Spring 2019 Seminars


Jennifer Smith, PhD, MPH | View Seminar
Assistant Professor
Department of Epidemiology, School of Public Health
Survey Research Center, Institute for Social Research
University of Michigan

"A Social Epigenomic Approach to Cardiovascular Health Disparities"

Low socioeconomic status (SES) and unfavorable neighborhood conditions are associated with increased risk of cardiovascular morbidity and mortality. The persistent stress associated with socioeconomic and neighborhood exposures may lead to dysregulation of the stress reactivity and inflammatory pathways, potentially mediated through epigenetic mechanisms such as DNA methylation. In this talk, findings from recent candidate gene and epigenome-wide association study (EWAS) approaches using data from the Multi-Ethnic Study of Atherosclerosis (MESA) will be presented. These studies demonstrate that adult and childhood SES, neighborhood-level SES, and neighborhood social environment are associated with alterations in the methylation and consequent gene expression of stress- and inflammation-related genes. Newly developed high-dimensional statistical methods for evaluating epigenetics as a mediator between SES/neighborhood conditions and cardiovascular risk factors will also be discussed.


Mieka Smart, DRPH | View Seminar
Division of Public Health
Associate Professor of Epidemiology and Biostatistics
Michigan State University

“Progress and partnership opportunities with the Flint Area Study”

Dr. Smart is developing and executing the Flint Area Study (FASt). The protocol includes extensive environmental surveys, blood specimen collection via venipuncture for epigenetic assessments, and an in-depth interviewer-assisted psychosocial survey designed to assess of five broadly defined domains: Demographic information, Physical health, Service access, Mental/behavioral health, and Family environment. Full epigenetic and survey measures will be taken every three years. We will recruit approximately 400 households to reach a target sample size of 1000 Flint residents. Dr. Smart will describe the study progress to date and encourage partnership around future analyses. 


Katherine Keyes, PhD, MPH 

Associate Professor of Epidemiology
Columbia University
Mailman School of Public Health

"Depression’s got a hold of me: Gender differences and generational trends in alcohol use and mental health among US adolescents and adults"

Alcohol, tobacco, and many other substances are at historically low prevalence among US adolescents and continue to decrease annually. At the same time, after a long period of relative stability, depression, suicidal behavior and death by suicide, and other mental health indicators have begun rapidly increasing among US adolescents, especially girls and women. In this talk, Dr. Keyes will provide a cross-generational and sociological framework to understand the connection (and recent disconnection) between substance use and mental health among adolescents across birth cohorts from the last 40 years, with a particular focus on gender. Topics will also include the discontinuity between temporal trends in adolescent and adult substance use/mental health, theories and evidence regarding why these patterns are emerging, and appropriate public health responses.


Daniel J. Schaid, PhD | View Seminar
Professor of Biostatistics
Mayo Clinic
Rochester, MN

Statistical methods for analyzing genetic pleiotropy (one gene to many traits)"

When a single gene influences more than one trait, known as pleiotropy, the gene can have a large impact on an organism. Detecting pleiotropy, and understanding its causes, can improve the biological understanding of a gene in multiple ways, including: 1) expanded understanding of the medical impact of a gene ; 2) the pharmacologic genetic target could impact multiple traits or diseases, allowing repurposing of a drug for multiple diseases, or monitoring multiple traits for toxicities; 3) joint analysis of multiple traits can increase accuracy of trait prediction. Yet, the statistical methods for analyzing genetic models have only recently been developed. This talk will review some of the recent developments of statistical methods for evaluating pleiotropy. The presentation will then focus on a recently developed approach to formally test which traits are associated with a set of SNPs, while accounting for correlations among the traits. Our methods are based on sequential testing with mixed models, starting with the usual null hypothesis that none of the traits are associated with a set of SNPs, using multivariate kernel statistics. If this hypothesis is rejected by a small p-value, we proceed by evaluating all possible ways of allowing one associated trait while testing the remaining traits, using a special kernel statistic. The maximum p-value from these tests is used as a summary p-value. If the maximum p-value is smaller than the nominal criterion (e.g., p-value < 0.05), we continue onto the next sequential step of evaluating all possible ways of allowing two associated traits and testing the remaining traits, etc. By simulations, we illustrate that the Type-I error rate is well controlled, and illustrate power of our new methods. We illustrate how the sequential method is influenced by sample size, the number of traits, and the trait correlations. We apply the new methods to multivariate phenotypes to illustrate interpretation and benefits of our new approach. This strategy provides new ways to perform gene-level analyses for multiple traits while accounting for correlations among the traits.


Pauline Mendola, PhD | View Seminar
NIH Intramural Research Program

“Does the ambient environment impact fertility? Findings from the Air Quality and Reproductive Health Study”

We consider traffic, air pollution and ambient temperature in relation to reproductive health, fertility and pregnancy loss. Emission and meteorology data are combined in modified Community Multi-scale Air Quality models to estimate exposures to common air pollutants and ambient temperature across the United States. These exposures are linked to biologically relevant time windows among the LIFE study participants and in the Consortium on Safe Labor to assess the impact of exposure on fertility, time-to-pregnancy, semen quality, early pregnancy loss and stillbirth.  


Tony Merriman, PhD | View Seminar
Research Professor
Department of Biochemistry
University of Otago, New Zealand

“Genetic approaches to gout: new insights and clinical relevance”

The arthritis gout is caused by an innate immune reaction to mono-sodium (MSU) urate crystals that form when urate levels are elevated (hyperuricemia). Genome-wide association studies in urate and gout have revealed numerous loci contributing to the progression from hyperuricemia through MSU crystal deposition through to gout. These loci not only reveal molecular mechanisms of urate control and gout, but the genetic variants serve as a tool to ask some important clinical questions. For example, what is the causal relationship between hyperuricemia and gout, and co-morbid metabolic diseases such as type 2 diabetes, heart and kidney disease? What is the comparable contribution of genetics and diet to urate levels? How do genetic variants interact with environment to influence the risk of gout?


Student Poster Event highlighting student research.
For information see Student Poster Event


Jiu-Chiuan Chen, MD, ScD
Associate Professor of Preventive Medicine
USC Leonard David
Los Angeles, CA

"The Continuum and Heterogeneity of Air Pollution Neurotoxicity on Brain Aging: Role of Ambient Particulate Matter"

An increasing number of epidemiologic studies have reported the associations of cognitive decline and increased risks for Alzheimer’s disease (AD) and related dementias with exposures to ambient air pollutants, especially the fine particulate matter (PM2.5: particulate matter with aerodynamic diameters <2.5 μm). Prompted by this recent wave of air pollution epidemiologic evidence, the Lancet Commission on Pollution and Health recently proposed future environmental health-related research agenda for pollution control and disease prevention, and defining the global burden of neurodegenerative disease in adults attributable to PM2.5 exposure is among the top priorities. Despite these supportive epidemiologic data, the underlying mechanisms linking air pollution exposure with brain aging remain elusive. Over the last few years, Dr. Chen has been leading several NIH-funded studies, aiming to strengthen the causal link between ambient air pollution and pathological brain aging. In this seminar, Dr. Chen will demonstrate a team-science approach that integrates the clinical neurosciences and population neuroinformatics to investigate how air pollution exposure alters the brain structures with gray matter atrophies in areas vulnerable to AD neuropathology. He will also report new epidemiologic data showing how long-term PM2.5 exposure in late life accelerates the early neuropsychological processes and contribute to the heterogeneity in the trajectories of cognitive decline during the preclinical stage, likely independent of cerebrovascular damage. Dr. Chen will also discuss a new NIA-funded PPG that promises to advance our understanding of risk, heterogeneity, and mechanisms linking exposure to traffic-related air pollutants with AD and related dementias.