Journal article
Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data
Nature genetics, Vol.54(3), pp.263-273
03/2022
DOI: 10.1038/s41588-021-00997-7
PMCID: PMC9119698
PMID: 35256806
Abstract
Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
Details
- Title: Subtitle
- Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data
- Creators
- Pierrick Wainschtein - The University of QueenslandDeepti Jain - University of WashingtonZhili Zheng - The University of QueenslandL Adrienne Cupples - Boston UniversityAladdin H Shadyab - University of California San DiegoBarbara McKnight - University of WashingtonBenjamin M Shoemaker - Vanderbilt University Medical CenterBraxton D Mitchell - University of Maryland, BaltimoreBruce M Psaty - University of WashingtonCharles Kooperberg - Fred Hutch Cancer CenterChing-Ti Liu - Boston UniversityChristine M Albert - Brigham and Women's HospitalDan Roden - Vanderbilt University Medical CenterDaniel I Chasman - Brigham and Women's HospitalDawood Darbar - University of Illinois ChicagoDonald M Lloyd-Jones - Northwestern UniversityDonna K Arnett - University of KentuckyElizabeth A Regan - National Jewish HealthEric Boerwinkle - The University of Texas at AustinJerome I Rotter - Harbor–UCLA Medical CenterJeffrey R O'Connell - Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USALisa R Yanek - Johns Hopkins MedicineMariza de Andrade - Mayo ClinicMatthew A Allison - University of California San DiegoMerry-Lynn N McDonald - University of Alabama at BirminghamMina K Chung - Cleveland ClinicMyriam Fornage - Brown FoundationNathalie Chami - Icahn School of Medicine at Mount SinaiNicholas L Smith - University of WashingtonPatrick T Ellinor - Harvard UniversityRamachandran S Vasan - Boston UniversityRasika A Mathias - Johns Hopkins MedicineRuth J F Loos - Icahn School of Medicine at Mount SinaiStephen S Rich - University of VirginiaSteven A Lubitz - Broad InstituteSusan R Heckbert - Kaiser Permanente Washington Health Research InstituteSusan Redline - Harvard UniversityXiuqing Guo - Harbor–UCLA Medical CenterY -D Ida Chen - Harbor–UCLA Medical CenterCecelia A Laurie - University of WashingtonRyan D Hernandez - University of California, San FranciscoStephen T McGarvey - Brown UniversityMichael E Goddard - The University of MelbourneCathy C Laurie - University of WashingtonKari E North - University of North CarolinaLeslie A Lange - University of Colorado SystemBruce S Weir - University of WashingtonLoic Yengo - The University of QueenslandJian Yang - The University of QueenslandPeter M Visscher - The University of QueenslandNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
- Contributors
- Karin Hoth (Contributor) - University of Iowa, Psychiatry
- Resource Type
- Journal article
- Publication Details
- Nature genetics, Vol.54(3), pp.263-273
- DOI
- 10.1038/s41588-021-00997-7
- PMID
- 35256806
- PMCID
- PMC9119698
- NLM abbreviation
- Nat Genet
- ISSN
- 1061-4036
- eISSN
- 1546-1718
- Grant note
- N01HC85080 / NHLBI NIH HHS HHSN268201200036C / NHLBI NIH HHS R01 AG023629 / NIA NIH HHS HHSN268200800007C / NHLBI NIH HHS U01 HL130114 / NHLBI NIH HHS U01 HL080295 / NHLBI NIH HHS R01 HL059367 / NHLBI NIH HHS HHSN268201800001C / NHLBI NIH HHS N01HC85081 / NHLBI NIH HHS N01HC85079 / NHLBI NIH HHS
- Language
- English
- Date published
- 03/2022
- Academic Unit
- Psychiatry; Iowa Neuroscience Institute
- Record Identifier
- 9984293654602771
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