Hispanic Latino Lipid Consortium

摘要 心脏代谢疾病（CMD），包括肥胖症、血脂异常、2型糖尿病和高血压，是 全球疾病负担的主要原因，对历史上被边缘化的人造成不成比例的影响 人口。在我们项目的第一个资助期，西班牙裔/拉丁裔脂质联盟（HLLC），我们的努力 集中在发现影响血脂水平、肥胖和T2 D的遗传因素， 西班牙裔/拉丁裔（HL），一个具有显著CMD健康差异的人群。这项极具影响力的研究， 迄今为止，已发表了39篇论文，利用了现存的遗传数据以及生成的新遗传数据 对于> 63 k参与者的项目，以确定多个新的CMD基因座。我们还描述了监管 使用新的全血（WB）基因表达谱资源，在880名受试者中研究影响脂质水平的机制。 HL参与者。然而，大多数GWAS信号的作用机制和分子途径 在代谢组织中的破坏仍然没有很好的理解。因此，在第二个供资期， HLLC，我们建议建立在我们显着的成功和经验，产生和分析转录组学 数据在HL在这里，我们的目的是研究多组织基因表达（WB和皮下脂肪）的作用， 组织[SAT]）和WB表达随时间的变化，目的是鉴定关键的可修饰分子 在更大、更多样化的HL样本中，与CMD相关的特征。具体而言，我们建议： 首先，鉴定与CMD和相关性状（肥胖，2型）相关的多组织转录组学模式 糖尿病、血脂异常、高血压测量）在最近获得的来自14 k HL的WB RNA测序数据中 参与者以及来自为本申请招募的HL参与者的300个SAT组织标本; 第二，确定与CMD相关风险变化相关的WB转录组学数据的纵向变化 HLCC参与者的因素（来自750名参与者的1500项RNA测量，平均5年 每个人的两种RNA测序方法之间的差异）;第三，对遗传学进行综合分析。 和转录组数据，以通过孟德尔随机化建立因果关系，并表征现有的基因组 功能性证据的发现。我们的目标是完全独立的，非常好的动力，和设计 以回答关键问题的因果途径的基础上观察到的转录组差异CMD。 这项工作将导致创建一个公开可用的HL代谢组织eQTL信息资源 并确定早期预防和药物干预的新靶点。重要的是，通过解决CMD 风险在一个代表性不足的人口，我们的工作直接有助于国家卫生研究院的使命，以促进疾病 预防和治疗在历史上被边缘化的人群。

ABSTRACT Cardiometabolic diseases (CMD), including obesity, dyslipidemia, type 2 diabetes, and hypertension, are the leading cause of disease burden in the world with a disproportionate impact on historically marginalized populations. In the first funding period of our project, The Hispanic/Latino Lipid Consortium (HLLC), our efforts centered on discovering genetic factors impacting serum lipid levels, obesity, and T2D in self-identified Hispanic/Latinos (HL), a population with significant CMD health disparities. This highly impactful research, which has resulted in 39 published papers to-date, leveraged extant genetic data as well as new genetic data generated for the project in >63k participants to identify multiple new CMD loci. We also characterized the regulatory mechanisms influencing lipid levels using a new resource of whole blood (WB) gene expression profiles in 880 HL participants. Yet, the mechanism of action of most GWAS signals and the molecular pathways disrupted in metabolic tissues are still not well understood. As such, in the second funding period of the HLLC, we propose to build on our remarkable success and experience generating and analyzing transcriptomic data in HL. Here, we aim to investigate the role of multi-tissue gene expression (WB and subcutaneous adipose tissue [SAT]) and changes in WB expression over time with the goal of identifying key modifiable molecular signatures associated with CMDs in an even larger, more diverse sample of HL. Specifically, we propose to: first, identify multi-tissue transcriptomic patterns associated with CMD and related traits (obesity, type 2 diabetes, dyslipidemia, hypertension measures) in recently acquired WB RNA sequencing data from 14k HL participants as well as in 300 SAT tissue specimens from HL participants recruited for the present application; second, identify longitudinal changes in WB transcriptomic data associated with changes in CMD-related risk factors in participants from the HLCC (1500 RNA measures from 750 participants with an average of 5 years between the two RNA sequencing measures for each person); and third, conduct integrative analyses of genetic and transcriptomic data to establish causality via Mendelian Randomization and characterize existing genomic findings with functional evidence. Our aims are entirely independent, exceptionally well powered, and designed to answer critical questions about the causal pathways underlying observed transcriptomic differences in CMD. This work will result in creation of a publicly available resource of eQTL information for metabolic tissues in HL and identify novel targets for early prevention and pharmaceutical intervention. Significantly, by addressing CMD risk in an under-represented population, our work contributes directly to the NIH’s mission to promote disease prevention and treatment in historically marginalized populations.