Diabetic Retinopathy: Genetics and Neurodegeneration (MSN246458)

糖尿病视网膜病变：遗传学和神经变性 (MSN246458)

• 批准号: 10320692
• 负责人: Roomasa Channa
• 金额: $ 24.88万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10320692
• 关键词: Address; Adult; Affect; Algorithmic Analysis; American; Appearance; Artificial Intelligence; Bioinformatics; Blindness; Blood Vessels; Clinical; Clinical Management; Clinical Research; Clinical Trials; Computational algorithm; Data; Data Analyses; Data Set; Development; Development Plans; Diabetes Mellitus; Diabetic Retinopathy; Disease; Disease Pathway; Environment; Family; Fundus; Future; Ganglion Cell Layer; Genes; Genetic; Genetic Predisposition to Disease; Genomics; Goals; Hyperglycemia; Image; Image Analysis; Intervention; K-Series Research Career Programs; Knowledge; Lead; Measurement; Medical center; Mentors; Mentorship; Methods; Molecular; Nerve Degeneration; Nerve Fibers; Optical Coherence Tomography; Outcome; Participant; Pathway interactions; Patients; Phenotype; Predisposition; Prevalence; Prevention; Process; Publications; Race; Regression Analysis; Reporting; Research; Retina; Retinal Diseases; Retinal Ganglion Cells; Risk Factors; Role; Sample Size; Scanning; Scientist; Specialist; Techniques; Testing; Thick; Time; Training; Translating; Translational Research; Vascular Endothelial Growth Factors; Vision; Visual; Work; aged; base; biobank; career development; clinical practice; cohort; collaborative environment; diabetes management; diabetic; disability; experience; family genetics; fiber cell; genetic risk factor; genome wide association study; genomic data; illness length; imaging modality; improved; large datasets; macular edema; nerve damage; novel; novel therapeutics; population based; prevent; retinal imaging; screening; skills; standard of care

PROJECT SUMMARY/ABSTRACT Diabetes mellitus (DM) is the leading cause of vision loss among working aged adults. Its prevalence is increasing and despite the strides in knowledge and treatments, our understanding of the pathways leading to vision loss in DM remains limited. Hyperglycemia and duration of DM contribute to but do not fully explain the predisposition to develop diabetic retinal diseases. Given the predisposition for diabetic retinal diseases to cluster in families, genetic risk factors are thought to be important but none has so far been definitively implicated. Furthermore, data from small studies suggest that there are more phenotypes of diabetic retinal disease than are currently recognized in clinical practice. Diabetic retinal disease has traditionally been considered primarily a vascular process: diabetic retinopathy (DR) and diabetic macular edema (DME) are the main clinical manifestations. With improved imaging modalities and image analysis algorithms, there has been increasing recognition of a new clinical manifestation of diabetic retinal disease, diabetic retinal neurodegeneration (DRN). This is visible as alterations in thickness of retinal nerve fiber (RNFL) and/or ganglion cell layer (GCL) on optical coherence tomography (OCT) images. To date, DRN is poorly understood, and its role in clinical management of patients with DM has not been established. However, if retinal neurodegeneration occurs and is progressive, it can lead to profound visual difficulties for patients with DM. DRN may account for previously unexplained poor visual outcomes among patients with diabetic retinal disease despite standard of care treatment. Dr. Channa is a retina specialist, with prior research experience in retinal imaging and clinical trials of novel treatments for DME. In this K23 career development award she proposes to use a nationally representative dataset, the UK Biobank cohort to: 1) improve our understanding of DRN by determining RNFL and GCL thickness, using OCT imaging, in participants with DM (who have no DR or DME) compared to those who do not have DM 2) determine genetic factors associated with DR, DME and DRN. Dr. Channa proposes a career development plan, which includes mentorship, coursework, publications and clinical time. This will situate her as an independent clinician-scientist with expertise in translational research employing bioinformatics and computational skills in genomics and retinal image analysis to elucidate pathways of vision loss among patients with DM, ultimately leading to development of novel therapies. Her research work and career development will take place in the academic and collaborative environment of the largest medical center in the world, where she has institutional support and mentorship to develop as an independent clinician-scientist.

项目总结/摘要 糖尿病（DM）是工作年龄的成年人中视力丧失的主要原因。其患病率 尽管在知识和治疗方面取得了长足的进步，但我们对导致疾病的途径的理解 糖尿病患者的视力丧失仍然有限。高血压和DM持续时间有助于但不能完全解释 易患糖尿病视网膜疾病。鉴于糖尿病视网膜疾病的易感性， 在家庭中聚集，遗传风险因素被认为是重要的，但迄今为止还没有明确的 牵连此外，来自小型研究的数据表明，糖尿病视网膜病变的表型更多， 比目前在临床实践中认识到的疾病。糖尿病视网膜疾病传统上是 糖尿病视网膜病变（DR）和糖尿病黄斑水肿（DME）是糖尿病视网膜病变的主要表现。 主要临床表现。利用改进的成像模态和图像分析算法， 糖尿病视网膜病变是糖尿病视网膜病变的一种新的临床表现， 神经变性（DRN）。这可以作为视网膜神经纤维（RNFL）厚度和/或 光学相干断层扫描（OCT）图像上的神经节细胞层（GCL）。到目前为止，对DRN的了解很少， 其在糖尿病患者临床管理中的作用尚未确定。如果视网膜 当神经退行性变发生并且是进行性的时，其可导致患有DM的患者的严重视觉困难。 DRN可能是糖尿病视网膜病变患者先前无法解释的视力不良结果的原因。 尽管有标准的护理治疗。Channa博士是一位视网膜专家，在以下领域有过研究经验： 视网膜成像和DME新疗法的临床试验。在K23职业发展奖中， 建议使用具有全国代表性的数据集，英国生物银行队列：1）提高我们对 通过使用OCT成像确定RNFL和GCL厚度，在DM参与者（无DR）中确定DRN 或DME）与没有DM的人相比2）确定与DR、DME和 DRN。Channa博士提出了一个职业发展计划，其中包括指导，课程，出版物 临床时间这将使她成为一名独立的临床医生-科学家，具有翻译方面的专业知识。 利用基因组学和视网膜图像分析中的生物信息学和计算技能来阐明 糖尿病患者的视力丧失途径，最终导致新的治疗方法的发展。她 研究工作和职业发展将在学术和协作环境中进行， 世界上最大的医疗中心，在那里她得到了机构的支持和指导， 独立临床科学家