Evidence map›Paper›PMID 38102690›Full record

ArticleArthritis research & therapy2023

Comprehensive multi-omics analysis reveals the core role of glycerophospholipid metabolism in rheumatoid arthritis development.

Congcong Jian, Lingli Wei, Tong Wu, Shilin Li, Tingting Wang, Jianghua Chen, Shengjia Chang, Jie Zhang, Binhan He, Jianhong Wu and 5 more

Abstract read
In one paragraph

Article in Arthritis research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

15 authors.

Congcong Jian *School of Basic Medical Science, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Lingli Wei *Department of Rheumatology and Immunology, Dazhou Central Hospital, Dazhou, China.
Tong Wu *Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu, China.
Shilin LiDepartment of Clinical Research Center, Dazhou Central Hospital, Dazhou, Sichuan, China.
Tingting WangDepartment of Rheumatology and Immunology, Dazhou Central Hospital, Dazhou, China.
Jianghua ChenInstitute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
Shengjia ChangShantou University Medical College, Shantou University, Guangdong, China.
Jie ZhangDepartment of Clinical Research Center, Dazhou Central Hospital, Dazhou, Sichuan, China.
Binhan HeDepartment of Clinical Research Center, Dazhou Central Hospital, Dazhou, Sichuan, China.
Jianhong WuDepartment of Rheumatology and Immunology, Dazhou Central Hospital, Dazhou, China.
Jiang SuDepartment of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu, China.
Jing ZhuDepartment of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu, China.
Min WuHuaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China. wuminscu@scu.edu.cn.
Yan ZhangLung Cancer Center of West China Hospital, Sichuan University, Chengdu, China. zhang.yan@scu.edu.cn.
Fanxin ZengSchool of Basic Medical Science, Chengdu University of Traditional Chinese Medicine, Chengdu, China. zengfx@pku.edu.cn.

Funding

Innovative Scientific Research Project of Medical in Sichuan Province S20001the Key Projects fund of Science & Technology Department of Sichuan Province 2021YFS0165, 2022YFS0250, 2022JDRC0069the Scientific Research Fund of Sichuan health and Health Committee 20PJ311, 21PJ085
6 · The paper itself

Abstract

objectivesRheumatoid arthritis (RA) is a chronic autoimmune disease with complex causes and recurrent attacks that can easily develop into chronic arthritis and eventually lead to joint deformity. Our study aims to elucidate potential mechanism among control, new-onset RA (NORA) and chronic RA (CRA) with multi-omics analysis.

methodsA total of 113 RA patients and 75 controls were included in our study. Plasma and stool samples were obtained for 16S rRNA sequencing, internally transcribed spacer (ITS) sequencing and metabolomics analysis. And PBMCs were obtained for RNA sequencing. We used three models, logistic regression, least absolute shrinkage and selection operator (LASSO), and random forest, respectively, to distinguish NORA from CRA, and finally we validated model performance using an external cohort of 26 subjects.

resultsOur results demonstrated intestinal flora disturbance in RA development, with significantly increased abundance of Escherichia-Shigella and Proteobacteria in NORA. We also found that the diversity was significantly reduced in CRA compared to NORA through fungi analysis. Moreover, we identified 29 differential metabolites between NORA and CRA. Pathway enrichment analysis revealed significant dysregulation of glycerophospholipid metabolism and phenylalanine metabolism pathways in RA patients. Next, we identified 40 differentially expressed genes between NORA and CRA, which acetylcholinesterase (ACHE) was the core gene and significantly enriched in glycerophospholipid metabolism pathway. Correlation analysis showed a strong negatively correlation between glycerophosphocholine and inflammatory characteristics. Additionally, we applied three approaches to develop disease classifier models that were based on plasma metabolites and gut microbiota, which effectively distinguished between new-onset and chronic RA patients in both discovery cohort and external validation cohort.

conclusionsThese findings revealed that glycerophospholipid metabolism plays a crucial role in the development and progression of RA, providing new ideas for early clinical diagnosis and optimizing treatment strategies.

Indexed as

Arthritis, RheumatoidMultiomicsAcetylcholinesteraseGlycerophospholipidsHumansRNA, Ribosomal, 16SAcetylcholinesteraseGlycerophospholipidsRNA, Ribosomal, 16SChronic RAMulti-omicsNew-onset RARheumatoid arthritis

Identifiers

PMID38102690
PMCPMC10722724

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.