Abstract
BackgroundIncomplete fracture healing may lead to chronic nonunion; thus, determining fracture healing is the primary issue in the clinical treatment. However, there are no validated early diagnostic biomarkers for assessing chronic nonunion. In this study, bioinformatics analysis combined with an experimental verification strategy was used to identify blood biomarkers for chronic nonunion.MethodsFirst, differentially expressed genes in chronic nonunion were identified by microarray data analysis. Second, Dipsaci Radix (DR), a traditional Chinese medicine for fracture treatment, was used to screen the drug target genes. Third, the drug-disease network was determined, and biomarker genes were obtained. Finally, the potential blood biomarkers were verified by ELISA and qPCR methods.ResultsFifty-five patients with open long bone fractures (39 healed and 16 nonunion) were enrolled in this study, and urgent surgical debridement and the severity of soft tissue injury had a significant effect on the prognosis of fracture. After the systems pharmacology analysis, six genes, including QPCT, CA1, LDHB, MMP9, UGCG, and HCAR2, were chosen for experimental validation. We found that all six genes in peripheral blood mononuclear cells (PBMCs) and serum were differentially expressed after injury, and five genes (QPCT, CA1, MMP9, UGCG, and HCAR2) were significantly lower in nonunion patients. Further, CA1, MMP9, and QPCT were markedly increased after DR treatment.ConclusionCA1, MMP9, and QPCT are biomarkers of nonunion patients and DR treatment targets. However, HCAR2 and UGCG are biomarkers of nonunion patients but not DR treatment targets. Therefore, our findings may provide valuable information for nonunion diagnosis and DR treatment.Trial registrationISRCTN, ISRCTN13271153. Registered 05 April 2020—Retrospectively registered.
Highlights
Fracture healing is a complex process and is dependent on multiple factors [1]
Most fractures were the result of a traffic accident, and 13 of the nonunion fractures were caused by traffic injury, compared to 27 of the healed fractures (p > 0.05)
We found that five active ingredients of Dipsaci Radix (DR) (Japonine, Gentisin, Gauloside A, Sylvestroside III, and 3,5-Di-O-caffeoylquinic acid) and six target genes (QPCT, Carbonic anhydrase I (CA1), LDHB, MMP9, UDP-glucose ceramide glycosyltransferase (UGCG), and Hydroxycarboxylic acid receptor 2 (HCAR2)) were related to nonunion
Summary
Fracture healing is a complex process and is dependent on multiple factors [1]. Limited fracture healing can occur in 5–10% of fracture cases [2], resulting in chronic nonunion and functional disability, which can have a devastating impact on the patient’s quality of life [3].The determination of nonunion is essential for fracture diagnosis and subsequent treatment, but there is a lack of objective tools to assess fracture healing, making nonunion as an uncertain outcome [4]. Limited fracture healing can occur in 5–10% of fracture cases [2], resulting in chronic nonunion and functional disability, which can have a devastating impact on the patient’s quality of life [3]. Establishing a new diagnosis method is vital for chronic nonunion diagnosis and treatment. The circulating biomarkers of bone fracture healing are gaining popularity as possible early predictors of chronic nonunion [5]. There are currently no valid biomarkers for chronic nonunion diagnosis in the blood. Incomplete fracture healing may lead to chronic nonunion; determining fracture healing is the primary issue in the clinical treatment. There are no validated early diagnostic biomarkers for assessing chronic nonunion. Bioinformatics analysis combined with an experimental verification strategy was used to identify blood biomarkers for chronic nonunion
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