Integrative genomic analysis and diagnostic modeling of osteoporosis: unraveling the interplay of autophagy, osteogenesis, adipogenesis, and immune infiltration
- Lin-Jing Han 1, Jian-Zong Zhu 1,2, Hong-Cai Liu 3, Xiao-Sheng Lin 1,4, Shu-Zhong Yang 1
- Lin-Jing Han 1, Jian-Zong Zhu 1,2, Hong-Cai Liu 3
- 1Orthopedics Department, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.
- 2Graduate School, Guangzhou University of Chinese Medicine, Guangzhou, China.
- 3Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.
- 4Osteoporosis Department, Baoan Central Hospital of Shenzhen, Shenzhen, China.
- 0Orthopedics Department, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies key genes and immune cell differences in osteoporosis (OP) to create a predictive diagnostic model. Findings offer insights into OP pathogenesis and personalized treatment strategies.
Area Of Science
- Genomics and Bioinformatics
- Immunology
- Molecular Biology
Background
- Osteoporosis (OP) is characterized by reduced bone density and structural deterioration, increasing fracture risk.
- Early diagnosis and effective therapeutic strategies for OP remain critical challenges in clinical practice.
Purpose Of The Study
- To develop a predictive diagnostic model for osteoporosis by analyzing differential gene expression.
- To elucidate the molecular mechanisms and immune system involvement in osteoporosis pathogenesis.
Main Methods
- Utilized Gene Expression Omnibus (GEO) datasets (GSE62402, GSE56815, GSE35958) to identify differentially expressed genes (DEGs).
- Performed network analysis, immune checkpoint analysis, and ssGSEA for immune cell infiltration assessment.
- Constructed and validated diagnostic models using logistic regression, SVM, and LASSO.
Main Results
- Identified 1,297 DEGs, including 14 key genes related to autophagy, osteogenesis, and adipogenesis.
- Highlighted the role of oxidative stress and inflammation-related pathways in OP.
- Pinpointed nine pivotal genes (AKT1, NFKB1, TNF, CTNNB1, LMNA, BHLHE40, BMP4, WNT1, COPS3) for diagnostic efficacy and observed significant immune cell infiltration variations.
Conclusions
- Established a gene network for OP and provided insights into immune response mechanisms.
- Identified key diagnostic genes and immune cell infiltration patterns crucial for understanding OP.
- Underscored the potential for personalized treatment and immune modulation in managing osteoporosis.
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