Amyotrophic lateral sclerosis (ALS) is a severe disease that causes thousands of deaths annually. Current treatments are either limited in effectiveness or not broadly applicable. To discover new options, we conducted a genetics-based screen to identify drugs that could be repurposed for ALS.
We analyzed genome-wide data from over 150,000 samples (n = 29,612 ALS patients and 122,656 controls) to assess the ability of FDA-approved drugs (n = 1001) to restore disease-related gene expression. Our findings were validated using U.S. Medicare prescription claims data from 114,950 participants across diverse populations.
The screen identified furosemide, a diuretic used for hypertension and heart failure, as a promising candidate for further research. Clinical trial simulations using public data further supported the beneficial effects of furosemide, and ex vivo experiments in mice suggest the drug may protect neurons by reducing hyperexcitability. Our data-driven, multidisciplinary approach has broad potential for repurposing drugs to treat neurodegenerative diseases.
This work was partly supported by the Intramural Research Program of the NIH, National Institute on Aging (ZIAAG000949, ZIAAG000928) and the National Institute of Neurological Disorders and Stroke (ZIANS003154). The contributions of the NIH authors were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the authors and do not necessarily reflect the views of NIH or the U.S.
Department of Health and Human Services. B.J.T. received additional support from Merck Sharp & Dohme Corporation (a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA), the Centers for Disease Control and Prevention, the Muscular Dystrophy Association, Microsoft Research, the Packard Center for ALS Research at Johns Hopkins, and the ALS Association. This study utilized the high-performance computational capabilities of the Biowulf Linux cluster at the NIH.
The authors would like to thank the Project MinE GWAS Consortium. The authors thank the patients and research subjects who contributed samples for this study, as well as the staff of the Laboratory of Neurogenetics for their collegial support. These authors contributed equally: Sara Saez-Atienzar, Luis A.
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