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Hum Mol Genet. 2016 May 15;25(10):2082-2092. Epub 2016 Feb 21.

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

Author information

1
Montreal Heart Institute, Montréal, Québec H1T 1C8, Canada Faculté de Médecine, Université de Montréal, Montréal, Québec H3T 1J4, Canada.
2
Medical and Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA 02114, USA Department of Medicine and.
3
School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201-0413, USA.
4
Division of Epidemiology, Institute for Medicine and Public Health and.
5
University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC 27599, USA.
6
The Charles Bronfman Institute for Personalized Medicine and The Mindich Child Health and Development Institute, the Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
7
Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK.
8
Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK.
9
Medical and Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA Estonian Genome Center, University of Tartu, Tartu, Estonia Division of Endocrinology, Genetics and Basic and Translational Obesity Research, Children's Hospital Boston, Boston, MA 02115, USA.
10
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.
11
The Charles Bronfman Institute for Personalized Medicine and.
12
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA.
13
Clinical Pharmacology, William Harvey Research Institute and NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
14
Division of Endocrinology, Diabetes and Metabolism, Ohio State University, Columbus, OH 43210, USA.
15
Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
16
Montreal Heart Institute, Montréal, Québec H1T 1C8, Canada.
17
Division of Cardiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA 98195-6422, USA.
18
Medical and Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology, Genetics and Basic and Translational Obesity Research, Children's Hospital Boston, Boston, MA 02115, USA.
19
Division of Epidemiology, Institute for Medicine and Public Health and Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
20
Medical and Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK The Big Data Institute, University of Oxford, Oxford, UK.
21
Montreal Heart Institute, Montréal, Québec H1T 1C8, Canada Faculté de Médecine, Université de Montréal, Montréal, Québec H3T 1J4, Canada guillaume.lettre@umontreal.ca.

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.

PMID:
26908616
PMCID:
PMC5062577
DOI:
10.1093/hmg/ddw055
[Indexed for MEDLINE]
Free PMC Article

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