Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation

Jessica C. Lal; Chengsheng Mao; Yadi Zhou; Shamone R. Gore-Panter; Julie H. Rennison; Beth S. Lovano; Laurie Castel; Jiyoung Shin; A. Marc Gillinov; Jonathan D. Smith; John Barnard; David R. Van Wagoner; Yuan Luo; Feixiong Cheng; Mina K. Chung

doi:10.1016/j.xcrm.2022.100749

Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation

Jessica C. Lal, Chengsheng Mao, Yadi Zhou, Shamone R. Gore-Panter, Julie H. Rennison, Beth S. Lovano, Laurie Castel, Jiyoung Shin, A. Marc Gillinov, Jonathan D. Smith, John Barnard, David R. Van Wagoner, Yuan Luo^*, Feixiong Cheng, Mina K. Chung^*

^*Corresponding author for this work

Preventive Medicine

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

Abstract

Effective drugs for atrial fibrillation (AF) are lacking, resulting in significant morbidity and mortality. This study demonstrates that network proximity analysis of differentially expressed genes from atrial tissue to drug targets can help prioritize repurposed drugs for AF. Using enrichment analysis of drug-gene signatures and functional testing in human inducible pluripotent stem cell (iPSC)-derived atrial-like cardiomyocytes, we identify metformin as a top repurposed drug candidate for AF. Using the active compactor, a new design analysis of large-scale longitudinal electronic health record (EHR) data, we determine that metformin use is significantly associated with a reduced risk of AF (odds ratio = 0.48, 95%, confidence interval [CI] 0.36–0.64, p < 0.001) compared with standard treatments for diabetes. This study utilizes network medicine methodologies to identify repurposed drugs for AF treatment and identifies metformin as a candidate drug.

Original language	English (US)
Article number	100749
Journal	Cell Reports Medicine
Volume	3
Issue number	10
DOIs	https://doi.org/10.1016/j.xcrm.2022.100749
State	Published - Oct 18 2022

Funding

This work was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) under awards R00HL138272 and K99HL138272 and the NIH National Institute on Aging under awards R01AG076448 , R01AG066707 , and U01AG073323 (to F.C.); NIH R01-HL111314 (to J.B., M.K.C., and D.R.V.W.); and P01HL158502 (to M.K.C., J.B., F.C., D.R.V.W., and J.S.). This work was also supported by the American Heart Association Atrial Fibrillation Strategically Focused Research Network grants 18SFRN34110067 , 18SFRN34170013 , and 18SFRN34170442 (to M.K.C., D.R.V.W., J.B., and J.S.), the NIH National Center for Research Resources for Case Western Reserve University and Cleveland Clinic Clinical and Translational Science award UL1-RR024989 , Cleveland Clinic Department of Cardiovascular Medicine philanthropy research funds, the Tomsich Atrial Fibrillation Research Fund (to M.K.C.), and Howard Hughes Medical Institute Gilliam Fellowship GT14941 (to J.C.L. and F.C.).

Keywords

EHR
atrial fibrillation
drug repurposing
electronic health record
human inducible pluripotent stem cells
network medicine
pharmacoepidemiology
systems biology

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.xcrm.2022.100749

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Lal, J. C., Mao, C., Zhou, Y., Gore-Panter, S. R., Rennison, J. H., Lovano, B. S., Castel, L., Shin, J., Gillinov, A. M., Smith, J. D., Barnard, J., Van Wagoner, D. R., Luo, Y., Cheng, F., & Chung, M. K. (2022). Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation. Cell Reports Medicine, 3(10), Article 100749. https://doi.org/10.1016/j.xcrm.2022.100749

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title = "Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation",

abstract = "Effective drugs for atrial fibrillation (AF) are lacking, resulting in significant morbidity and mortality. This study demonstrates that network proximity analysis of differentially expressed genes from atrial tissue to drug targets can help prioritize repurposed drugs for AF. Using enrichment analysis of drug-gene signatures and functional testing in human inducible pluripotent stem cell (iPSC)-derived atrial-like cardiomyocytes, we identify metformin as a top repurposed drug candidate for AF. Using the active compactor, a new design analysis of large-scale longitudinal electronic health record (EHR) data, we determine that metformin use is significantly associated with a reduced risk of AF (odds ratio = 0.48, 95%, confidence interval [CI] 0.36–0.64, p < 0.001) compared with standard treatments for diabetes. This study utilizes network medicine methodologies to identify repurposed drugs for AF treatment and identifies metformin as a candidate drug.",

keywords = "EHR, atrial fibrillation, drug repurposing, electronic health record, human inducible pluripotent stem cells, network medicine, pharmacoepidemiology, systems biology",

author = "Lal, {Jessica C.} and Chengsheng Mao and Yadi Zhou and Gore-Panter, {Shamone R.} and Rennison, {Julie H.} and Lovano, {Beth S.} and Laurie Castel and Jiyoung Shin and Gillinov, {A. Marc} and Smith, {Jonathan D.} and John Barnard and {Van Wagoner}, {David R.} and Yuan Luo and Feixiong Cheng and Chung, {Mina K.}",

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year = "2022",

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doi = "10.1016/j.xcrm.2022.100749",

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Lal, JC, Mao, C, Zhou, Y, Gore-Panter, SR, Rennison, JH, Lovano, BS, Castel, L, Shin, J, Gillinov, AM, Smith, JD, Barnard, J, Van Wagoner, DR, Luo, Y, Cheng, F & Chung, MK 2022, 'Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation', Cell Reports Medicine, vol. 3, no. 10, 100749. https://doi.org/10.1016/j.xcrm.2022.100749

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AU - Lal, Jessica C.

AU - Mao, Chengsheng

AU - Zhou, Yadi

AU - Gore-Panter, Shamone R.

AU - Rennison, Julie H.

AU - Lovano, Beth S.

AU - Castel, Laurie

AU - Shin, Jiyoung

AU - Gillinov, A. Marc

AU - Smith, Jonathan D.

AU - Barnard, John

AU - Van Wagoner, David R.

AU - Luo, Yuan

AU - Cheng, Feixiong

AU - Chung, Mina K.

PY - 2022/10/18

Y1 - 2022/10/18

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AB - Effective drugs for atrial fibrillation (AF) are lacking, resulting in significant morbidity and mortality. This study demonstrates that network proximity analysis of differentially expressed genes from atrial tissue to drug targets can help prioritize repurposed drugs for AF. Using enrichment analysis of drug-gene signatures and functional testing in human inducible pluripotent stem cell (iPSC)-derived atrial-like cardiomyocytes, we identify metformin as a top repurposed drug candidate for AF. Using the active compactor, a new design analysis of large-scale longitudinal electronic health record (EHR) data, we determine that metformin use is significantly associated with a reduced risk of AF (odds ratio = 0.48, 95%, confidence interval [CI] 0.36–0.64, p < 0.001) compared with standard treatments for diabetes. This study utilizes network medicine methodologies to identify repurposed drugs for AF treatment and identifies metformin as a candidate drug.

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Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

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