Aging is characterized by wide variation in healthspan; some adults become frail in early old age while others remain fit into their 90s and beyond. In animal models, genetic mutations that slow aging also delay a diverse set of age-related diseases. Our GWAS of longevity and age-related phenotypes have identified both genome- wide significant as well as interesting suggestive associations. Many genes function in neuronal, immune, and DNA repair pathways known to be of importance to aging. However, the causal mechanisms underlying the genetic associations have not been elucidated. We propose to use a systems biology approach to extend our genetic studies of aging to examine the relationships among healthy aging phenotypes, genetic polymorphisms, gene expression, DNA methylation, and metabolic factors. Framingham Heart Study (FHS) participants are deeply phenotyped including all domains of aging and have dense genotyping, gene expression (mRNA), DNA methylation, and state-of-the-art metabolomics data providing us with the unique opportunity to extend our GWAS findings to identify multi-omic profiles associated with healthy aging phenotypes. This renewal application seeks to leverage these existing resources in FHS participants using new teams of accomplished investigators in the areas of omics. We hypothesize that using multiple-omics resources and novel integrative models will facilitate discovery of single genes and multi-gene biologic networks underpinning healthy aging phenotypes. Using cross-sectional and longitudinal healthy aging phenotypes from our parent grant (including longevity, morbidity-free survival, healthy aging index, grip strength, measures of physical and cognitive function) we propose the following specific aims:
Aim 1. To identify mRNA transcripts associated with healthy aging phenotypes;
Aim 2. To investigate genome-wide DNA methylation patterns in relation to healthy aging phenotypes;
Aim 3. To investigate the association of metabolomic markers with healthy aging phenotypes;
Aim 4. To integrate the results of the genomic and metabolomics associations in Aims 1- 3 and to identify molecular mechanisms underlying healthy aging phenotypes. Systematically integrating results across healthy aging phenotypes and Omics using network approaches will facilitate identification of key sets of genes and biologic pathways regulating aging. We will incorporate SNPs from existing GWAS and Exomechip data in the identified genes. Our established collaborations permit replication of findings in independent samples. We plan to take the most promising results on to future validation work in animal models. The knowledge gained from this proposal will elucidate important mechanistic insights into the molecular basis of aging. Ultimately the knowledge may lead to interventions to slow aging, and/or to identification of therapeutic targets to delay age-related disease so that older adults may enjoy good health.

Public Health Relevance

The goal of this project is to examine genetic, genomic (gene expression, DNA methylation) and metabolomic markers in relation to measures of healthy aging in a community-based sample to gain better understanding of biologic pathways involved in aging. The knowledge gained from this proposal may ultimately lead to interventions to slow aging and/or to identification of therapies to delay age-related disease.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
High Priority, Short Term Project Award (R56)
Project #
2R56AG029451-05A1
Application #
9118529
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Guo, Max
Project Start
2006-12-01
Project End
2016-08-31
Budget Start
2015-09-15
Budget End
2016-08-31
Support Year
5
Fiscal Year
2015
Total Cost
$473,831
Indirect Cost
$180,330
Name
Boston University
Department
Neurology
Type
Schools of Medicine
DUNS #
604483045
City
Boston
State
MA
Country
United States
Zip Code
02118
Huan, Tianxiao; Chen, George; Liu, Chunyu et al. (2018) Age-associated microRNA expression in human peripheral blood is associated with all-cause mortality and age-related traits. Aging Cell 17:
Murabito, Joanne M; Zhao, Qiang; Larson, Martin G et al. (2018) Measures of Biologic Age in a Community Sample Predict Mortality and Age-Related Disease: The Framingham Offspring Study. J Gerontol A Biol Sci Med Sci 73:757-762
Sarnowski, ChloƩ; Kavousi, Maryam; Isaacs, Steve et al. (2018) Genetic variants associated with earlier age at menopause increase the risk of cardiovascular events in women. Menopause 25:451-457
Lu, Ake T; Xue, Luting; Salfati, Elias L et al. (2018) GWAS of epigenetic aging rates in blood reveals a critical role for TERT. Nat Commun 9:387
Murabito, Joanne M; Rong, Jian; Lunetta, Kathryn L et al. (2017) Cross-sectional relations of whole-blood miRNA expression levels and hand grip strength in a community sample. Aging Cell 16:888-894
Mahalingaiah, Shruthi; Sun, Fangui; Cheng, J Jojo et al. (2017) Cardiovascular risk factors among women with self-reported infertility. Fertil Res Pract 3:7
Ben-Avraham, Dan; Karasik, David; Verghese, Joe et al. (2017) The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY) 9:209-246
Lin, Honghuang; Lunetta, Kathryn L; Zhao, Qiang et al. (2017) Transcriptome-wide association study of inflammatory biologic age. Aging (Albany NY) 9:2288-2301
Day, Felix R (see original citation for additional authors) (2017) Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat Genet 49:834-841
McCabe, Elizabeth L; Larson, Martin G; Lunetta, Kathryn L et al. (2016) Association of an Index of Healthy Aging With Incident Cardiovascular Disease and Mortality in a Community-Based Sample of Older Adults. J Gerontol A Biol Sci Med Sci 71:1695-1701

Showing the most recent 10 out of 14 publications