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Related Experiment Video

Updated: Apr 4, 2026

An Adoptive Transfer Model of Rheumatoid Arthritis in Mice
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Mitochondrial Hub Genes in Rheumatoid Arthritis Identified by Machine Learning and Mendelian Randomization with

Xiaolin Luo1, Zhuqing Dong2, Yuansong Song1

  • 1The First Affiliated Hospital of Guangxi Medical University, Nanning, People's Republic of China.

Journal of Inflammation Research
|April 3, 2026
PubMed
Summary

Researchers identified six key mitochondria-related genes (UCP2, BCL2A1, FASN, AKR1B10, IFI27, PDK1) as potential diagnostic biomarkers for rheumatoid arthritis (RA). BCL2A1 was confirmed as a causal risk factor for RA.

Keywords:
Mendelian randomizationbiomarkersmachine learningmolecular dockingrheumatoid arthritis

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Area of Science:

  • Genomics and Bioinformatics
  • Immunology
  • Mitochondrial Biology

Background:

  • Rheumatoid arthritis (RA) pathogenesis involves complex mechanisms, with mitochondria playing a critical but not fully understood role.
  • Identifying specific mitochondrial genes implicated in RA is crucial for understanding disease development and finding new therapeutic targets.

Purpose of the Study:

  • To identify key mitochondria-related genes associated with rheumatoid arthritis (RA) using machine learning approaches.
  • To validate the causal relationship of identified genes with RA susceptibility using Mendelian randomization (MR).
  • To explore potential therapeutic targets and drug candidates for RA based on identified genes.

Main Methods:

  • Machine learning algorithms (LASSO, SVM, RF) were applied to RA gene expression data to screen hub genes.
  • Gene Ontology (GO), KEGG, and Metascape analyses were performed for functional enrichment.
  • Two-sample Mendelian randomization (MR) was used to assess causal relationships between genes and RA.

Main Results:

  • Six mitochondria-related hub genes (UCP2, BCL2A1, FASN, AKR1B10, IFI27, PDK1) were identified and formed a diagnostic model with good discriminatory ability.
  • Mendelian randomization analysis confirmed a significant causal relationship between BCL2A1 and RA, identifying it as a risk factor.
  • Bioinformatics analyses suggested potential drug targets among the hub genes, with preliminary validation via RT-qPCR.

Conclusions:

  • UCP2, BCL2A1, FASN, AKR1B10, IFI27, and PDK1 are identified as potential mitochondria-related diagnostic biomarkers for RA.
  • BCL2A1 is confirmed as a causal risk factor for rheumatoid arthritis, highlighting its importance in disease pathogenesis.
  • The study provides novel insights into mitochondria's role in RA and suggests potential therapeutic avenues.