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Yin X, Bose D, Kwon A, Hanks SC, Jackson AU, Stringham HM, Welch R, Oravilahti A, Fernandes Silva L, Locke AE, Fuchsberger C, Service SK, Erdos MR, Bonnycastle LL, Kuusisto J, Stitziel NO, Hall IM, Morrison J, Ripatti S, Palotie A, Freimer NB, Collins FS, Mohlke KL, Scott LJ, Fauman EB, Burant C, Boehnke M, Laakso M, Wen X. Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. Am J Hum Genet 2022; 109:1727-1741. [PMID: 36055244 PMCID: PMC9606383 DOI: 10.1016/j.ajhg.2022.08.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/09/2022] [Indexed: 01/25/2023] Open
Abstract
Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.
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Affiliation(s)
- Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Debraj Bose
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Annie Kwon
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Sarah C. Hanks
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Anne U. Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Heather M. Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Anniina Oravilahti
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | | | - Adam E. Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA,Institute for Biomedicine, Eurac Research, Bolzano 39100, Italy
| | - Susan K. Service
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Michael R. Erdos
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lori L. Bonnycastle
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland,Center for Medicine and Clinical Research, Kuopio University Hospital, Kuopio 70210, Finland
| | - Nathan O. Stitziel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108, USA,Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO 63110, USA,Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Ira M. Hall
- Center for Genomic Health, Department of Genetics, Yale University, New Haven, CT 06510, USA
| | - Jean Morrison
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki 00290, Finland,Department of Public Health, University of Helsinki, Helsinki 00014, Finland,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki 00290, Finland,Department of Public Health, University of Helsinki, Helsinki 00014, Finland,Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nelson B. Freimer
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Francis S. Collins
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Laura J. Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Eric B. Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA 02139, USA
| | - Charles Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland.
| | - Xiaoquan Wen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
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