Integration of genomics database and bioinformatics to identify genome-wide variants for myasthenia gravis across multiple continents

Fitri, Dwiki and Irham, Lalu Muhammad and Sulistyani, Nanik and Ma’ruf, Muhammad Farid and Puspitaningrum, Anisa Nova and Adikusuma, Wirawan and Mazaya, Maulida and Chong, Rockie (2023) Integration of genomics database and bioinformatics to identify genome-wide variants for myasthenia gravis across multiple continents. Brain Behavior and Immunity Integrative, 5. p. 100041. ISSN 2949-8341

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Abstract

Autoimmune disease is an immune response that damages the body’s tissues, thereby disrupting the body’s physiological functions. Myasthenia gravis represents one such condition characterized by muscle weakness due to impaired neuromuscular transmission. While it can affect anyone, it tends to be more prevalent among women aged 20-30 and men over 50. This disease, deemed a genetic disorder, typically emerges in old age when antibodies target receptors in the muscles. In this study, we sought to identify the genes that can affect myasthenia gravis by leveraging several databases, including the GWAS Catalog, HaploReg Version 4.2, GTEX portal, and ensemble. Specifically, our focus was on exploring genomic variants and the expression of the LTA and CTLA4 genes. Our findings reveal that two variants (rs2071591 and rs231770) impact LTA expression in both muscle and brain tissue, while affecting CTLA4 expression in testicular cell tissue. Subsequently, we assessed the allele frequency of these variants across regional populations, namely African, American, East Asian, European, and Southeast Asian. This study demonstrates that the LTA and CTLA4 genes have a higher frequency in African, East Asian, and European populations compared to American and Southeast Asian populations. Consequently, our finding suggests that the latter two populations might have relatively higher susceptibility to the autoimmune disease myasthenia gravis. Therefore, variations in these genes not only offer insights into disease susceptibility, diagnostic and prognostic biomarkers but also open avenues for identifying candidate drug targets through genomic-driven drug repurposing.

Item Type: Article
Uncontrolled Keywords: Myasthenia gravis; Autoimmune; Bioinformatics; Genetic variation
Subjects: Medicine & Biology
Biomedical Technology & Human Factors Engineering
Depositing User: Rizzal Rosiyan
Date Deposited: 27 Aug 2026 04:04
Last Modified: 27 Aug 2026 04:04
URI: https://karya.brin.go.id/id/eprint/59968

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