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

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
Source :
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract It has been postulated that rare coding variants (RVs; MAF 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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.178b4267dff4643bed6e59ce258ffbb
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-024-45407-8