Identification and analysis of diverse cell death patterns in osteomyelitis via microarray-based transcriptome...

Area of Science:

• Biomedical Science
• Molecular Biology
• Immunology

Background:

• Osteomyelitis (OM) is a bone infection with poorly understood pathogenesis.
• Emerging evidence implicates programmed cell death (PCD) in OM development.
• The precise roles of various PCD types in OM require further elucidation.

Purpose of the Study:

• To comprehensively analyze the involvement of multiple programmed cell death (PCD) modalities in osteomyelitis (OM).
• To identify novel diagnostic biomarkers for early detection and treatment stratification of OM.
• To explore potential therapeutic targets based on PCD pathways in OM.

Main Methods:

• Retrieved and analyzed microarray-based transcriptome datasets for OM from the Gene Expression Omnibus (GEO) database.
• Defined thirteen PCD modalities and evaluated their pathway activities using Gene Set Variation Analysis (GSVA).
• Employed Weighted Gene Co-expression Network Analysis (WGCNA) and SHapley Additive exPlanations (SHAP) for hub gene identification and diagnostic model construction.

Main Results:

• Eight core PCD pathways, including apoptosis, autophagy, cuproptosis, and entosis, were significantly associated with OM.
• Five hub genes (SORT1, KIF1B, TMEM106B, NPC1, ATP6V0B) were identified as key diagnostic candidates.
• Quantitative PCR (qPCR) validated differential expression of these genes in OM patients, confirming their biomarker potential.

Conclusions:

• This research provides a detailed landscape of PCD involvement in osteomyelitis.
• Novel diagnostic biomarkers for OM have been identified, facilitating early detection.
• The study highlights potential therapeutic targets for clinical intervention in OM management.