Detailed Information on Publication Record
2019
The Pathosome: A Dynamic Three-Dimensional View of Disease-Environment Interaction
LENÁRT, Peter, Martin SCHERINGER and Julie DOBROVOLNÁBasic information
Original name
The Pathosome: A Dynamic Three-Dimensional View of Disease-Environment Interaction
Authors
LENÁRT, Peter (703 Slovakia, belonging to the institution), Martin SCHERINGER (756 Switzerland, belonging to the institution) and Julie DOBROVOLNÁ (203 Czech Republic, guarantor, belonging to the institution)
Edition
BIOESSAYS, HOBOKEN, WILEY, 2019, 0265-9247
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10602 Biology , Evolutionary biology
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 4.631
RIV identification code
RIV/00216224:14310/19:00110768
Organization unit
Faculty of Science
UT WoS
000474783900008
Keywords in English
disease; environment; health; pathosome; phenotype; preconditioning
Tags
International impact, Reviewed
Změněno: 24/3/2020 14:32, Mgr. Marie Šípková, DiS.
Abstract
V originále
Most contemporary models of disease development consider the interaction between genotype and environment as static. The authors argue that because time is a key factor in genotype-environment interaction, this approach oversimplifies the pathology analysis and may lead to wrong conclusions. In reviewing the field, the authors suggest that the history of genotype-environment interactions plays an important role in the development of diseases and that this history may be analyzed using the phenotype as a proxy. Furthermore, a theoretical and experimental framework is proposed based on the assumption that phenotypes do not change from one to another randomly but are interconnected and follow certain phenotype trajectories. It then follows that analysis of such phenotype trajectories might be useful to predict the future phenotypes including the onset of disease. In addition, an analysis of phenotype trajectories can be subsequently used to choose better control subjects in comparative studies reducing noise and bias in studies investigating disease mechanisms.
Links
EF15_003/0000469, research and development project |
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EF16_013/0001761, research and development project |
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LM2015051, research and development project |
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MUNI/A/1553/2018, interní kód MU |
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