Perfluoroalkyl substances and incident type 2 diabetes in a multi-ethnic population: A metabolome-genome investigation

项目总结 2型糖尿病(T2D)患病率的增加伴随着种族/民族差异，但病因 促进T2D流行病和T2D差异还没有完全被理解。越来越多的实验证据表明 暴露于内分泌干扰性化学品(EDCs)，如全氟烷基物质和多氟烷基物质(PFAS)， 促进T2D发育，可能与已知的风险因素协同作用，如遗传变异。全氟辛烷磺酸是 无处不在的、持久的扰乱新陈代谢的化学物质。然而，很少有前瞻性研究考察 PFAS和T2D风险之间的关联，而且这些几乎只发生在白人人群中。上一首 研究也缺乏临床上确定的T2D诊断，只调查了许多潜在的 危险的全氟辛烷磺酸，并且没有审查全氟辛烷磺酸混合物或基因-全氟辛烷磺酸相互作用的潜在影响。现状-- 最先进的集成组学方法可以克服这些障碍，推动该领域的发展。我们提出了第一个 代谢组-基因组综合方法用于(1)表征PFAS浓度之间的关联 诊断前血浆样本中的(单独的全氟辛烷磺酸和混合物)和事件的T2D风险和潜在影响 用多基因风险评分作为研究创新方案的遗传易感性对T2D的修饰 相互作用，(2)识别潜在的失调代谢途径，以及(3)识别代谢特征 由EDC暴露和与T2D相关的内源性代谢物确定的诊断前血浆样本 风险。我们将利用BIOME进行嵌套病例对照研究，BIOME是一种正在进行的与电子健康记录相关的研究 Biobank自2007年以来在西奈山医院(NY)寻求初级保健时注册了55,000名参与者。 发生的T2D病例与BIOME T2D非对照(N=1700)匹配(1：1)，并且是非裔美国人， 西班牙裔和白人血统，从抽血到T2D诊断的平均时间为6年。我们将使用 诊断前血浆使用最先进的高分辨率测量PFAS和代谢途径 代谢组学(HRM)方法。我们将在T2D事件病例和匹配的对照组中复制研究结果 来自洛杉矶和夏威夷基于人群的多种族队列(MEC)研究，使用现有的基因组数据 诊断前血浆中PFAS和HRM的浓度与生物群样本在同一实验室测量。在……里面 与以前的研究相比，我们纳入了一系列传统的和新兴的PFAS、曝光-混合效应、 通过利用最先进的代谢组-基因组方法和 严格的发现-在两个独特的、表型良好的多民族队列中进行复制设计，并进行诊断前研究 血浆样本以确定与T2D相关的早期生物标记物。这项研究依赖于多学科的 在环境/遗传流行病学、全氟辛烷磺酸和T2D研究方面具有专长的经验丰富的调查人员团队， 以及最先进的人力资源管理、基因组学和生物统计学暴露混合方法。调查结果将告知精确度 T2D预防和治疗的医学方法，特别是对高危多民族人群。

PROJECT SUMMARY Increasing prevalence of type 2 diabetes (T2D) is accompanied by racial/ethnic disparities, but etiological factors promoting the T2D epidemic and T2D disparities are not fully understood. Growing experimental evidence shows that exposures to endocrine-disrupting chemicals (EDCs), such as per- and polyfluoroalkyl substances (PFAS), promote T2D development, likely in synergy with known risk factors such as genetic variations. PFAS are ubiquitous and persistent chemicals that perturb metabolism. However, few prospective studies examined the association between PFAS and T2D risk, and those were almost exclusively in White populations. Previous studies also lacked clinically ascertained T2D diagnosis, investigated only a few of the many potentially hazardous PFAS, and did not examine potential effects of PFAS mixtures or gene–PFAS interactions. State-of- the-art integrated omics approaches can overcome these barriers to advance the field. We propose the first integrated metabolome–genome approach to (1) characterize the associations between PFAS concentrations (individual PFAS and mixtures) in prediagnostic plasma samples and incident T2D risk and potential effect modification by genetic predisposition to T2D using polygenic risk scores as an innovative solution for studying interactions, (2) identify underlying dysregulated metabolic pathways, and (3) identify metabolic signatures in prediagnostic plasma samples defined by EDC exposures and endogenous metabolites associated with T2D risk. We will perform a nested case–control study leveraging BioMe, an ongoing electronic health record-linked biobank with >55,000 participants enrolled while seeking primary care at Mount Sinai Hospital (NY) since 2007. Incident T2D cases are matched (1:1) to BioMe T2D-free controls (N = 1,700) and are of African American, Hispanic and White ancestry, with ~6 years average time between blood draw and T2D diagnosis. We will use prediagnostic plasma to measure PFAS and metabolic pathways using state-of-the-art high-resolution metabolomics (HRM) approaches. We will replicate findings among incident T2D cases and matched controls from the population-based Multiethnic Cohort (MEC) study in Los Angeles and Hawaii with extant genome data and prediagnostic plasma concentrations of PFAS and HRM measured at the same lab as BioMe samples. In contrast to prior studies, we incorporate a wide suite of legacy and emerging PFAS, exposure-mixture effects, and gene–environment interactions by leveraging state-of-the-art metabolome–genome approaches and a rigorous discovery–replication design in two unique, well-phenotyped multiethnic cohorts with prediagnostic plasma samples to identify early biomarkers associated with T2D. This research relies on a multidisciplinary team of seasoned investigators with expertise in environmental/genetic epidemiology, PFAS and T2D research, and state-of-the-art HRM, genomics, and biostatistical exposure–mixture methods. Findings will inform precision medicine approaches for T2D prevention and treatment, particularly for high-risk multiethnic populations.