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: 8691636
• 负责人: Steve Horvath
• 金额: $ 31.57万
• 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 2017-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8691636
• 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; Economics; Elderly; Epidemiologist; Expenditure; Gene Expression; Genes; Genetic; Genetic Markers; 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; child depression; cognitive function; cohort; design; economic implication; endophenotype; exome; gene environment interaction; genetic analysis; genetic variant; genome wide association study; improved; interest; novel; novel strategies; positional cloning; psychosocial; public health relevance; repository; 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）：高通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整合分析已经识别出数百个可以组织成网络模块的年龄相关基因。这些基因组以及从有关衰老和长寿的大量文献中已知的基因和途径为美国老年人的健康和福祉的等位基因关联研究提供了有价值的候选者。健康与退休研究 (HRS) 中丰富的纵向数据集和 DNA 样本的全基因组扫描提供了独特的资源，用于评估衰老相关基因、基因集背后的遗传变异的表型效应，以及开发包括行为、心理因素、遗传因素。该提案旨在应用系统生物学和系统遗传学方法，基于现有的基因表达、基因甲基化和多个大规模全基因组关联研究（GWAS）来识别基因集。然后，使用多变量回归、机器学习和加权网络分析方法，将这些基因背后的单核苷酸多态性 (SNP) 与健康、认知、行为和经济表型联系起来。 SNP 和表型选择之间的迭代过程有助于在遗传控制（反向表型分析）下定义临床和经济上重要的表型。该提案不仅将阐明退休相关表型（认知功能、心理社会因素和健康相关支出）的遗传和分子基础，还将对衰老相关基因和途径进行表型注释。