Department Seminar SERIES

The Department sponsors a biweekly seminar series during the academic year on topics of epidemiologic and biostatistical interests. Speakers include Michigan State University faculty, Michigan Department of Community Health public health professionals or invited guests from around the nation or, occasionally, overseas.

The seminar is open to all members of the MSU and public health community, and unless otherwise noted, takes place in person or Zoom (or both) at 3:30 p.m. Most seminars are recorded and available for viewing.

• The Patenge Room, C102, is located in the C wing of East Fee Hall. 
• Zoom seminars links will be provided when necessary

Miss a Seminar or would like to revisit one?

Most seminars are recorded and available for viewing by clicking on the SEMINAR ARCHIVES link located on the upper right side of this page.

FALL 2023 SEMINAR SERIES SCHEDULE

 

Pregnancy complications, such as hypertensive disorders of pregnancy and other severe maternal morbidity, disproportionately affect Black and Hispanic women and other vulnerable populations and can result in serious short-term health outcomes for both mother (e.g., eclampsia and stroke), and child (e.g., stillbirth, and preterm delivery), as well as long-term outcomes e.g., increased risk of cardiovascular disease in women. Pregnancy may therefore serve as a window to identify women and children at high-risk of chronic health outcomes, including Black women, and prevent adverse outcomes through early prediction of risks, clinical surveillance, and effective interventions. In this talk, I highlight my studies on the prediction of adverse maternal outcomes and identifying long-term health risks after pregnancy complications, using epidemiological methods and large datasets.

Evidence from studies of dementia shows that some older adults continue to maintain their cognitive abilities despite signs of ongoing neuropathological diseases. Commonly referred to as cognitive reserve, this phenomenon has unclear neurobiological substrates and a current understanding of corresponding markers is lacking. This study aims at investigating the immense system of structural connections between brain regions constituting subcortical white matter (WM) as potential markers of cognitive reserve. Diffusion MRI tractography is an established computational neuroimaging method to model WM fiber organization throughout the brain. Standard statistical analyses capable of leveraging the high dimensionality of tractography data face additional methodological complications beyond those encountered in typical feature selection problems. We propose a flexible feature selection algorithm in the context of highly correlated high-dimensional predictors, a well-known challenge for traditional variable selection algorithms. Specifically, we adopt a screening and cleaning strategy that relies on deep learning for cluster-level discovery with a controlled error rate. Extensive simulation studies demonstrate a substantial gain in power with minimal false discoveries, compared with state-of-the-art methods for feature selection. Our application to predicting cognitive reserve in a clinical aging neuroimaging tractography dataset produces anatomically meaningful discoveries in brain regions associated with risk and resilience to neurodegeneration.

Recent GWAS for gout and serum urate have identified hundreds of candidate genes. Some top candidates will be described in detail. Current methods and results from our lab for exploring candidate gene expression and its regulation in immune cells will be presented. The research is producing many new questions and creating avenues for identification of targets for therapy.