David Ferguson PhD
Assistant Professor
Michigan State University
Department of Kinesiology
“Early life nutrition influences cardiac function and exercise capacity"
The Developmental Origins of Health and Disease Hypothesis (DoHAD) states that a brief period of malnutrition in early life could cause permanent physiological changes that would lead to a higher incidence of chronic disease later in life. This is supported by studies on populations that experienced famine during the neonatal period whom present with a higher incidence of cardiovascular disease later in adult life. The DoHAD hypothesis has been observed not only in human studies but also mice, sheep, pigs, and rats. However, there is limited information regarding the mechanistic pathways responsible for the higher incidence of cardiovascular disease as a result of developmental programing, thereby limiting the potential for therapeutic countermeasures. The goal of our lab is to identify these epigenetic changes and improve cardiac function.
Abdul El-Sayed, MD, DPhil
Executive Director & Health Officer
Detroit Health Department
‘Between Health Science and Policy: Reflections from Detroit’
Health science is fundamentally applied - we pursue biostatistical, epidemiologic, and health policy research with the aspiration of tangibly improving the health of populations with this knowledge. Dr. Abdul El-Sayed was appointed Executive Director of the Detroit Health Department and Health Officer for the City of Detroit in August 2015. Previously, he was Assistant Professor of Epidemiology at Columbia University. In this Talk, Dr. El-Sayed reflects on the advice he would have given himself as an epidemiologist from his current position in Detroit, with generalizable observations about the policy process and the limits of policymaking from research. Dr. El-Sayed will also discuss the social epidemiology of Detroit and his plans for integrating the health sciences into the core of the Detroit Health Department.
Cancelled due to winter storm
Enrique Schisterman, PhD
Chief and Senior Investigator, Epidemiology Branch
National Institute of Health
Enrique F. Schisterman, Ph.D., is a senior investigator and chief of the Epidemiology Branch. He earned both his master's degree in Statistics and his doctorate degree in Epidemiology from the State University of New York, Buffalo. Overall, his research interests focus on epidemiological methods and reproductive epidemiology. He has specific interests in biomarkers and their impact on general health, particularly women's health (i.e., endometriosis, infertility, and menstrual cycle function).
"Pooling Bio-Markers as a Cost-Effective Design"
Evaluating biomarkers in epidemiological studies can be expensive and time consuming. Many investigators use techniques such as random sampling or pooling biospecimens in order to cut costs and save time on experiments. Commonly, analyses based on pooled data are strongly restricted by distributional assumptions that are challenging to validate because of the pooled biospecimens. Random sampling provides data that can be easily analyzed. However, random sampling methods are not optimal cost-efficient designs for estimating means. We propose and examine a cost-efficient hybrid design that involves taking a sample of both pooled and unpooled data in an optimal proportion in order to efficiently estimate the unknown parameters of the biomarker distribution.
"Aspirin restores diminished pregnancy and live birth rates in women with low-grade inflammation."
Inflammation contributes to many diseases, and is an increasingly recognized factor in certain causes of infertility. Inflammation may impact live birth rates, and may identify women who would benefit from anti-inflammatory therapy with aspirin. Thus, our objective was to investigate whether pre-pregnancy C-reactive protein (hsCRP), as a marker of low-grade chronic inflammation, could identify women who have improvement in clinical pregnancy and live birth rates from preconception-initiated low dose aspirin (LDA) therapy. This analysis was a secondary, stratified analysis of the Effects of Aspirin in Gestation and Reproduction (EAGeR), a multi-center, block-randomized, double-blind, placebo-controlled trial. Participants were women aged 18-40 (N=1228) years with a history of one or two pregnancy losses actively attempting to conceive. Women were stratified by tertile of pre-pregnancy, pre-intervention serum hsCRP (low: <0.70 mg/L; mid: 0.70- <1.95 mg/L; high: ≥1.95 mg/L). Daily LDA plus folic acid was compared with matching placebo plus folic acid for up to six menstrual cycles while attempting pregnancy and through 36 weeks gestation in women who conceived.
Michelle Mielke, PhD | View Seminar
Associate Professor of Epidemiology and Neurology
Health Sciences Research, Mayo Clinic
“Understanding the role of sphingolipids in neurodegeneration diseases and depression: from basic science to epidemiology”
Cellular and animal studies suggest that sphingolipids may cause or accelerate amyloid-beta (Aβ), tau, and alpha-synuclein pathology, thereby contributing to the etiopathogenesis of Alzheimer’s disease (AD), Parkinson’s disease (PD), and Lewy Body Dementia (DLB). Sphingolipids have also been linked to major depression, which is common in all three of these neurodegenerative conditions. These findings suggest a potential common pathway for multiple neurodegenerative and neuropsychiatric diseases. However, despite the abundant pre-clinical research, little research has extended or translated these findings to humans. This talk will first discuss the basic science research supporting associations between sphingolipids and AD, PD, and DLB pathology. Next, epidemiological evidence will be examined, demonstrating associations between sphingolipids and clinical and neuroimaging or neuropathological measures of each neurodegenerative disease. Lastly, ongoing research into the utility of sphingolipids as biomarkers will be discussed as will and the potential therapeutic implications.
Mark Klebanoff, MD, MPH | View Seminar | Luncheon Lecture
Professor of Pediatrics and OB/GYN at The Ohio State University College of Medicine,
and Professor of Epidemiology at the Ohio State University College of Public Health
“Maternal methylxanthine metabolites and reproductive, perinatal and pediatric outcomes”
In spite of maternal consumption of caffeine and related alkaloids being among the most studied of all pregnancy exposures, 35 years of research has not produced consistent results. In addition, very few studies have evaluated child outcomes beyond the immediate neonatal period, and almost all studies have assessed maternal intake by self-report only. The presentation will describe the association with serum biomarkers for caffeine and other methylxanthine compounds with pregnancy outcomes and child growth and development. The advantages and disadvantages of employing a biomarker for intake will be discussed.
Li-Shiun Chen, MD, ScD, MPH | View Seminar
Assistant Professor
Department of Psychiatry
Washington University School of Medicine, St. Louis
"Precision Medicine – From smoking to cessation"
Li-Shiun Chen, MD, MPH, ScD is a physician scientist with significant experience in psychiatry, epidemiology and psychiatric genetics. Her research areas include 1) the use of genetic information to inform clinical diagnoses, treatments, and public health and 2) smoking cessation in the general population and high risk populations. She is the Principal Investigator of a NIDA-funded R01 award entitled Genetically Informed Smoking Cessation Trial which examines how genetic markers can be used to inform treatments. She is also currently funded by a NIDA career development award to investigate genetic and environmental risks for smoking cessation. She led the work on the pharmacogenetics of smoking cessation treatments involving both pharmacokinetic and pharmacodynamic markers, and how genetics informs risk of smoking related diseases such as lung cancer. Her goal is to generate evidence for future genetically informed treatments allowing patients to be matched with treatments that maximize efficacy and minimize side effects and precise clinical risk prediction.