Genetic determinants of fracture non-union: A systematic review from the literature

Bioinformatics Analysis and Experimental Validation of Differential Genes and Pathways in Bone Nonunions

Non-union fractures pose a significant clinical challenge, often leading to prolonged pain and disability. Understanding the molecular mechanisms underlying non-union fractures is crucial for developing effective therapeutic interventions. This study integrates bioinformatics analysis and experimental validation to unravel key genes and pathways associated with non-union fractures. We identified differentially expressed genes (DEGs) between non-union and fracture healing tissues using bioinformatics techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological processes and pathways involved. Common DEGs were identified, and a protein-protein interaction (PPI) network was constructed. Fibronectin-1 (FN1), Thrombospondin-1 (THBS1), and Biglycan (BGN) were pinpointed as critical target genes for non-union fracture treatment. Experimental validation involved alkaline phosphatase (ALP) and Alizarin Red staining to confirm osteogenic differentiation. Our analysis revealed significant alterations in pathways related to cell behavior, tissue regeneration, wound healing, infection, and immune responses in non-union fracture tissues. FN1, THBS1, and BGN were identified as key genes, with their upregulation indicating potential disruptions in the bone remodeling process. Experimental validation confirmed the induction of osteogenic differentiation. The study provides comprehensive insights into the molecular mechanisms of non-union fractures, emphasizing the pivotal roles of FN1, THBS1, and BGN in extracellular matrix dynamics and bone regeneration. The findings highlight potential therapeutic targets and pathways for further investigation. Future research should explore interactions between these genes, validate results using in vivo fracture models, and develop tailored treatment strategies for non-union fractures, promising significant advances in clinical management.

Genetic Influence of Fracture Nonunion (FNU): A Systematic Review

Purpose

Nonunion of fractures occurs in about 15% of all fractures causing repeated surgical interference and prolonged morbidity. We performed this systematic review to assess genes and polymorphisms influencing fractures' nonunion (FNU).

Methods

We searched between 2000 and July 2022 in PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews, Genome Wide Association Studies (GWAS) Catalog, and the Science Citation Index, with the keywords nonunion of fractures, genetic influence, and GWAS. The exclusion criteria were review articles and correspondence. The data were retrieved to determine the number of studies, genes, and polymorphisms and the total number of subjects screened.

Results

A total of 79 studies were reported on nonunion of fractures and genetic influence. After the inclusion and exclusion criteria, ten studies with 4402 patients' data were analyzed. Nine studies were case-controlled, and 1 GWAS. It was identified that patients with polymorphisms in the genes ANXA3, BMP2, CALY, CYR61, FGFR1, IL1β, NOG, NOS2, PDGF gene, and TACR1 are prone to develop a nonunion of fractures.

Conclusion

We believe that for patients who develop an early nonunion of fractures, a genetic study should be conducted for single nucleotide polymorphism (SNP) and genes so that alternative and more aggressive treatment can be performed to heal fractures without prolonged morbidity.

Predicting fracture healing with blood biomarkers: the potential to assess patient risk of fracture nonunion

Fracture non-union is a significant orthopaedic problem affecting a substantial number of patients yearly. Treatment of nonunions is devastating to patients and costly to the healthcare system. Unfortunately, the diagnosis of non-union is typically made in a reactionary fashion by an orthopaedic surgeon based on clinical assessment and radiographic features several months into treatment. For this reason, investigators have been trying to develop prediction algorithms; however, these have relied on population-based approaches and lack the predictive capability necessary to make individual treatment decisions. There is also a growing body of literature focussed on identifying blood biomarkers that are associated with non-union. This review describes the research that has been done in this area. Further studies of patient-centered, precision medicine approaches will likely improve fracture non-union diagnostic/prognostic capabilities.