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Testing the role of predicted gene knockouts in human anthropometric trait variation.

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Lessard, Samuel 
Manning, Alisa K 
Low-Kam, Cécile 
Auer, Paul L 
Giri, Ayush 

Abstract

Although the role of complete gene inactivation by two loss-of-function mutations inherited in trans is well-established in recessive Mendelian diseases, we have not yet explored how such gene knockouts (KOs) could influence complex human phenotypes. Here, we developed a statistical framework to test the association between gene KOs and quantitative human traits. Our method is flexible, publicly available, and compatible with common genotype format files (e.g. PLINK and vcf). We characterized gene KOs in 4498 participants from the NHLBI Exome Sequence Project (ESP) sequenced at high coverage (>100×), 1976 French Canadians from the Montreal Heart Institute Biobank sequenced at low coverage (5.7×), and >100 000 participants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an exome array. We tested associations between gene KOs and three anthropometric traits: body mass index (BMI), height and BMI-adjusted waist-to-hip ratio (WHR). Despite our large sample size and multiple datasets available, we could not detect robust associations between specific gene KOs and quantitative anthropometric traits. Our results highlight several limitations and challenges for future gene KO studies in humans, in particular when there is no prior knowledge on the phenotypes that might be affected by the tested gene KOs. They also suggest that gene KOs identified with current DNA sequencing methodologies probably do not strongly influence normal variation in BMI, height, and WHR in the general human population.

Description

Keywords

Anthropometry, Body Height, Body Mass Index, Canada, Exome, Female, Gene Knockout Techniques, Genotype, Humans, Male, Mutation, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Waist-Hip Ratio

Journal Title

Hum Mol Genet

Conference Name

Journal ISSN

0964-6906
1460-2083

Volume Title

25

Publisher

Oxford University Press (OUP)
Sponsorship
MRC (MC_PC_13046)
MRC (5PV0E)
MRC (MC_PC_13048)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0512-10135)
Medical Research Council (MC_UU_12015/1)
Medical Research Council (MC_U106179471)
Medical Research Council (MC_PC_13048)
Medical Research Council (MC_PC_13046)
PBM and MC acknowledge this work forms part of the research program of the NIHR Barts Cardiovascular Biomedical Research Unit. MC is a senior National Institute for Health Research Investigator. Sequencing of the MHI Biobank samples was performed at the McGill University and Génome Québec Innovation Centre. The authors wish to acknowledge the support of the National Heart, Lung, and Blood Institute (NHLBI) and the contributions of the research institutions, study investigators, field staff and study participants in creating this resource for biomedical research. SL is funded by a Canadian Institutes of Health research Banting doctoral scholarship. GL is funded by Genome Canada and Génome Québec; the Canada Research Chair program; and the Montreal Heart Institute Foundation. CML is supported by Wellcome Trust [grant numbers 086596/Z/08/Z, 086596/Z/08/A]; and the Li Ka Shing Foundation. NS is funded by National Institutes of Health [grant numbers HL088456, HL111089, HL116747]. The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI [RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP]. The ESP exome sequencing was performed through NHLBI [RC2 HL-102925 to BroadGO, RC2 HL-102926 to SeattleGO]. EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education [grant number 20 SF0180142s08]; the Development Fund of the University of Tartu [grant number SP1GVARENG]; the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 [grant number 313010]. EGCUT were further supported by the US National Institute of Health [grant number R01DK075787].