2018 Advanced Methods Workshop
June 18, 2018
2:00 – 4:30pm
The SPER Advanced Methods Workshop immediately precedes the SPER annual meeting. The workshop provides researchers and students with an introduction to advanced epidemiologic methods. There are 2 different methods topics covered every year, and registration for the workshop includes admission to both sessions.
Introduction to Epigenetics and high dimensional Epigenome-Wide Association Studies (EWAS) for Perinatal Epidemiology
Presenter: Andres Cardenas
Epidemiologic Evidence without P-values
Presenter: Sonia Hernandez-Diaz
Session Overview: Epigenetic modifications are stable and heritable changes to gene expression that occur without directly changing the underlying DNA sequence. These modifications are responsive to early life exposures and events providing a great opportunity in the field of pediatric and perinatal epidemiology. Epigenetics is a rapidly growing field and many studies including birth cohorts are currently implementing emerging epigenetic technologies and methods to address complex hypotheses and accelerate scientific discovery. This workshop will serve as an introduction to general concepts and methods used in epigenetics applied to birth cohorts for the investigation of fetal programming hypotheses with a focus on high dimensional DNA methylation data analyses. The workshop will present key concepts of study design, sample collection and processing, platforms for analysis, high dimensional data handling and interpretation. In the interest of time, computational methods will be presented by the instructor with the goal of giving participants a working understanding of multiple methods.
Andres Cardenas is a postdoctoral fellow in the Department of Population Medicine at the Harvard Medical School and Harvard Pilgrim Health Care Institute. His research evaluates the role of environmental exposures in utero and epigenetic modifications and their potential role in the developmental origins of health and disease. Dr. Cardenas’ current research examines the prenatal influence of nutrients, hyperglycemia, and exposure to environmental contaminants on the epigenome of infants.
Sonia Hernandez-Diaz, MD, DrPH is a Professor of Epidemiology at the Harvard T.H. Chan School of Public Health. Her area of interest is drug safety evaluation, with a special emphasis on the design, conduct, and analysis of studies in pregnant women and their infants. Another area of interest concerns the application of causal inference approaches to define confounding and selection biases in ways that facilitate the identification, communication, and resolution of common analytical problems in non-randomized studies. Read more
Hernandez-Diaz has published more than 200 articles, papers, and reports in respected clinical and epidemiological journals over the last decade; and has contributed to the development and application of methodology to improve the validity of epidemiological studies in her field. She teaches one of the core epidemiological methods courses at the School of Public Health, as well as multiple invited short courses and lectures at other academic and Government institutions.
Hernandez-Diaz’s research focuses on pregnant women and their infants. In collaboration with colleagues at Brigham and Women’s Hospital, she identified a cohort of more than 2 million low income pregnant women ascertained in multiple large administrative databases from the Medicaid Analytic eXtract (MAX). The MAX, national Medicaid data available from the Centers of Medicare and Medicaid Services, provides a unique opportunity to examine important descriptive, etiologic and comparative safety questions in a national sample. She has recently implemented the same methods to identify cohorts of mothers linked to infants within Electronic Medical Records from the UK (THIN) and an US nationwide commercial claims insurance administrative database (Truven MarketScan Research Data). She has also experience in the use of Scandinavian Registers, case-control surveillance designs, case-only designs, and ad hoc pregnancy cohorts (registries).