Metabolomic Quantitative Trait Locus (mQTL) Genetic Mapping in Human CVD

人类 CVD 代谢组学数量性状位点 (mQTL) 遗传图谱

• 批准号: 8470689
• 负责人: Svati H. Shah
• 金额: $ 55.25万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8470689
• 关键词: 9p21; Angiography; Architecture; Biological; Branched-Chain Amino Acids; Candidate Disease Gene; Cardiovascular Diseases; Cardiovascular system; Catabolism; Cause of Death; Chromosome Mapping; Chromosomes; Clinical Research; Comorbidity; Complex; Computer Simulation; Coronary; Coronary Arteriosclerosis; DNA Resequencing; Data; Data Set; Detection; Developing Countries; Diabetes Mellitus; Discipline; Disease; Disease susceptibility; Enrollment; Epidemic; Evaluation; Event; Family; Foundations; Functional disorder; Future; Genes; Genetic; Genetic Screening; Genotype; Goals; Heritability; Heterogeneity; Human; Inborn Errors of Metabolism; Individual; Maps; Measurement; Mediating; Metabolic; Metabolic Pathway; Metabolism; Methods; Mitochondria; Molecular; Nature; Obesity; Pathway interactions; Phenotype; Plasma; Population; Preventive; Principal Component Analysis; Public Health; Quantitative Trait Loci; Reporting; Research Design; Research Personnel; Resolution; Risk; Risk Factors; Role; SNP genotyping; Susceptibility Gene; Technology; Testing; Training; Validation; Variant; analytical tool; base; biobank; clinical phenotype; cohort; disease diagnosis; disorder risk; early onset; fatty acid oxidation; genetic variant; genome wide association study; genome-wide; insight; metabolomics; novel; novel strategies; peripheral blood; response; small molecule; tool; trait; urea cycle

Coronary artery disease (CAD) is the leading cause of the death in the US and, in concert with the epidemic of obesity and diabetes, is becoming the leading cause of death in many developing countries. The genetic predilection of CAD is well-established. Despite this, the genetics of CAD remain largely unknown. Given the complex nature of CAD, evaluation of the disease with more comprehensive analytical tools may provide needed insights into biological pathways converging on this heterogeneous phenotype. Many of the commonly accepted risk factors for CAD are metabolic. Metabolomics, the study of small-molecule metabolites, is an emerging discipline that may be particularly useful for understanding metabolic imbalances and for diagnosis of disease. Using these granular metabolic phenotypes, which reflect biological responses to exogenous and endogenous inputs, in a genetic screen may provide more a more powerful method for uncovering molecular mechanisms of cardiovascular disease. We have previously shown a novel finding of high heritabilities of metabolomic profiles in families burdened with early-onset CAD, suggesting a genetic basis to these metabolite profiles. Furthermore, we have shown that these metabolomic profiles strongly, and independently, discriminate individuals with CAD from those without, and predict risk of future cardiovascular events. Therefore, we propose to perform metabolic quantitative trait loci (mQTL) mapping in a large, well-phenotyped cardiovascular cohort using genomewide association (GWAS) and targeted, quantitative metabolic profiling, with the goal of elucidating the underlying genetic architecture of metabolic traits predisposing to CAD. We hypothesize that metabolomic profiling in this cohort will identify novel phenotypes underlying CAD pathophysiology, and that mQTL mapping will identify novel genes for CAD risk mediated through metabolic pathways. The specific aims of this proposal are to: (1) perform targeted, quantitative metabolic profiling in a well-phenotyped cardiovascular cohort of 1000 individuals; (2) perform genomewide association (GWAS) in the same cardiovascular cohort of 1000 individuals and perform genetic mapping to identify metabolic quantitative trait loci (mQTLs); (3) replicate GWAS findings in silico and in independent familial and nonfamilial cardiovascular cohorts; and (4) resequence candidate loci identified from Aims 2 and 3 to identify novel genetic variants. This proposal has the potential for having a significant impact on a major public health problem that has a very strong heritable component that is poorly

冠状动脉疾病（CAD）是美国死亡的主要原因，并与流行病一起 肥胖症和糖尿病已成为许多发展中国家死亡的主要原因。遗传 CAD的偏爱是完善的。尽管如此，CAD的遗传学仍然在很大程度上未知。鉴于 CAD的复杂性质，使用更全面的分析工具对疾病的评估可能会提供 需要深入了解这种异质表型的生物学途径。许多 CAD通常接受的危险因素是代谢。代谢组学，小分子的研究 代谢物，是一门新兴学科，可能对于理解代谢失衡特别有用 并用于诊断疾病。使用这些颗粒状代谢表型，反映生物学反应 对于外源性和内源性输入，在遗传屏幕中可能会提供更多强大的方法 发现心血管疾病的分子机制。 我们以前已经显示了家庭中代谢组概况高遗产的新发现 负担早期发作的CAD，这表明了这些代谢物谱的遗传基础。此外，我们 已经表明，这些代谢组谱强烈，并独立地区分CAD的个体 从没有的人那里，并预测未来心血管事件的风险。因此，我们建议执行 代谢定量性状基因座（MQTL）映射在大型，良好的心血管群中 使用全基因组关联（GWAS）并进行定量代谢谱分析，目的是 阐明代谢性状的基本遗传结构易于CAD。我们 假设该队列中的代谢组分析将识别CAD的新表型 病理生理学，该MQTL映射将鉴定通过代谢介导的CAD风险的新基因 途径。该提案的具体目的是：（1）在A中执行针对性的定量代谢分析 1000个人的表型心血管队列； （2）在全基因组联想（GWAS）中 相同的1000个个体的心血管队列并执行遗传学图以识别代谢 定量性状基因座（MQTL）； （3）在硅和独立的家族和非家庭中复制GWAS的发现 心血管队列； （4）从AIM 2和3确定的重新设备候选基因座以识别 新型遗传变异。该提案有可能对主要公众产生重大影响 健康问题具有非常强大的可遗传成分

项目成果

Genome-Wide Variants Associated With Longitudinal Survival Outcomes Among Individuals With Coronary Artery Disease.

• DOI: 10.3389/fgene.2021.661497
• 发表时间: 2021
• 期刊: Frontiers in genetics
• 影响因子: 3.7
• 作者: Dungan JR;Qin X;Hurdle M;Haynes CS;Hauser ER;Kraus WE
• 通讯作者: Kraus WE

Metabolic Dysfunction in Heart Failure: Diagnostic, Prognostic, and Pathophysiologic Insights From Metabolomic Profiling.

• DOI: 10.1007/s11897-016-0289-5
• 发表时间: 2016-06
• 期刊: Current heart failure reports
• 作者: Hunter WG;Kelly JP;McGarrah RW 3rd;Kraus WE;Shah SH
• 通讯作者: Shah SH

Metabolomic Profiling Identifies Novel Circulating Biomarkers of Mitochondrial Dysfunction Differentially Elevated in Heart Failure With Preserved Versus Reduced Ejection Fraction: Evidence for Shared Metabolic Impairments in Clinical Heart Failure.

• DOI: 10.1161/jaha.115.003190
• 发表时间: 2016-07-29
• 期刊: Journal of the American Heart Association
• 影响因子: 5.4
• 作者: Hunter WG;Kelly JP;McGarrah RW 3rd;Khouri MG;Craig D;Haynes C;Ilkayeva O;Stevens RD;Bain JR;Muehlbauer MJ;Newgard CB;Felker GM;Hernandez AF;Velazquez EJ;Kraus WE;Shah SH
• 通讯作者: Shah SH