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Mendelian imputation of parental genotypes improves estimates of direct genetic effects
Effects estimated by genome-wide association studies (GWASs) include effects of alleles in an individual on that individual (direct genetic effects), indirect genetic effects (for example, effects of alleles in parents on offspring through the environment) and bias from confounding. Within-family ge...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197765/ https://www.ncbi.nlm.nih.gov/pubmed/35681053 http://dx.doi.org/10.1038/s41588-022-01085-0 |
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author | Young, Alexander I. Nehzati, Seyed Moeen Benonisdottir, Stefania Okbay, Aysu Jayashankar, Hariharan Lee, Chanwook Cesarini, David Benjamin, Daniel J. Turley, Patrick Kong, Augustine |
author_facet | Young, Alexander I. Nehzati, Seyed Moeen Benonisdottir, Stefania Okbay, Aysu Jayashankar, Hariharan Lee, Chanwook Cesarini, David Benjamin, Daniel J. Turley, Patrick Kong, Augustine |
author_sort | Young, Alexander I. |
collection | PubMed |
description | Effects estimated by genome-wide association studies (GWASs) include effects of alleles in an individual on that individual (direct genetic effects), indirect genetic effects (for example, effects of alleles in parents on offspring through the environment) and bias from confounding. Within-family genetic variation is random, enabling unbiased estimation of direct genetic effects when parents are genotyped. However, parental genotypes are often missing. We introduce a method that imputes missing parental genotypes and estimates direct genetic effects. Our method, implemented in the software package snipar (single-nucleotide imputation of parents), gives more precise estimates of direct genetic effects than existing approaches. Using 39,614 individuals from the UK Biobank with at least one genotyped sibling/parent, we estimate the correlation between direct genetic effects and effects from standard GWASs for nine phenotypes, including educational attainment (r = 0.739, standard error (s.e.) = 0.086) and cognitive ability (r = 0.490, s.e. = 0.086). Our results demonstrate substantial confounding bias in standard GWASs for some phenotypes. |
format | Online Article Text |
id | pubmed-9197765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-91977652022-06-16 Mendelian imputation of parental genotypes improves estimates of direct genetic effects Young, Alexander I. Nehzati, Seyed Moeen Benonisdottir, Stefania Okbay, Aysu Jayashankar, Hariharan Lee, Chanwook Cesarini, David Benjamin, Daniel J. Turley, Patrick Kong, Augustine Nat Genet Technical Report Effects estimated by genome-wide association studies (GWASs) include effects of alleles in an individual on that individual (direct genetic effects), indirect genetic effects (for example, effects of alleles in parents on offspring through the environment) and bias from confounding. Within-family genetic variation is random, enabling unbiased estimation of direct genetic effects when parents are genotyped. However, parental genotypes are often missing. We introduce a method that imputes missing parental genotypes and estimates direct genetic effects. Our method, implemented in the software package snipar (single-nucleotide imputation of parents), gives more precise estimates of direct genetic effects than existing approaches. Using 39,614 individuals from the UK Biobank with at least one genotyped sibling/parent, we estimate the correlation between direct genetic effects and effects from standard GWASs for nine phenotypes, including educational attainment (r = 0.739, standard error (s.e.) = 0.086) and cognitive ability (r = 0.490, s.e. = 0.086). Our results demonstrate substantial confounding bias in standard GWASs for some phenotypes. Nature Publishing Group US 2022-06-09 2022 /pmc/articles/PMC9197765/ /pubmed/35681053 http://dx.doi.org/10.1038/s41588-022-01085-0 Text en © The Author(s) 2022 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 | Technical Report Young, Alexander I. Nehzati, Seyed Moeen Benonisdottir, Stefania Okbay, Aysu Jayashankar, Hariharan Lee, Chanwook Cesarini, David Benjamin, Daniel J. Turley, Patrick Kong, Augustine Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title | Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title_full | Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title_fullStr | Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title_full_unstemmed | Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title_short | Mendelian imputation of parental genotypes improves estimates of direct genetic effects |
title_sort | mendelian imputation of parental genotypes improves estimates of direct genetic effects |
topic | Technical Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197765/ https://www.ncbi.nlm.nih.gov/pubmed/35681053 http://dx.doi.org/10.1038/s41588-022-01085-0 |
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