التفاصيل البيبلوغرافية
| العنوان: |
Evaluation of Biomarkers and Immune Microenvironment of Osteoarthritis: Evidence From Omics Data and Machine Learning. |
| المؤلفون: |
Liu, Zhixin, Liu, Heng, Li, Deqiang, Ma, Liang, Lu, Tongxin, Sun, Hao, Zhang, Yuankai, Yang, Hui |
| المصدر: |
Frontiers in Genetics; 5/16/2022, Vol. 13, p1-13, 13p |
| مصطلحات موضوعية: |
MACHINE learning, RECEIVER operating characteristic curves, BIOMARKERS, IMMUNOLOGIC memory, OSTEOARTHRITIS, DENDRITIC cells |
| مستخلص: |
Objectives: This study aimed to identify novel biomarkers for osteoarthritis (OA) and explore potential pathological immune cell infiltration. Methods: We identified differentially expressed genes (DEGs) between OA and normal synovial tissues using the limma package in R, and performed enrichment analyses to understand the functions and enriched pathways of DEGs. Weighted gene co-expression network analysis (WGCNA) and distinct machine-learning algorithms were then used to identify hub modules and candidate biomarkers. We assessed the diagnostic value of the candidate biomarkers using receiver operating characteristic (ROC) analysis. We then used the CIBERSORT algorithm to analyze immune cell infiltration patterns, and the Wilcoxon test to screen out hub immune cells that might affect OA occurrence. Finally, the expression levels of hub biomarkers were confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Results: We identified 102 up-regulated genes and 110 down-regulated genes. The functional enrichment analysis results showed that DEGs are enriched mainly in immune response pathways. Combining the results of the algorithms and ROC analysis, we identified GUCA1A and NELL1 as potential diagnostic biomarkers for OA, and validated their diagnosibility using an external dataset. Construction of a TF-mRNA-miRNA network enabled prediction of potential candidate compounds targeting hub biomarkers. Immune cell infiltration analyses revealed the expression of hub biomarkers to be correlated with CD8 T cells, memory B cells, M0/M2 macrophages, resting mast cells and resting dendritic cells. qRT-PCR results showed both GUCA1A and NELL1 were significantly increased in OA samples (p < 0.01). All validations are consistent with the microarray hybridization, indicating that GUCA1A and NELL1 may be involved in the pathogenesis of OA. Conclusion: The findings suggest that GUCA1A and NELL1, closely related to OA occurrence and progression, represent new OA candidate markers, and that immune cell infiltration plays a significant role in the progression of OA. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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