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Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data

Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indir...

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Autores principales: Warrington, Nicole M., Hwang, Liang-Dar, Nivard, Michel G., Evans, David M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440517/
https://www.ncbi.nlm.nih.gov/pubmed/34521848
http://dx.doi.org/10.1038/s41467-021-25723-z
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author Warrington, Nicole M.
Hwang, Liang-Dar
Nivard, Michel G.
Evans, David M.
author_facet Warrington, Nicole M.
Hwang, Liang-Dar
Nivard, Michel G.
Evans, David M.
author_sort Warrington, Nicole M.
collection PubMed
description Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indirect genetic effects. Using data from the UK Biobank, we contrast point estimates and standard errors at individual loci compared to those obtained using individual level data. We show that Genomic structural equation modelling (SEM) outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We apply Genomic SEM to fertility data in the UK Biobank and partition the genetic effect into female and male fertility and a sibling specific effect. We identify a novel locus for fertility and genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We recommend Genomic SEM be used to partition genetic effects into direct and indirect components when using summary results from genome-wide association studies.
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spelling pubmed-84405172021-10-04 Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data Warrington, Nicole M. Hwang, Liang-Dar Nivard, Michel G. Evans, David M. Nat Commun Article Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indirect genetic effects. Using data from the UK Biobank, we contrast point estimates and standard errors at individual loci compared to those obtained using individual level data. We show that Genomic structural equation modelling (SEM) outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We apply Genomic SEM to fertility data in the UK Biobank and partition the genetic effect into female and male fertility and a sibling specific effect. We identify a novel locus for fertility and genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We recommend Genomic SEM be used to partition genetic effects into direct and indirect components when using summary results from genome-wide association studies. Nature Publishing Group UK 2021-09-14 /pmc/articles/PMC8440517/ /pubmed/34521848 http://dx.doi.org/10.1038/s41467-021-25723-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Warrington, Nicole M.
Hwang, Liang-Dar
Nivard, Michel G.
Evans, David M.
Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title_full Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title_fullStr Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title_full_unstemmed Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title_short Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
title_sort estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440517/
https://www.ncbi.nlm.nih.gov/pubmed/34521848
http://dx.doi.org/10.1038/s41467-021-25723-z
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