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From Bench to Bedside: Personalized Genomics in the Diagnosis and Treatment of Osteomyelitis
Amir Human Hoveidaei1, Arian Rahimzadeh2, Sara Mohammadi2
1International Center for Limb Lengthening, Rubin Institute for Advanced Orthopedics, Sinai Hospital of Baltimore, Baltimore, MD 21215, USA.
Abstract:
Osteomyelitis (OM), an inflammatory condition of the bone tissue, is a complex orthopedic condition marked by chronic inflammation, diagnostic uncertainty, and recurrent infections. Despite standard treatments-including surgical debridement, antimicrobial therapy, and bone reconstruction-many patients continue to experience recurrence and treatment failure. Growing molecular evidence indicates that host genetic factors play a crucial role in shaping immune responses and influencing disease progression in OM. This narrative review synthesizes current knowledge from candidate gene single-nucleotide polymorphism (SNP) association studies to illustrate how specific genetic variations contribute to OM pathogenesis, diagnostic refinement, and treatment outcomes. We examined key immunogenetic variants within genes involved in inflammatory signaling, pathogen recognition, and neutrophil regulation. Our synthesis identifies a landscape of pro-inflammatory SNPs, such as IL-1β rs16944 and NLRP3 rs10754558, that are associated with increased susceptibility to chronic or post-traumatic OM, as well as SNPs that are associated with protective effects that may favor infection resolution, such as within the NOS2 and VDR genes. These SNP-driven differences in inflammasome activity, cytokine pathways, and oxidative stress responses highlight emerging opportunities for individualized therapeutic strategies. This review consolidates these variants, providing a genetic framework to analyze host susceptibility and differentiating high risk from protective genetic profiles. Integrating genomic insights into OM management represents a promising shift toward personalized medicine, enhancing diagnostic precision, informing targeted interventions, and improving prognostic assessment. Continued large-scale validation of candidate SNPs and translational genomic models will be essential to support their future clinical application.
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