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I am a social epidemiologist and serve as an Associate Professor in the Department of Epidemiology and Population Health and in the Department of Medicine in the Division of Primary Care and Population Health. I joined the faculty at Stanford School of Medicine in 2011. I am currently the co-director of the Stanford Center for Population Health Sciences. In this position I am committed to making high value data resources available to researchers across disciplines in order to better enable them to answer their most pressing clinical and population health questions.My own research is focused on understanding the health implications of the myriad decisions that are made by corporations and governments every day - decisions that profoundly shape the social and economic worlds in which we live and work. While these changes are often invisible to us on a daily basis, these seemingly minor actions and decisions form structural nudges that can create better or worse health at a population level. My work demonstrates the health implications of corporate and governmental decisions that can give the public and policy makers evidence to support new strategies for promoting health and well-being. In all of his work, I have a focus on the implications of these exposures for health inequalities.Since often policy and programmatic changes can take decades to influence health, my work also includes more basic research in understanding biological signals that may act as early warning signs of systemic disease, in particular accelerated aging. I examine how social and economic policy changes influence a range of early markers of disease and aging, with a particular recent focus on DNA methylation. I am supported by several grants from the National Institute on Aging and the National Institute on Minority Health and Health Disparities to develop new more sensitive ways to understand the health implications of social and economic policy changes.
Research on DNA methylation has uncovered remarkable correlations with age, far stronger than previous putative biomarkers of aging. Although these findings are promising, it remains unknown whether DNA methylation patterns contribute to population differences in healthy aging and longevity. To address this question, we will build on our prior work in the demographically well-defined high longevity population of the Nicoya Peninsula in Costa Rica, to identify key DNA methylation signatures underlying the low levels of frailty and high longevity of this population. We will build on prior characterizations of DNA methylation associated with aging to support our central hypothesis that environmental exposures become biologically encoded in DNA methylation and have important associations with healthy aging. We will then examine how these identified signatures relate to healthy aging in Canada. The innovation of this proposal is that we will be analyzing differences in DNA methylation profiles that are modifiable by the environment and characteristic of a population.
Profs. Marcel Goldberg and Marie Zins are leading one of the largest detailed population based cohorts to date in the CONSTANCES cohort in France. While currently in the United States the largest population based cohort to study the social, economic and genetic factors influencing healthy aging is the Health and Retirement Study which has a sample size of around 25,000 for most samples, the CONSTANCES cohort follows 200,000 individuals, with even more detailed socioeconomic, geographic and biological data than the most comparable U.S. studies. The unprecedented size and comprehensiveness of the CONSTANCES cohort will allow fundamentally new discoveries in terms of isolated effects within population subgroups and higher order interactions. Many of the statistical methods to achieve these discoveries have been developed by faculty in the Statistics department at Stanford University and other members of the Stanford faculty are leaders in the application of these methods. The proposed project will foster a collaboration of the application of machine learning methods for examining heterogeneity of treatment effects in the CONSTANCES cohort. In addition, learning about the implementation and promise of very large, detailed cohort studies will inform the early stages of related research efforts in the United States, such as the newly proposed Precision Medicine Initiative cohort of 1,000,000 individuals.