Genetic Structures of Population Cohorts Change with Increasing Age: Implications for Genetic Analyses of Human aging and Life Span.
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2017-06-02
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Abstract
BACKGROUND: Correcting for the potential effects of population stratification is an important issue in genome wide association studies (GWAS) of complex traits. Principal component analysis (PCA) of the genetic structure of the population under study with subsequent incorporation of the first several principal components (PCs) in the GWAS regression model is often used for this purpose. PROBLEM: For longevity related traits such a correction may negatively affect the accuracy of genetic analyses. This is because PCs may capture genetic structure induced by mortality selection processes in genetically heterogeneous populations. DATA AND METHODS: We used the Framingham Heart Study data on life span and on individual genetic background to construct two sets of PCs. One was constructed to separate population stratification due to differences in ancestry from that induced by mortality selection. The other was constructed using genetic data on individuals of different ages without attempting to separate the ancestry effects from the mortality selection effects. The GWASs of human life span were performed using the first 20 PCs from each of the selected sets to control for possible population stratification. RESULTS: The results indicated that the GWAS that used the PC set separating population stratification induced by mortality selection from differences in ancestry produced stronger genetic signals than the GWAS that used PCs without such separation. CONCLUSION: The quality of genetic estimates in GWAS can be improved when changes in genetic structure caused by mortality selection are taken into account in controlling for possible effects of population stratification.
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Scholars@Duke
Anatoli I. Yashin
Dequing Wu
Konstantin Arbeev
Konstantin G. Arbeev received the M.S. degree in Applied Mathematics from Moscow State University (branch in Ulyanovsk, Russia) in 1995 and the Ph.D. degree in Mathematics and Physics (specialization in Theoretical Foundations of Mathematical Modeling, Numerical Methods and Programming) from Ulyanovsk State University (Russia) in 1999. He was a post-doctoral fellow in Max Planck Institute for Demographic Research in Rostock (Germany) before moving to Duke University in 2004 to work as a Research Scientist and a Senior Research Scientist in the Department of Sociology and the Social Science Research Institute (SSRI). He is currently an Associate Research Professor in SSRI. Dr. Arbeev's major research interests are related to three interconnected fields of biodemography, biostatistics and genetic epidemiology as pertains to research on aging. The focus of his research is on discovering genetic and non-genetic factors that can affect the process of aging and determine longevity and healthy lifespan. He is interested in both methodological advances in this research area as well as their practical applications to analyses of large-scale longitudinal studies with phenotypic, genetic and, recently, genomic information. Dr. Arbeev authored and co-authored more than 150 peer-reviewed publications in these areas.
Svetlana Ukraintseva
Dr. Ukraintseva studies the causes of human aging and the associated decline in whole-body resilience, with the goal of identifying genetic and other factors that drive this decline and contribute to the age-related increase in all-cause mortality risk, ultimately limiting longevity even in individuals without major diseases. She also investigates the “multi-hit” mechanism of Alzheimer’s disease and the complex, including trade‑off–like, relationships between Alzheimer’s disease and cancer. She actively explores the role of infectious diseases and compromised immunity in Alzheimer’s development, as well as the interplay between vaccines and genetic factors, to advance personalized vaccine repurposing for AD prevention. To address these questions, Dr. Ukraintseva and her team analyze large human datasets containing comprehensive information on millions of individuals. She is a PI and key investigator on several NIH-funded grants and has authored more than 150 peer‑reviewed publications, including in major journals such as JAMA, Nature group journals, Stroke, Alzheimer’s & Dementia, and others.
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