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Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study
INTRODUCTION: Rheumatoid arthritis (RA) is a chronic inflammatory illness that mostly affects the joints of the hands and feet and can reduce life expectancy by an average of 3 to 10 years. Although tremendous progress has been achieved in the treatment of RA, a large minority of patients continue t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496392/ https://www.ncbi.nlm.nih.gov/pubmed/37697373 http://dx.doi.org/10.1186/s12967-023-04474-z |
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author | Cao, Yu Yang, Ying Hu, Qingfeng Wei, Guojun |
author_facet | Cao, Yu Yang, Ying Hu, Qingfeng Wei, Guojun |
author_sort | Cao, Yu |
collection | PubMed |
description | INTRODUCTION: Rheumatoid arthritis (RA) is a chronic inflammatory illness that mostly affects the joints of the hands and feet and can reduce life expectancy by an average of 3 to 10 years. Although tremendous progress has been achieved in the treatment of RA, a large minority of patients continue to respond poorly to existing medications, owing in part to a lack of appropriate therapeutic targets. METHODS: To find therapeutic targets for RA, a Mendelian randomization (MR) was performed. Cis-expression quantitative trait loci (cis-eQTL, exposure) data were obtained from the eQTLGen Consortium (sample size 31,684). Summary statistics for RA (outcome) were obtained from two largest independent cohorts: sample sizes of 97,173 (22,350 cases and 74,823 controls) and 269,377 (8279 cases and 261,098), respectively. Colocalisation analysis was used to test whether RA risk and gene expression were driven by common SNPs. Drug prediction and molecular docking was further used to validate the medicinal value of drug targets. RESULTS: Seven drug targets were significant in both cohorts in MR analysis and supported by localization. PheWAS at the gene level showed only ATP2A1 associated with other traits. These genes are strongly associated with immune function in terms of biological significance. Molecular docking showed excellent binding for drugs and proteins with available structural data. CONCLUSION: This study identifies seven potential drug targets for RA. Drugs designed to target these genes have a higher chance of success in clinical trials and is expected to help prioritise RA drug development and save on drug development costs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04474-z. |
format | Online Article Text |
id | pubmed-10496392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104963922023-09-13 Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study Cao, Yu Yang, Ying Hu, Qingfeng Wei, Guojun J Transl Med Research INTRODUCTION: Rheumatoid arthritis (RA) is a chronic inflammatory illness that mostly affects the joints of the hands and feet and can reduce life expectancy by an average of 3 to 10 years. Although tremendous progress has been achieved in the treatment of RA, a large minority of patients continue to respond poorly to existing medications, owing in part to a lack of appropriate therapeutic targets. METHODS: To find therapeutic targets for RA, a Mendelian randomization (MR) was performed. Cis-expression quantitative trait loci (cis-eQTL, exposure) data were obtained from the eQTLGen Consortium (sample size 31,684). Summary statistics for RA (outcome) were obtained from two largest independent cohorts: sample sizes of 97,173 (22,350 cases and 74,823 controls) and 269,377 (8279 cases and 261,098), respectively. Colocalisation analysis was used to test whether RA risk and gene expression were driven by common SNPs. Drug prediction and molecular docking was further used to validate the medicinal value of drug targets. RESULTS: Seven drug targets were significant in both cohorts in MR analysis and supported by localization. PheWAS at the gene level showed only ATP2A1 associated with other traits. These genes are strongly associated with immune function in terms of biological significance. Molecular docking showed excellent binding for drugs and proteins with available structural data. CONCLUSION: This study identifies seven potential drug targets for RA. Drugs designed to target these genes have a higher chance of success in clinical trials and is expected to help prioritise RA drug development and save on drug development costs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04474-z. BioMed Central 2023-09-11 /pmc/articles/PMC10496392/ /pubmed/37697373 http://dx.doi.org/10.1186/s12967-023-04474-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Cao, Yu Yang, Ying Hu, Qingfeng Wei, Guojun Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title | Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title_full | Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title_fullStr | Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title_full_unstemmed | Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title_short | Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study |
title_sort | identification of potential drug targets for rheumatoid arthritis from genetic insights: a mendelian randomization study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496392/ https://www.ncbi.nlm.nih.gov/pubmed/37697373 http://dx.doi.org/10.1186/s12967-023-04474-z |
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