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