Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach
A major challenge in translating genomic variants of Tuberculosis (TB) into clinical implementation is to integrate the disease-associated variants and facilitate drug discovery through the concept of genomic-driven drug repurposing. Here, we utilized two established genomic databases, namely a Geno...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Biochemistry and Biophysics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405580822001340 |
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| author | Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari |
| author_facet | Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari |
| author_sort | Lalu Muhammad Irham |
| collection | DOAJ |
| description | A major challenge in translating genomic variants of Tuberculosis (TB) into clinical implementation is to integrate the disease-associated variants and facilitate drug discovery through the concept of genomic-driven drug repurposing. Here, we utilized two established genomic databases, namely a Genome-Wide Association Study (GWAS) and a Phenome-Wide Association Study (PheWAS) to identify the genomic variants associated with TB disease and further utilize them for drug-targeted genes. We evaluated 3.425 genomic variants associated with TB disease which overlapped with 200 TB-associated genes. To prioritize the biological TB risk genes, we devised an in-silico pipeline and leveraged an established bioinformatics method based on six functional annotations (missense mutation, cis-eQTL, biological process, cellular component, molecular function, and KEGG molecular pathway analysis). Interestingly, based on the six functional annotations that we applied, we discovered that 14 biological TB risk genes are strongly linked to the deregulation of the biological TB risk genes. Hence, we demonstrated that 12 drug target genes overlapped with 40 drugs for other indications and further suggested that the drugs may be repurposed for the treatment of TB. We highlighted that CD44, CCR5, CXCR4, and C3 are highly promising proposed TB targets since they are connected to SELP and HLA-B, which are biological TB risk genes with high systemic scores on functional annotations. In sum, the current study shed light on the genomic variants involved in TB pathogenesis as the biological TB risk genes and provided empirical evidence that the genomics of TB may contribute to drug discovery. |
| first_indexed | 2024-04-14T05:33:02Z |
| format | Article |
| id | doaj.art-9c0d7473e14c4548a5ad532ec78a2f80 |
| institution | Directory Open Access Journal |
| issn | 2405-5808 |
| language | English |
| last_indexed | 2024-04-14T05:33:02Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Biochemistry and Biophysics Reports |
| spelling | doaj.art-9c0d7473e14c4548a5ad532ec78a2f802022-12-22T02:09:44ZengElsevierBiochemistry and Biophysics Reports2405-58082022-12-0132101334Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approachLalu Muhammad Irham0Wirawan Adikusuma1Dyah Aryani Perwitasari2Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, IndonesiaDepartment of Pharmacy, University of Muhammadiyah Mataram, Mataram, IndonesiaFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia; Corresponding author.A major challenge in translating genomic variants of Tuberculosis (TB) into clinical implementation is to integrate the disease-associated variants and facilitate drug discovery through the concept of genomic-driven drug repurposing. Here, we utilized two established genomic databases, namely a Genome-Wide Association Study (GWAS) and a Phenome-Wide Association Study (PheWAS) to identify the genomic variants associated with TB disease and further utilize them for drug-targeted genes. We evaluated 3.425 genomic variants associated with TB disease which overlapped with 200 TB-associated genes. To prioritize the biological TB risk genes, we devised an in-silico pipeline and leveraged an established bioinformatics method based on six functional annotations (missense mutation, cis-eQTL, biological process, cellular component, molecular function, and KEGG molecular pathway analysis). Interestingly, based on the six functional annotations that we applied, we discovered that 14 biological TB risk genes are strongly linked to the deregulation of the biological TB risk genes. Hence, we demonstrated that 12 drug target genes overlapped with 40 drugs for other indications and further suggested that the drugs may be repurposed for the treatment of TB. We highlighted that CD44, CCR5, CXCR4, and C3 are highly promising proposed TB targets since they are connected to SELP and HLA-B, which are biological TB risk genes with high systemic scores on functional annotations. In sum, the current study shed light on the genomic variants involved in TB pathogenesis as the biological TB risk genes and provided empirical evidence that the genomics of TB may contribute to drug discovery.http://www.sciencedirect.com/science/article/pii/S2405580822001340BioinformaticsDrug repurposingDrug discoveryGenomic variantsTuberculosis |
| spellingShingle | Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach Biochemistry and Biophysics Reports Bioinformatics Drug repurposing Drug discovery Genomic variants Tuberculosis |
| title | Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach |
| title_full | Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach |
| title_fullStr | Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach |
| title_full_unstemmed | Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach |
| title_short | Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach |
| title_sort | genomic variants driven drug repurposing for tuberculosis by utilizing the established bioinformatic based approach |
| topic | Bioinformatics Drug repurposing Drug discovery Genomic variants Tuberculosis |
| url | http://www.sciencedirect.com/science/article/pii/S2405580822001340 |
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