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Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data

Rheumatoid arthritis (RA) is an autoimmune and inflammatory disease for which there is a lack of therapeutic options. Genome-wide association studies (GWASs) have identified over 100 genetic loci associated with RA susceptibility; however, the most causal risk genes (RGs) associated with, and molecu...

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Autores principales: Birga, Anteneh M., Ren, Liping, Luo, Huaichao, Zhang, Yang, Huang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8820924/
https://www.ncbi.nlm.nih.gov/pubmed/35140805
http://dx.doi.org/10.1155/2022/6783659
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author Birga, Anteneh M.
Ren, Liping
Luo, Huaichao
Zhang, Yang
Huang, Jian
author_facet Birga, Anteneh M.
Ren, Liping
Luo, Huaichao
Zhang, Yang
Huang, Jian
author_sort Birga, Anteneh M.
collection PubMed
description Rheumatoid arthritis (RA) is an autoimmune and inflammatory disease for which there is a lack of therapeutic options. Genome-wide association studies (GWASs) have identified over 100 genetic loci associated with RA susceptibility; however, the most causal risk genes (RGs) associated with, and molecular mechanism underlying, RA remain unknown. In this study, we collected 95 RA-associated loci from multiple GWASs and detected 87 candidate high-confidence risk genes (HRGs) from these loci via integrated multiomics data (the genome-scale chromosome conformation capture data, enhancer-promoter linkage data, and gene expression data) using the Bayesian integrative risk gene selector (iRIGS). Analysis of these HRGs indicates that these genes were indeed, markedly associated with different aspects of RA. Among these, 36 and 46 HRGs have been reported to be related to RA and autoimmunity, respectively. Meanwhile, most novel HRGs were also involved in the significantly enriched RA-related biological functions and pathways. Furthermore, drug repositioning prediction of the HRGs revealed three potential targets (ERBB2, IL6ST, and MAPK1) and nine possible drugs for RA treatment, of which two IL-6 receptor antagonists (tocilizumab and sarilumab) have been approved for RA treatment and four drugs (trastuzumab, lapatinib, masoprocol, and arsenic trioxide) have been reported to have a high potential to ameliorate RA. In summary, we believe that this study provides new clues for understanding the pathogenesis of RA and is important for research regarding the mechanisms underlying RA and the development of therapeutics for this condition.
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spelling pubmed-88209242022-02-08 Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data Birga, Anteneh M. Ren, Liping Luo, Huaichao Zhang, Yang Huang, Jian Comput Math Methods Med Research Article Rheumatoid arthritis (RA) is an autoimmune and inflammatory disease for which there is a lack of therapeutic options. Genome-wide association studies (GWASs) have identified over 100 genetic loci associated with RA susceptibility; however, the most causal risk genes (RGs) associated with, and molecular mechanism underlying, RA remain unknown. In this study, we collected 95 RA-associated loci from multiple GWASs and detected 87 candidate high-confidence risk genes (HRGs) from these loci via integrated multiomics data (the genome-scale chromosome conformation capture data, enhancer-promoter linkage data, and gene expression data) using the Bayesian integrative risk gene selector (iRIGS). Analysis of these HRGs indicates that these genes were indeed, markedly associated with different aspects of RA. Among these, 36 and 46 HRGs have been reported to be related to RA and autoimmunity, respectively. Meanwhile, most novel HRGs were also involved in the significantly enriched RA-related biological functions and pathways. Furthermore, drug repositioning prediction of the HRGs revealed three potential targets (ERBB2, IL6ST, and MAPK1) and nine possible drugs for RA treatment, of which two IL-6 receptor antagonists (tocilizumab and sarilumab) have been approved for RA treatment and four drugs (trastuzumab, lapatinib, masoprocol, and arsenic trioxide) have been reported to have a high potential to ameliorate RA. In summary, we believe that this study provides new clues for understanding the pathogenesis of RA and is important for research regarding the mechanisms underlying RA and the development of therapeutics for this condition. Hindawi 2022-01-31 /pmc/articles/PMC8820924/ /pubmed/35140805 http://dx.doi.org/10.1155/2022/6783659 Text en Copyright © 2022 Anteneh M. Birga et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Birga, Anteneh M.
Ren, Liping
Luo, Huaichao
Zhang, Yang
Huang, Jian
Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title_full Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title_fullStr Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title_full_unstemmed Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title_short Prediction of New Risk Genes and Potential Drugs for Rheumatoid Arthritis from Multiomics Data
title_sort prediction of new risk genes and potential drugs for rheumatoid arthritis from multiomics data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8820924/
https://www.ncbi.nlm.nih.gov/pubmed/35140805
http://dx.doi.org/10.1155/2022/6783659
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