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Integrated Toxicogenomic Analysis Reveals Potential Molecular Signatures Associated with Cadmium-Related Osteoarthritis

  • Lichun Qiao
  • , Husna Wali
  • , Xiangyu Fan
  • , Jing Tang
  • , Yiming Shen
  • , Qingsong Li
  • , Qian Dong
  • , Jing Han
  • , Yijie Guo
  • Department of Psychiatry
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • School of Public Health
  • Xi'an Jiaotong University
  • Global Health Institute
  • Zhejiang University
  • MOE Key Laboratory of Environment and Genes Related to Diseases
  • Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province
  • Center for Brain Science

Research output: Contribution to journal › Article › peer-review

Abstract

Osteoarthritis (OA) is a common chronic joint disease, and cadmium (Cd) exposure may contribute to its progression. This study integrated network toxicology, transcriptomic datasets from the Gene Expression Omnibus (GEO), weighted gene co-expression network analysis (WGCNA), and machine-learning methods to identify molecular signatures potentially associated with Cd exposure-related OA. A total of 740 overlapping targets between Cd-associated genes and OA-related genes were identified. These targets were primarily enriched in oxidative stress, inflammation, apoptosis, extracellular matrix degradation, and the phosphoinositide 3-kinase/protein kinase B (PI3K-Akt), mitogen-activated protein kinase (MAPK), tumor necrosis factor (TNF), nuclear factor kappa B (NF-κB), interleukin 17 (IL-17), and hypoxia-inducible factor 1 (HIF-1) signaling pathways. Integrated transcriptomic analysis identified 174 differentially expressed genes (DEGs), and WGCNA identified the yellow module as the module most strongly associated with OA. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest analyses identified BCL6 and FOSL2 as robust diagnostic feature genes. Both genes were consistently down-regulated in OA samples and demonstrated strong diagnostic performance across the analyzed cohorts. These findings suggest that BCL6 and FOSL2 may be potential diagnostic biomarkers of Cd-associated OA.

Original languageEnglish
JournalBiological Trace Element Research
DOIs
StateAccepted/In press - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cadmium exposure
  • Diagnostic biomarkers
  • Machine learning
  • Osteoarthritis
  • Toxicogenomics

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