miR-92a as a biomarker of diabetic retinopathy

miR-92a 作为糖尿病视网膜病变的生物标志物

基本信息

批准号：
10677876
负责人：
Ashay D Bhatwadekar
金额：
$ 52.93万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-30 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10677876
关键词：
Animal Model Background Diabetic Retinopathy Biological Markers Biological Models Biometry Blindness Blood Vessels Blood capillaries Bone Marrow Bone Marrow Cells CD14 gene CD34 gene Cell physiology Cells Chimera organism Circulation Clinical Data Defect Development Diabetes Mellitus Diabetic Retinopathy Diagnosis Electroretinography Endothelial Cells Endothelium Exhibits Flow Cytometry Foundations Future Genomics Goals Grant Health Healthcare Human ITGA5 gene Impairment Individual Inflammation Inflammatory Inflammatory Response Injury Interleukin-1 beta Lesion Longitudinal Studies Machine Learning Maps Messenger RNA MicroRNAs Modeling Mus Non-Insulin-Dependent Diabetes Mellitus Pathologic Pathology Patients Peripheral Persons Phenotype Prognosis Proliferating Proto-Oncogene Protein c-kit RNA Reporter Research Research Design Retina Retinal Diseases Rodent Rodent Model Role Sampling Series Severities Solid Surface System Systems Biology Testing Toll-like receptors Up-Regulation Validity of Results Vascular Diseases Visual impairment autocrine biomarker discovery candidate marker cohort db/db mouse diabetic diagnostic tool differential expression endothelial repair feature selection improved inflammatory marker insight machine learning model migration non-diabetic novel marker overexpression paracrine potential biomarker predictive tools prognostic algorithm proliferative diabetic retinopathy repaired reparative capacity retinal damage standard of care transcriptome sequencing transcriptomics vascular injury

项目摘要

Diabetic retinopathy (DR) is a global problem due to an alarming increase in the number of individuals with diabetes. The lack of an early diagnostic tool predicting retinal vascular health is a critical barrier to progress. To this end, we have identified circulating angiogenic cells (CACs) as ideal reporter cells, which are most receptive to changes of diabetic milieu and retinopathy. Our preliminary studies suggest that CACs map a distinct RNA signature. We also found that a miRNA, miR-92a, is downregulated explicitly in CACs with DR, and its overexpression in CACs of people with diabetes decreased pro-inflammatory markers, such as IL-1β and CD14, emphasizing the importance of CACs for biomarker discovery of retinal vascular health. Our preliminary studies using machine learning models could accurately predict DR providing us a stronger rationale for developing this paradigm for our robust study design. Furthermore, using rodent models, we found a decrease in miR-92a in lineage-Sca1+c-kit+ (LSK; mouse equivalent of CACs) parallels with an increase in acellular capillaries, and miR- 92a inhibition in LSKs triggered a stronger inflammatory response. Therefore, this proposal's overarching goal is to study RNA (miRNA and mRNA) and inflammatory signature using a robust sequencing paradigm and differential modeling in individuals with different severities of DR and animal models to gain insights into retinal vascular health. Our central hypothesis is that RNA signature in CACs mirror DR severity, and miR-92a decrease within CACs serves as a candidate biomarker. We propose the following specific aims to test our hypothesis: Aim 1: To assess changes in RNA levels in CACs of patients with different severity of DR and validate miR-92a as a candidate biomarker. Aim 2: Determine whether the miR-92a loss in bone marrow cells is associated with the development of DR in rodents. We anticipate that our proposed studies will identify specific mRNA and miRNA changes of DR severity and validate miR-92a as a novel biomarker for retinal vascular health. Overall, our studies will help improve the standard of care of DR individuals by aiding in diagnosis, prognosis and providing mechanistic insights for future therapies.

糖尿病性视网膜病（DR）是一个全球问题，因为糖尿病。缺乏预测视网膜血管健康的早期诊断工具是进步的关键障碍。到这端，我们已经确定循环的血管生成细胞（CAC）是理想的报道细胞，这是最容易接受的细胞改变糖尿病环境和视网膜病。我们的初步研究表明CACS映射了一个独特的RNA 签名。我们还发现，miRNA miR-92a在带有DR的CAC中明确下调，它糖尿病患者CAC的过表达降低了促炎标记，例如IL-1β和CD14，强调CACS对视网膜血管健康发现生物标志物的重要性。我们的初步研究使用机器学习模型可以准确预测DR，为我们提供更强大的理由来开发这种情况我们强大的研究设计范式。此外，使用啮齿动物模型，我们发现miR-92a的减少 lineage-sca1+ c-kit+（LSK;小鼠相当于CAC）的相似之处，其毛细血管增加，mir- LSK中的92A抑制作用引发了更强的炎症反应。因此，该提议的总体目标是使用可靠的测序范式研究RNA（miRNA和mRNA）和炎症特征 DR和动物模型严重程度不同的个体中的差异建模，以洞悉残留血管健康。我们的中心假设是CACS中的RNA签名Mirror Dr的严重程度和miR-92a CAC中的减少是候选生物标志物。我们提出了以下特定目标，以测试我们的假设：目标1：评估DR和DR不同严重程度患者的RNA水平的变化验证miR-92a作为候选生物标志物。 AIM 2：确定骨髓细胞中的miR-92a是否损失与啮齿动物中DR的发展有关。我们预计我们的拟议研究将确定特定的 mRNA和miRNA DR严重程度的变化并验证miR-92a作为永久性血管健康的新生物标志物。总体而言，我们的研究将通过帮助诊断，预后来帮助提高DR个人的护理标准并为未来疗法提供机械见解。