Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.

Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exp...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jean-Baptiste Pingault, Frühling Rijsdijk, Tabea Schoeler, Shing Wan Choi, Saskia Selzam, Eva Krapohl, Paul F O'Reilly, Frank Dudbridge
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Genetics QH426-470
Acceso en línea:	https://doaj.org/article/1702e9f4a66d468cbb5f0b7e9f547c7e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:1702e9f4a66d468cbb5f0b7e9f547c7e
record_format	dspace
spelling	oai:doaj.org-article:1702e9f4a66d468cbb5f0b7e9f547c7e2021-12-02T20:02:42ZGenetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.1553-73901553-740410.1371/journal.pgen.1009590https://doaj.org/article/1702e9f4a66d468cbb5f0b7e9f547c7e2021-06-01T00:00:00Zhttps://doi.org/10.1371/journal.pgen.1009590https://doaj.org/toc/1553-7390https://doaj.org/toc/1553-7404Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes - child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely.Jean-Baptiste PingaultFrühling RijsdijkTabea SchoelerShing Wan ChoiSaskia SelzamEva KrapohlPaul F O'ReillyFrank DudbridgePublic Library of Science (PLoS)articleGeneticsQH426-470ENPLoS Genetics, Vol 17, Iss 6, p e1009590 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Genetics QH426-470
spellingShingle	Genetics QH426-470 Jean-Baptiste Pingault Frühling Rijsdijk Tabea Schoeler Shing Wan Choi Saskia Selzam Eva Krapohl Paul F O'Reilly Frank Dudbridge Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
description	Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes - child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely.
format	article
author	Jean-Baptiste Pingault Frühling Rijsdijk Tabea Schoeler Shing Wan Choi Saskia Selzam Eva Krapohl Paul F O'Reilly Frank Dudbridge
author_facet	Jean-Baptiste Pingault Frühling Rijsdijk Tabea Schoeler Shing Wan Choi Saskia Selzam Eva Krapohl Paul F O'Reilly Frank Dudbridge
author_sort	Jean-Baptiste Pingault
title	Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
title_short	Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
title_full	Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
title_fullStr	Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
title_full_unstemmed	Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.
title_sort	genetic sensitivity analysis: adjusting for genetic confounding in epidemiological associations.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/1702e9f4a66d468cbb5f0b7e9f547c7e
work_keys_str_mv	AT jeanbaptistepingault geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT fruhlingrijsdijk geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT tabeaschoeler geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT shingwanchoi geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT saskiaselzam geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT evakrapohl geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT paulforeilly geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations AT frankdudbridge geneticsensitivityanalysisadjustingforgeneticconfoundinginepidemiologicalassociations
_version_	1718375645622304768

Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations.

Ejemplares similares