Integrated serum metabolomics and lipidomics for identifying metabolic changes in rheumatoid arthritis

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disorder with complex pathogenesis, and conventional biomarkers often fail to capture disease-associated metabolic changes. A more comprehensive understanding of the metabolic alterations in RA may provide deeper insights into disease mechanisms. OBJECTIVE: This study aimed to identify serum metabolic changes associated with RA using non-targeted metabolomics and lipidomics, and to explore the potential impact of these metabolic alterations on RA pathophysiology. METHODS: A case-control study was conducted using baseline data from the Inflammatory Immune Disease Cohort at the First Affiliated Hospital of Anhui Medical University (October 2021 to June 2023). A total of 91 RA patients and 125 healthy controls were included. Serum samples were analyzed by non-targeted liquid chromatography-mass spectrometry (LC-MS). Differential metabolites were identified using orthogonal partial least squares discriminant analysis (OPLS-DA), followed by filtration with Student's t-test (P < 0.05). Logistic regression was applied to identify potential metabolic alterations for further investigation. Pathway enrichment analysis identified significant metabolic pathways associated with RA. RESULTS: The median age of both groups was 50.0 years, with no significant demographic differences (P > 0.05). Metabolomics and lipidomics identified 41 differential metabolites, including 16 small molecules and 25 lipids. Pathway analysis revealed disturbances in the urea cycle, sphingolipid metabolism, arginine and proline metabolism, and glycine and serine metabolism. These findings suggest systemic metabolic alterations in RA and provide new insights into the disease's metabolic profile. CONCLUSIONS: The study identified significant metabolic alterations in RA, contributing to a better understanding of the disease's pathophysiology. These findings highlight the importance of metabolic reprogramming in RA and offer directions for further investigation into metabolic pathways involved in disease progression.

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Journal
Metabolomics
Published
2026-05-16
DOI
https://doi.org/10.1007/s11306-026-02447-z
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
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article

Integrated serum metabolomics and lipidomics for identifying metabolic changes in rheumatoid arthritis

Xin‐Yu Fang, Zi-Xing Zhang, Hua-Hui Zhu, Dong-Qing Ye et al.
Metabolomics
Rheumatoid Arthritis Research and Therapies
article

Integrated serum metabolomics and lipidomics for identifying metabolic changes in rheumatoid arthritis

Xin‐Yu Fang, Zi-Xing Zhang, Hua-Hui Zhu, Dong-Qing Ye, Zhao-Hui Ruan
article en

Abstract

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disorder with complex pathogenesis, and conventional biomarkers often fail to capture disease-associated metabolic changes. A more comprehensive understanding of the metabolic alterations in RA may provide deeper insights into disease mechanisms. OBJECTIVE: This study aimed to identify serum metabolic changes associated with RA using non-targeted metabolomics and lipidomics, and to explore the potential impact of these metabolic alterations on RA pathophysiology. METHODS: A case-control study was conducted using baseline data from the Inflammatory Immune Disease Cohort at the First Affiliated Hospital of Anhui Medical University (October 2021 to June 2023). A total of 91 RA patients and 125 healthy controls were included. Serum samples were analyzed by non-targeted liquid chromatography-mass spectrometry (LC-MS). Differential metabolites were identified using orthogonal partial least squares discriminant analysis (OPLS-DA), followed by filtration with Student's t-test (P < 0.05). Logistic regression was applied to identify potential metabolic alterations for further investigation. Pathway enrichment analysis identified significant metabolic pathways associated with RA. RESULTS: The median age of both groups was 50.0 years, with no significant demographic differences (P > 0.05). Metabolomics and lipidomics identified 41 differential metabolites, including 16 small molecules and 25 lipids. Pathway analysis revealed disturbances in the urea cycle, sphingolipid metabolism, arginine and proline metabolism, and glycine and serine metabolism. These findings suggest systemic metabolic alterations in RA and provide new insights into the disease's metabolic profile. CONCLUSIONS: The study identified significant metabolic alterations in RA, contributing to a better understanding of the disease's pathophysiology. These findings highlight the importance of metabolic reprogramming in RA and offer directions for further investigation into metabolic pathways involved in disease progression.

MetabolomicsVol. 22(3)
Anhui University (CN), Anhui Medical University (CN), Fuyang Second People's Hospital (CN)
Reduced inequalities
Openalex Percentile: Top 4%
Rheumatoid Arthritis Research and Therapies
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