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Multi-omics Analysis to Identify Key Immune Genes for Osteoporosis based on Machine Learning and Single-cell
Baoxin Zhang1,2,3,4,5, Zhiwei Pei3, Aixian Tian3
1Suzhou Medical College of Soochow University, Suzhou, People's Republic of China.
Orthopaedic Surgery
|September 6, 2024
Summary
This study identifies neutrophils and four key genes (DND1, HIRA, SH3GLB2, F7) as crucial in osteoporosis development. These findings offer new diagnostic and therapeutic targets for bone disease.
Area of Science:
- Immunology
- Genetics
- Bioinformatics
Background:
- Osteoporosis pathogenesis involves complex immune processes.
- Understanding bone immune mechanisms is vital for identifying new therapeutic targets.
Purpose of the Study:
- Explore novel bone immune markers for osteoporosis using single-cell and transcriptome data.
- Utilize bioinformatics and machine learning to discover new diagnostic and therapeutic strategies for osteoporosis.
Main Methods:
- Acquired single-cell and transcriptome data from GEO.
- Performed cell communication, pseudotime, and hdWGCNA analyses.
- Used machine learning algorithms to screen hub genes and evaluated immune/pathway scores.
Main Results:
- Identified increased proportions of bone marrow-derived mesenchymal stem cells and neutrophils in osteoporosis samples.
- Discovered four hub genes (DND1, HIRA, SH3GLB2, F7) with significant correlations to immune cell types.
- RT-qPCR confirmed reduced expression of DND1, HIRA, and SH3GLB2 in osteoporosis patients.
Conclusions:
- Neutrophils play a critical role in osteoporosis occurrence and progression.
- The identified hub genes may inhibit metabolic activities and promote inflammation, contributing to osteoporosis onset and diagnosis.
