Rachel G. Miller, PhD
Research Associate Professor
University of Pittsburgh
Featured in the Session: Molecular Architecture of Diabetic Retinopathy: Genes and Epigenomics
When
Monday, June 8
at 8:00 a.m.
Where
R05 (Level 2)
Ernest N. Morial Convention Center
What is your presentation about?
My presentation focuses on what we know about the epigenomics of diabetes-related retinopathy and how epigenetic mechanisms might help to explain residual risk observed even in people meeting glycemic targets. While the field has historically focused on “metabolic memory” and glucose-driven epigenetic changes, such as those at the TXNIP locus, our work leveraged the 28-year prospective follow-up of the Pittsburgh Epidemiology of Diabetes Complications (EDC) cohort to identify epigenetic pathways independent of A1C. Specifically, we identified DNA methylation at a novel locus, KIF16B, demonstrating that its protective effect against incident retinopathy is independent of glycemia but significantly attenuated by other systemic stressors like hypertension.
How do you hope your presentation will impact diabetes research or care?
I hope this work encourages the field to expand its focus beyond strictly glycemia-centric models of complication risk to identify novel, independent therapeutic targets. By demonstrating how other systemic factors like elevated blood pressure can affect protective epigenetic signals, this research underscores the necessity of comprehensive, multifactorial risk management in clinical care. Ultimately, the goal is to uncover biological pathways that can be targeted in parallel with glucose management.
How did you become involved with this area of diabetes research or care?
As an epidemiologist, my interest in epigenomics evolved from observing that our statistical models for diabetes complications consistently show residual risk unexplained by traditional risk factors. Epigenetic modifications provide a critical link between a person’s underlying genetic risk and their lifetime exposures. Studying these mechanisms in real-world cohorts can give us a more comprehensive picture of risk and potentially identify novel ways to intervene to prevent complications in people living with diabetes.