Integrated exposome profiling to identify environmental risk factors of metabolic disease in mid- and late-life

综合暴露组分析可识别中晚年代谢疾病的环境危险因素

• 批准号: 10638457
• 负责人: Sung Kyun Park
• 金额: $ 66.94万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-17 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10638457
• 关键词: Address; Age Years; Air Pollutants; Air Pollution; Area; Biological; Biological Markers; Blood; Blood Glucose; Blood specimen; Body mass index; Chemicals; Clinical; Communities; Diagnosis; Diagnostic; Diet; Discrimination; Disease; Disease Progression; Early Diagnosis; Early Intervention; Elderly; Environmental Exposure; Environmental Health; Environmental Risk Factor; Ethnic Origin; Evaluation; Evolution; Exposure to; Family; Fasting; Future; Genotype; Goals; Human; Individual; Life Style; Link; Longitudinal cohort; Mass Spectrum Analysis; Measures; Metabolic; Metabolic Diseases; Metabolic syndrome; Metabolism; Metals; Natural History; Newly Diagnosed; Nitrogen Dioxide; Non-Insulin-Dependent Diabetes Mellitus; Organophosphates; Outcome; Ozone; Parabens; Particulate Matter; Pathogenesis; Perimenopause; Pesticides; Phenols; Play; Poly-fluoroalkyl substances; Population; Precision Health; Predisposition; Prevalence; Prevention; Process; Prospective Studies; Public Health; Recording of previous events; Research; Resolution; Risk; Risk Assessment; Risk Factors; Risk Marker; Role; Sampling; Serum; Study of Women' s Health Across the Nation; Testing; Toxic effect; United States; Vulnerable Populations; Woman; cohort; cost; demographics; diagnostic signature; disorder risk; effective intervention; environmental chemical; epidemiology study; fine particles; health data; improved; inorganic phosphate; insight; machine learning method; metabolic phenotype; metabolome; metabolomics; middle age; multi-ethnic; multi-racial; novel; phthalates; response; risk prediction; risk prediction model; risk stratification

PROJECT SUMMARY/ABSTRACT Exposure to environmental chemicals may play an important role in the pathogenesis of type-2 diabetes (T2D) and metabolic syndrome (MetS) as these exposures are widespread in the population, and the prevalence of these metabolic disorders has dramatically increased over the past several decades. In the US, >42,000 types of chemicals are actively produced, but only a handful of chemicals are tested for their toxicity. Epidemiologic studies have also been restricted to a few targeted metabolism-disrupting chemicals, while relatively little is known about the potential metabolic toxicity of the majority of these chemicals. Analyses spanning wide classes of chemicals are critically needed to identify novel areas of risk, as well as specific associations with metabolic phenotypes. In addition, the underlying biological mechanisms linking environmental chemicals and T2D and MetS are still not well understood. Although risk assessment is critical for early detection and prevention of T2D and MetS, current risk prediction models generally use only a few known risk factors such as demographics, clinical measures including fasting blood glucose and body mass index, and family history and susceptible genotypes. Integrated exposomic signatures may improve risk stratification/discrimination to identify vulnerable populations and provide a more effective intervention approach at the individual- and population-level (i.e., precision health). To address these scientific gaps, we propose to conduct an exposome- metabolome wide association study in relation to incident T2D and Mets in the Study of Women’s Health Across the Nation (SWAN), a multi-racial/ethnic longitudinal cohort of women from midlife to late-life. Using untargeted, high-resolution mass spectrometry that provides the high-quality measures needed for sequencing the human blood exposome, we aim to establish a new paradigm for environmental health research addressing metabolic disease risk. This can be achieved by taking advantage of the rich longitudinal features of the SWAN. Specifically, we aim to 1) conduct an integrated exposome- and metabolome-wide association study of incident T2D and MetS using pre-diagnosis blood samples collected at baseline to characterize known and novel environmental exposures detected using untargeted high-resolution mass spectrometry linked to future T2D and MetS risk and identify endogenous metabolite and disease-associated alterations underlying T2D and MetS; 2) evaluate temporal evolution of exposome and metabolome profiles in T2D and MetS cases and metabolically healthy controls; 3) identify pre-diagnostic metabolomic signatures that link targeted exposures of metabolism disrupting chemicals and novel exposome biomarkers to incident T2D and MetS; and 4) develop and validate exposome-based risk prediction models for T2D and MetS. Successful completion of these aims will identify critical pre-diagnostic exposome biomarkers that may improve risk prediction for T2D and MetS.

项目摘要/摘要 暴露于环境化学物质可能在2型糖尿病的发病机理中起重要作用（T2D） 和代谢综合征（MetS），因为这些暴露在人群中是广泛的，并且患病率是 在过去的几十年中，这些代谢障碍已大大增加。在美国，> 42,000种 积极生产化学物质，但仅对其毒性进行了少数化学物质的测试。流行病学 研究也仅限于一些靶向代谢的化学物质，而相对较少的是 关于大多数化学物质的潜在代谢毒性已知。分析范围很广 需要迫切需要进行化学品类，以识别新的风险领域以及与 代谢表型。另外，将环境化学物质和 T2D和Mets仍然不太了解。尽管风险评估对于早期检测至关重要 预防T2D和Mets，当前的风险预测模型通常仅使用一些已知的风险因素 作为人口统计学，包括空腹血糖和体重指数在内的临床测量以及家族史 和易感基因型。综合的外传签名可能会改善风险分层/歧视 确定弱势群体，并在个人和 人群级别（即精确健康）。为了解决这些科学的差距，我们建议进行剥离 - 与事件T2D和Mets有关的妇女健康研究中的代谢范围广泛的协会研究 整个国家（天鹅），这是一个多种族/民族的纵向人群，从中年到后期的妇女。使用 未靶向的高分辨率质谱法提供了测序所需的高质量措施 人类血液展示体，我们旨在建立一个新的环境健康研究范式 解决代谢疾病风险。这可以通过利用丰富的纵向特征来实现 天鹅。特别是，我们的目标是1）进行整体的杂物组和代谢室的关联 使用诊断前的血液样本在基线上收集的入射T2D和MetS的研究以表征已知的 以及使用不固定的高分辨率质谱法检测到的新型环境暴露。 未来的T2D和大都会的风险，并确定内源性代谢物和与疾病相关的改变 T2D和大都会2）评估T2D和Mets病例中的杂物体和代谢组剖面的临时演变 和代谢健康的对照； 3）确定链接针对的诊断前代谢组学特征 代谢的暴露破坏了化学物质和新型的外向生物标志物，对T2D和MetS的事件；和 4）开发并验证了T2D和METS的基于外向的风险预测模型。成功完成 这些目的将确定诊断前的杂物体生物标志物，这些生物标志物可能会改善T2D的风险预测 和大都会。