We propose to comprehensively characterize exceptionally healthy aging and its determinants measured across the adult life span in two generations of community-dwelling adults. Risk factors (RFs) and behaviors associated with common conditions have been found to predict healthy aging. It is not known whether the trajectory of RF changes occurring over the adult life span is associated with a greater impact on healthy aging than RF levels averaged over time or RFs measured in old age. Genetic factors related to longevity and healthy aging remain largely unknown. Given the complexity of human aging, it is likely that many genes contribute to a broad network of basic functions underlying aging. Data from the longitudinal Framingham Heart Study (FHS) original cohort and offspring cohort (adult children of the original cohort and their spouses) can be used to track RF levels over the adult life span, document the occurrence of disease, and relate RF trajectories to aging. The FHS has a comprehensive genetics database that can be used to identify genetic factors related to longevity and healthy aging. We postulate that improvements in exceptionally healthy aging, defined as the absence of comorbidity, physical and cognitive impairment, and frailty, are directly related to decreases in lifetime levels of RFs and behaviors known to predict cardiovascular and other major diseases. We propose to examine the contribution of genetic determinants to longevity and healthy aging traits using heritability and genome-wide association studies (GWAS). The proposal has the following specific aims:
Aim 1. To characterizes the prevalence of exceptionally healthy aging among FHS original cohort and offspring cohort who survive to at least age 65 years.
Aim 2. To examine whether early and mid-adulthood trajectories of prospectively measured RFs and overall Framingham risk score are better predictors of healthy aging compared to RF levels obtained at old age or RF levels averaged over time.
Aim 3. To estimate the genetic contribution to the variance in longevity and healthy aging using a heritability analysis.
Aim 4. To identify genetic variants that influence heritable longevity and healthy aging phenotypes through a GWAS using extant genotyping data from a 550k genome scan. Insights from this project may contribute fundamentally to the understanding of the mechanisms responsible for healthy aging and in turn identify directions for health promotion and disease prevention efforts in middle-aged and older adults so that older persons can enjoy more time in good health.

Public Health Relevance

Surveillance of the health of older adults and identification of factors, both genetic and non-genetic, that promote a long and healthy life are important public health priorities. Knowledge gained from this proposal may lead to interventions that prevent age-related disease and disability so that older persons spend more time in good health.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG029451-03
Application #
7803575
Study Section
Special Emphasis Panel (ZRG1-HOP-D (02))
Program Officer
Rossi, Winifred K
Project Start
2008-05-01
Project End
2012-04-30
Budget Start
2010-05-01
Budget End
2011-04-30
Support Year
3
Fiscal Year
2010
Total Cost
$378,953
Indirect Cost
Name
Boston University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
604483045
City
Boston
State
MA
Country
United States
Zip Code
02118
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
Matteini, Amy M; Tanaka, Toshiko; Karasik, David et al. (2016) GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium. Aging Cell 15:792-800
Zhuang, Wei Vivian; Murabito, Joanne M; Lunetta, Kathryn L (2016) Phenotypically Enriched Genotypic Imputation in Genetic Association Tests. Hum Hered 81:35-45
Pilling, L C; Joehanes, R; Kacprowski, T et al. (2016) Gene transcripts associated with muscle strength: a CHARGE meta-analysis of 7,781 persons. Physiol Genomics 48:1-11
Chen, Brian H; Marioni, Riccardo E; Colicino, Elena et al. (2016) DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY) 8:1844-1865
Pilling, Luke C; Atkins, Janice L; Bowman, Kirsty et al. (2016) Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants. Aging (Albany NY) 8:547-60
Liu, Christine K; Lyass, Asya; Larson, Martin G et al. (2016) Biomarkers of oxidative stress are associated with frailty: the Framingham Offspring Study. Age (Dordr) 38:1
Therkelsen, Kate E; Pedley, Alison; Hoffmann, Udo et al. (2016) Intramuscular fat and physical performance at the Framingham Heart Study. Age (Dordr) 38:31
Demirkan, A; Lahti, J; Direk, N et al. (2016) Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies. Psychol Med 46:1613-23
Broer, Linda; Buchman, Aron S; Deelen, Joris et al. (2015) GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J Gerontol A Biol Sci Med Sci 70:110-8

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