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Predictive utility of polygenic risk scores for chronic kidney disease.

Predictive utility of polygenic risk scores for chronic kidney disease.
慢性肾脏病多基因风险评分的预测效用。
批准号:
10376794
负责人:
Atlas Khan
金额:
$16.92万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-07-01 至 2026-03-31

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中文摘要
翻译
摘要 在这份为期5年的K25职业发展奖的申请中,我提出了一个指导性的研究和职业生涯 发展计划,为未来作为肾脏疾病独立研究者的职业生涯奠定基础。 该研究项目的目标是开发和测试慢性肾脏病(CKD)的多基因风险评分 及其肾小球亚型,如免疫球蛋白A肾病(IgAN)、膜性肾病(MN) 和局灶节段性肾小球硬化(FSGS)。虽然传统上遗传学研究主要集中在 关于与疾病高风险相关的罕见遗传变异,越来越多的证据表明, 对常见慢性病的风险有实质性的多基因贡献,这些发现可能 对公众健康造成重大影响。最近的研究表明,多基因风险最高的1-5%的个体 得分分布的疾病风险相当于目前临床测试的许多罕见变异,包括 导致疾病的突变,例如肥胖症、乳腺癌、结肠癌、炎症性肠病, 心房颤动或冠状动脉疾病。例如,BMI的全基因组多基因风险评分已被 开发并验证了使用210万种常见遗传变异来准确预测 在生命早期严重肥胖。该提案将采用类似的方法来评估多基因对CKD的贡献 及其各种亚型,其中新的强大的全基因组关联研究(GWAS)数据集 目前出现在我们的实验室(我是大多数研究的合著者,贡献了来自eMERGE的数据, UK biobank consortia)。在导师的指导下,我起草了一份5年职业发展计划, 包括肾脏疾病及其亚型的临床领域知识的培训,包括熟悉 常见肾脏疾病的发病机制模型和多基因评分在肾脏疾病中的潜在临床应用 肾脏学(主要导师:Dr. Krzysztof Kiryluk),生物医学信息学(共同导师:Dr. Chunhua Weng)和 用于分析多维遗传和表型数据的新的统计遗传学方法(尤利阿纳博士 Ionita-Laza)。在获奖的最后两年,我将申请R 01资助并过渡到独立。的 拟议的活动将准备我进行以病人为导向的生物医学研究,以发现新的遗传 CKD的危险因素和CKD及其主要亚型的早期诊断策略。
英文摘要
ABSTRACT In this application for a 5-year K25 Career Development Award, I propose a mentored research and career development plan providing a foundation for a future career as an independent investigator in kidney disease. The goal of this research project is to develop and test polygenic risk scores for chronic kidney disease (CKD) and its glomerular subtypes, such as immunoglobulin A nephropathy (IgAN), membranous nephropathy (MN) and focal segmental glomerulosclerosis (FSGS). Although traditionally genetic studies have been focused largely on rare genetic variants associated with a high risk of disease, there is mounting evidence that common variants have substantial polygenic contributions to the risk for common chronic diseases and these findings may have a significant public health impact. Recent studies demonstrate that individuals in the top 1-5% of polygenic risk score distribution have disease risk equivalent to many of the rare variants currently tested for clinically, including mutations that are causal for diseases such as obesity, breast cancer, colon cancer, inflammatory bowel disease, atrial fibrillation, or coronary artery disease. For example, a genome-wide polygenic risk score for BMI has been developed and validated that uses 2.1 million common genetic variants to accurately predict the development of severe obesity early in life. This proposal will apply similar methods to evaluate polygenic contributions to CKD and its various subtypes for which new powerful genome-wide association studies (GWAS) datasets are presently emerging from our lab (I am co-author of most of the studies by contributing data from eMERGE and UK biobank consortia). With guidance from my mentors, I have drafted a 5-year career development plan that includes training in clinical domain knowledge of kidney disease and its subtypes including familiarity with the pathogenesis models for common kidney disorders and potential clinical applications of polygenic scores in nephrology (primary-mentor: Dr. Krzysztof Kiryluk), biomedical informatics (co-mentor: Dr. Chunhua Weng) and novel statistical genetics methods for the analysis of multidimensional genetic and phenotypic data (Dr. Iuliana Ionita-Laza). In the last two years of the award I will apply for R01 funding and transition to independence. The proposed activities will prepare me to conduct patient-oriented and biomedical research to discover novel genetic risk factors for CKD and early diagnosis strategies for CKD and its major subtypes.
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Predictive utility of polygenic risk scores for chronic kidney disease.
Predictive utility of polygenic risk scores for chronic kidney disease.
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