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Lesmana MHS, Le NQK, Chiu WC, Chung KH, Wang CY, Irham LM, Chung MH. Genomic-Analysis-Oriented Drug Repurposing in the Search for Novel Antidepressants. Biomedicines 2022; 10:biomedicines10081947. [PMID: 36009493 PMCID: PMC9405592 DOI: 10.3390/biomedicines10081947] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 08/07/2022] [Accepted: 08/08/2022] [Indexed: 12/02/2022] Open
Abstract
From inadequate prior antidepressants that targeted monoamine neurotransmitter systems emerged the discovery of alternative drugs for depression. For instance, drugs targeted interleukin 6 receptor (IL6R) in inflammatory system. Genomic analysis-based drug repurposing using single nucleotide polymorphism (SNP) inclined a promising method for several diseases. However, none of the diseases was depression. Thus, we aimed to identify drug repurposing candidates for depression treatment by adopting a genomic-analysis-based approach. The 5885 SNPs obtained from the machine learning approach were annotated using HaploReg v4.1. Five sets of functional annotations were applied to determine the depression risk genes. The STRING database was used to expand the target genes and identify drug candidates from the DrugBank database. We validated the findings using the ClinicalTrial.gov and PubMed databases. Seven genes were observed to be strongly associated with depression (functional annotation score = 4). Interestingly, IL6R was auspicious as a target gene according to the validation outcome. We identified 20 drugs that were undergoing preclinical studies or clinical trials for depression. In addition, we identified sarilumab and satralizumab as drugs that exhibit strong potential for use in the treatment of depression. Our findings indicate that a genomic-analysis-based approach can facilitate the discovery of drugs that can be repurposed for treating depression.
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Affiliation(s)
| | - Nguyen Quoc Khanh Le
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Wei-Che Chiu
- Department of Psychiatry, Cathay General Hospital, Taipei 10630, Taiwan
- School of Medicine, Fu Jen Catholic University, New Taipei City 242062, Taiwan
| | - Kuo-Hsuan Chung
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan
| | - Chih-Yang Wang
- Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta 55164, Indonesia
- Correspondence: (L.M.I.); (M.-H.C.); Tel.: +62-851-322-55-414 (L.M.I.); +886-02-2736-1661 (M.-H.C.)
| | - Min-Huey Chung
- School of Nursing, College of Nursing, Taipei Medical University, Taipei 11031, Taiwan
- Department of Nursing, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan
- Correspondence: (L.M.I.); (M.-H.C.); Tel.: +62-851-322-55-414 (L.M.I.); +886-02-2736-1661 (M.-H.C.)
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