We will exploit the multicenter Long Life Family Study (LLFS), a unique resource for research on human longevity and healthy aging, to find genetic variants associated with these traits. In the current period, we successfully enrolled and extensively phenotyped 4,953 individuals in 539 two-generational families that demonstrate clustering for exceptional survival in the upper generation. Fewer than 1% of the Framingham Heart Study (FHS) families (a roughly random sample of families) would meet the minimal entrance criteria for exceptional survival required in the LLFS. Thus our least exceptional families show more clustering for exceptional longevity than 99% of the Framingham families. Further, the children's generation have significantly lower rates of major diseases of aging including diabetes, chronic pulmonary disease, peripheral artery disease and show significantly more favorable profiles of quantitative mariners of healthy aging such as blood pressure, lipids, functional performance, and cognitive indices compared to FHS. These endophenotypes show greater clustering (with high heritability) in the LLFS familiesthan in FHS. Thus, LLFS has likely greatly enriched the prevalence of any gene variants for longevity and healthy aging endophenotypes, thereby increasing detection power. Most importantly, the family design of LLFS provides additional power and analytic opportunities to discover genetic influences than would be possible in a study of unrelated individuals, especially with regard to rare alleles.
Our specific aims are to: 1) continue phenotyping by assaying biomarkers of healthy aging on stored samples, annually tracking subjects for new significant medical and health events, and comparing Medicare (and Danish equivalent) disease and utilization data with reference samples;2) identiy common genetic variants for healthy aging and excepional survival using GWAS;3) identify rare variants for exceptional survival and healthy aging by targeted sequencing;and 4) more clearly dissect the genetic architecture of exceptional survival an healthy aging through a systems approach involving genet networks and pathways, to better understand the complex interplay between genetic variants, exposures, and covariates in the development of endophenotypes. Taking a multidisciplinary approach involving clinicians, demographers, geneticists, epidemiologists, and computational scientists, we propose to capitalize on the investments already made in creating this unique cohort to further our understanding of the nature of exceptional survival and healthy aging.

Public Health Relevance

Exceptional longevity and healthy aging are highly enriched in the families enrolled in the LLFS thus allowing us a unique opportunity to discover both common and rare genetic associations with these traits. Such associations will not only markedly enhance our understanding of why some people age so much better than others, but will also lead to enhanced prognostication for healthy and unhealthy aging and potentially disease prevention strategies.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZAG1-ZIJ-8 (M2))
Program Officer
Dutta, Chhanda
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Washington University
Schools of Medicine
Saint Louis
United States
Zip Code
Sun, Fangui; Sebastiani, Paola; Schupf, Nicole et al. (2015) Extended maternal age at birth of last child and women's longevity in the Long Life Family Study. Menopause 22:26-31
An, Ping; Miljkovic, Iva; Thyagarajan, Bharat et al. (2014) Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: the Long Life Family Study (LLFS). Metabolism 63:461-8
Zhang, Qunyuan; Wang, Lihua; Koboldt, Dan et al. (2014) Adjusting family relatedness in data-driven burden test of rare variants. Genet Epidemiol 38:722-7
Cosentino, Stephanie; Schupf, Nicole; Christensen, Kaare et al. (2013) Reduced prevalence of cognitive impairment in families with exceptional longevity. JAMA Neurol 70:867-74
Barral, Sandra; Cosentino, Stephanie; Costa, Rosann et al. (2013) Exceptional memory performance in the Long Life Family Study. Neurobiol Aging 34:2445-8
Schupf, Nicole; Barral, Sandra; Perls, Thomas et al. (2013) Apolipoprotein E and familial longevity. Neurobiol Aging 34:1287-91
Province, Michael A; Borecki, Ingrid B (2013) A correlated meta-analysis strategy for data mining "OMIC" scans. Pac Symp Biocomput :236-46
Elo, Irma T; Mykyta, Laryssa; Sebastiani, Paola et al. (2013) Age validation in the long life family study through a linkage to early-life census records. J Gerontol B Psychol Sci Soc Sci 68:580-5
Kulminski, Alexander M; Arbeev, Konstantin G; Christensen, Kaare et al. (2011) Do gender, disability, and morbidity affect aging rate in the LLFS? Application of indices of cumulative deficits. Mech Ageing Dev 132:195-201
Newman, Anne B; Glynn, Nancy W; Taylor, Christopher A et al. (2011) Health and function of participants in the Long Life Family Study: A comparison with other cohorts. Aging (Albany NY) 3:63-76

Showing the most recent 10 out of 14 publications