Application of a novel polygenic risk score to the study of diabetic cardiomyopathy in diverse populations

新型多基因风险评分在不同人群糖尿病心肌病研究中的应用

• 批准号: 10669753
• 负责人: Changwei Li
• 金额: $ 12.2万
• 依托单位: TULANE UNIVERSITY OF LOUISIANA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10669753
• 关键词: Accounting; Adolescence; Adult; Age; Algorithms; American Heart Association; Articulation; Behavior; Biological; Black race; Cardiovascular Diseases; Caring; Child; Childhood; Childhood diabetes; Classification; Clinical; Computational algorithm; Coronary Artery Risk Development in Young Adults Study; Data; Data Set; Development; Diabetes Mellitus; Early identification; European; Functional disorder; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genomics; Glucose; Glycosylated hemoglobin A; Health and Retirement Study; Heart; Heart failure; Hispanic Populations; Hyperglycemia; Incidence; Individual; Insulin; Intervention; Left; Life; Link; Linkage Disequilibrium; Longevity; Measures; Mediating; Mediation; Metabolic Pathway; Modeling; Molecular; Molecular Target; Non-Insulin-Dependent Diabetes Mellitus; Participant; Pathologic; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacologic Substance; Phenotype; Population; Population Heterogeneity; Predisposition; Prevention; Prevention strategy; Public Health; Recommendation; Reporting; Research; Resources; Risk; Risk Factors; Risk Reduction; Sampling; Serum; Societies; Testing; Trans-Omics for Precision Medicine; Ventricular; Work; biobank; biracial; cardiovascular risk factor; clinical risk; clinically significant; cohort; diabetes risk; diabetic cardiomyopathy; drug development; emerging adult; endophenotype; fasting plasma glucose; follow-up; genetic testing; genetic variant; genome wide association study; genome-wide; genomic data; genomic profiles; healthy lifestyle; high risk; innovation; lifestyle intervention; metabolome; middle age; molecular drug target; molecular phenotype; multi-ethnic; multiple omics; novel; personalized intervention; polygenic risk score; prevent; programs; risk prediction; statistics; young adult

Summary Type 2 diabetes (T2D) is an important risk factor for heart failure (HF) independent of traditional risk factors for cardiovascular disease. However, lowering hemoglobin A1c levels has little effect on reducing HF risk among T2D patients. These findings highlight the importance of primordial prevention strategies to curb T2D-related HF and suggest that pathophysiologic mechanisms independent of hyperglycemia may link these conditions. Hence, molecular phenotyping to better predict T2D and articulate biological pathways relating T2D to HF are critically needed and in line with recommendations by the American Heart Association and Heart Failure Society of America urging further research into the shared genomic susceptibility of these conditions. Recently, a novel genome-wide polygenic risk score (PRS) that combined contributions of millions of genetic variants showed promise for classifying individuals according to T2D status. However, its value for longitudinally predicting the development of T2D from childhood was not assessed and its generalizability was limited to European populations. We hypothesize that a PRS developed using large-scale multi-ancestry genomics datasets will have optimal risk prediction accuracy and be applicable to ancestrally diverse samples. We further hypothesize that the serum metabolomes of individuals with high genetic risk for T2D contain endogenous molecules reflecting mechanisms of diabetic cardiomyopathy, an important T2D-related HF endophenotype. Therefore, the objectives of this proposed study are to develop a PRS to predict T2D risk from early life to midlife and to identify mechanisms underlying diabetes-induced HF. Our PRS will be generated by combining summary statistics from a multi-ethnic GWAS of T2D among more than 1.4 million participants with linkage disequilibrium data from a nationally representative sample of US adults (Aim 1a). Following PRS testing using individual level genomic data from ~600,000 multi-ancestry participants, we will apply our PRS to biracial cohorts of the Bogalusa Heart Study (BHS; n=1,808) and Coronary Artery Risk Development in Young Adults (n=2,341) with measures of glycemic status and glucose lowering medication across the lifespan. Leveraging these unique resources, we will be the first to evaluate the clinical utility of genomic information in the prediction of T2D in childhood and early adulthood (Aim 1b). Finally, we will perform mediation analyses to identify circulating metabolites and metabolic pathways linking genetically elevated T2D risk to subclinical measures of HF leveraging combined sample of 10,929 BHS and the Trans-omics for Precision Medicine program participants (Aim 2). This innovative multi-omics study will likely aid in developing targeted primordial interventions by providing a genomic algorithm to identify individuals at high risk for T2D at an early age and prior to the manifestation of clinical risk factors. Further, our findings may reveal novel molecular mechanisms for diabetic cardiomyopathy, helping to guide pharmaceutical development to treat this condition.

摘要 2型糖尿病(T2D)是心力衰竭(HF)的重要危险因素，独立于传统的 心血管疾病。然而，降低血红蛋白A1c水平对降低心力衰竭风险几乎没有影响 T2D患者。这些发现强调了原始预防策略的重要性，以遏制与T2D相关的 心衰，并提示独立于高血糖的病理生理机制可能与这些情况有关。 因此，更好地预测T2D和阐明T2D与HF相关的生物学途径的分子表型是 急需并符合美国心脏协会和心力衰竭协会的建议 美国社会敦促进一步研究这些疾病的共同基因组易感性。 最近，一种新的全基因组多基因风险评分(PR)结合了数百万个基因的贡献 变体显示了根据T2D状态对个体进行分类的前景。然而，它的价值在于 没有对儿童T2D发展的纵向预测进行评估，其概括性是 仅限于欧洲人口。我们假设一个PR使用大规模的多祖先发展而来 基因组学数据集将具有最佳的风险预测准确性，并适用于祖先不同的样本。 我们进一步假设具有T2D高遗传风险的个体的血清代谢体包含 反映糖尿病心肌病机制的内源性分子--一种重要的T2D相关心衰 内表型。因此，这项拟议的研究的目标是开发一种预测T2D风险的PRS 从早年到中年，并确定糖尿病引起心力衰竭的潜在机制。我们的计划将由以下人员生成 结合T2D的多种族GWA对140多万名参与者的汇总统计数据， 来自具有全国代表性的美国成年人样本的连锁不平衡数据(目标1a)。跟随prs 使用来自约600,000名多血统参与者的个人水平基因组数据进行测试，我们将把我们的PR应用于 博加卢萨心脏研究(BHS；n=1,808)的双族队列与年轻人的冠状动脉风险发展 成年人(n=2,341)，在整个生命周期内接受血糖状况和降糖药物的测量。 利用这些独特的资源，我们将第一个评估基因组信息在 儿童和成年早期T2D的预测(目标1b)。最后，我们将执行调解分析，以 确定循环代谢物和代谢途径，将遗传升高的T2D风险与亚临床联系起来 精准医学利用10,929例BHS和易位组学联合样本的措施 方案参与者(目标2)。这一创新的多组学研究可能有助于开发有针对性的原始数据 通过提供基因组算法在T2D的早期和 临床危险因素出现前的表现。此外，我们的发现可能揭示新的分子机制。 对于糖尿病心肌病，帮助指导治疗这种情况的药物开发。