机构:[1]Guangzhou Univ Chinese Med, Clin Coll 2, Dept Orthoped, Guangzhou, Peoples R China广东省中医院[2]Guangzhou Univ Chinese Med, Clin Coll 2, Guangzhou, Peoples R China广东省中医院[3]Xi An Jiao Tong Univ, Honghui Hosp, Spine Surg, Xi'an, Peoples R China
Osteoarthritis (OA) is thought to be the most prevalent chronic joint disease. The incidence of OA is rising because of the ageing population and the epidemic of obesity. This research was designed for the identification of novel diagnostic biomarkers for OA and analyzing the possible association between critical genes and infiltrated immune cells. 10 OA samples from patients with spinal OA and 10 normal samples were collected. GSE55235 and GSE55457 datasets including human OA and normal samples were downloaded from the GEO datasets. Differentially expressed genes (DEGs) were identified between 20 OA and 20 controls. SVM-RFE analysis and LASSO regression model were carried out to screen possible markers. The compositional patterns of the 22 types of immune cell fraction in OA were determined by the use of CIBERSORT. The expression level of the biomarkers in OA was examined by the use of RT-PCR. In this study, an overall 44 DEGs were identified: 18 genes were remarkably upregulated and 26 genes were distinctly downregulated. KEGG pathway analyses revealed that pathways were significantly enriched including IL-17 signal path, rheumatoid arthritis, TNF signal path, and lipid and atherosclerosis. Based on the results of machine learning, we identified APOLD1 and EPYC as critical diagnostic genes in OA, which were further confirmed using ROC assays. Immune cell infiltration analysis revealed that APOLD1 was correlated with mastocytes stimulated, NK cells resting, T cells CD4 memory resting, DCs stimulated, T cells gamma delta, macrophages M0, NK cells stimulated, and mastocytes resting. Moreover, we found that EPYC was correlated with mastocytes stimulated, NK cells resting, T cells CD4 memory resting, DCs stimulated, T cells gamma delta, macrophages M0, NK cells stimulated, and mastocytes resting. Overall, our findings might provide some novel clue for the exploration of novel markers for OA diagnosis. The critical genes and their associations with immune infiltration may offer new insight into understanding OA developments.
基金:
Shaanxi Province Science and Technology Department [2021JM-575]
第一作者机构:[1]Guangzhou Univ Chinese Med, Clin Coll 2, Dept Orthoped, Guangzhou, Peoples R China
通讯作者:
推荐引用方式(GB/T 7714):
Liang Yihao,Lin Fangzheng,Huang Yunfei.Identification of Biomarkers Associated with Diagnosis of Osteoarthritis Patients Based on Bioinformatics and Machine Learning[J].JOURNAL OF IMMUNOLOGY RESEARCH.2022,2022:doi:10.1155/2022/5600190.
APA:
Liang, Yihao,Lin, Fangzheng&Huang, Yunfei.(2022).Identification of Biomarkers Associated with Diagnosis of Osteoarthritis Patients Based on Bioinformatics and Machine Learning.JOURNAL OF IMMUNOLOGY RESEARCH,2022,
MLA:
Liang, Yihao,et al."Identification of Biomarkers Associated with Diagnosis of Osteoarthritis Patients Based on Bioinformatics and Machine Learning".JOURNAL OF IMMUNOLOGY RESEARCH 2022.(2022)