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

项目摘要 糖尿病足溃疡（DFU）是糖尿病的一种广泛、严重和常见的并发症。糖尿病 截肢与残疾、生活质量的急剧下降、高发病率以及由此产生的 五年内死亡率高达35%与愈合相关的非侵入性可检测生物标志物 DFU的结果对于难以愈合的溃疡的早期靶向进行高级干预至关重要 超标准护理（SOC）治疗，以及及时监测对治疗的反应。初步 在我们的实验室中开发的证据支持循环尿microRNAs（miRNAs）可检测 DFU和其他糖尿病相关并发症的生物标志物;这些miRNA可以被分离， 以技术上稳健和可重现的方式从尿液中定量。利用R61/R33供资机制 作为对RFA-DK-21-001的响应，本项目将利用现有方案中的患者入组， 糖尿病足联盟的基础设施，以开发一个实用的，定量的，非侵入性的，具有成本效益的 包括尿microRNA亚组的预后生物标志物，当在基线时对患者进行评估时， 准确可靠地区分具有SOC修复能力的DFU和不具有SOC修复能力的DFU。 具体而言，在R61/探索性阶段，将采用联合数据简化和预后建模方法 应用于缩小预测DFU临床愈合的前10-20个miRNA参数的确定miRNome 第12周的结果。将评估预测的灵敏度、特异性和准确性， 成功完成R61里程碑后，模型将进入R33/验证阶段， 将询问定制的miRNA子集生物标志物面板，以确定其预测治疗结果的能力。 前瞻性入组了另外100例开放性DFU患者队列。验证阶段的结果将 产生生物标志物，准备提交FDA生物标志物资格批准和随后的直接临床 作为护理点评估实施，以指导临床管理决策并改善伤口 闭合结局，从而降低相关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.