When:
Monday, March 10, 2025
10:00 AM - 11:00 AM CT
Where: Simpson Querrey Biomedical Research Center, Simpson Querrey Auditorium, 303 E. Superior Street, Chicago, IL 60611 map it
Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students
Contact:
Beverly A Kirk
(312) 503-5217
Group: Simpson Querrey Institute for Epigenetics Lecture Series
Category: Lectures & Meetings
The Simpson Querrey Institute for Epigenetics presents:
Andrew Pospisilik, PhD
Full Professor and Chair, Department of Epigenetics
Van Andel Research Institute, Grand Rapids, MI
"Variegating Epigenetic Mechanisms as Complex Disease Switches"
Abstract:
Our goal is to elucidate mechanisms underpinning complex disease susceptibility and presentation. Focusing on non-genetic, non-environmental origins of disease susceptibility, we previously identified the epigenetic silencer, Trim28, and the imprinted gene Nnat, as critical regulators of developmental robustness. Loss-of-function of either gene, intriguingly, triggers a unique developmental phenomenon known as ‘polyphenism’, in which animals can take on one of two distinct developmental phenotypic forms (and disease risk states) despite being genetically identical and environmentally controlled. Profiling human cohorts we find signatures of the same processes being active in approximately 50% of metabolically diseased patients. Our models represent the first formal demonstrations of mammalian polyphenisms and carry profound implications for our understanding of the origins of disease risk. I will share data that (i) characterize the distinctions between these triggerable disease in cancer, obesity and food-addiction; (ii) dissect the mechanism underpinning the underlying developmental bifurcation; (iii) provide evidence for alternate developmental trajectories in humans; and (iv) show one machine learning approach we are using to begin to tackle this problem in the genetically and environmentally heterogeneous human population. Collectively, our data highlight an underappreciated mechanistic layer heterogeneity (or sub-types) across the disease landscape.
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