Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data.


Small sample size of genetic data is often a limiting factor for desirable accuracy of estimated genetic effects on age-specific risks and survival. Longitudinal non-genetic data containing information on survival or disease onsets of study participants for whom the genetic data were not collected may provide an additional "reserve" for increasing the accuracy of respective estimates. We present a novel method for joint analyses of "genetic" (covering individuals for whom both genetic information and mortality/morbidity data are available) and "non-genetic" (covering individuals for whom only mortality/morbidity data were collected) subsamples of longitudinal data. Our simulation studies show substantial increase in the accuracy of estimates in such joint analyses compared to analyses based on genetic subsample alone. Application of this method to analysis of the effect of common apolipoprotein E (APOE) polymorphism on survival using combined genetic and non-genetic subsamples of the Framingham Heart Study original cohort data showed that female, but not male, carriers of the APOE e4 allele have significantly worse survival than non-carriers, whereas empirical analyses did not produce any significant results for either sex.





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Publication Info

Arbeev, Konstantin G, Svetlana V Ukraintseva, Liubov S Arbeeva, Igor Akushevich, Alexander M Kulminski and Anatoliy I Yashin (2011). Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data. Biogerontology, 12(2). pp. 157–166. 10.1007/s10522-010-9316-1 Retrieved from https://hdl.handle.net/10161/14856.

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Konstantin Arbeev

Associate Research Professor in the Social Science Research Institute

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

Research Professor in the Social Science Research Institute

Dr. Ukraintseva studies causes of human aging and related decline in resilience, to identify genetic and other factors responsible for the increase in mortality risk with age eventually limiting longevity. She explores complex relationships, including trade-offs, between physiological aging-changes and risks of major diseases (with emphasis on Alzheimer’s and cancer), as well as survival, to find new genetic and other targets for anti-aging interventions and disease prevention. She also investigates possibilities of repurposing of existing vaccines and treatments for AD prevention and interventions into the aging. For this, Dr. Ukraintseva and her team use data from several large human studies containing rich genetic and phenotypic information (including longitudinal measurements) on thousands of individuals. Dr. Ukraintseva is a PI and Key Investigator on several NIH funded grants, and has more than 130 peer-reviewed publications, including in major journals such as Nature Reviews, Stroke, European Journal of Human Genetics, and some other.

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