 and 99 in the
Netherlands were similar to the concentrations in human milk samples from Belgium,
but concentrations of B D E 153 was approximately 1.5 times greater than in Belgium
(Croes et al., 2012). Three Dutch areas were compared in terms of P B D E
concentrations in human milk: the agricultural area of Zwolle with a low degree of
urbanization (n=64), the urban site of Purmerend (n=30) and a fishery region of Den
Helder (n=26) (de Cock et al., 2016). The differences in concentrations of B D E 28, 47,
100 and 153 were not statistically significant among the three localities (p<0.05), but
mothers living in the rural area of Zwolle had higher concentrations of B D E 99
(median 0.09 ng g"1
lw) compared to the highly urbanized Purmerend or den Helder.
This is opposite to the study by Kalantzi et al. (2004), who reported higher
concentrations of PBDEs in London compared to the rural area of Lancaster.
In Slovakia, the median of L 7 P B D E s was 0.49 ng g"1
lw. The congener profile was
similar to the Netherlands with the highest abundance of B D E 153 (0.12 ng g"1
lw) and
11
B D E 47 (0.17 ng g"1
lw). Median concentrations of B D E 47 were similar to the
Netherlands, but the median of B D E 153 (0.12 ng g" lw) was four times lower.
3.3 Alternative FRs
The sums of the 12 most frequently detected AFRs (PBBz, H B B , PBT, p-TBX, E H T
B B , B E H - T E B P , B T B P E , syn-DDC-CO, anti-DDC-CO, D B E - D B C H , T B P - D B P E
and A T E ) were 0.14, 0.25 and 0.23 ng g"1
lw in Norway, the Netherlands and
Slovakia, respectively. This is 2-15 times lower compared to the L 7 P B D E s . In all three
countries PBBz, H B B , P B T and E H - T B B were detected in 42-100% of all samples.
The comparison of the median concentrations of these 4 compounds is shown in Fig.
2.
0.25
0.20
0.15
0.10
0.05
0.00
EH-TBB
PBT
PBBz
HBB
1 " INorway the Netherlands Slovakia
Fig. 2 Median concentrations of AFRs with the highest detection frequencies in the human
milk samples in three European countries
Other AFRs were detected with frequencies of 0-67%. The concentrations and related
detection frequencies of AFRs in the three countries are shown in Fig. 3. The detailed
distribution is provided in Table SI in the Supplementary Material.
12
Norway the Netherlands Slovakia
S-DDC-CO
"B P
^A E
_DPTE
, DPMA
PBEB *TBX 1
I i
0.90
0.30
0.70
r 0.50
j, 0,50
:
0.40
0.30
0.20
„ 0 . 1 0
EH-TBE
TBX PBBz PET HBE
Detection frequency %
DBE-DBCH
40 50 £
Detection frequency, %
0.35
0.30
0.25
0.20
i
1
0.15
0.10
0.05
Detection frequency, %
Fig. 3 The dependency of the median concentrations on the detection frequency in each
country. Median values are calculated onlyfrom the samples with the concentrations of AFRs
above LOD. The scale of the y-axis is different in each graph
For further data analysis, correlations between the concentrations of H B B , PBBz, P B T
and E H - T B B and B D E 28, 47, 99, 100 and 153 were investigated in human milk
(Table S4 a-c in the Supplementary Material). No significant correlations were
observed between PBDEs and AFRs. In Slovakia, high correlations were observed
between PBBz, P B T and H B B (0.73<r<0.91).
3.3.1 Bromobenzenes
The group of bromobenzene-related alternative flame retardants includes H B B , PBBz,
PBT, T B X , P B E B and P B B A (Venier et a l , 2016). H B B , P B B z and P B T were the
most frequently detected A F R s in 3 countries despite the fact that H B B is not
produced in Europe (Dodson et al., 2012). The median concentrations ranged from
0.02-0.04 ng g"1
lw for these compounds in Norway, the Netherlands and Slovakia.
Although the p-values of the Kruskal-Wallis test showed significant differences in the
concentrations between the countries (Table S3), no evident trend showing lower
concentrations in the Norwegian samples collected earlier was observed. T B X was
detected in 13% of the Norwegian samples and in 69% of the Dutch samples, but in no
Slovak milk samples. There is no information about the use of the A F R s in individual
countries, but within the E U each country has different rules for fire safety and
13
compound use so our findings might indicate that the use of T B X in Slovakia is low.
But the sample size in Slovakia was limited. P B E B was present at a very low
concentration (0.005 ng g"1
lw) with a detection frequency of <2%. H B B was
previously reported in human serum samples in Norway and the median
concentrations were 0.03 ng g"1
lw with a detection frequency of 48% (Cequier et al.,
2015), which was comparable to our results. From other studies, only one study from
China reported H B B and P B T in mother milk samples collected in 12 provinces in
2011 (Shi et al., 2016) and the concentrations were comparable to our study ranging
from 0.03 to 0.09 ng g"1
lw. In studies from Sweden or Tanzania, concentrations of
H B B , T B X and P B E B in human milk were <LOD (Müller et al., 2016; Sahistrom et
al., 2015).
3.3.2 PBDE replacements
E H - T B B and B E H - T E B P are the two components of Firemaster 550 (FM-550), which
has been used as a replacement of Penta-BDE technical mixture (Covaci et al., 2011).
E H - T B B was detected regularly (46-69%) and the median concentrations ranged
between 0.02-0.13 ng g"1
lw across the three countries. The concentrations were
approximately 6 times higher in the Netherlands compared to Norway or Slovakia.
B E H - T E B P was present in the milk samples with lower detection frequencies ranging
between 15-27% in all three countries, but the median concentrations calculated from
the concentrations >LOD (0.31-0.99 ng g"1
lw in all countries) were the greatest from
of all measured AFRs. We identified only one study from Canada where E H - T B B and
B E H - T E B P concentrations were analysed in human milk (Zhou et al., 2014a). E H T
B B median concentrations were up to 20 times greater concentrations compared to
this study and B E H - T E B P 90% percentiles were approximately 2 times greater than in
this study. In Sweden, E H - T B B and B E H - T E B P concentrations in mother milk were <
L O D (Sahistrom et a l , 2015).
In order to assess the differences to the composition of the commercial mixture, the
ratio of E H - T B B and B E H - T E B P in mother milk samples was calculated:
14
In the commercial mixture FM-550 fEH-TBB ratio is 0.8 (Stapleton et al., 2008). In
Norway, the median of fEH-TBB in milk was 0.05, in the Netherlands 0.20 and in
Slovakia 0.11. The lower value of the ratio in the milk samples indicates lower
concentrations of E H - T B B or higher concentrations of B E H - T E B P compared to F M -
550, which might be caused by different metabolism of the compound in the human
body or additional sources of B E H - T E B P , such as its use as a plasticizer in polyvinyl
chloride and in neoprene (Andersson et al., 2006). Comparing these ratios to fEH-TBB
ratios measured in indoor dust, which could be one of the important sources of AFRs
similarly to other lipophilic flame retardants such as PBDEs (Ali et al., 2011), it was
found that the ratios in dust vary among individual countries, from 0.14 in the Czech
Republic to 0.71 in Canada, while the ratios in indoor air are quite consistent; 0.63-
0.83 in Canada, U S and the Czech Republic (Venier et al., 2016) and correspond
closely to the fEH-TBB in the commercial mixture.
B T B P E is used as a replacement of the Octa-BDE commercial mixture. The median
concentrations ranged between 0.01-0.03 ng g"1
lw and they were detected in
approximately one fourth of all samples. Both the concentrations and the detection
frequencies correspond to the concentrations found in another study from Norway
(0.19 ng g"1
lw, D F 9%) (Cequier et al., 2015) or in Sweden (1-3.4 pg g"1
fresh weight,
which is approximately 0.03-0.1 ng g"1
lw when the average lipid content of 3.5% in
the human milk is used (Sahlstrom et al., 2015)). The concentrations in China were
shown to be approximately 3-8 times higher than in our study (Shi et al., 2016).
3.3.3 Other alternative brominated FRs
From other measured AFRs in all three countries, only D B E - D B C H isomers and TBPD
B P E were present in milk samples with an average detection frequency of 25-32%
(median of the concentrations >LOD ranged between 0.01-0.03 ng g"1
lw) and 0-46%
(<LOD-0.06 ng g"1
lw), respectively. Other compounds, such as T B P - A E , T B P - B A E ,
T B C O , TBCT, D D C - C O M A and D B H C T D were present with low detection
15
frequencies (0-6%). To the best of our knowledge, no other studies have reported the
concentrations of these compounds in human matrices.
3.3.4 Dechlorane plus (DDC-CO)
The medians of detection frequencies of sy«-DDC-CO ranged between 3-9%, for antiD
D C - C O 20-26% in the three countries. In Norway, median concentrations of synD
D C - C O were 0.20 ng g"1
lw and of a«//-DDC-CO 0.04 ng g"1
lw, in the Netherlands
0.16 and 0.05 ng g"1
lw for syn- and a«//-DDC-CO, respectively, and in Slovakia 0.11
and 0.05 ng g"1
lw for syn- and a«//-DDC-CO.
Previous studies from Norway, France, Canada and China reported concentrations of
D D C - C O in human serum or breast milk (Ben et al., 2013; Brasseur et al., 2014;
Cequier et al., 2015; Ren et al., 2009; Siddique et a l , 2012; Yan et al., 2012; Zhou et
al., 2014b). The median concentrations of sy«-DDC-CO in those studies (0.22-0.49 ng
g"1
lw) were comparable to this study, but a«//-DDC-CO was shown to be
approximately 3 to 14 times greater in other studies (medians 0.44-0.89 ng g"1
lw).
Also, detection frequencies in Canada, Norway and France were greater than in this
study, ranging from 40-100% for syn-DDC-CO and from 50-100% for anti-DDC-CO.
Two studies from China investigated D D C - C O concentrations in human serum in ewaste
dismantling areas (Ren et al., 2009; Yan et al., 2012) and one in human serum
and mother milk (Ben et al., 2013). In all three studies the concentrations of syn-DDCCO
exceeded the concentrations in our study or other published results from Canada
by 1 up to 3 orders of magnitude (0.5-80.7 ng g"1
lw and 1.58-180 ng g"1
lw for synand
a«//-DDC-CO, respectively).
Using the dechlorane concentrations, the isomer ratio of D D C - C O (5) was calculated
as an indicator of the mixture composition and potential transformation or metabolism
of individual isomers.
16
In the technical mixture fa n t i varies between 0.65 to 0.75 (Xian et al., 2011), i.e. the
a«//-DDC-CO dominates in the mixture with a total content of 75%. In this study, the
median values of fa n t i were 0.50, 0.42 and 0.43 for Norway, the Netherlands and
Slovakia, respectively, suggesting equal contributions of both or slightly higher
content of the syw-isomer. fa n t i values reported in human serum or milk from China or
Norway were slightly higher than in our study ranging from 0.52 to 0.86 (Cequier et
al., 2013; Y a n et al., 2012). Zhou et al. (2014b) reported that fa n u varied significantly
(0.6-1) for the low values of L D D C - C O (approximately below 1 ng g"1
lw). Thus the
difference between the published values of fa n u could be explained by low mean
concentrations of L D D C - C O in this study which ranged between 0.2-0.39 ng g" lw
for all three countries. Also, these ratios were calculated from the low number of
samples where both isomers were detected above the L O D .
The comparison of the summed concentrations of bromobenzenes, P B D E
replacements and other A F R s including D D C - C O in the three countries is shown in
Fig. 4.
17
1.0 -
0.9 -
0.8 -
0.7 -
0.6 -
0.5 -
0.4 -
0.3 -
0.2 -
0.1 -
0.0 Norway
the Netherlands
n
Slovakia
C3
J? &
/ / if
<7
F/g. 4 Box-Whiskers plots showing the sums of most often detected bromobenzenes (HBB,
PBBz, PBT and TBX), PBDE replacements (EH-TBB, BEH-TEBP and BTBPE) and other
AFRs (ATE, TBP-DBPE, DBE-DBCH and syn- and anti-DDC-CO) in human milk in three
countries. The lower and upper ends of the box shows 25th
and 75th
percentiles and medians
values within the box and Whiskers are 10th
and 90th
percentiles
3.4 Determinants of FR concentrations in human milk
During this study a range of basic details from the mothers was investigated, such as
mothers' age and the number of children. It was shown several times that the higher
number of children lowers mothers' body burden for persistent compounds (Gasull et
al., 2013; Salihovic et al., 2012). On the contrary, some publications reported that
parity does not influence the concentrations of these compounds (LaKind et al., 2009)
which was also confirmed in our previous study with polychlorinated biphenyls and
organochlorine pesticides in mother milk samples (Čechova et al., 2016b). In this
study, no significant associations between the mothers' age and the concentrations
were evident in any country for B D E 28, 47, 99, 100 and 153, H B B , PBBz, P B T and
E H - T B B . Additionally, differences between primipara and multipara mothers were
assessed using Mann-Whitney U test (details in Table S5 in the Supplementary
18
Material), and a statistically significant difference was found only for B D E 153 in
Norway and for P B B z and P B T in Slovakia (p<0.05).
3.5 Implications for children's health
Exposure of infants was estimated at ~6 months of age. At this age dietary intake is
ideally still from the mother milk (WHO, 2015), while the child has independent
mobility and thus the additional exposure pathway of dust ingestion becomes
important. The total intake includes intakes via breastfeeding, dust ingestion and air
inhalation. Individual median contributions to the total infant body burden are shown
in Fig. 5.
Fig.5 Contribution of the individual exposure pathways to the total infant's body burden;
intakes for BDE 28 in Slovakia were not calculated due to the low detection frequency in the
milk samples. The scale ofy-axis for PBDEs and AFRs is different
For PBDEs, the dietary intakes via breastfeeding ranged from 0.5-25.8 ng day"1
for all
three countries. In the case of AFRs, the dietary intakes ranged between 0.28-2.54 ng
day" for the three countries.
Intakes via dust ingestion and air inhalation were calculated only for Norway and
Slovakia because no data about concentrations in dust and air were available from the
Netherlands. The infant P B D E intakes via dust ingestion ranged between 0.07-2.72 ng
day"1
for both countries. While in Norway dust contributed from -0.6% for B D E 28 up
to 30% for B D E 99 to the total infant exposure, in Slovakia the contribution from dust
ingestion was much lower, from 0.2-2.2%. The A F R intakes via dust ingestion ranged
19
between 0.01-0.23 ng day"1
for both countries and the highest contribution was from
E H - T B B , which was up to 21-30% of the overall exposure in both countries.
Intakes via air inhalation ranged from 0.001-0.009 ng day"1
for PBDEs and from 0.02-
0.04 ng day"1
for AFRs. The air inhalation route constituted less than 4% of the total
exposure for PBDEs in both countries. In the case of AFRs, it was 1-7% of the total
intake with the biggest contribution of P B B z in Norway and H B B in Slovakia.
Several uncertainty factors could influence the total infant exposure. In the case of the
dust ingestion, the concentrations in air and dust showed the between-room and intraroom
variability. For the infant exposure estimate it therefore depends, in which room
the child spends most of their time indoors. For instance, rooms with more putative
sources of FRs exerted markedly higher concentrations than the rooms without these
sources (Muenhor and Harrad, 2012). Allen et al. (2008) showed that the
concentrations of Penta-BDEs were 72% higher in the main living area compared to
bedrooms. In this study, indoor air and dust concentrations from Norway were
reported to be collected in residential living rooms (Cequier et al., 2014). In the case of
intra-room variability, Muenhor and Harrad (2012) showed significant differences
with up to 1.8 times higher concentrations in the areas closer to the putative sources of
FRs. The next parameter in the dust ingestion estimates influencing the intake was the
bioaccessible fraction fa b s . Since fa b s was available only for 4 B D E congeners, we used
0.5 for the other compounds, but this may involve great uncertainties. Additionally, the
used dust ingestion rates were shown to vary among different studies, Sahlstrom et al.
(2015) used 60 mg day"1
, while we used the value published by U S EPA, (2011) i.e. 30
mg day"1
.
The important uncertainty factor is also the fact that the year of the sample collection
of the indoor samples from the Norwegian study (Cequier et al., 2014) does not
correspond to the sample collection of the human milk samples (2012 versus 2003-
2009). As the concentrations of selected congeners, such as B D E 47, were shown to
decrease over time, the real contribution of the dust ingestion for the PBDEs could be
greater.
20
4. Conclusions
Concentrations of legacy and alternative current-use halogenated flame retardants
were determined in human milk samples from three European countries. The highest
concentrations of PBDEs were found in Norway, most likely reflecting the earlier
collection of Norwegian samples, compared to the Netherlands and Slovakia. The
concentrations of A F R s were an order of magnitude lower, dominated by the
replacements of the Penta-BDE commercial mixtures, B E H - T E B P , in some cases even
exceeding the concentrations of B D E 47, the most concentrated P B D E congener.
Although at much lower concentrations, the most frequently detected A F R s in mother
milk samples were bromobenzenes, such as H B B , P B B z and P B T which were present
in 42-100% of the samples in each country. Together with F R data available in indoor
dust and air, the obtained concentrations in human milk were used for an estimation of
the contributions from various exposure routes for infants. Breastfeeding was found to
be the dominant source of exposure for all FRs in this study, but in the cases of B D E
99 or E H - T B B , intake via dust ingestion contributed up to 43% to the total intake.
Investigations into A F R concentrations in human bodies are still at the beginning and
the available data are not yet sufficient to assess time trends. Thus, further studies into
A F R concentrations and intakes are needed to characterize i f the concentrations of
replacement F R compounds increase within humans and more information on the
toxicity of these compounds is needed to identify the risks that these compounds may
pose to brain development in early life.
Acknowledgements
We would like to acknowledge Jakub Martinik, Marcela Kadlecova and Martina
Partykova for their laboratory assistance during sample preparation. The research was
supported by the Seventh Framework Programme of E U , Grant Agreement No.
282957: Developmental Neurotoxicity Assessment of Mixtures in Children
(DENAMIC), by the Czech Ministry of Education, Youth, and Sports (L01214,
LM2015051 and LM2011028), and Masaryk University ( C E T O C O E N P L U S project
21
CZ.02.1.01/0.0/0.0/15_003/0000469). The P R E N A T A L cohort was supported by
Ministry of Health no. 2007/07-SZU-03 and Slovak Research and Development
Agency no. APVV-0444-11 and no. DO7RP-0030-12.
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27
Supplementary Material
Legacy and alternative halogenated flame retardants in human milk in
Europe: implications for children's health
Eliška Cechová, Simon Vojta, Petr Kukučka, Anton Kočan, Tomáš Trnovec, Ľubica
Palkovičová Murínová, Marijke de Cock, Margot van de Bor, Joakim Askevold,
Europe: implications for children's health
Eliška Cechová, Simon Vojta, Petr Kukučka, Anton Kočan, Tomáš Trnovec, Ľubica
Palkovičová Murínová, Marijke de Cock, Margot van de Bor, Joakim Askevold,
Merete Eggesbo, Martin Scheringer
Table of content
Instrumental methods S2
Blank samples and limits of detection S2
Table SI Blank contributions and LODs of PBDEs and AFRs S2
Table S2 Concentrations in indoor environment (dust and air) used for the estimations of
infants daily intake S3
Table S3 Detection frequencies (DF, %) and percentile distribution of FR concentrations in
three European countries S4
Table S4a Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs with
>50% detection frequency in human milk samples from Norway S6
Table S4b Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs with
>50% detection frequency in human milk samples from the Netherlands S6
Table S4c Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs with
>50% detection frequency in human milk samples from Slovakia S6
Table S5 p-values from Mann-Whitney U test showing differences between primipara and
multipara mothers in individual countries S7
Table S6 Contributions of individual exposure pathways to the total daily intake S7
References S7
SI
Instrumental methods
The analysis of PBDEs and A F R s was performed with an Agilent 7890A gas
Chromatograph (GC) coupled with a Waters Micromass AutoSpec Premier high
resolution mass spectrometer (HRMS). Electron impact in positive mode (EI+
) was
used as an ionization mode with an energy of 35 eV. The M S resolution was set at
10,000 defined at 10 % valley.
A 15-m Restek Rtx-1614 column was used to analyze PBDEs and AFRs. G C
conditions were optimized as follows: splitless injection of 2 uL at 280 °C (250 °C for
AFRs) and an initial temperature of 80 °C with a 1 min hold, then 20 °C min"1
to
250 °C, followed by 1.5 °C min"1
to 260 °C with a 2 min hold and 25 °C min"1
to
320 °C with a 4.5 min hold. Helium was used as the carrier gas with a flow rate of
1 ml min"1
.
Blank samples and limits of detection
Limits of detection (LODs) were calculated from the 3 x standard deviation of blank
samples. For adjusting LODs to the lipid weight, 0.35 g of the lipids in 10 ml of the
milk sample were used.
Table SI Blank contributions and LODs ofPBDEs andAFRs
Blanks
(ngg1
Iw)
LODs
(ngg1
Iw)
Blanks
(ngg1
Iw)
LODs
(ng g1
Iw)
BDE 28 0.0002 0.0033 HBB 0.0018 0.0016
BDE 47 0.0014 0.0029 PBBz 0.0003 0.0004
BDE 66 0.0002 0.0026 PBT 0.0006 0.0009
BDE 100 0.0001 0.0010 TBX 0.0003 0.0007
BDE 99 0.0004 0.0031 PBEB 0.0001 0.0004
BDE 85 0.0030 PBBA 0.0064
BDE 154 0.0022 syn-DDC-CO 0.0019 0.0089
BDE 153 0.0038 anti-DDC-CO 0.0013 0.0026
BDE 183 0.0024 EH-TBB 0.0002 0.0012
BDE 209 0.0059 0.1367 BEH-TEBP 0.0077 0.0226
DBE-DBCH 0.0007 0.0012
BTBPE 0.0002 0.0008
DPTE 0.0013 0.0034
TBP-AE 0.0018 0.0038
TBP-BAE 0.0004 0.0006
TBCO 0.0021
TBCT 0.0012
DDC-COMA 0.0004 0.0006
DBHCTD 0.0035
S2
Table S2 Concentrations in indoor environment (dust and air) usedfor the estimations
of infants daily intake
Norway" Czech Republic13
Bioaccessibility Indoor dust. Indoor air, Indoor dust, Indoor air,
factorsc
(ngg1
) (Pg m"3
) (ngg1
) (Pg m-3
)
Sample 2012 2012 2013 2013
collection
BDE 28 0.5d
0.688 7.53 0.003 0.003
BDE 47 0.58 126 128 3.8 1.6
BDE 100 0.41 33.1 6.78 0.53 0.11
BDE 99 0.53 171 21 2.5 0.29
BDE 153 0.48 26 0.927 0.77 0.069
PBBz 0.5d
0.177 5.66 0.29 3.4
PBT 0.5d
0.633 7.64 na na
H B B 0.5d
0.671 4.11 1.4 7.6
E H - T B B 0.5d
2.54 na 7.8 5.5
" concentrations in dust and air in residential living rooms from Norwayfrom Cequier et al. (2014)
b
oncentrations in dust and indoor air from the Czech Republic from Venier et al. (2016),
concentrations in Czech Republic and Slovakia considered the same
c
bioaccesibilityfactorsfrom Abdallah et al. (2012)
d
due to the deficiency of the data, bioaccesility factor of 0.5 for BDE 28 andfor selected AFRs was
assumed
S3
Table S3 Detection frequencies (DF, %) and percentile distribution ofFR concentrations (ng g'1
Iw) in three European countries
Norway (n=360) the Netherlands (n=116) Slovakia (n=37)
BDE28
BDE 47
BDE 66
BDE 100
BDE 99
BDE 85
BDE 154
BDE 153
BDE 183
BDE 209
HBB
PBBz
PBT
TBX
PBEB
PBBA
syn-DDC-CO
anti-DDC-CO
DF, % 5fh
%ile
71
99 0.332
21
31
49
34
0
42
83
14
2
2
7
26
median mean
0.079 0.163
1.008 1.945
0.076
100 0.077 0.255 0.403
98 0.075 0.269 0.463
0.098
0.054
99 0.223 0.478 0.664
0.059
0.036
97 0.005 0.016 0.024
0.025 0.029
0.019
0.005
0.004
0.355
0.055
95th
%tile
0.457
6.180
0.242
1.127
1.329
0.319
0.110
1.349
0.175
0.102
0.063
0.065
0.038
DF. % 5th %ile median
0.882
0.180
97
100
41
100
100
22
39
100
54
4
88
75
85
69
0
0
9
20
0.006
0.064
0.017
0.024
0.223 0.483
0.037
95th
%tile
DF. %
0.017 0.025
0.197 0.350
0.008
0.059 0.083
0.083
0.062
1.051
0.020
0.180
0.139 0.231
0.019 0.046
0.025
0.525
0.047
0.039 0.048
0.022 0.026
0.020 0.028
0.016 0.035
0.278
0.155
0.052
0.959
0.110
5.806 20.886
0.099
0.055
0.065
0.128
0.848
0.491
11
100
3
100
70
5
3
100
32
0
62
100
100
0
3
0
3
24
5th
%ile
0.083
0.016
median mean 95th %tile Kruskal-Wallis
0.023
0.016
0.172
0.041
0.069
0.066 0.119
0.023
0.038
0.030
0.063
0.286
0.017
0.070
0.100
0.032
0.022
0.206
0.035
0.041
0.051
0.039
0.002
0.111
0.057
0.086
1.136
0.170
0.287
0.036
0.419
0.066
0.170
0.133
0.089
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0011
0.128
S4
EH-TBB
BEH-TEBP
DBE-DBCH
BTBPE
DPTE
TBP-AE
TBP-BAE
TBCO
TBCT
DDC-COMA
DBHCTD
46
27
25
23
10
6
0
0
0
1
0
0.084
0.613
0.038
0.586
0.086
0.061
0.100
1.508
0.083
0.140
0.224
0.137
0.019
69
15
26
26
0
0
5
0
0
2
0
0.041 0.125 0.240
1.34
0.019
1.103
0.683
2.75
0.035
2.380
0.005 0.008
0.092
59
27
32
22
46
0
3
0
0
0
0
0.022 0.037
0.622
0.017
0.023
0.072
0.005
0.091
1.887
0.042
0.078
0.143
0.0000
S5
Table S4a Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs
with >50% detection frequency in human milk samples from Norway
BDE 47 BDE 100 BDE 99 BDE 153 PBBz
BDE 100 0.26*
BDE 99 0.30* 0.80*
BDE 153 0.14* 0.69* 0.47*
PBBz -0.07 0.03 0.05 0.07
PBT -0.06 0.04 0.04 0.02 0.39*
HBB -0.04 0.02 0.04 0.05 0.51*
EH-TBB 0.01 0.00 0.00 -0.02 -0.01
HBB
0.62*
-0.01 0.07
*correlation was significant at the level 0.05
Table S4b Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs
with >50% detection frequency in human milk samples from the Netherlands
BDE 100
BDE 99
BDE 153
PBBz
PBT
HBB
EH-TBB
correlation was significant at the level 0.05
BDE 47 BDE 100 BDE 99 BDE 153 PBBz PBT HBB
0.91*
0.77* 0.88*
0.22* 0.35* 0.17
0.05 0.10 0.12 0.05
0.02 0.08 0.07 0.20*
0.27* 0.22* 0.13 0.15
-0.05 0.00 0.02 0.07
0.50*
0.51* 0.48*
0.45* 0.52* 0.41*
Table S4c Spearman's correlation coefficients (p<0.05) between PBDEs and AFRs with >50%
detectionfrequency in human milk samplesfrom Slovakia
BDE 47 BDE 100 BDE 99 BDE 153 PBBz PBT HBB
BDE 100 0.88*
BDE 99 0.80* 0.51*
BDE 153 0.69* 0.87* 0.24
PBBz 0.03 0.01 0.11 0.11
PBT -0.02 -0.02 0.05 0.08 0.88*
HBB 0.00 -0.04 0.07 0.08 0.91* 0.73*
EH-TBB 0.10 0.14 0.22 -0.08 0.39* 0.43* 0.21
correlation was significant at the level 0.05
S6
Table S5 p-values from Mann-Whitney U test showing differences between primipara
and multipara mothers in individual countries (red values are statistically significant
withp<0.05)
Norway the Netherlands Slovakia
BDE28 0.09 0.09 0.67
BDE 47 0.68 0.56 0.08
BDE 100 0.46 0.66 0.09
BDE 99 0.22 0.23 0.13
BDE 153 0.02 0.60 0.08
PBBz 0.33 0.23 0.048
PBT 0.72 0.82 0.042
HBB 0.91 0.11 0.45
EH-TBB 0.72 0.81 0.11
Table S6 Contributions of individual exposure pathways to the total daily intake
(ng day1
)
Norway the Netherlands Slovakia
breastfeeding dust indoor air breastfeeding breastfeeding dust indoor
BDE 28 1.72 0.02 0.041 0.53
BDE 47 25.84 2.19 0.69 6.31 6.26 0.07 0.01
BDE 100 6.16 0.41 0.04 2.03 1.43 0.01 0.00
BDE 99 6.31 2.72 0.11 2.55 1.79 0.04 0.00
BDE 153 12.43 0.37 0.01 16.60 5.23 0.01 0.00
PBBz 0.40 0.01 0.03 0.65 1.49 0.01 0.02
PBT 0.58 0.02 0.04 0.73 1.03
HBB 0.40 0.02 0.02 1.34 0.58 0.04 0.04
EH-TBB 0.28 0.08 2.54 0.51 0.23 0.03
References
Abdallah, M.A.-E., Tilston, E., Harrad, S., Collins, C , 2012. In vitro assessment of the
bioaccessibility of brominated flame retardants in indoor dust using a colon extended
model of the human gastrointestinal tract. J. Environ. Monit. 14, 3276-3283.
doi:10.1039/c2em30690e
Cequier, E., Ionas, A.C., Covaci, A., Marce, R . M . , Becher, G., Thomsen, C , 2014.
Occurrence of a Broad Range of Legacy and Emerging Flame Retardants in Indoor
Environments in Norway. Environ. Sci. Technol. 48, 6827-6835.
doi:10.1021/es500516u
Venier, M . , Audy, O., Vojta, S., Bečanová, J., Romanak, K., Melymuk, L., Krátká, M . ,
Kukučka, P., Okeme, J., Saini, A., Diamond, M L . , Klánová, J., 2016. Brominated flame
retardants in the indoor environment — Comparative study of indoor contamination from
S7
three countries. Environ. Int. 94, 150-160. doi:http://dx.doi.org/10.1016/
j.envint.2016.04.029
S8
Curriculum Vitae
Personal details
Birth: May 17th, 1988, Ružomberok, Slovak Republic
Nationality: Czech
Employment
Since 2013 Researcher at RECETOX, Masaryk University, Brno, Czech Republic
Education
Since 2012 PhD student of Environmental Chemistry, RECETOX, Masaryk
University Brno
2013 doctor of natural sciences RNDr
2010-2012 MSc in Analytical chemistry, Masaryk University Brno (with honours)
2007-2010 BSc in Chemistry, Masaryk University Brno (with honours)
1999-2007 Grammar School with the focus on natural sciences in Krnov (with
honours)
Research stays
April-May 2016 Wien University, Department of Analytical Chemistry, Prof.
Christopher Gerner's group (sample preparation for proteomic analysis, LC-HRMS
measurements of tissue samples, HRMS data evaluation)
December 2014 Orebro University, Sweden, Prof. Bert van Bavel's group
(miniaturized analytical methods for blood samples)
May 2013 Vrije University Amsterdam, Prof. Pirn Leonard" s group, Institute for
environmental studies I V M (processing of biological samples, system of
accredited laboratories)
June-September 2012 Helmholtz Zentrum Geesthacht, Institute of Coastal Research,
Germany, Prof. Ralf Ebinghaus' group (development of the LC-MS method for
determination of fullerens in air samples)
155
June 2011 T E V A Pharmaceuticals, Opava, Czech Republic (Qualitative and
Quantitative analyses of pharmaceuticals)
Awards
2017 best PhD presentation at the student conference of Chemistry, Masaryk University
2012 best MSc thesis in the field of environmental sciences, awarded by South
Moravian region (LIPKA)
156