2014 Outstanding New Investigator Award: Rehana Leak

Rehana Leak is an Assistant Professor of Pharmacology at Duquesne University and studies stress-induced adaptations or toxicity in models of neurodegeneration. Dr. Leak was trained in Neuroscience at Barnard College (B.A., graduated magna cum laude with Phi Beta Kappa induction) and the University of Pittsburgh (M.S., Ph.D., National Science Foundation graduate scholarship). Following a brief post-doctoral fellowship with an NIH trainee award, she took a career hiatus to take care of her young children while her husband was on active military duty. After returning to science with an NIH career reentry award, Dr. Leak focused on adaptive defenses in models of Parkinson’s disease and then opened her own lab in 2010. The Leak lab is currently examining the impact of sublethal and lethal protein-misfolding stress as a function of brain region and cell type, because neurons and astrocytes from different brain regions are differentially vulnerable to protein inclusions in neurodegenerative disorders.

Dr. Leak has published 41 original research papers, 9 review articles, 5 book chapters, and 3 editorials. Her work has been cited 1593 times. Dr. Leak is currently funded by the Michael J. Fox foundation and the Pennsylvania Department of Health. In the past, she has received funding from the American Parkinson’s Disease Association. Dr. Leak was voted Professor of the Year by the Duquesne pharmacy class of 2015 and received the Faculty Award from the university in 2013. She is a member of the Society for Neuroscience and the International Dose-Response Society.

A summary presentation of Dr. Leak’s work on adaptive responses in astrocytes can be found above. As described in the video, the Leak lab discovered that severe stress can elicit protection against a second challenge in the survivors of the original insult. These findings challenge the traditional view that severe stress only weakens defenses and broaden the range of stressor doses that are able to elicit adaptive preconditioning.