Age effects in humans are observed at all levels of organization from molecular pathways to organ systems. While there is substantial evidence that genetic variation influences the rate at which aging occurs, identifying the specific genes involved in human differential aging has been difficult. Most human genetic studies of aging have focused on exceptional longevity which may be too far removed from the direct action of genes to be a reliable phenotype for genetic dissection. Additionally, much of the public health interest in aging is less in absolute longevity than in maintenance of normal function in old age. In the proposed project, we focus on quantitative differential aging in specific molecular pathways which should offer a more powerful approach to identify specific genes and their sequence variants that are involved in human variation in the aging process. In this project, we will identify a novel set of gene expression-based biomarkers using large-scale genome- wide transcriptional profiling of lymphocytes to identify quantitative phenotypes that are involved in differential aging. Such phenotypes have the great advantage of being directly proximal to gene action. An existing major human genetic resource (families from the San Antonio Family Heart Study) will be employed to examine the genetic basis of transcriptional aging in a cost-effective way. Extensive genome-wide genotypic and transcriptomic data from 1,240 Mexican Americans who are members of large extended pedigrees will be used. Analysis of existing cross-sectional transcriptional profiles from lymphocyte samples have revealed over 4,000 quantitative transcripts that correlate with age. For this project, we will perform follow-up transcriptional profiles on 1,000 of these individuals using lymphocytes obtained 15 years after the initial baseline examination. Using these novel mixed longitudinal transcriptional data, we will identify genes and their sequence variants that influence differential aging.
The specific aims of this project are to: (1) develop a mixed longitudinal sample of genome-wide transcriptional profiles of lymphocytes from 1,000 Mexican Americans who are members of large extended kindreds; (2) localize quantitative trait loci influencing function/pathway-specific biological ages in order to detect genetic regulators of differential aging using linkage-based genome scanning; and (3) identify specific regulatory variants that interact with age to influence transcript levels in sixty novel cis-regulated aging-related genes. The proposed research should lead to the discovery of novel genes underlying variation in human biological aging. By focusing on novel-expression based phenotypes shown to be both age-related cis-regulated, we will maximize our probability for finding causal genetic variants influencing differential aging. Morbidity due to aging currently costs the United States billions of dollars annually and this economic burden is rapidly increasing. In this project, we will identify genes involved in human differential response to aging. A better understanding of the genetic underpinnings of molecular aging will provide novel approaches for the characterization, treatment and potential prevention of loss of vitality during aging and may lead to a significant reduction of this considerable public health burden. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
1R01AG031277-01
Application #
7354276
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Mccormick, Anna M
Project Start
2008-02-15
Project End
2013-01-31
Budget Start
2008-02-15
Budget End
2009-01-31
Support Year
1
Fiscal Year
2008
Total Cost
$536,675
Indirect Cost
Name
Texas Biomedical Research Institute
Department
Type
DUNS #
007936834
City
San Antonio
State
TX
Country
United States
Zip Code
78245
Diego, Vincent P; Curran, Joanne E; Charlesworth, Jac et al. (2012) Systems genetics of the nuclear factor-?B signal transduction network. I. Detection of several quantitative trait loci potentially relevant to aging. Mech Ageing Dev 133:11-9
Kent Jr, Jack W; Göring, Harald H H; Charlesworth, Jac C et al. (2012) Genotype×age interaction in human transcriptional ageing. Mech Ageing Dev 133:581-90