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Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels
BACKGROUND: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune inflammatory disease, the pathogenesis of which is not clear. Clinical remission, or decreased disease activity, is the aim of treatment for RA. However, our understanding of disease activity is inadequate, and clinical remissio...
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/PMC10155393/ https://www.ncbi.nlm.nih.gov/pubmed/37138305 http://dx.doi.org/10.1186/s13075-023-03049-z |
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author | Chen, Jianghua Li, Shilin Zhu, Jing Su, Wei Jian, Congcong Zhang, Jie Wu, Jianhong Wang, Tingting Zhang, Weihua Zeng, Fanwei Chang, Shengjia Jia, Lihua Su, Jiang Zhao, Yi Wang, Jing Zeng, Fanxin |
author_facet | Chen, Jianghua Li, Shilin Zhu, Jing Su, Wei Jian, Congcong Zhang, Jie Wu, Jianhong Wang, Tingting Zhang, Weihua Zeng, Fanwei Chang, Shengjia Jia, Lihua Su, Jiang Zhao, Yi Wang, Jing Zeng, Fanxin |
author_sort | Chen, Jianghua |
collection | PubMed |
description | BACKGROUND: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune inflammatory disease, the pathogenesis of which is not clear. Clinical remission, or decreased disease activity, is the aim of treatment for RA. However, our understanding of disease activity is inadequate, and clinical remission rates for RA are generally poor. In this study, we used multi-omics profiling to study potential alterations in rheumatoid arthritis with different disease activity levels. METHODS: Fecal and plasma samples from 131 rheumatoid arthritis (RA) patients and 50 healthy subjects were collected for 16S rRNA sequencing, internally transcribed spacer (ITS) sequencing, and liquid chromatography-tandem mass spectrometry (LC–MS/MS). The PBMCS were also collected for RNA sequencing and whole exome sequencing (WES). The disease groups, based on 28 joints and ESR (DAS28), were divided into DAS28L, DAS28M, and DAS28H groups. Three random forest models were constructed and verified with an external validation cohort of 93 subjects. RESULTS: Our findings revealed significant alterations in plasma metabolites and gut microbiota in RA patients with different disease activities. Moreover, plasma metabolites, especially lipid metabolites, demonstrated a significant correlation with the DAS28 score and also associations with gut bacteria and fungi. KEGG pathway enrichment analysis of plasma metabolites and RNA sequencing data demonstrated alterations in the lipid metabolic pathway in RA progression. Whole exome sequencing (WES) results have shown that non-synonymous single nucleotide variants (nsSNV) of the HLA-DRB1 and HLA-DRB5 gene locus were associated with the disease activity of RA. Furthermore, we developed a disease classifier based on plasma metabolites and gut microbiota that effectively discriminated RA patients with different disease activity in both the discovery cohort and the external validation cohort. CONCLUSION: Overall, our multi-omics analysis confirmed that RA patients with different disease activity were altered in plasma metabolites, gut microbiota composition, transcript levels, and DNA. Our study identified the relationship between gut microbiota and plasma metabolites and RA disease activity, which may provide a novel therapeutic direction for improving the clinical remission rate of RA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-023-03049-z. |
format | Online Article Text |
id | pubmed-10155393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101553932023-05-04 Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels Chen, Jianghua Li, Shilin Zhu, Jing Su, Wei Jian, Congcong Zhang, Jie Wu, Jianhong Wang, Tingting Zhang, Weihua Zeng, Fanwei Chang, Shengjia Jia, Lihua Su, Jiang Zhao, Yi Wang, Jing Zeng, Fanxin Arthritis Res Ther Research BACKGROUND: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune inflammatory disease, the pathogenesis of which is not clear. Clinical remission, or decreased disease activity, is the aim of treatment for RA. However, our understanding of disease activity is inadequate, and clinical remission rates for RA are generally poor. In this study, we used multi-omics profiling to study potential alterations in rheumatoid arthritis with different disease activity levels. METHODS: Fecal and plasma samples from 131 rheumatoid arthritis (RA) patients and 50 healthy subjects were collected for 16S rRNA sequencing, internally transcribed spacer (ITS) sequencing, and liquid chromatography-tandem mass spectrometry (LC–MS/MS). The PBMCS were also collected for RNA sequencing and whole exome sequencing (WES). The disease groups, based on 28 joints and ESR (DAS28), were divided into DAS28L, DAS28M, and DAS28H groups. Three random forest models were constructed and verified with an external validation cohort of 93 subjects. RESULTS: Our findings revealed significant alterations in plasma metabolites and gut microbiota in RA patients with different disease activities. Moreover, plasma metabolites, especially lipid metabolites, demonstrated a significant correlation with the DAS28 score and also associations with gut bacteria and fungi. KEGG pathway enrichment analysis of plasma metabolites and RNA sequencing data demonstrated alterations in the lipid metabolic pathway in RA progression. Whole exome sequencing (WES) results have shown that non-synonymous single nucleotide variants (nsSNV) of the HLA-DRB1 and HLA-DRB5 gene locus were associated with the disease activity of RA. Furthermore, we developed a disease classifier based on plasma metabolites and gut microbiota that effectively discriminated RA patients with different disease activity in both the discovery cohort and the external validation cohort. CONCLUSION: Overall, our multi-omics analysis confirmed that RA patients with different disease activity were altered in plasma metabolites, gut microbiota composition, transcript levels, and DNA. Our study identified the relationship between gut microbiota and plasma metabolites and RA disease activity, which may provide a novel therapeutic direction for improving the clinical remission rate of RA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-023-03049-z. BioMed Central 2023-05-03 2023 /pmc/articles/PMC10155393/ /pubmed/37138305 http://dx.doi.org/10.1186/s13075-023-03049-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Chen, Jianghua Li, Shilin Zhu, Jing Su, Wei Jian, Congcong Zhang, Jie Wu, Jianhong Wang, Tingting Zhang, Weihua Zeng, Fanwei Chang, Shengjia Jia, Lihua Su, Jiang Zhao, Yi Wang, Jing Zeng, Fanxin Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title | Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title_full | Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title_fullStr | Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title_full_unstemmed | Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title_short | Multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
title_sort | multi-omics profiling reveals potential alterations in rheumatoid arthritis with different disease activity levels |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155393/ https://www.ncbi.nlm.nih.gov/pubmed/37138305 http://dx.doi.org/10.1186/s13075-023-03049-z |
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