Genome, Metabolome, Ancestry and Diabetes Health Disparity

基因组、代谢组、血统和糖尿病健康差异

基本信息

批准号：
10468147
负责人：
RAVINDRANATH DUGGIRALA
金额：
$ 61.01万
依托单位：
UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-05 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10468147
关键词：
Affect African American population Age Alleles American American Indians Area Asian Americans Asian Indian Asian ancestry Asian population Biochemical Biological Biological Markers Blood specimen Body mass index Cardiometabolic Disease Cardiovascular Diseases Caucasians Child Complex Data Diabetes Mellitus Disease Disease Pathway Disparity Environmental Exposure Environmental Risk Factor Ethnic Origin European Family Functional disorder General Population Genetic Genetic Markers Genetic Risk Genetic Variation Genome Genotype Health Heart Heart Diseases Heritability High Prevalence Hispanic Hispanic Americans India Individual Investigation Knockout Mice Link Low Prevalence Measures Mediating Metabolic Minority Groups Molecular Non obese Non-Insulin-Dependent Diabetes Mellitus Obesity Pathway interactions Patients Persons Phenotype Population Predisposition Prevalence Quantitative Trait Loci Reporting Research Priority Resources Risk Sampling Serum South American South Asian Specimen Technology Therapeutic Underserved Population United States United States National Institutes of Health Variant Zebrafish cardiometabolism clinical heterogeneity clinically significant cohort cost cost effective diabetes pathogenesis diabetes risk diabetic early onset endophenotype ethnic minority population genetic pedigree genetic variant genome wide association study genome-wide genomic data health disparity high risk high risk population insight interest metabolome metabolomics mouse model multi-ethnic novel novel marker pandemic disease pleiotropism population based precision medicine premature racial minority population small molecule trait underserved minority

项目摘要

ABSTRACT Our genome-metabolome investigations of type 2 diabetes (T2D) and the associated cardiometabolic (CM) complications are one of the high-priority research areas for the NIH to understand the causes of disparities in health in underserved populations of the US. T2D prevalence is projected to increase from 10% currently to 33% by the year 2050 in the US. South Asians (SAs) are a rapidly growing ethnic minority group, and have a well-documented high predisposition to T2D and cardiovascular diseases. Although it is well known that genetic and environmental factors influence T2D, the underlying mechanisms are poorly characterized in SAs. Recent studies performed in European populations have identified genetic factors influencing metabolite concentrations in patients with a wide spectrum of cardiometabolic diseases using metabolome-wide/genome-wide technologies. However, no such study has ever been performed in any population from India despite the fact that about one in four people in the global population are part of the SA population. Unlike conventional genome-wide association studies (GWAS), the metabolome GWAS (mGWAS) has higher statistical power to capture common genetic variation. Given the promise of the genome-metabolome approaches in elucidating underlying genetic causes for disease, such investigations in other non-white ethnic cohorts are critical to achieve advances in precision medicine. Essentially, such studies will help characterize unique metabolites linked with the “non- obese/metabolically-obese” phenotype of T2D in SAs and others. Therefore in this investigation, using existing resources of already collected family and population-based samples (n=5,250) from the Asian Indian Diabetic Heart Study (AIDHS), our strategy is to cost-effectively integrate phenotypic, metabolomic, and genomic data to investigate the underlying genetic mechanisms regulating T2D pathophysiology. We propose these three specific aims for this proposal: AIM 1: Generate global (untargeted) metabolome profiles to identify and characterize small heritable molecules genetically correlated with T2D and related cardiometabolic traits using GCxGC-MS; AIM 2: Perform mGWAS to identify mQTLs and variants simultaneously associated with T2D, metabolites, and other traits; Replicate association of the top mQTL variants and ~15-20 of most significant metabolites in additional independent SA samples; AIM 3: Determine differences and similarities of putative biomarkers for T2D by performing look-up analysis in US multiethnic families, and perform preliminary functional characterization of a few of the most interesting mQTL loci by using zebrafish and knockout mouse models. OVERALL IMPACT: No comparable study has ever been undertaken in people of Asian Indian descent. With our outstanding team, a unique high-risk homogenous Sikh population, and cost-effective utilization of existing resources, our project has high potential to identify novel biomarkers of therapeutic importance. Of these, some may predict a subtype of T2D risk linked to early onset at lower obesity thresholds in relevance to multi-ethnic US populations.

抽象的我们对 2 型糖尿病 (T2D) 和相关心脏代谢 (CM) 的基因组代谢组研究并发症是 NIH 了解健康差异原因的高度优先研究领域之一在美国服务不足的人群中，T2D 患病率预计将从目前的 10% 增加到 33%。到 2050 年，南亚人 (SA) 是一个快速增长的少数族裔群体，并且拥有大量记录。尽管众所周知，遗传和环境因素对 T2D 和心血管疾病具有较高的易感性。虽然影响 T2D 的因素很多，但 SA 中的潜在机制尚不清楚。最近在欧洲人群中进行的研究已经确定了影响代谢物的遗传因素使用全代谢组/全基因组研究患有多种心脏代谢疾病的患者的浓度然而，尽管事实如此，但从未在印度的任何人群中进行过此类研究。与传统的全基因组人群不同，全球人口中约有四分之一是 SA 人群的一部分。关联研究 (GWAS)，代谢组 GWAS (mGWAS) 具有更高的统计能力来捕获常见的鉴于基因组代谢组方法在阐明潜在遗传原因方面的前景。对于疾病，在其他非白人种族群体中进行此类研究对于实现精确度的进步至关重要从本质上讲，此类研究将有助于表征与“非-非”相关的独特代谢物。 SA 和其他人群中 T2D 的“肥胖/代谢肥胖”表型。因此，在本次调查中，利用已收集的家庭和人口的现有资源来自亚洲印度糖尿病心脏研究 (AIDHS) 的样本 (n=5,250)，我们的策略是经济高效地整合表型、代谢组学和基因组数据，用于研究调节 T2D 的潜在遗传机制我们提出了该提案的三个具体目标：目标 1：生成全局（非目标）代谢组图谱可识别和表征与 T2D 及相关疾病遗传相关的小遗传分子使用 GCxGC-MS 检测心脏代谢特征；目标 2：执行 mGWAS 以同时识别 mQTL 和变异与 T2D、代谢物和其他性状相关；顶级 mQTL 变体和大多数 mQTL 变体的重复关联；其他独立 SA 样本中的显着代谢物；目标 3：确定假定的差异和相似之处通过在美国多种族家庭中进行查找分析来确定 T2D 的生物标志物，并进行初步功能分析使用斑马鱼和基因敲除小鼠模型表征一些最有趣的 mQTL 位点。总体影响：我们还没有对亚裔印度裔进行过类似的研究。优秀的团队、独特的高风险同质锡克教人口以及对现有资源的经济有效利用，我们的项目具有识别具有治疗重要性的新型生物标志物的巨大潜力，其中一些可以预测。 T2D 风险亚型与美国多民族人群中肥胖阈值较低时的早发有关。