Circulating urinary microRNAs as systemic biomarkers of healing outcomes in diabetic foot ulcers

项目总结 糖尿病足溃疡(DFU)是一种广泛、严重和常见的糖尿病并发症。糖尿病相关疾病 截肢与残疾、生活质量的急剧下降、高发病率和由此导致的 令人震惊的死亡率在5年内达到35%。与愈合相关的非侵入性可检测生物标志物 DFU的结果对于早期针对难以治愈的溃疡进行高级干预是至关重要的 超越标准护理(SOC)治疗，以及及时监测治疗反应。初步 我们实验室发展的证据支持循环中的尿微RNA(MiRNAs)是可以检测到的 DFU和其他糖尿病相关并发症的生物标志物；这些miRNAs可以分离和 以一种技术稳健和可重复的方式从尿液中定量。利用R61/R33筹资机制 作为对RFA-DK-21-001的响应，该项目将利用现有方案和 糖尿病足联盟的基础设施，以开发实用的、定量的、非侵入性的、具有成本效益的 由尿微RNA亚群组成的预后生物标记物，当在基线水平对患者进行评估时， 准确、可靠地区分有能力使用SOC进行治疗的DFU和没有能力使用SOC的DFU。 具体地说，在R61/探索阶段，数据简化和预测建模的组合方法将是 应用于确定预测DFU临床愈合的前10-20个miRNA参数中的miRNome 第12周的结果。将评估预测的敏感性、特异性和准确性，并与 成功完成R61里程碑模型将进入R33/验证阶段，在该阶段 自定义miRNA子集生物标记物面板将被询问其预测康复结果的能力 前瞻性纳入另外100名开放式DFU患者的队列。验证阶段的结果将 生产生物标记物，准备提交FDA生物标记物资格审批和随后的直接临床 实施作为护理点评估，以指导临床管理决策和改善伤口 关闭结果，从而减少相关的DFU发病率和死亡率。

Project summary Diabetic foot ulcers (DFUs) are a widespread, serious, and common complication of diabetes. Diabetes-related amputations are associated with disability, drastic reduction in quality of life, high morbidity and resulting alarming mortality rate of 35% over 5 years. Non-invasive detectable biomarkers that correlate with healing outcomes of DFU are critically needed for early targeting of hard-to-heal ulcers for advanced interventions beyond standard of care (SOC) therapy, as well as for timely monitoring of response to treatment. Preliminary evidence developed in our laboratory supports circulating urinary microRNAs (miRNAs) as detectable biomarkers for DFUs and other diabetes-associated complications; these miRNAs can be isolated and quantified from urine in a technically robust and reproducible manner. Utilizing an R61/R33 funding mechanism in response to RFA-DK-21-001, this project will capitalize upon patient enrollment in the existing protocols and infrastructure of the Diabetic Foot Consortium to develop a practical, quantitative, non-invasive, cost-effective prognostic biomarker comprised of a urinary microRNA subset that, when assessed in patients at baseline, accurately and reliably differentiates DFUs that have the capacity to heal with SOC from those that do not. Specifically, in R61/ Exploratory phase, a combined data reduction and prognostic modeling approach will be applied to narrow the determine miRNome of top 10-20 miRNA parameters that predict DFU clinical healing outcomes at Week 12. Sensitivity, specificity, and accuracy of predictions will be evaluated and with successful completion of R61 milestones the model will progress to the R33/Validation phase, in which the custom miRNA subset biomarker panel will be interrogated for its ability to predict healing outcomes in a prospectively enrolled cohort of 100 additional patients with open DFUs. Results of the Validation phase will yield a biomarker ready for submission for FDA biomarker qualification approval and subsequent direct clinical implementation as a point-of-care assessment to guide clinical management decisions and improve wound closure outcomes, thereby reducing associated DFU morbidity and mortality.