Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease in the central nervous system (CNS) marked by inflammation, demyelination, and axonal loss. Currently available MS medication is limited, thereby calling for a strategy to accelerate new drug discovery. One of the strategies to discover new drugs is to utilize old drugs for new indications, an approach known as drug repurposing. Herein, we first identified 421 MS-associated SNPs from the Genome-Wide Association Study (GWAS) catalog (p-value 0.8. MS risk genes were then prioritized using bioinformatics analysis to identify biological MS risk genes. The prioritization was performed based on six defined categories of functional annotations, namely missense mutation, cis-expression quantitative trait locus (cis-eQTL), molecular pathway analysis, protein-protein interaction (PPI), genes overlap with knockout mouse phenotype, and primary immunodeficiency (PID). A total of 144 biological MS risk genes were found and mapped into 194 genes within an expanded PPI network. According to the DrugBank and the Therapeutic Target. Database, 27 genes within the list targeted by 68 new candidate drugs were identified. Importantly, the power of our approach is confirmed with the identification of a known approved drug (dimethyl fumarate) for MS. Based on additional data from ClinicalTrials.gov, eight drugs targeting eight distinct genes are prioritized with clinical evidence for MS disease treatment. Notably, CD80 and CD86 pathways are promising targets for MS drug repurposing. Using in silico drug repurposing, we identified belatacept as a promising MS drug candidate. Overall, this study emphasized the integration of functional genomic variants and bioinformatic-based approach that reveal important biological insights for MS and drive drug repurposing efforts for the treatment of this devastating disease

Mapping rheumatoid arthritis susceptibility through integrative bioinformatics and genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation.  This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis

Perkembangan Studi Dengue Kaitannya Dengan Interleukin (Il-6) : Bibliometrik Analisis Dari Tahun 1992-2022

Kasus demam berdarah (DB) atau Dengue Fever masih banyak dijumpai di daerah tropis dengan lingkungan yang kurang baik. Penelitian tentang DB telah dilakukan berkaitan dengan mekanisme peradangan dan terbentuknya interleukin-6 akibat respon tubuh terhadap infeksi dengue. Sebanyak 571 artikel berbahasa inggris yang diperoleh dari database scopus tahun 1992 hingga 2022 digunakan dalam analisa bibliometrik tentang dengue yang berkaitan dengan interleukin-6. Analisa bibliometrik digunakan untuk melihat tren penelitian meliputi kata kunci yang banyak digunakan, jurnal penerbit terbanyak, penerbit yang paling banyak dikutip, instansi penulis dan kolaborasi antar penulis digambarkan dalam visualisasi menggunakan aplikasi VOSViewer. Analisa bibliometrik menunjukkan tren penelitian semakin meningkat dari tahun 1992 hingga tahun 2022. Kata kunci yang paling banyak digunakan adalah dengue virus, dengue, cytokines, cytokine, dengue hemorrhagic fever dan inflammation. Jurnal penerbit yang paling banyak menerbitkan artikel adalah Jurnal Frontiers in Immunology dengan 34 artikel dan yang paling banyak dikutip adalah dari Jurnal Immunology sebanyak 1078 kali. Penulis terbanyak berasal dari National Cheng Kung University Taiwan sebanyak 103 penulis, diikuti oleh Mahidol University Thailand sebanyak 71 penulis. Kolaborasi antar penulis Single Country Publication (SCP) maupun Multiple Country Publication (MCP) yang paling banyak adalah Amerika Serikat diikuti negara China kemudian Brazil. Hasil analisa menunjukkan bahwa penelitian mengenai demam dengue yang berkaitan dengan interleukin-6 menunjukkan tren yang semakin meningkat dari tahun ke tahun. Kontribusi penulis didominasi oleh negara-negara maju seperti Amerika dan China. Peran penulis dari negara-negara Asia Tenggara dengan kasus dengue yang tinggi diharapkan dapat semakin berkembang. Studi tentang farmakoterapi yang berpengaruh terhadap sistem imun dan peradangan yang melibatkan Interleukin masih diperlukan untuk perkembangan pengobatan infeksi dengue

Investigation of susceptibility genes for chickenpox disease across multiple continents

Chickenpox (varicella) is caused by infection with the varicella-zoster virus (VZV), a neurotropic alpha herpes virus with a double-stranded DNA genome. Chickenpox can cause life-threatening complications, including subsequent bacterial infections, central nervous system symptoms, and even death without any risk factors. Few studies have been reported to investigate genetic susceptibility implicated in chickenpox. Herein, our study identified global genetic variants that potentially contributed to chickenpox susceptibility by utilizing the established bioinformatic-based approach. We integrated several databases, such as genome-wide association studies (GWAS) catalog, GTEx portal, HaploReg version 4.1, and Ensembl databases analyses to investigate susceptibility genes associated with chickenpox. Notably, increased expression of HLA-S, HCG4P5, and ABHD16A genes underlie enhanced chickenpox susceptibility in the European, American, and African populations. As compared to the Asian population, Europeans, Americans, and Africans have higher allele frequencies of the extant variants rs9266089, rs10947050, and rs79501286 from the susceptibility genes. Our study suggested that these susceptibility genes and associated genetic variants might play a critical role in chickenpox progression based on host genetics with clinical implications

Mapping rheumatoid arthritis susceptibility through integrative bioinformatics and genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation. This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis

Mapping Rheumatoid Arthritis Susceptibility through Integrative Bioinformatics and Genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, and is associated with multiple genetic and environmental factors. Numerous databases provide information on the relationship between a specific gene and the disease pathogenesis. However, it is important to further prioritize biological risk genes for downstream development and validation. This study aims to map RA-association genetic variation using genome-wide association study (GWAS) databases and prioritize influential genes in RA pathogenesis based on functional annotations. These functional annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), and primary immunodeficiency (PID). 119 genetic variants mapped had a potential high risk for RA based on functional scoring. The top eight risk genes of RA are TYK2 and IFNGR2, followed by TNFRSF1A, IL12RB1 and CD40, C5, NCF2, and IL6R. These candidate genes are potential biomarkers for RA that can aid drug discovery and disease diagnosis