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A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case
Case–control genetic association studies are often used to examine the role of the genetic basis in complex diseases, such as cancer and neurodegenerative diseases. The role of the genetic basis might vary by nongenetic (environmental) measures, what is traditionally defined as gene–environment inte...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6812609/ https://www.ncbi.nlm.nih.gov/pubmed/31681402 http://dx.doi.org/10.3389/fgene.2019.00886 |
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author | Lobach, Iryna Kim, Inyoung Alekseyenko, Alexander Lobach, Siarhei Zhang, Li |
author_facet | Lobach, Iryna Kim, Inyoung Alekseyenko, Alexander Lobach, Siarhei Zhang, Li |
author_sort | Lobach, Iryna |
collection | PubMed |
description | Case–control genetic association studies are often used to examine the role of the genetic basis in complex diseases, such as cancer and neurodegenerative diseases. The role of the genetic basis might vary by nongenetic (environmental) measures, what is traditionally defined as gene–environment interactions (G×E). A commonly overlooked complication is that the set of clinically diagnosed cases might be contaminated by a subset with a nuisance pathologic state that presents with the same symptoms as the pathologic state of interest. The genetic basis of the pathologic state of interest might differ from that of the nuisance pathologic state. Often, frequencies of the pathologically defined states within the clinically diagnosed set of cases vary by the environment. We derive a simple and general approximation to bias in G×E parameter estimates when the presence of the nuisance pathologic state is ignored. We then perform extensive simulation studies to show that ignoring the presence of the nuisance pathologic state can result in substantial bias in G×E estimates and that the approximation we derived is reasonably accurate in finite samples. We demonstrate the applicability of the proposed approximation in a study of Alzheimer’s disease. |
format | Online Article Text |
id | pubmed-6812609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68126092019-11-01 A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case Lobach, Iryna Kim, Inyoung Alekseyenko, Alexander Lobach, Siarhei Zhang, Li Front Genet Genetics Case–control genetic association studies are often used to examine the role of the genetic basis in complex diseases, such as cancer and neurodegenerative diseases. The role of the genetic basis might vary by nongenetic (environmental) measures, what is traditionally defined as gene–environment interactions (G×E). A commonly overlooked complication is that the set of clinically diagnosed cases might be contaminated by a subset with a nuisance pathologic state that presents with the same symptoms as the pathologic state of interest. The genetic basis of the pathologic state of interest might differ from that of the nuisance pathologic state. Often, frequencies of the pathologically defined states within the clinically diagnosed set of cases vary by the environment. We derive a simple and general approximation to bias in G×E parameter estimates when the presence of the nuisance pathologic state is ignored. We then perform extensive simulation studies to show that ignoring the presence of the nuisance pathologic state can result in substantial bias in G×E estimates and that the approximation we derived is reasonably accurate in finite samples. We demonstrate the applicability of the proposed approximation in a study of Alzheimer’s disease. Frontiers Media S.A. 2019-10-09 /pmc/articles/PMC6812609/ /pubmed/31681402 http://dx.doi.org/10.3389/fgene.2019.00886 Text en Copyright © 2019 Lobach, Kim, Alekseyenko, Lobach and Zhang http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Lobach, Iryna Kim, Inyoung Alekseyenko, Alexander Lobach, Siarhei Zhang, Li A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title | A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title_full | A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title_fullStr | A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title_full_unstemmed | A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title_short | A Simple Approximation to Bias in Gene–Environment Interaction Estimates When a Case Might Not Be the Case |
title_sort | simple approximation to bias in gene–environment interaction estimates when a case might not be the case |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6812609/ https://www.ncbi.nlm.nih.gov/pubmed/31681402 http://dx.doi.org/10.3389/fgene.2019.00886 |
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