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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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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. |
format | Online Article Text |
id | pubmed-8440517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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