ASCI / Young Physician-Scientist Awards, 2020
The Young Physician-Scientist Awards (YPSA) recognize physician-scientists who are early in their first faculty appointment and have made notable achievements in their research.
About the awardee
Ayodeji Adegunsoye, MD, is a pulmonary physician-scientist interested in utilizing genetic data from diverse races to improve clinical decision-making and outcomes for patients with pulmonary fibrosis (PF), a destructive interstitial lung disease (ILD) often characterized by profound scarring of the lungs. He completed his pulmonary/critical care fellowship at the University of Chicago, during which he focused his clinical training on patients with PF. His work seeks to understand PF from both clinical and translational facets while investigating the pathophysiologic mechanisms influencing outcomes. Predicated on differing phenotypic characteristics at baseline evaluation, he developed a cutting-edge statistical algorithm for classifying patients with ILD using a cluster analysis technique, the first in the ILD field. This model substantially improved the classification of patients with ILD into more prognostically useful phenotypes and distinguished clinically meaningful outcomes in ILD.
He recently identified race as an important independent predictor of survival, with data showing that this influence of race on ILD outcomes may stem from genetic variation between racial groups. His data suggests a substantial interplay between race and genetics in modulating PF outcomes, the central premise of his research interests is that the inclusion of genomic biomarkers from diverse racial populations into a cluster-based classification model will improve classification and prediction in PF.
In recognition of this work, he received the I.M. Rosenzweig Junior Investigator Award, and obtained research funding from the Pulmonary Fibrosis Foundation, the American College of Chest Physicians, and the Respiratory Disease Young Investigators’ Forum, amongst others. As he initiates his NIH K-funded project, the application of novel statistical tools and state of the art genomic technology to data from patients with PF will provide an invaluable pharmacogenomic resource for studying PF across diverse races and improve PF classification and prediction, thus channeling discovery into translation and ultimately to clinical implementation.