Identification of Genetic Variation Influencing Metformin Response in a Multi-Ancestry Genome-Wide Association Study in the Diabetes Prevention Program (DPP)

Josephine H. Li, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
James A. Perry, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.
Kathleen A. Jablonski, Department of Epidemiology and Biostatistics, George Washington University Biostatistics Center, Washington, District of Columbia.
Shylaja Srinivasan, Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University of California at San Francisco, San Francisco, California.
Ling Chen, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Jennifer N. Todd, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Maegan Harden, Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Josep M. Mercader, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Qing Pan, Department of Epidemiology and Biostatistics, George Washington University Biostatistics Center, Washington, District of Columbia.
Adem Y. Dawed, Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, Scotland, U.K.
Sook Wah Yee, Department of Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, California.
Ewan R. Pearson, Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, Scotland, U.K.
Kathleen M. Giacomini, Department of Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, California.
Ayush Giri, Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee.
Adriana M. Hung, Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Shujie Xiao, Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan.
L Keoki Williams, Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan.
Paul W. Franks, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Lund University, Malmo, Sweden.
Robert L. Hanson, Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona.
Steven E. Kahn, Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington.
William C. Knowler, Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona.
Toni I. Pollin, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland.
Jose C. Florez, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.

Document Type

Journal Article

Publication Date

12-16-2022

Journal

Diabetes

DOI

10.2337/db22-0702

Abstract

Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in pre-diabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in metformin (MET, n=876) and placebo (PBO, n=887) arms. Multiple linear regression assessed association with one-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (p<9×10-9). In MET, rs144322333 near ENOSF1 (minor allele frequency [MAF]AFR=0.07, MAFEUR=0.002) was associated with an increase in % glycated hemoglobin (per minor allele β=0.39 [95% CI 0.28, 0.50], p=2.8×10-12). Rs145591055 near OMSR (MAF=0.10 in American Indians), was associated with weight loss (kg) (per G allele β=-7.55 [95% CI -9.88, -5.22], p=3.2×10-10) in MET. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants (p(G×T)<1.0×10-4). Replication in individuals with diabetes did not yield significant findings. A GWAS for metformin response in pre-diabetes revealed novel ethnic-specific associations that require further investigation but may have implications for tailored therapy.

Department

Epidemiology

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