Exogenous and Genetic Determinants of the Internal Environment

内部环境的外源和遗传决定因素

• 批准号: 9072859
• 负责人: Duncan C. Thomas
• 金额: $ 26.88万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9072859
• 关键词: Accounting; Address; Affect; Antibiotics; Anus; Bayesian Modeling; Biological Markers; Biological Process; Biological Products; Blood Circulation; Case Study; Cell Proliferation; Chemicals; Climate; Clinical; Cohort Studies; Colonic Polyps; Colonoscopy; Colorectal Cancer; Colorectal Polyp; Communities; Companions; Complex; Constitutional; Data; Dependency; Descriptor; Diet; Environment; Environmental Exposure; Epidemiologic Studies; Etiology; Evolution; Genes; Genetic; Genetic Determinism; Genome; Genomics; Genotype; Goals; High-Throughput Nucleotide Sequencing; Incidence; Infection; Inherited; Intestines; Lamina Propria; Link; Malignant Neoplasms; Mass Spectrum Analysis; Measurement; Measures; Mediating; Mediation; Methods; Microbial Genetics; Modeling; Monozygotic twins; Mucous Membrane; Nature; Obesity; Oral; Organ; Outcome; Phenotype; Phylogenetic Analysis; Pilot Projects; Play; Polyps; Population; Probability; Probiotics; Process; Program Research Project Grants; Recording of previous events; Risk Factors; Role; Rural; Series; Side; Socioeconomic Status; Statistical Methods; Structure; Techniques; Time; Tumor Promotion; Twin Multiple Birth; Uncertainty; Variant; cancer type; cohort; colon cancer patients; computer based statistical methods; disease phenotype; disorder risk; genetic association; genetic makeup; genome wide association study; gut microbiome; gut microbiota; instrument; interest; metabolome; metabolomics; microbial; microbial community; microbiome; microbiota; microorganism interaction; non-genetic; novel; outcome forecast; outcome prediction; prebiotics; resilience; response; treatment response; tumor

ABSTRACT The remarkable yield of novel genetic associations over the last decade resulting from the agnostic approach of genome-wide association studies (GWAS) had not been matched by comparable advances on the environmental side. The "exposome" concept introduced by Chris Wild in 2005 as a "comprehensive description of lifelong exposure history" of external exposures (e.g., chemical, physical, and biological agents), general external environment (e.g., climate, urban-rural, socioeconomic position), and internal exposures (e.g., metabolites, gut microflora) has been operationalized in terms of the measurement of internal chemicals at particular points in time, typically using mass spectrometry to characterize the "metabolome." With this machinery Environment-Wide Association Studies (EWAS) are now feasible, but there remain numerous methodological challenges before the EWAS concept can be considered a real companion to GWASs, including the dynamic nature of the external and internal environment, the problem of reverse causation, control of non-genetic host and environmental confounders, measurement error (temporal variability, instrument error, identification of unknown chemicals, etc.), and ways of conducting Gene-Environment-Wide Interaction Studies (GEWIS). An important component of the exposome is the microbiome. Evidence is mounting linking tumor promotion in a broad array of cancer types to the effects of bacterial microbiota. Local environmental conditions, affected by diet, antibiotics, pre- and probiotics, etc., could affect the structure of microbial communities, affecting risk of disease and response to therapy. The advent of high-throughput sequencing has allowed the relatively inexpensive identification and quantification of thousands of operational taxonomic units (OTUs) in a single biospecimen, providing a wealth of information on the complex structure of resident microbial communities. The microbiome raises many of the same methodological challenges as the exposome, such as time dependency, reverse causation, and non-genetic confounding, but also some different ones like ways of characterizing community effects like diversity and resilience. Although GxE and GxG are also relevant, equally interesting are host-microbial interactions and exposome-microbiome interactions. We propose an integrated approach to developing statistical methods for studying the determinants of the internal environment (the metabolome and the microbiome jointly) in relation to the external environment and the host genome and the relationship of the internal environment to disease risk. As part of this we propose to develop Bayesian network methods to relate all these variables and investigate mediation. We will apply our methods to data from, e.g., the Multi-Ethnic Cohort, the ColoCare Consortium, and a study of colorectal polyps in twins.

抽象的 在过去的十年中，新型遗传关联的显着产率是由不可知论方法产生的 全基因组关联研究（GWAS）的相当进步尚未与 环境方面。克里斯·怀尔德（Chris Wild）在2005年引入的“杂物”概念是“综合的” 终身暴露历史的描述“外部暴露（例如化学，物理和生物剂）的描述， 一般外部环境（例如气候，城市农村，社会经济地位）和内部暴露（例如， 代谢物，肠道菌群）已根据测量内部化学物质在 特定的时间点，通常使用质谱法来表征“代谢组”。与此 机械范围环境协会研究（EWAS）现在是可行的，但仍然存在许多 在EWA概念之前，方法论挑战可以被视为GWASS的真正伴侣， 包括外部和内部环境的动态性质，反向因果关系的问题， 控制非遗传宿主和环境混杂因素，测量误差（时间变异性， 仪器误差，未知化学品的识别等）以及在范围内进行基因环境的方式 相互作用研究（GEWIS）。展览组的重要组成部分是微生物组。证据是 将各种癌症类型的肿瘤促进与细菌菌群的作用联系起来。当地的 受饮食，抗生素，预生物和益生菌等影响的环境状况可能会影响 微生物群落，影响疾病的风险和对治疗的反应。高通量的出现 测序允许相对廉价的识别和数千个操作的量化 单个生物测量中的分类单元（OTU），提供有关复杂结构的丰富信息 居民微生物社区。微生物组提出了许多相同的方法论挑战 揭示体，例如时间依赖性，反向因果关系和非遗传混淆，但也有些不同 诸如表征社区效应等多样性和韧性的方式。虽然GXE和GXG是 同样有趣的是宿主 - 微生物相互作用和Exposome-Microbiome相互作用。我们 提出了一种综合方法来开发统计方法来研究内部的决定因素 与外部环境和主机有关的环境（代谢组和微生物组） 基因组和内部环境与疾病风险的关系。作为其中的一部分，我们建议开发 贝叶斯网络方法与所有这些变量相关联并研究中介。我们将应用我们的方法 从例如多种族队列，Colocare Consortium和双胞胎中大肠息肉的研究中的数据。