Development of Prognostic Algorithms to Identify Subjects at High Risk of ESKD in Type 2 Diabetes

开发预后算法来识别 2 型糖尿病 ESKD 高风险受试者

• 批准号: 10491130
• 负责人: Andrzej S Krolewski
• 金额: $ 69.9万
• 依托单位: JOSLIN DIABETES CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-20 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10491130
• 关键词: Age; Albuminuria; Algorithms; Antibodies; Biological Assay; Biological Markers; Characteristics; Chronic Kidney Failure; Chronic Kidney Insufficiency; Clinic; Clinical; Clinical Trials; Cohort Studies; Costs and Benefits; Country; Data; Development; Diabetes Mellitus; Diabetic Nephropathy; Discrimination; End stage renal failure; Follow-Up Studies; Goals; Immunoassay; Impairment; Individual; Intervention; Kidney; Laboratories; Measures; Modeling; Molecular; Non-Insulin-Dependent Diabetes Mellitus; Online Systems; Outcome; Participant; Patient Care; Patients; Performance; Prevalence; Preventive therapy; Prognostic Marker; Proteins; Proteomics; Renal function; Research; Research Personnel; Risk; Sampling; Serum; Serum Proteins; Specificity; Specimen; Techniques; Testing; Time; United States National Institutes of Health; base; biomarker panel; candidate marker; cardiovascular risk factor; clinical care; clinical predictors; cohort; diabetic; diabetic patient; disorder risk; experience; follow-up; high risk; improved; loss of function; multiplex assay; non-diabetic; novel therapeutics; participant enrollment; patient stratification; prediction algorithm; prevent; primary outcome; prognostic algorithm; prognostic model; prognostic performance; prognostic tool; risk prediction; secondary outcome; sex; success

PROJECT SUMMARY/ABSTRACT With the rising prevalence of diabetes in the US and other countries, there is an ongoing research effort to find biomarkers allowing the identification of patients with diabetes at high risk of end stage kidney disease (ESKD). With support from NIH and JDRF, we have identified 21 serum proteins that were significantly associated with increased risk of kidney function loss and ESKD in the Joslin Kidney Study, and have developed an ad hoc OLINK multiplex assay (so called Joslin Kidney Panel [JKP]) to measure these biomarkers. Preliminary data strongly suggest that a subset of the JKP can significantly improve the ability to predict ESKD risk in subjects with type 2 diabetes (T2D) when added to GFR and allbuminuria. In this proposal, we aim to validate these preliminary findings in other settings, in order to develop improved algorithms for ESKD risk prediction. We intend to accomplish these goals using existing data and specimens from individuals with and without T2D from 1. the Chronic Renal Insufficiency Cohort (CRIC) Study; and 2. the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and its follow-up study ACCORDION. Our Specific Aims are: 1: To identify the most informative of the 21 biomarkers in the Joslin Kidney Panel and evaluate their performance, when added to GFR and albuminuria, in predicting ESKD risk among subjects with T2D and chronic kidney disease. We will measure the 21 proteins of the JKP in baseline serum specimens from ~1,500 CRIC participants with T2D, and will use these data together with GFR and albuminuria to develop and internally validate multi-marker prognostic algorithms predicting the risk of ESKD (primary outcome) or the composite of ESKD and/or 50% loss of kidney function (secondary outcome) during 10 years of follow-up. 2: To evaluate the generalizability of findings from CRIC to T2D individuals with a broader spectrum of kidney function. We will assay the JKP in baseline serum specimens from a case- cohort sample of ~2,000 ACCORD/ACCORDION participants and will use these data to investigate the generalizability of the predictive algorithms built in CRIC to diabetic patients with different characteristics. The prognostic models developed in Aim 1 and externally validated in Aim 2 will be used to build a web-based Kidney Risk Calculator for the estimation of the 10-year risk of ESKD in a clinical setting. 3: To evaluate the transferability of the Kidney Risk Calculator from diabetic to non-diabetic kidney disease. We will measure the 21 JKP biomarkers in baseline serum samples from ~1,700 non-diabetic subjects from the CRIC study and will assess the performance of the Kidney Risk Calculator developed in Aim 2 in predicting the risk of ESKD and ESKD/50% kidney function loss in patients with non-diabetic kidney disease. The proposed research has a high likelihood of resulting in the development of improved prognostic tools for the stratification of patients with diabetes according to their risk of progression to ESKD. This would be a great advancement for optimizing patient care and for improving the efficiency of clinical trials of new ESKD-preventing interventions.

项目概要/摘要 随着美国和其他国家糖尿病患病率的上升，人们正在进行研究以寻找 生物标志物可以识别患有终末期肾病高风险的糖尿病患者 （ESKD）。在 NIH 和 JDRF 的支持下，我们鉴定了 21 种血清蛋白，这些蛋白与 Joslin 肾脏研究中与肾功能丧失和 ESKD 风险增加相关，并且 开发了一种特殊的 OLINK 多重检测（所谓的 Joslin Kidney Panel [JKP]）来测量这些 生物标志物。初步数据强烈表明，JKP 的一个子集可以显着提高以下能力： 结合 GFR 和白蛋白尿预测 2 型糖尿病 (T2D) 受试者的 ESKD 风险。在这个 建议，我们的目标是在其他环境中验证这些初步发现，以便开发改进的 ESKD 风险预测算法。我们打算利用现有的数据和样本来实现这些目标 来自患有和未患有 T2D 的个体 1. 慢性肾功能不全队列 (CRIC) 研究；和 2. 控制糖尿病心血管风险的行动（ACCORD）试验及其后续研究 ACCORDION。我们的 具体目标是： 1：确定 Joslin 肾脏面板中 21 种生物标志物中信息最丰富的 并评估其在与 GFR 和白蛋白尿相结合后预测 ESKD 风险的表现 患有 T2D 和慢性肾脏疾病的受试者。我们将测量基线中 JKP 的 21 种蛋白质 来自大约 1,500 名患有 T2D 的 CRIC 参与者的血清样本，并将这些数据与 GFR 和 蛋白尿开发并内部验证预测 ESKD 风险的多标志物预后算法 （主要结果）或 ESKD 和/或 50% 肾功能丧失的复合（次要结果） 10年的追踪。 2：评估 CRIC 的研究结果对具有以下特征的 T2D 个体的普遍性： 更广泛的肾功能。我们将检测来自病例的基线血清样本中的 JKP- 约 2,000 名 ACCORD/ACCORDION 参与者的队列样本，并将使用这些数据来调查 CRIC 中构建的预测算法对具有不同特征的糖尿病患者的通用性。这 在目标 1 中开发并在目标 2 中经过外部验证的预后模型将用于构建基于网络的预测模型 肾脏风险计算器，用于估计临床环境中 ESKD 的 10 年风险。 3：评估 肾脏风险计算器从糖尿病肾病到非糖尿病肾病的可转移性。我们将 测量来自 CRIC 约 1,700 名非糖尿病受试者的基线血清样本中的 21 种 JKP 生物标志物 研究并将评估目标 2 中开发的肾脏风险计算器在预测风险方面的性能 非糖尿病肾病患者的 ESKD 和 ESKD/50% 肾功能丧失。拟议的 研究很有可能开发出改进的分层预后工具 根据糖尿病患者进展为 ESKD 的风险进行评估。这将是一个巨大的进步 优化患者护理并提高新的 ESKD 预防干预措施的临床试验效率。