ORIGINAL RESEARCH article

Front. Immunol.

Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1611000

Molecular Subtype and RNA Transcriptomics Validation for Rheumatoid Arthritis Characterized by Fatty Acid Metabolism-Related Immune Landscape

Provisionally accepted
Peng  ZhangPeng Zhang1Yu  WenYu Wen1Xin  LiXin Li1Yihong  YangYihong Yang1Youbang  LiangYoubang Liang1Chenguang  ZhanChenguang Zhan1Liyan  MeiLiyan Mei2Haifang  DuHaifang Du2Xiumin  ChenXiumin Chen2Maojie  WangMaojie Wang2*Runyue  HuangRunyue Huang2*Xiaodong  WuXiaodong Wu2*
  • 1Guangzhou University of Chinese Medicine, Guangzhou, China
  • 2The Second Affiliated Hospital, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China

The final, formatted version of the article will be published soon.

Rheumatoid Arthritis (RA) is a rheumatic disease charactered by severe bone destruction. Evidence suggests that fatty acid metabolism (FAM)-related proteins can regulate inflammation of synoviocytes in RA. However, the fundamental roles of FAM regulators in RA remain to be elucidated. We selected the GSE93272 dataset sourced from the Gene Expression Omnibus (GEO) for the classification of FAM-associated molecular subtypes and immune microenvironments in RA. Subsequently, bone marrow-derived macrophages (BMMs) with or without receptor activator of nuclear factor kappa-B ligand (RANKL) intervention were harvested for RNA sequencing (RNA-seq) to verify FAM hub gene expressions. Finally, difference analysis between RA samples and controls screened 53 significant FAM regulators. Random forest algorithm for RA risk prediction was utilized to identify ten diagnostic FAM regulators (hub genes). A nomogram incorporating hub genes was developed, and decision curve analysis suggested its potential utility in clinical practice. Additionally, consensus clustering analysis of these hub genes categorized RA patients to different FAM clusters (cluster A and cluster B). To quantify FAM clusters, principal component analysis (PCA) was adopted to count FAM score of every sample. ClusterB may be more linked with osteoclastogenesis in RA characterized by RXRA, IL17RA, and TBXA2R. Additionally, cases in cluster A were associated with the immunity of activated CD4 T cell, activated CD8 T cell, eosinophil, Gamma delta T cell, immature dendritic cell, MDSC, macrophage, regulatory T cell, and Type 2 T helper cell, while cluster B was linked to CD56dim natural killer cell, Natural killer T cell, T follicular helper cell, Type 1 T helper cell immunity, which has a higher FAM score. Remarkably, RNA-seq analysis confirmed the expression trend of SREBF1, FASN, CD36, SCD1 and SCD2, consistent with bioinformatics predictions. Therefore, this scoring system of FAM subtypes provided promising markers and immunotherapeutic strategies for future RA treatment.

Keywords: Rheumatoid arthritis, fatty acid metabolism, Subtype classification, Immune Cell Infiltration, RNA sequencing

Received: 14 Apr 2025; Accepted: 20 Jun 2025.

Copyright: © 2025 Zhang, Wen, Li, Yang, Liang, Zhan, Mei, Du, Chen, Wang, Huang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Maojie Wang, The Second Affiliated Hospital, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510000, China
Runyue Huang, The Second Affiliated Hospital, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510000, China
Xiaodong Wu, The Second Affiliated Hospital, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510000, China

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