The broad, long-term objective of the proposed research is to evaluate the effects of dynamic interplay of genetic, physiological, demographic, and behavioral factors on the age-trajectories of the """"""""systemic"""""""" variables characterizing aging process in humans, risks of development and progression of health disorders in adult and elderly individuals, life span, and free-of-disease life span, using newly elaborated statistical methods. These methods are based on mathematical and computer models of aging, health, and longevity capable of describing longitudinal samples with and without genetic information and estimating age patterns of morbidity and mortality risks, as well as new """"""""systemic"""""""" variables characterizing age-dependent physiological """"""""norm"""""""", rate of allostatic adaptation, levels of accumulated allostatic load, rates of decline in stress resistance, adaptive capacity, and stochasticity, along with the associated risks of morbidity, overall and cause-specific mortality, in the presence of demographic and behavioral factors. Such comprehensive evaluation is possible due to unique information collected in the Framingham Heart (FHS) and Offspring (FHSO) Studies. The unique advantage of these data is a combination of genetic and non-genetic factors, detailed longitudinal information on physiological changes, risks of major chronic diseases and mortality risk. The following specific aims will be addressed: 1) Evaluate the effects of selected genetic polymorphisms on age patterns of morbidity and mortality rates. 2) Evaluate time trends in the respective morbidity/mortality age patterns and estimate their alteration for the selected polymorphisms. 3) Evaluate the effects of selected genetic polymorphisms on the age-trajectories of physiological indices and new """"""""systemic"""""""" variables. 4) Examine the effects of additive superposition and nonlinear interaction of the selected physiological indices and genetic characteristics. 5) Evaluate the effect of genetic factors on trends in the new """"""""systemic"""""""" variables and morbidity and mortality age patterns. This research is directly relevant to public health, as it focuses on a sample of the U.S. adult and elderly individuals and proposes evaluation of the most important characteristics of aging organisms linking them with genetic information. These characteristics are of great importance for developing targeted approach in disease prevention and medical intervention for aging individuals.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
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Social Sciences and Population Studies Study Section (SSPS)
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Rossi, Winifred K
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Duke University
Social Sciences
Schools of Arts and Sciences
United States
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Yashin, Anatoliy I; Arbeev, Konstantin G; Wu, Deqing et al. (2016) How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data. N Am Actuar J 20:201-232
Kulminski, Alexander M; Arbeev, Konstantin G; Culminskaya, Irina et al. (2014) Age, gender, and cancer but not neurodegenerative and cardiovascular diseases strongly modulate systemic effect of the Apolipoprotein E4 allele on lifespan. PLoS Genet 10:e1004141
Kulminski, Alexander M (2013) Unraveling genetic origin of aging-related traits: evolving concepts. Rejuvenation Res 16:304-12
Kulminski, Alexander M; Culminskaya, Irina; Arbeev, Konstantin G et al. (2013) Trade-off in the effect of the APOE gene on the ages at onset of cardiocascular disease and cancer across ages, gender, and human generations. Rejuvenation Res 16:28-34
Kulminski, Alexander M; Culminskaya, Irina; Yashin, Anatoli I (2013) Inter-chromosomal level of genome organization and longevity-related phenotypes in humans. Age (Dordr) 35:501-18
Yashin, Anatoliy I; Arbeev, Konstantin G; Wu, Deqing et al. (2013) How lifespan associated genes modulate aging changes: lessons from analysis of longitudinal data. Front Genet 4:3
Kulminski, Alexander M; Culminskaya, Irina; Arbeev, Konstantin G et al. (2013) The role of lipid-related genes, aging-related processes, and environment in healthspan. Aging Cell 12:237-46
Yashin, A I; Arbeev, K G; Akushevich, I et al. (2012) The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. Phys Life Rev 9:177-88; discussion 195-7
Arbeev, Konstantin G; Ukraintseva, Svetlana V; Kulminski, Alexander M et al. (2012) Effect of the APOE Polymorphism and Age Trajectories of Physiological Variables on Mortality: Application of Genetic Stochastic Process Model of Aging. Scientifica (Cairo) 2012:
Yashin, Anatoliy I; Wu, Deqing; Arbeev, Konstantin G et al. (2012) Polygenic effects of common single-nucleotide polymorphisms on life span: when association meets causality. Rejuvenation Res 15:381-94

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