Systems genetic and reverse phenotypic analysis of age and retirement

年龄和退休的系统遗传和反向表型分析

• 批准号: 8882214
• 负责人: Steve Horvath
• 金额: $ 30.62万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8882214
• 关键词: Affect; Age; Aging; American; Americas; Behavioral; Biological; Birth; Cognitive; Cohort Studies; Computer software; Coupled; DNA; DNA Methylation; Data; Data Analyses; Data Set; Databases; Development; Elderly; Epidemiologist; Expenditure; Gene Expression; Genes; Genetic; Genetic Markers; Genome Scan; Genomics; Genotype; Goals; Health; Heterogeneity; Human; Impairment; Income; Individual; Lead; Link; Literature; Longevity; Machine Learning; Measures; Mental Health; Methodology; Methods; Methylation; Mining; Modeling; Molecular Genetics; Pathway Analysis; Pathway interactions; Personal Satisfaction; Phenotype; Physical Function; Population; Process; Psychologist; Psychosocial Factor; Research Personnel; Resources; Retirement; Sampling; Scanning; Single Nucleotide Polymorphism; Specificity; Statistical Models; Subgroup; Surveys; System; Techniques; Testing; Time; Variant; Weight; age effect; age related; base; bead chip; behavioral economics; child depression; cognitive function; cohort; design; economic implication; endophenotype; exome; gene environment interaction; genetic analysis; genetic variant; genome wide association study; health data; improved; interest; novel; novel strategies; psychosocial; repository; reverse genetics; social implication; sociologist; statistics; text searching

DESCRIPTION (provided by applicant): High throughput genomic platforms have revealed a profound effect of age on gene expression and gene methylation levels. For example, our integromic analysis of multiple publicly available data sets have identified hundreds of age related genes that can be organized into network modules. These gene sets along with genes and pathways known from the vast literature on aging and longevity provide valuable candidates in allelic association studies of the health and well-being of older Americans. The rich longitudinal data set and the genome wide scans of DNA samples from the Health and Retirement Study (HRS) provide a unique resource for evaluating the phenotypic effects of genetic variants underlying aging related genes, gene sets and for developing multivariable models that include behavioral, psychosocial, and genetic factors. This proposal aims to apply systems biologic and systems genetic methods for identifying gene sets based on existing gene expression, gene methylation, and multiple large scale genome wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) underlying these genes will then be related to health, cognitive, behavioral, and economic phenotypes using multivariable regression-, machine learning-, and weighted network analysis approaches. An iterative process between SNP and phenotype selection facilitates the definition of clinically and economically important phenotypes under genetic control (reverse phenotyping). The proposal will not only elucidate the genetic and molecular underpinnings of retirement relevant phenotypes (cognitive functioning, psychosocial factors, and health related expenditures) but also lead to a phenotypic annotation of aging related genes and pathways.

描述（由申请人提供）：高吞吐量基因组平台揭示了年龄对基因表达和基因甲基化水平的深远影响。例如，我们对多个公开数据集的集成分析已经确定了数百个相关的基因，这些基因可以组织到网络模块中。这些基因集以及从衰老和寿命的广泛文献中知道的基因和途径在等位基因和福祉的研究中为老年美国人的健康和福祉提供了宝贵的候选者。健康与退休研究（HRS）中丰富的纵向数据集和对DNA样品的基因组广泛扫描提供了一种独特的资源，用于评估与衰老相关的基因，基因集和开发包括行为，心理社会和遗传因素在内的多变量模型的遗传变异的表型效应。该建议旨在将系统生物学和系统遗传方法应用于基于现有基因表达，基因甲基化和多个大型基因组广泛关联研究（GWAS）的基因集。这些基因基因的单核苷酸多态性（SNP）将使用多变量回归，机器学习和加权网络分析方法与健康，认知，行为和经济表型有关。 SNP和表型选择之间的迭代过程促进了遗传控制下临床和经济上重要表型的定义（反向表型）。该提案不仅将阐明退休相关表型的遗传和分子基础（认知功能，社会心理因素和与健康相关的支出），还导致与衰老相关的基因和途径的表型注释。