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Article Open Access

Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications

  • Authors:
    • Qingyuan Kang
    • Ping Yuan
    • Peisen Xie
    • Wentao Xiao
    • Liguang Dong
    • Zhenpeng Guan
    • Keshi Zhang
  • View Affiliations / Copyright

    Affiliations: School of Basic Medicine, Shenyang Medical College, Shenyang, Liaoning 110034, P.R. China, Department of Orthopedics, Peking University Shougang Hospital, Beijing 100144, P.R. China, Medical Examination Department, Peking University Shougang Hospital, Beijing 100144, P.R. China
    Copyright: © Kang et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].
  • Article Number: 40
    |
    Published online on: November 12, 2025
       https://doi.org/10.3892/mmr.2025.13750
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Abstract

The combination of knee osteoarthritis (KOA) and atherosclerosis (AS) is a common multimorbidity. Epidemiological studies have demonstrated the existence of common risk factors, with metabolic syndrome possibly considered the most critical. In the present study, metabolism‑related clinical information was analyzed and metabolic profiles were assessed in healthy controls, patients with KOA, patients with AS and patients with both conditions using untargeted serum metabolomics assays. Potential KOA‑AS multimorbidity hub genes were identified using transcriptomics datasets from the Gene Expression Omnibus database and were validated using clinical samples and animal experiments. Finally, the clinical applications of the analyzed biomolecules were predicted. The results showed that the caffeine metabolic pathway was markedly associated with KOA‑AS multimorbidity and caffeine interacted with two potential hub genes (EGR1 and GSK3B). In the validation experiment using clinical samples, early growth response 1 (Egr1) protein was only associated with AS. In the mouse disease model, Egr1 protein in the serum and cartilage was associated with KOA‑AS multimorbidity, with consistent expression trends. Receiver operating characteristic (ROC) analysis showed three metabolites with an area under the ROC curve of >0.7; drug prediction yielded two drugs that interacted with EGR1. In conclusion, KOA‑AS multimorbidity may be associated with metabolic abnormalities in the early stages and could develop into chronic inflammation in the later stages. Through multi‑omics analysis, three caffeine‑related metabolites with diagnostic value were obtained and EGR1 was identified as the key gene for KOA‑AS multimorbidity.
View Figures

Figure 1

Metabolomics data quality assessment
and metabolite characterization. (A) Heat map of Pearson
correlation coefficient for QC samples. (B) Heatmap of metabolite
clustering for between-group differences. (C) Pie chart of the
distribution of detected metabolite classes in QC samples. QC,
Quality Control.

Figure 2

Screening and Functional Analysis of
Differential Metabolites. (A) PLS-DA modeling between comparison
groups. (B) Volcano plots of differential metabolites identified
across comparison groups. (C) KEGG enrichment analysis of
differential metabolites among comparison groups. PLS-DA, partial
least squares discriminant analysis; KEGG, Kyoto Encyclopedia of
Genes and Genomes.

Figure 3

Analysis of Caffeine and Its
Metabolites. (A) Box plots for comparison between groups of
caffeine and its secondary metabolites. (B) Heat map of Pearson
correlation coefficients for relative quantitative values of
caffeine and its secondary metabolites.

Figure 4

Multi-omics integration and
regulatory network analysis based on shared DEGs. (A) Volcano plots
of DEGs for the OA dataset and the AS dataset. (B) DEGs shared by
OA and AS (categorized into up- and downregulation). (C) KEGG
enrichment analysis of shared DEGs. (D) PPI network constructed by
DEGs. (E) Top 5 scoring Hub genes. (F) Gene-metabolite interaction
network. DEGs, differentially expressed genes; OA, osteoarthritis;
AS, atherosclerosis; KEGG, Kyoto Encyclopedia of Genes and Genomes;
PPI, protein-protein interaction.

Figure 5

Validation of Serum Egr1 and GSK-3β
Protein Levels by ELISA. (A) Relative concentrations of human serum
Egr1, GSK-3β proteins in each group. (B) Relative concentrations of
mice serum Egr1, GSK-3β proteins in each group. *P<0.05,
**P<0.01, ***P<0.0001, ****P<0.00001. Egr1, early growth
response 1; GSK-3β, Glycogen Synthase Kinase-3β.

Figure 6

Results of animal model construction
for each group of diseases.

Figure 7

Molecular validation of EGR1
and GSK3B Expression in Cartilage Tissue. (A) Relative RNA
levels of EGR1 and GSK3B in mouse cartilage in each
group. (B) Protein expression levels and electropherograms of
cartilage Egr1 and GSK-3β in mice of each group. *P<0.05,
**P<0.01, ***P<0.0001, ****P<0.00001.Egr1, Early Growth
Response 1; GSK-3β, glycogen synthase kinase-3β.

Figure 8

ROC curve analysis of caffeine and
its secondary metabolites. ROC, receiver operating
characteristic.
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Copy and paste a formatted citation
Spandidos Publications style
Kang Q, Yuan P, Xie P, Xiao W, Dong L, Guan Z and Zhang K: Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications. Mol Med Rep 33: 40, 2026.
APA
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., & Zhang, K. (2026). Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications. Molecular Medicine Reports, 33, 40. https://doi.org/10.3892/mmr.2025.13750
MLA
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., Zhang, K."Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications". Molecular Medicine Reports 33.1 (2026): 40.
Chicago
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., Zhang, K."Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications". Molecular Medicine Reports 33, no. 1 (2026): 40. https://doi.org/10.3892/mmr.2025.13750
Copy and paste a formatted citation
x
Spandidos Publications style
Kang Q, Yuan P, Xie P, Xiao W, Dong L, Guan Z and Zhang K: Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications. Mol Med Rep 33: 40, 2026.
APA
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., & Zhang, K. (2026). Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications. Molecular Medicine Reports, 33, 40. https://doi.org/10.3892/mmr.2025.13750
MLA
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., Zhang, K."Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications". Molecular Medicine Reports 33.1 (2026): 40.
Chicago
Kang, Q., Yuan, P., Xie, P., Xiao, W., Dong, L., Guan, Z., Zhang, K."Identification of multimorbidity hub genes for knee osteoarthritis-atherosclerosis and potential clinical applications". Molecular Medicine Reports 33, no. 1 (2026): 40. https://doi.org/10.3892/mmr.2025.13750
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