Leveraging Hispanic/Latino diversity to map and characterize cardiovascular disease loci

摘要 心血管疾病是美国拉美裔或拉丁裔发病率和死亡率的主要原因(H/L) 人口。H/L是相对年轻的人群，大多数心血管疾病的风险差异较大 危险因素，包括肥胖、2型糖尿病(T2D)、血脂异常和高血压；因此，他们的绝对 心血管疾病负担预计将增加。心血管疾病给公共卫生和临床带来的重大挑战包括 积极努力了解潜在的生物机制--治疗、风险的关键障碍 分层，并最终预防疾病。冠心病的数千个基因座 心血管疾病的危险因素已经被绘制成通过脂代谢、血液的紊乱来影响冠心病风险 压力调节、炎症和血小板功能，以及尚不清楚的机制。 然而，关于H/L人群中冠心病和卒中的全基因组关联研究一直很少。 事实上，尽管之前在H/L心血管疾病危险因素的遗传学方面的工作(我们小组有几个)，但没有立场- H/L的《冠心病和卒中的单独治疗》已出版。因此，对于冠心病、中风和心血管疾病的危险因素， 基因组学、公共卫生和医学之间的知识差距可以通过丰富基因组来改善 翻译流水线，包括发现心血管疾病相关性状的新基因座及其潜在原因 变异体；阐明生物和/或病理生理机制；以及建立证据 临床效用和/或对健康结果的影响。我们建议利用现有的关于H/L个人的数据 大规模流行病学和临床生物库研究，并生成新的eQTL数据以发现和表征 H/L人群心血管疾病风险和事件的遗传结构我们的具体目标是(1)发现和 通过研究的荟萃分析描述拉美裔/拉丁裔心血管疾病相关特征的遗传结构 共确定超过159,622名H/L参与者；(2)获得首个H/L特异eQTL图谱，以 构建H/L相关基因表达预测模型，并将其应用于我们的研究样本 基因分型数据(发现样本减去测量RNA的参与者：N~146,822)和行为 每项单独研究中的转录组范围关联研究(TWAS)分析，然后是Meta分析 对于每个感兴趣的特征；以及(3)执行共定位并采样孟德尔随机化(MR)分析 识别H/L心血管疾病危险基因座的致病基因，并使用电子健康记录链接的生物库 通过表型广谱关联研究表征基因座对H/L的更广泛的临床影响 心血管疾病风险基因座。我们的研究具有很高的影响力，因为心血管疾病的负担在西班牙裔/拉丁裔人群中迅速增长 人口趋势表明，到2050年，H/L人口将占美国人口的35%左右。 我们的研究将确保不同的人群不会是最后一批受益于精准医学新时代的人 同时，它制定了将基因组学转化为功能和临床用途的快速战略。

SUMMARY Cardiovascular disease (CVD) is a leading cause of morbidity and mortality among US Hispanic or Latino (H/L) populations. H/Ls are a relatively young population and experience heightened disparities in risk for most CVD risk factors, including obesity, type 2 diabetes (T2D), dyslipidemia, and hypertension; therefore, their absolute CVD burden is expected to increase. The major public health and clinical challenge imposed by CVD has motivated large efforts to understand underlying biologic mechanisms–a critical barrier to treatment, risk stratification, and ultimately, disease prevention. Thousands of genetic loci for coronary heart disease (CHD) and CVD risk factors have been mapped influencing risk of CHD via perturbations of lipid metabolism, blood pressure regulation, inflammation, and platelet function, as well as through mechanisms that remain unknown. Yet, genome-wide association studies (GWAS) for CHD and stroke in H/L populations have been scarce. Indeed, despite previous work on the genetics of CVD risk factors in H/L (several by our group), no stand- alone GWAS for CHD and stroke in H/L has been published. Thus, for CHD, stroke, and CVD risk factors, the knowledge gap between genomics, public health, and medicine could be improved by enriching the genomic translational pipeline, which includes discovering new loci for CVD related traits and their underlying causal variants; elucidating the biological and/or pathophysiological mechanisms; and establishing evidence for clinical utility and/or impact on health outcomes. We propose to leverage extant data on H/L individuals from large epidemiologic and clinical biobank studies and to generate new eQTL data to discover and characterize the genetic architecture of CVD risk and events in H/L populations. Our specific aims are to (1) discover and characterize the genetic architecture of CVD related traits in Hispanic/Latinos through meta-analysis of studies ascertaining more than 159,622 H/L participants in total; (2) derive the first ever H/L-specific eQTL map to build H/L-relevant gene expression prediction models and apply these models to our study samples with genotyping data (discovery sample less the participants with measured RNA: n~146,822) and conduct transcriptome-wide association studies (TWAS) analyses in each individual study followed by meta-analysis for each trait of interest; and (3) perform colocalization and to sample Mendelian Randomization (MR) analyses to identify causal genes amongst H/L CVD risk loci, and use electronic health record (EHR)-linked biobanks to characterize the broader clinical impact of loci via phenome wide association studies (PheWAS) for H/L CVD risk loci. Our study is high impact as the burden of CVD is rapidly growing in Hispanic/Latino populations and demographic trends suggest that the H/L population will constitute ~35% of the US population by 2050. Our research will ensure diverse populations are not the last to benefit from the new era of precision medicine at the same time it develops expedited strategies for translating genomics to function and clinical utility.