Investigating Angiogenesis-Related Biomarkers in Osteoarthritis Patients Through Transcriptomic Profiling

Yang Zheng,1 Miaojia Fang,2 Shriya Sanan,1 Xi-Hui Meng,1 Jie-Feng Huang,1 Yu Qian1 1Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, People’s Republic of China; 2Institute of Forensic Science, Yuhang Public Security Department, Hangzhou, People’s Republic of ChinaCorrespondence: Yu Qian, Zhejiang Provincial Hospital of Traditional Chinese Medicine, 54 Youdian Road, Shangcheng District, Hangzhou, 310006, People’s Republic of China, Tel +86-571-87068001, Fax +86-571-87034117, Email [email protected]: Osteoarthritis (OA) is a common age-related joint disease characterized by joint destruction and impaired quality of life. Angiogenesis plays a vital role in OA progression. This study aimed to identify key angiogenesis-related genes (ARGs) in OA using transcriptomic and machine learning methods.Methods: The GSE55235 dataset (10 OA and 10 healthy synovial tissue samples) was analyzed for differentially expressed genes (DEGs), integrated with weighted gene co-expression network analysis (WGCNA), and ARGs to identify differentially expressed ARGs (DE-ARGs). Candidate genes were identified through three machine learning algorithms and evaluated using ROC curve analysis. Gene set enrichment analysis (GSEA), immune cell infiltration analysis, and therapeutic agent prediction were performed. Synovial samples from 5 OA patients and 5 matched controls were collected for RT-qPCR validation of biomarkers.Results: From 1552 DEGs, 11 DE-ARGs were identified, and six candidate genes were selected using machine learning. Four genes—COL3A1, OLR1, STC1, and KCNJ8—showed AUC > 0.8 in both GSE55235 and GSE1919, indicating strong diagnostic value. GSEA linked biomarkers to the “lysosome” pathway, and eosinophils and Th2 cells were significantly associated with biomarkers. Potential therapeutic agents included bisphenol A, tetrachlorodibenzo-p-dioxin, and valproic acid. Clinical validation confirmed that COL3A1, OLR1, and STC1 expression levels were consistent with database findings.Conclusion: The study identified COL3A1, OLR1, STC1, and KCNJ8 as key angiogenesis-related biomarkers in osteoarthritis, which could serve as potential diagnostic tools and therapeutic targets. The research underscores the importance of angiogenesis in osteoarthritis progression and suggests that targeting angiogenesis-related pathways may offer new treatment strategies.Keywords: osteoarthritis, angiogenesis, biomarker, immune infiltration, regulatory network

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating Angiogenesis-Related Biomarkers in Osteoarthritis Patients Through Transcriptomic Profiling

SHILAP Revista de lepidopterología
Prenatal Screening and Diagnostics
article

Investigating Angiogenesis-Related Biomarkers in Osteoarthritis Patients Through Transcriptomic Profiling

article en

Abstract

Yang Zheng,1 Miaojia Fang,2 Shriya Sanan,1 Xi-Hui Meng,1 Jie-Feng Huang,1 Yu Qian1 1Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, People’s Republic of China; 2Institute of Forensic Science, Yuhang Public Security Department, Hangzhou, People’s Republic of ChinaCorrespondence: Yu Qian, Zhejiang Provincial Hospital of Traditional Chinese Medicine, 54 Youdian Road, Shangcheng District, Hangzhou, 310006, People’s Republic of China, Tel +86-571-87068001, Fax +86-571-87034117, Email [email protected]: Osteoarthritis (OA) is a common age-related joint disease characterized by joint destruction and impaired quality of life. Angiogenesis plays a vital role in OA progression. This study aimed to identify key angiogenesis-related genes (ARGs) in OA using transcriptomic and machine learning methods.Methods: The GSE55235 dataset (10 OA and 10 healthy synovial tissue samples) was analyzed for differentially expressed genes (DEGs), integrated with weighted gene co-expression network analysis (WGCNA), and ARGs to identify differentially expressed ARGs (DE-ARGs). Candidate genes were identified through three machine learning algorithms and evaluated using ROC curve analysis. Gene set enrichment analysis (GSEA), immune cell infiltration analysis, and therapeutic agent prediction were performed. Synovial samples from 5 OA patients and 5 matched controls were collected for RT-qPCR validation of biomarkers.Results: From 1552 DEGs, 11 DE-ARGs were identified, and six candidate genes were selected using machine learning. Four genes—COL3A1, OLR1, STC1, and KCNJ8—showed AUC > 0.8 in both GSE55235 and GSE1919, indicating strong diagnostic value. GSEA linked biomarkers to the “lysosome” pathway, and eosinophils and Th2 cells were significantly associated with biomarkers. Potential therapeutic agents included bisphenol A, tetrachlorodibenzo-p-dioxin, and valproic acid. Clinical validation confirmed that COL3A1, OLR1, and STC1 expression levels were consistent with database findings.Conclusion: The study identified COL3A1, OLR1, STC1, and KCNJ8 as key angiogenesis-related biomarkers in osteoarthritis, which could serve as potential diagnostic tools and therapeutic targets. The research underscores the importance of angiogenesis in osteoarthritis progression and suggests that targeting angiogenesis-related pathways may offer new treatment strategies.Keywords: osteoarthritis, angiogenesis, biomarker, immune infiltration, regulatory network

SHILAP Revista de lepidopterología
Openalex Percentile: Top 36%
Prenatal Screening and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Investigating Angiogenesis-Related Biomarkers in Osteoarthritis Patients Through Transcriptomic Profiling · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS