Overview
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.
Current Appointments & Affiliations
Recent Publications
Towards personalized vaccine repurposing for Alzheimer's prevention: genotype-specific protective association of the shingles vaccine with odds of Alzheimer's disease in participants of two large cohort studies.
Journal Article BMC neurology · February 2026 Full text CiteWhole blood transcriptional signatures of age and survival identified in long life family and integrative longevity omics studies.
Journal Article GeroScience · February 2026 Although aging is a universal event, some individuals are able to achieve extreme longevity. The Long-Life Family Study (LLFS) enrolls participants from families enriched with long-lived individuals, serves as a valuable dataset for studying ageing phenoty ... Full text CiteDevelopment of an Exact Theory of Decomposing Population Attributable Fractions and Application to Decomposition of Alzheimer's Disease Risk.
Journal Article Mathematical population studies · January 2026 A new mathematically exact method of population attributable fraction (PAF) decomposition free of limitations inherent in existing approaches was developed and compared to existing methods based on the Miettinen, Norton, and Niedhammer-Chastang formulae. T ... Full text CiteRecent Grants
The Long Life Family Study
ResearchSenior Investigator · Awarded by Washington University in St. Louis · 2019 - 2030Leveraging population-based human data to uncover mechanisms connecting Alzheimer's disease and common infections and facilitate vaccines repurposing for AD prevention
ResearchCo-Principal Investigator · Awarded by National Institutes of Health · 2021 - 2027Dissecting genetic and non-genetic heterogeneity in predisposition to Alzheimer's disease and vascular traits in pleiotropic context
ResearchSenior Investigator · Awarded by National Institutes of Health · 2020 - 2026View All Grants