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A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records
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 geneticall...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328805/ https://www.ncbi.nlm.nih.gov/pubmed/37399599 http://dx.doi.org/10.1016/j.ebiom.2023.104674 |
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author | Shuey, Megan M. Lee, Kyung Min Keaton, Jacob Khankari, Nikhil K. Breeyear, Joseph H. Walker, Venexia M. Miller, Donald R. Heberer, Kent R. Reaven, Peter D. Clarke, Shoa L. Lee, Jennifer Lynch, Julie A. Vujkovic, Marijana Edwards, Todd L. |
author_facet | Shuey, Megan M. Lee, Kyung Min Keaton, Jacob Khankari, Nikhil K. Breeyear, Joseph H. Walker, Venexia M. Miller, Donald R. Heberer, Kent R. Reaven, Peter D. Clarke, Shoa L. Lee, Jennifer Lynch, Julie A. Vujkovic, Marijana Edwards, Todd L. |
author_sort | Shuey, Megan M. |
collection | PubMed |
description | 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: 10.13039/100000002National Institutes of Health, 10.13039/501100000265Medical Research Council Integrative Epidemiology Unit at the 10.13039/501100000883University of Bristol, 10.13039/501100000265UK Medical Research Council, 10.13039/100000968American Heart Association, and 10.13039/100000738Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program. |
format | Online Article Text |
id | pubmed-10328805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103288052023-07-09 A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records Shuey, Megan M. Lee, Kyung Min Keaton, Jacob Khankari, Nikhil K. Breeyear, Joseph H. Walker, Venexia M. Miller, Donald R. Heberer, Kent R. Reaven, Peter D. Clarke, Shoa L. Lee, Jennifer Lynch, Julie A. Vujkovic, Marijana Edwards, Todd L. eBioMedicine Articles 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: 10.13039/100000002National Institutes of Health, 10.13039/501100000265Medical Research Council Integrative Epidemiology Unit at the 10.13039/501100000883University of Bristol, 10.13039/501100000265UK Medical Research Council, 10.13039/100000968American Heart Association, and 10.13039/100000738Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program. Elsevier 2023-07-01 /pmc/articles/PMC10328805/ /pubmed/37399599 http://dx.doi.org/10.1016/j.ebiom.2023.104674 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Shuey, Megan M. Lee, Kyung Min Keaton, Jacob Khankari, Nikhil K. Breeyear, Joseph H. Walker, Venexia M. Miller, Donald R. Heberer, Kent R. Reaven, Peter D. Clarke, Shoa L. Lee, Jennifer Lynch, Julie A. Vujkovic, Marijana Edwards, Todd L. A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title | A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title_full | A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title_fullStr | A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title_full_unstemmed | A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title_short | A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
title_sort | genetically supported drug repurposing pipeline for diabetes treatment using electronic health records |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328805/ https://www.ncbi.nlm.nih.gov/pubmed/37399599 http://dx.doi.org/10.1016/j.ebiom.2023.104674 |
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