Genome, Metabolome, Ancestry and Diabetes Health Disparity

摘要 我们对2型糖尿病(T2D)及其相关的心脏代谢(CM)的基因组代谢研究 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%上升到33% 美国的2050年。南亚人(SA)是一个迅速发展的少数民族，有很好的文献记载 T2D和心血管疾病的高易感性。尽管众所周知，遗传和环境 影响T2D的因素，在SAS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 应用代谢组/基因组研究广泛心脏代谢性疾病患者的血药浓度 技术。然而，从来没有在印度的任何人群中进行过这样的研究，尽管事实是 全球人口中约有四分之一是南非人。与传统的全基因组不同 关联研究(GWAS)，代谢组学(MGWAS)具有更高的统计能力来捕捉共同的 遗传变异。鉴于基因组代谢组方法在阐明潜在遗传原因方面的前景 对于疾病来说，在其他非白人群体中进行这样的调查对于实现精确度的进步至关重要 医药。本质上，这样的研究将有助于确定独特的代谢物的特征，这些代谢物与 SAS等患者的T2D表型为肥胖/代谢性肥胖。 因此，在本次调查中，利用已收集的现有资源，以家庭和人口为基础 样本(n=5,250)来自亚洲印度糖尿病心脏研究(AIDHS)，我们的战略是经济高效地整合 表型、代谢和基因组数据，以研究调节T2D的潜在遗传机制 病理生理学。我们为这项提议提出了以下三个具体目标：目标1：产生全球(无目标) 识别和表征与T2D和相关基因相关的可遗传小分子的代谢组谱 GCxGC-MS用于心脏代谢性状的研究；目的2：同时进行mGWAS以识别mQTL和变异 与T2D、代谢物和其他性状相关；复制关联最大的mQTL变体和~15-20个大多数 其他独立SA样本中的重要代谢物；目标3：确定推定的 通过在美国多民族家庭中进行查找分析，进行T2D的生物标志物，并执行初步的功能 利用斑马鱼和基因敲除小鼠模型对几个最有趣的mQTL基因座进行了表征。 总体影响：从来没有对亚裔印度人进行过类似的研究。带着我们的 优秀的团队，独特的高风险同质锡克教徒群体，以及对现有资源的成本效益利用， 我们的项目在识别具有治疗重要性的新生物标志物方面具有很高的潜力。其中一些人可能会预测 T2D风险亚型与肥胖阈值较低的早期发病有关，与美国多种族人口相关。

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.