Yashin researches aging, with expertise in developing mathematical and statistical methods of analysis of genetic and non-genetic data on aging, health, and survival using data collected in various longitudinal human studies. His major research interest is in understanding mechanisms regulating rates of physiological aging changes, age-associated health decline, and longevity, with emphases on complex connections between these traits, on interacting genetic and non-genetic factors in longevity and age-associated diseases, and on polygenic effects on health and survival.
He has more than twenty years of experience in the field and a strong record of more than 200 peer-reviewed publications, including in high impact journals (such as Science and Nature group). He has authored and co-authored a number of novel approaches to the analysis of survival and longitudinal data, including new methods for studying aging, health, and longevity in twins and other related individuals (e.g., family members), methods for studying effects of stress on survival and longevity as well as new methods of analyzing longitudinal data. These methods were further extended and applied to the longitudinal data with subsets of genetic data, including in FHS.
Prior to Duke, he was a professor at Odense University in Denmark and later served as the Head of the Laboratory of Advanced Statistical Methods at the Max Planck Institute of Demographic Research, where he performed intensive studies of the role of genes in human life span using survival data on Danish, Swedish, and Finnish twins using unique data from three Scandinavian twin registers.
At Duke, Yashin has worked as a principle investigator on several NIH funded grants. His current research emphasis is on the use of dynamic biomarkers of aging to predict survival, and on the effects of interacting between genetic and non-genetic factors on longevity and age-associated diseases. His research group has developed new methods of genetic analysis of the life span in centenarian studies. They have also developed methods of genetic analysis of incomplete genetic data and dynamic models, and effective statistical methods capable of analyzing genetic and phenotypic information collected for participants of Framingham and other longitudinal studies of aging, health and longevity. The results of this research are reflected in more than 50 recent papers published during the last 5 years.