Novel Biomarkers of Chronic Kidney Disease in Children

项目摘要。候选人。我是耶鲁大学的一名儿科肾病专家，致力于改善预后 适用于患有慢性肾病(CKD)的儿童。我申请的目标是获得有指导的研究培训 建立儿科慢性肾脏病进展的生物标志物增强风险预测模型，以供将来临床使用。 审判。这项研究将建立在我之前的训练基础上，那次训练的重点是急性肾损伤后慢性肾脏病的风险。 以及使用生物标记物来预测儿童的肾脏结果。这份建议书将为我提供实践经验 高级统计学、生物标记物方法学和儿科慢性肾脏病的学习和正规教学课程。这就做 还将重点放在培养建立有效合作所需的专业技能上， 科学写作，并获得资金支持我的研究。为了完成我所说的计划，我得到了 我非常合格的主要导师(希拉克·帕里克博士和苏珊·弗思博士)和指导委员会(博士。 林海群、尤金·夏皮罗和普拉萨德·德瓦拉扬)在肾脏损伤领域拥有跨学科的专业知识 生物标记物、转化研究、生物统计学和儿科慢性肾脏病。这种多学科的指导以及 Parikh博士的应用翻译研究项目的高技能培训环境将使我能够 进行我提议的研究，并建立一个独立资助的研究计划。 项目。儿童慢性肾脏病的进展导致终末期肾病(ESRD)，这与 死亡率是普通儿科人口的30-150倍。传统的生物标志物，血清 肌酐和蛋白尿在临床试验中被用来预测慢性肾脏病的进展，尽管两者相关。 随着慢性肾脏病的进展和对干预措施的反应不佳。有许多候选疗法 对于CKD，但随着对血清肌酐和蛋白尿的持续依赖，临床试验可能会继续失败。 儿童慢性肾脏病生物标志物领域是一个非常有前途的研究领域，只有少量的 到目前为止投入的资源。预测CKD的进展将使临床医生能够更好地跟踪、转诊 移植，并为家庭提供更好的指导。更重要的是，生物标志物和风险的最佳组合 在生物标志物指导的临床试验中，预测模型可以替代尿蛋白和血肌酐。我们计划 从基线开始测量尿液和血清中肾脏损伤、炎症、修复和纤维化的生物标志物 在CKID队列中登记的869名CKD儿童样本，并测定其 与纵向测量的GFR下降和入射的ESRD的关系。生物标志物的最佳组合 另外，2/3的CKiD患者的临床变量将产生一个预测CKD进展的风险预测模型。 我们的风险预测模型将在三分之一的CKiD患者中对纵向GFR下降进行验证，并 在AKI队列中对124名儿童进行外部评估、系列评估和后续后遗症。 开发CKD进展的风险预测模型可以改变范式，改变临床护理 患有CKD的儿童。

Project Summary. Candidate. I am a pediatric nephrologist at Yale University dedicated to improving outcomes for children with chronic kidney disease (CKD). The goal of my application is to obtain mentored research training to develop a biomarker-augmented risk prediction model of pediatric CKD progression for use in future clinical trials. This research will build upon my prior training, which focused on the risk of CKD after acute kidney injury and the use of biomarkers to predict renal outcomes in children. This proposal will provide me with hands-on learning and formal didactic coursework in advanced statistics, biomarker methodology, and pediatric CKD. I will also intensely focus on developing the professional skills necessary for establishing effective collaborations, scientific writing, and obtaining funding to support my research. To accomplish my stated plan, I have the support of my highly qualified primary co-mentors (Drs. Chirag Parikh and Susan Furth) and mentoring committee (Drs. Haiqun Lin, Eugene Shapiro, and Prasad Devarajan) with interdisciplinary expertise in the fields of kidney injury biomarkers, translational research, biostatistics, and pediatric CKD. This multidisciplinary mentorship along with the highly skilled training environment at Dr. Parikh's, Program of Applied Translational Research will allow me to conduct my proposed research and establish an independently funded research program. Project. Progression of CKD in children leads to end stage renal disease (ESRD), which is associated with mortality rates 30-150 times higher than the general pediatric population. The traditional biomarkers, serum creatinine and proteinuria, are used to predict progression of CKD in clinical trials even though both correlate poorly with the progression of CKD and the response to interventions. There are numerous candidate therapies for CKD, but with a continued reliance on serum creatinine and proteinuria, clinical trials will likely continue to fail. The field of CKD biomarkers in children is a very promising area of research with a small amount of resources invested to date. Predicting progression of CKD will allow clinicians to better time follow-up, referral for transplant, and provide better guidance to families. More importantly, an optimal panel of biomarkers and risk prediction model can replace proteinuria and serum creatinine in biomarker guided clinical trials. We plan to measure urine and serum biomarkers of kidney injury, inflammation, repair, and fibrosis from the baseline samples of the 869 children with CKD enrolled in the CKD in Children (CKiD) cohort and determine their relationship with longitudinal measured GFR decline and incident ESRD. The optimal combination of biomarkers plus clinical variables from 2/3rd's of the CKiD patients will yield a risk prediction model to predict CKD progression. Our risk prediction model will be validated for longitudinal GFR decline, internally in 1/3rd of the CKiD patients, and externally in the 124 children of the Assessment, Serial Evaluation, and Subsequent Sequelae in AKI cohort. Developing a risk prediction model of CKD progression can be paradigm changing, transforming clinical care for children with CKD.