In-silico analysis predicts disruption of normal angiogenesis as a causative factor in osteoporosis pathogenesis

Area of Science:

• Biomedical Engineering
• Genetics
• Molecular Biology

Background:

• Angiogenesis-osteogenesis coupling is vital for bone health, and its disruption contributes to bone loss.
• Osteoporosis (OP) is a metabolic disorder characterized by bone microarchitecture deterioration and increased fracture risk.
• Angiogenesis is impaired during OP progression, particularly in postmenopausal osteoporosis (PMOP).

Purpose of the Study:

• To computationally identify hub genes and molecular pathways involved in OP and PMOP.
• To analyze the impact of genetic variations, specifically single nucleotide polymorphisms (SNPs), on identified hub genes.
• To propose mechanical loading as a preventive strategy for PMOP based on molecular insights.

Main Methods:

• Gene retrieval from DisGeNET for OP and PMOP.
• Hub gene identification and molecular pathway enrichment using Cytoscape plugins (STRING, MCODE, CytoHubba, ClueGO) and Enrichr.
• SNP analysis using gnomAD, I-Mutant2.0, MUpro, ConSurf, and COACH servers; protein modeling with SWISS-MODEL and YASARA FoldX.

Main Results:

• Identified 28 hub genes, including 8 transcription factors (e.g., HIF1A, JUN, TP53, ESR1).
• The F201L substitution in IL6 was identified as the most deleterious SNP, reducing protein stability.
• Thirteen hub genes, including IL6, and associated pathways are involved in angiogenesis and immune signaling.

Conclusions:

• Mechanical loading of bone may prevent PMOP by maintaining angiogenesis and immune status.
• In silico analysis provides insights into the molecular basis of OP and potential therapeutic targets.
• Understanding gene-disease associations and SNP effects can inform novel therapeutic strategies for osteoporosis.