An emerging problem for societies in developed countries is extending years of healthy life. Specialists in biology and genetics argue that major breakthrough in the field can be achieved by revealing genetic variants which can be involved in regulation of phenotypes characterizing health, wellbeing and survival in late life. A puzzling problem is that phenotypes in late life are not the result of direct evolutionary selection that reinforces the role of the life course processes shaping genetic effects on health, wellbeing and survival within and across generations. Analysis of the role of the life course in genetic effects s not in mainstream of standard strategies of genome-wide association studies. The objective of this proposal is to identify systemic contribution of genetic and non-genetic factors to health, wellbeing, and survival over the life course by revealing associations of genetic factors with physiological and behavioral endophenotypes (EPs), by identifying their roles in risks of morbidity (cardiovascular disease (CVD) and cancer), disability, mortality, and mortality attributed to CVD and cancer, by elucidating the role of life-course related processes in shaping genetic effects on the risk outcomes, and by integrating the effects of genetic factors with the lie course in men and women within and across generations. To achieve this goal, we will use rich data on individuals from different generations longitudinally followed in the Framingham Heart Study, Health and Retirement Study linked with Medicare data, the Coronary Artery Risk Development in Young Adults study, and the Long Life Family Study. The following Specific Aims will be addressed.
Aim 1. Construction of phenotypes.
Aim 2. Identification of genetic associations with EPs.
Aim 3. Identification of genetic associations with risks of morbidity, disability, and mortality.
Aim 4. Elucidating systemic role of the revealed genetic variants in health, wellbeing, and survival and conducting dynamic integration.
Aim 5. Dissecting biological role of genes for the revealed SNPs.
This project is inherently relevant to public health because its results will address concerns on translation of genetic insights in practice. Specifically, new information on pleiotropic genetic effects will be inherently useful for evaluating potential side effects of medical interventions. New information on improved specification of genetic profiles of individuals at excessive health and mortality risks will be important for development and testing new drugs.
|Kulminski, Alexander M; Huang, Jian; Wang, Jiayi et al. (2018) Apolipoprotein E region molecular signatures of Alzheimer's disease. Aging Cell :e12779|
|Kulminski, Alexander M; Huang, Jian; Loika, Yury et al. (2018) Strong impact of natural-selection-free heterogeneity in genetics of age-related phenotypes. Aging (Albany NY) 10:492-514|
|He, Liang; Culminskaya, Irina; Loika, Yury et al. (2018) Causal effects of cardiovascular risk factors on onset of major age-related diseases: A time-to-event Mendelian randomization study. Exp Gerontol 107:74-86|
|Doherty, Aoife; Kernogitski, Yelena; Kulminski, Alexander M et al. (2017) Identification of polymorphisms in cancer patients that differentially affect survival with age. Aging (Albany NY) 9:2117-2136|
|He, Liang; Zhbannikov, Ilya; Arbeev, Konstantin G et al. (2017) A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data. Genet Epidemiol 41:620-635|
|Moskalev, Alexey; Anisimov, Vladimir; Aliper, Aleksander et al. (2017) A review of the biomedical innovations for healthy longevity. Aging (Albany NY) 9:7-25|
|Kulminski, Alexander M; Kernogitski, Yelena; Culminskaya, Irina et al. (2017) Uncoupling associations of risk alleles with endophenotypes and phenotypes: insights from the ApoB locus and heart-related traits. Aging Cell 16:61-72|
|Kulminski, Alexander M; He, Liang; Culminskaya, Irina et al. (2016) Pleiotropic Associations of Allelic Variants in a 2q22 Region with Risks of Major Human Diseases and Mortality. PLoS Genet 12:e1006314|
|Kulminski, Alexander M; Loika, Yury; Culminskaya, Irina et al. (2016) Explicating heterogeneity of complex traits has strong potential for improving GWAS efficiency. Sci Rep 6:35390|
|He, Liang; Sillanpää, Mikko J; Silventoinen, Karri et al. (2016) Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models. Genetics 202:1313-28|
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