Project 2 The objective of the Project 2 is to significantly improve our understanding of complex genetic regulation of human aging, and investigate relevance of genetic factors influencing physiological aging changes in body to risks of major diseases and to longevity. To address this objective, we will identify genetic variants which individually and jointly influence markers of physiologicalaging specified in this project, using sets of longitudinal human data available through dbGaP. A special emphasis of the research will be on pleiotropic effects (both antagonistic and non-antagonistic) of a genotype on different traits, and on one trait at different ages.
Specific Aims : 1) Evaluate individual and additive polygenic influence of SNPs on markers of physiological aging. For this we will conduct a hypothesis-free GWAS of aging phenotypes specified in this project and evaluate individual and joint (additive) effects of selected genetic variants on the aging phenotypes, using polygenic risk scores;2) Investigate pleiotropic (both antagonistic and non-antagonistic) effects of individual SNPs and polygenic scores evaluated in Aim 1 on aging traits specified in this project, and on health and longevity traits evaluated in two other projects. We will test hypotheses about the pleiotropic (including trade-offs)influence of a genotype on: (i) different traits;and (ii) one trait at different ages. 3) Investigate functional relationships among genes/regulatory elements linked to SNPs detected in Aim1. For this, we will use online resources and tools for SNPs/genes/proteins annotating, gene-to-function and pathway analysis, to specify biological functions most relevant to the detected genes, and investigate their involvement in known aging pathways and networks. 4) Evaluate epistatic genetic influence on markers of physiological aging. We will select subsets of SNPs for their: a) pleiotropic effects on aging phenotypes detected in Aim 2;b) relation to genes involved in similar biological functions in Aim 3;c) involvement in aging-related pathways. For these subsets of SNPs, we will evaluate epistatic genetic effects on aging phenotypes.Results of this study will significantly improve our understanding of genetic regulation of aging, and its role in health and longevity.

Public Health Relevance

The study addresses complex genetic regulation of aging and among genetic factors affecting aging, health and longevity. Understanding these relationships is critically important for public health and will help developing optimal strategies of extending lifespan along with prolonging youth and healthy periods of life.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
1P01AG043352-01A1
Application #
8668231
Study Section
Special Emphasis Panel (ZAG1-ZIJ-8 (J2))
Project Start
Project End
Budget Start
2014-06-15
Budget End
2015-04-30
Support Year
1
Fiscal Year
2014
Total Cost
$320,132
Indirect Cost
$116,226
Name
Duke University
Department
Type
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Yashin, Anatoliy I; Arbeev, Konstantin G; Arbeeva, Liubov S et al. (2016) How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity. Biogerontology 17:89-107
Yashin, Anatoliy I; Zhbannikov, Ilya; Arbeeva, Liubov et al. (2016) Pure and Confounded Effects of Causal SNPs on Longevity: Insights for Proper Interpretation of Research Findings in GWAS of Populations with Different Genetic Structures. Front Genet 7:188
Ukraintseva, Svetlana; Yashin, Anatoliy; Arbeev, Konstantin et al. (2016) Puzzling role of genetic risk factors in human longevity: ""risk alleles"" as pro-longevity variants. Biogerontology 17:109-27
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
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
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
Kulminski, Alexander M; Raghavachari, Nalini; Arbeev, Konstantin G et al. (2016) Protective role of the apolipoprotein E2 allele in age-related disease traits and survival: evidence from the Long Life Family Study. Biogerontology 17:893-905
Arbeev, Konstantin G; Cohen, Alan A; Arbeeva, Liubov S et al. (2016) Optimal Versus Realized Trajectories of Physiological Dysregulation in Aging and Their Relation to Sex-Specific Mortality Risk. Front Public Health 4:3
Arbeev, Konstantin G; Ukraintseva, Svetlana V; Yashin, Anatoliy I (2016) Dynamics of biomarkers in relation to aging and mortality. Mech Ageing Dev 156:42-54
Kulminski, Alexander M; Culminskaya, Irina; Arbeev, Konstantin G et al. (2015) Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies. PLoS One 10:e0136319

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