Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology

Yosuke Tanigawa; Jiehan Li; Johanne M. Justesen; Heiko Horn; Matthew Aguirre; Christopher DeBoever; Chris Chang; Balasubramanian Narasimhan; Kasper Lage; Trevor Hastie; Chong Y Park; Gill Bejerano; Erik Ingelsson; Manuel A Rivas

doi:10.1038/s41467-019-11953-9

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology

Yosuke Tanigawa, Jiehan Li, Johanne M. Justesen, Heiko Horn, Matthew Aguirre, Christopher DeBoever, Chris Chang, Balasubramanian Narasimhan, Kasper Lage, Trevor Hastie, Chong Y Park, Gill Bejerano, Erik Ingelsson, Manuel A Rivas

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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.

Original language	English
Article number	4064
Journal	Nature Communications
Volume	10
Number of pages	14
ISSN	2041-1723
DOIs	https://doi.org/10.1038/s41467-019-11953-9
Publication status	Published - 1 Dec 2019

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Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biologyFinal published version, 2.62 MB

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Tanigawa, Y., Li, J., Justesen, J. M., Horn, H., Aguirre, M., DeBoever, C., Chang, C., Narasimhan, B., Lage, K., Hastie, T., Park, C. Y., Bejerano, G., Ingelsson, E., & Rivas, M. A. (2019). Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology. Nature Communications, 10, Article 4064. https://doi.org/10.1038/s41467-019-11953-9

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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.",

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AU - Tanigawa, Yosuke

AU - Li, Jiehan

AU - Justesen, Johanne M.

AU - Horn, Heiko

AU - Aguirre, Matthew

AU - DeBoever, Christopher

AU - Chang, Chris

AU - Narasimhan, Balasubramanian

AU - Lage, Kasper

AU - Hastie, Trevor

AU - Park, Chong Y

AU - Bejerano, Gill

AU - Ingelsson, Erik

AU - Rivas, Manuel A

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AB - 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.

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JO - Nature Communications

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Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology

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