A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

Megan M Shuey; Kyung Min Lee; Jacob Keaton; Nikhil K Khankari; Joseph H Breeyear; Venexia M Walker; Donald R Miller; Kent R Heberer; Peter D Reaven; Shoa L Clarke; Jennifer Lee; Julie A Lynch; Marijana Vujkovic; Todd L Edwards

doi:10.1016/j.ebiom.2023.104674

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

EBioMedicine. 2023 Aug:94:104674. doi: 10.1016/j.ebiom.2023.104674. Epub 2023 Jul 1.

Authors

Affiliations

¹ Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
² VA Informatics and Computer Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA.
³ Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
⁴ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Nashville VA Medical Center, Nashville, TN, USA.
⁵ Medical Research Council, Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Bristol Medical School, UK; Population Health Sciences, University of Bristol, Bristol, UK; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
⁶ Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA; Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA.
⁷ VA Palo Alto Health Care System, Palo Alto, CA, USA; Departments of Medicine and Endocrinology, Stanford University School of Medicine, Stanford, CA, USA.
⁸ Phoenix VA Health Care System, Phoenix, AZ, USA; College of Medicine, University of Arizona, Phoenix, AZ, USA.
⁹ Departments of Medicine and Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ VA Palo Alto Health Care System, Palo Alto, CA, USA.
¹¹ VA Informatics and Computer Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; School of Medicine, University of Utah, Salt Lake City, UT, USA.
¹² Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. Electronic address: vujkovic@pennmedicine.upenn.edu.
¹³ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Nashville VA Medical Center, Nashville, TN, USA. Electronic address: todd.l.edwards@vumc.org.

Abstract

Background: The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery.

Methods: We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

Findings: After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25).

Interpretation: Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

Funding: National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Keywords: Diabetes; Drug-repurposing; Glucose; Hemoglobin A1c; Mendelian randomization; Transcriptome-wide association study.

MeSH terms

Antihypertensive Agents / therapeutic use
Calcium Channel Blockers
Diabetes Mellitus, Type 2* / drug therapy
Diabetes Mellitus, Type 2* / genetics
Drug Repositioning
Electronic Health Records
Genome-Wide Association Study
Humans
Mendelian Randomization Analysis

Substances

Antihypertensive Agents
Calcium Channel Blockers

Abstract

MeSH terms

Substances

Grants and funding