Leveraging Genomic and Bioinformatic Analysis to Enhance Drug Repositioning for Dermatomyositis

Lalu Muhammad Irham; Wirawan Adikusuma; Anita Silas La'ah; Rockie Chong; Abdi Wira Septama; Marissa Angelina

doi:10.3390/bioengineering10080890

Leveraging Genomic and Bioinformatic Analysis to Enhance Drug Repositioning for Dermatomyositis

Bioengineering (Basel). 2023 Jul 27;10(8):890. doi: 10.3390/bioengineering10080890.

Authors

Lalu Muhammad Irham^{1

2}, Wirawan Adikusuma^{3

4}, Anita Silas La'ah⁵, Rockie Chong⁶, Abdi Wira Septama², Marissa Angelina²

Affiliations

¹ Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta 55164, Indonesia.
² Research Centre for Pharmaceutical Ingredients and Traditional Medicine, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia.
³ Department of Pharmacy, University of Muhammadiyah Mataram, Mataram 83127, Indonesia.
⁴ Research Center for Vaccine and Drugs, National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia.
⁵ Taiwan International Graduate Program in Molecular Medicine, National Yang Ming Chiao Tung University and Academia Sinica, Taipei 112304, Taiwan.
⁶ Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.

Abstract

Dermatomyositis (DM) is an autoimmune disease that is classified as a type of idiopathic inflammatory myopathy, which affects human skin and muscles. The most common clinical symptoms of DM are muscle weakness, rash, and scaly skin. There is currently no cure for DM. Genetic factors are known to play a pivotal role in DM progression, but few have utilized this information geared toward drug discovery for the disease. Here, we exploited genomic variation associated with DM and integrated this with genomic and bioinformatic analyses to discover new drug candidates. We first integrated genome-wide association study (GWAS) and phenome-wide association study (PheWAS) catalogs to identify disease-associated genomic variants. Biological risk genes for DM were prioritized using strict functional annotations, further identifying candidate drug targets based on druggable genes from databases. Overall, we analyzed 1239 variants associated with DM and obtained 43 drugs that overlapped with 13 target genes (JAK2, FCGR3B, CD4, CD3D, LCK, CD2, CD3E, FCGR3A, CD3G, IFNAR1, CD247, JAK1, IFNAR2). Six drugs clinically investigated for DM, as well as eight drugs under pre-clinical investigation, are candidate drugs that could be repositioned for DM. Further studies are necessary to validate potential biomarkers for novel DM therapeutics from our findings.

Keywords: dermatomyositis; drug discovery; drug repositioning; genomic variants.

Grants and funding

This study is part of collaboration as a visiting researcher at the National Research and Innovation Agency (BRIN) South Tangerang, Indonesia (NO: B 14853/III.9/KS.00.00/12/2022 and NO:15/II/HK/2023).