A method to estimate the contribution of rare coding variants to complex trait heritability

Abstract It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the “missing” heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability (h 2 RV) without assuming a particular genetic architecture...

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Main Authors: Nazia Pathan, Wei Q. Deng, Matteo Di Scipio, Mohammad Khan, Shihong Mao, Robert W. Morton, Ricky Lali, Marie Pigeyre, Michael R. Chong, Guillaume Paré
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-45407-8
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author Nazia Pathan
Wei Q. Deng
Matteo Di Scipio
Mohammad Khan
Shihong Mao
Robert W. Morton
Ricky Lali
Marie Pigeyre
Michael R. Chong
Guillaume Paré
author_facet Nazia Pathan
Wei Q. Deng
Matteo Di Scipio
Mohammad Khan
Shihong Mao
Robert W. Morton
Ricky Lali
Marie Pigeyre
Michael R. Chong
Guillaume Paré
author_sort Nazia Pathan
collection DOAJ
description Abstract It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the “missing” heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability (h 2 RV) without assuming a particular genetic architecture. We applied RARity to 31 complex traits in the UK Biobank (n = 167,348) and showed that gene-level RV aggregation suffers from 79% (95% CI: 68-93%) loss of h 2 RV. Using unaggregated variants, 27 traits had h 2 RV > 5%, with height having the highest h 2 RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h 2 RV, enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.
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spelling doaj.art-c178b4267dff4643bed6e59ce258ffbb2024-03-05T19:37:07ZengNature PortfolioNature Communications2041-17232024-02-0115111610.1038/s41467-024-45407-8A method to estimate the contribution of rare coding variants to complex trait heritabilityNazia Pathan0Wei Q. Deng1Matteo Di Scipio2Mohammad Khan3Shihong Mao4Robert W. Morton5Ricky Lali6Marie Pigeyre7Michael R. Chong8Guillaume Paré9Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPeter Boris Centre for Addictions Research, St. Joseph’s Healthcare HamiltonPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityPopulation Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster UniversityAbstract It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the “missing” heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability (h 2 RV) without assuming a particular genetic architecture. We applied RARity to 31 complex traits in the UK Biobank (n = 167,348) and showed that gene-level RV aggregation suffers from 79% (95% CI: 68-93%) loss of h 2 RV. Using unaggregated variants, 27 traits had h 2 RV > 5%, with height having the highest h 2 RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h 2 RV, enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.https://doi.org/10.1038/s41467-024-45407-8
spellingShingle Nazia Pathan
Wei Q. Deng
Matteo Di Scipio
Mohammad Khan
Shihong Mao
Robert W. Morton
Ricky Lali
Marie Pigeyre
Michael R. Chong
Guillaume Paré
A method to estimate the contribution of rare coding variants to complex trait heritability
Nature Communications
title A method to estimate the contribution of rare coding variants to complex trait heritability
title_full A method to estimate the contribution of rare coding variants to complex trait heritability
title_fullStr A method to estimate the contribution of rare coding variants to complex trait heritability
title_full_unstemmed A method to estimate the contribution of rare coding variants to complex trait heritability
title_short A method to estimate the contribution of rare coding variants to complex trait heritability
title_sort method to estimate the contribution of rare coding variants to complex trait heritability
url https://doi.org/10.1038/s41467-024-45407-8
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