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: 10525120
• 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/10525120
• 关键词: Accounting; Adolescence; Adult; Age; Algorithms; American Heart Association; Americas; 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; Sampling; Serum; Societies; Testing; Trans-Omics for Precision Medicine; Ventricular; Work; base; 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.

总结 2型糖尿病（T2 D）是心力衰竭（HF）的重要风险因素，与传统的心力衰竭风险因素无关。 心血管疾病然而，降低血红蛋白A1 c水平对降低HF风险几乎没有影响， T2 D患者这些发现强调了基本预防策略对遏制T2 D相关疾病的重要性。 HF和提示独立于高血糖的病理生理机制可能与这些条件有关。 因此，更好地预测T2 D和阐明T2 D与HF相关的生物学途径的分子表型是 这是非常需要的，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条件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（PRS），结合了数百万个基因的贡献， 变体显示出根据T2 D状态对个体进行分类的希望。然而，其价值 未评估从儿童期开始纵向预测T2 D发展的可能性， 仅限于欧洲人口。我们假设PRS是通过大规模的多祖先研究开发的， 基因组学数据集将具有最佳的风险预测准确性，并适用于祖先多样化的样本。 我们进一步假设T2 D遗传风险高的个体的血清代谢组含有 反映糖尿病心肌病机制的内源性分子，一种重要的T2 D相关HF 内表型因此，本拟议研究的目的是开发PRS，以预测T2 D风险， 早期生活到中年，并确定糖尿病诱导的HF的潜在机制。我们的PRS将由 结合来自140多万参与者的T2 D多种族GWAS的汇总统计数据， 连锁不平衡数据来自美国成年人的全国代表性样本（Aim 1a）。在PRS之后 使用来自约60万多血统参与者的个体水平基因组数据进行测试，我们将把我们的PRS应用于 博加卢萨心脏研究（BHS; n= 1，808）的birthday队列和年轻人的冠状动脉风险发展 成年人（n= 2，341），在整个生命周期内测量血糖状态和降糖药物。 利用这些独特的资源，我们将是第一个评估基因组信息的临床效用， 儿童和成年早期T2 D的预测（目标1b）。最后，我们将执行中介分析， 确定循环代谢物和代谢途径，将遗传上升高的T2 D风险与亚临床 利用10，929 BHS和精准医学跨组学的组合样本进行HF测量 项目参与者（目标2）。这项创新的多组学研究可能有助于开发有针对性的原始基因。 通过提供基因组算法来识别早期T2 D高风险个体， 在临床危险因素出现之前。此外，我们的发现可能揭示新的分子机制， 糖尿病心肌病，帮助指导药物开发，以治疗这种情况。