Abstract

Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we apply truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identify key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

Details

Title
Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology
Author
Tanigawa, Yosuke 1   VIAFID ORCID Logo  ; Li, Jiehan 2 ; Justesen, Johanne M 3 ; Horn, Heiko 4   VIAFID ORCID Logo  ; Aguirre, Matthew 5   VIAFID ORCID Logo  ; DeBoever, Christopher 6 ; Chang, Chris 7 ; Balasubramanian Narasimhan 8 ; Kasper Lage 9 ; Hastie, Trevor 8 ; Park, Chong Y 10 ; Bejerano, Gill 11   VIAFID ORCID Logo  ; Ingelsson, Erik 2   VIAFID ORCID Logo  ; Rivas, Manuel A 1   VIAFID ORCID Logo 

1  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA 
2  Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA 
3  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark 
4  Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA 
5  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, CA, USA 
6  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA 
7  Grail, Inc., Menlo Park, CA, USA 
8  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA; Department of Statistics, Stanford University, Stanford, CA, USA 
9  Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Institute for Biological Psychiatry, Mental Health Center Sct. Hans, University of Copenhagen, Roskilde, Denmark 
10  Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA 
11  Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Department of Developmental Biology, Stanford University, Stanford, CA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA 
Pages
1-14
Publication year
2019
Publication date
Sep 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-019-11953-9
ProQuest document ID
2285699778
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.