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 dru...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
|
| Series: | Biochemistry and Biophysics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405580822001376 |
| _version_ | 1797998961624088576 |
|---|---|
| author | Arief Rahman Afief Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari Ageng Brahmadhi Rocky Cheung |
| author_facet | Arief Rahman Afief Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari Ageng Brahmadhi Rocky Cheung |
| author_sort | Arief Rahman Afief |
| collection | DOAJ |
| description | 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 < 5 × 10−8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r2 > 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. |
| first_indexed | 2024-04-11T10:57:04Z |
| format | Article |
| id | doaj.art-0c49185b3a0c431ea63678fe71a528e9 |
| institution | Directory Open Access Journal |
| issn | 2405-5808 |
| language | English |
| last_indexed | 2024-04-11T10:57:04Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Biochemistry and Biophysics Reports |
| spelling | doaj.art-0c49185b3a0c431ea63678fe71a528e92022-12-22T04:28:44ZengElsevierBiochemistry and Biophysics Reports2405-58082022-12-0132101337Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosisArief Rahman Afief0Lalu Muhammad Irham1Wirawan Adikusuma2Dyah Aryani Perwitasari3Ageng Brahmadhi4Rocky Cheung5Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, IndonesiaFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia; Corresponding author.Department of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia; Corresponding author.Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, IndonesiaFaculty of Medicine, Universitas Muhammadiyah Purwokerto, Purwokerto, Central Java, IndonesiaDepartment of Chemistry and Biochemistry, University of California, Los Angeles, USAMultiple 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 < 5 × 10−8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r2 > 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.http://www.sciencedirect.com/science/article/pii/S2405580822001376Autoimmune diseaseBioinformaticsDrug repurposingGenomic variantsMultiple sclerosis |
| spellingShingle | Arief Rahman Afief Lalu Muhammad Irham Wirawan Adikusuma Dyah Aryani Perwitasari Ageng Brahmadhi Rocky Cheung Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis Biochemistry and Biophysics Reports Autoimmune disease Bioinformatics Drug repurposing Genomic variants Multiple sclerosis |
| title | Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis |
| title_full | Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis |
| title_fullStr | Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis |
| title_full_unstemmed | Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis |
| title_short | Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis |
| title_sort | integration of genomic variants and bioinformatic based approach to drive drug repurposing for multiple sclerosis |
| topic | Autoimmune disease Bioinformatics Drug repurposing Genomic variants Multiple sclerosis |
| url | http://www.sciencedirect.com/science/article/pii/S2405580822001376 |
| work_keys_str_mv | AT ariefrahmanafief integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis AT lalumuhammadirham integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis AT wirawanadikusuma integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis AT dyaharyaniperwitasari integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis AT agengbrahmadhi integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis AT rockycheung integrationofgenomicvariantsandbioinformaticbasedapproachtodrivedrugrepurposingformultiplesclerosis |