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

Nazia Pathan; Wei Q. Deng; Matteo Di Scipio; Mohammad Khan; Shihong Mao; Robert W. Morton; Ricky Lali; Marie Pigeyre; Michael R. Chong; Guillaume Paré

doi:10.1038/s41467-024-45407-8

Nature Communications (Feb 2024)

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

Nazia Pathan,
Wei Q. Deng,
Matteo Di Scipio,
Mohammad Khan,
Shihong Mao,
Robert W. Morton,
Ricky Lali,
Marie Pigeyre,
Michael R. Chong,
Guillaume Paré

Affiliations

Nazia Pathan: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Wei Q. Deng: Peter Boris Centre for Addictions Research, St. Joseph’s Healthcare Hamilton
Matteo Di Scipio: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Mohammad Khan: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Shihong Mao: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Robert W. Morton: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Ricky Lali: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Marie Pigeyre: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Michael R. Chong: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University
Guillaume Paré: Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences and McMaster University

DOI: https://doi.org/10.1038/s41467-024-45407-8
Journal volume & issue: Vol. 15, no. 1
pp. 1 – 16

Abstract

Read online

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.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal