Integrating genome, other layers of omics, and non-genetic data to improve understanding of the etiology of human diseases in multi-ethnic populations

整合基因组、组学的其他层面和非遗传数据，以提高对多种族人群中人类疾病病因学的理解

• 批准号: 10749846
• 负责人: Lang Wu
• 金额: $ 84.85万
• 依托单位: UNIVERSITY OF HAWAII AT MANOA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10749846
• 关键词: Address; African; African American population; Alzheimer' s Disease; American; Architecture; Arterial Disorder; Asian Americans; Asian population; Assessment tool; Atherosclerosis Risk in Communities; Basic Science; Biological Markers; Blood; Cohort Studies; Communities; DNA Methylation; Data; Development; Disease; Disease Marker; Disparity; Epidemiology; Ethnic Origin; Ethnic Population; Etiology; European; European ancestry; Framingham Heart Study; Gene Expression; Genes; Genetic; Genetic Markers; Genome; Genomics; Goals; Hispanic Populations; Individual; Knowledge; Latino Population; Malignant neoplasm of pancreas; Malignant neoplasm of prostate; Measures; Methodology; Methods; Methylation; Multi-Ethnic Study of Atherosclerosis; Native Hawaiian; Participant; Population; Population Group; Proteins; Reduce health disparities; Reporting; Research; Research Design; Research Support; Risk; Risk Factors; Role; Selection Bias; Series; Site; Statistical Methods; Testing; Tissues; Training; Veterans; Work; Workforce Development; biobank; biomarker identification; design; disorder risk; epidemiologic data; epidemiology study; genetic epidemiology; genetic predictors; genetic risk factor; genetic variant; human disease; improved; innovation; instrument; interest; multi-ethnic; non-genetic; novel; novel marker; predictive modeling; programs; protein expression; protein metabolite; risk prediction; statistics; trait

ABSTRACT A variety of human disease show disparities across different populations and ethnic groups, such as Africans, Hispanics/Latinos, Asians, Europeans, and Native Hawaiians. The etiology of many human diseases is not fully understood, despite substantial efforts to identify associated non-genetic and genetic factors, including common and rare genetic variants. More work focusing on different layers of omic markers including DNA methylation (DNAm), gene, protein, and metabolite markers is urgently needed. Basic research supports the important roles of certain CpG sites, genes, proteins, and metabolites in development of many diseases. Epidemiological studies also have identified multiple candidate DNAm, gene, protein, and metabolite biomarkers for diseases/traits. However, conventional epidemiologic studies were conducted primarily in individuals with European ancestry, and it is unclear which DNAm/gene/protein/metabolite biomarkers identified to date are European ancestry- specific or pan-ancestry. Also, findings with many of these biomarkers have been inconsistent, potentially due to major methodological limitations, such as selection bias and uncontrolled confounding. There are critical needs to apply a novel study design with reduced limitations of conventional biomarker studies for characterizing causally related biomarkers in blood for human diseases across populations to improve our understanding of disease etiology and reduce health disparities. One strategy to potentially decrease limitations of selection bias and unmeasured confounding is to use genetic instruments for assessing the relationship between DNAm/gene/protein/metabolite markers and diseases. Our preliminary work applying conventional methods to develop genetic prediction models has revealed promising DNAm, gene, protein, and metabolite biomarkers in blood associated with risk of several diseases in Europeans. The proposed project will apply a series of new studies to address these important knowledge gaps. Specifically, we will 1) develop ethnic-specific DNAm, gene, protein, and metabolite marker genetic prediction models in blood tissue across African Americans, Hispanics/Latinos, Asian Americans, European Americans, and Native Hawaiians by applying novel methods (Aim 1); 2) identify putative causal DNAm, gene, protein, and metabolite biomarkers in blood for risk of multiple diseases across multi-ethnic populations by leveraging large scale genetic and non-genetic data (Aim 2); and 3) evaluate potential interactions between known risk factors and predicted levels of established and newly identified markers on risks of diseases of interest (Aim 3). Our study will generate important new knowledge for substantially improving our understanding of the etiology of multiple human diseases across Africans, Hispanics/Latinos, Asians, Europeans, and Native Hawaiians. The proposed new methods can also be applied to other omic markers.

摘要 各种人类疾病在不同人群和种族群体之间表现出差异，如非洲人， 西班牙裔/拉丁美洲人、亚洲人、欧洲人和夏威夷原住民。许多人类疾病的病因学并不完全 尽管为确定相关的非遗传和遗传因素做出了大量努力， 和罕见的基因变异更多的工作集中在不同层次的组学标记，包括DNA甲基化 （DNAm）、基因、蛋白质和代谢物标记物是迫切需要的。基础研究支持的重要作用 某些CpG位点，基因，蛋白质和代谢物在许多疾病的发展中起作用。流行病学研究 还鉴定了多种候选DNAm、基因、蛋白质和疾病/性状的代谢物生物标志物。 然而，传统的流行病学研究主要在欧洲血统的个体中进行， 目前还不清楚哪些DNA/基因/蛋白质/代谢物生物标志物是欧洲血统- 特定或泛祖先。此外，许多这些生物标志物的发现并不一致，可能是由于 主要的方法学限制，如选择偏差和不受控制的混杂。存在临界 需要应用一种新的研究设计，减少传统生物标志物研究的局限性， 血液中与人类疾病有因果关系的生物标志物，以提高我们对 疾病病因学和减少健康差距。一种可能减少选择偏差限制的策略 和不可测量的混杂是使用遗传工具来评估 DNA/基因/蛋白质/代谢物标记物和疾病。我们的初步工作采用传统的方法， 发展遗传预测模型揭示了有前途的DNA，基因，蛋白质和代谢物生物标志物， 血液与欧洲人患几种疾病的风险有关。拟议项目将采用一系列新的 研究以解决这些重要的知识差距。具体来说，我们将1）开发种族特异性DNA，基因， 蛋白质和代谢物标记物遗传预测模型在非洲裔美国人的血液组织中， 西班牙裔/拉丁美洲人，亚裔美国人，欧洲裔美国人和夏威夷土著人通过应用新的方法 (Aim 1）; 2）鉴定血液中推定的致病DNA m、基因、蛋白质和代谢物生物标志物，以确定多种疾病的风险。 通过利用大规模遗传和非遗传数据，在多种族人群中开展疾病研究（目标2）;以及3） 评估已知风险因素与已建立和新建立风险因素的预测水平之间的潜在相互作用。 确定感兴趣疾病风险的标志物（目标3）。我们的研究将产生重要的新知识， 大大提高了我们对非洲多种人类疾病病因的理解， 西班牙裔/拉丁美洲人、亚洲人、欧洲人和夏威夷原住民。所提出的新方法也可以应用于 与其他基因组学标记的联系