TY - JOUR
T1 - Integrated Toxicogenomic Analysis Reveals Potential Molecular Signatures Associated with Cadmium-Related Osteoarthritis
AU - Qiao, Lichun
AU - Wali, Husna
AU - Fan, Xiangyu
AU - Tang, Jing
AU - Shen, Yiming
AU - Li, Qingsong
AU - Dong, Qian
AU - Han, Jing
AU - Guo, Yijie
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Cadmium exposure
KW - Diagnostic biomarkers
KW - Machine learning
KW - Osteoarthritis
KW - Toxicogenomics
UR - https://www.scopus.com/pages/publications/105049523177
U2 - 10.1007/s12011-026-05327-8
DO - 10.1007/s12011-026-05327-8
M3 - 文章
C2 - 42698020
AN - SCOPUS:105049523177
SN - 0163-4984
JO - Biological Trace Element Research
JF - Biological Trace Element Research
ER -