Jason D. Christie, MD, MSCE

Jason D. Christie, MD, MSCE

Professor of Medicine (Pulmonary and Critical Care) and Epidemiology

Jason D. Christie, M.D., M.S.C.E. is the Chief of the Pulmonary, Allergy, and Critical Care Division, The Paul F. Harron Jr. Family Chair, and Professor of Medicine and Epidemiology at the University of Pennsylvania. His career is focused on translational research studies of the risks, pathogenesis, treatment, and outcomes of acute lung injury in the transplant and non-transplant critically ill populations.  Dr. Christie’s research integrates new knowledge generated from bench studies with epidemiology approaches in well-phenotyped, large human populations to generate new definitions of human syndromes, improved diagnostics and prognostics, and targeted therapy approaches in advanced lung diseases and acute organ dysfunction in critical illness.  His leadership and research achievements have been recognized with membership in the American Society of Clinical Investigation and the Association of American Physicians.


Dr. Christie is the founder of the lung transplant outcomes group (LTOG), which is a multicenter cohort study the etiology and pathogenesis of acute lung injury following lung transplantation (termed primary graft dysfunction). Active LTOG research themes focus on the mechanisms of clinical factors that elevate PGD risk, including donor smoke exposure, recipient obesity and body composition, pulmonary hypertension, alterations in lung microbiome, and autoimmunity to lung collagens. His multidisciplinary lung transplant research focuses on genetics, innate immunity, regulatory T-cells, innate lymphoid cell (ILC) populations in the lung, ischemia reperfusion injury, inflammation, and autoimmunity.

Content Area Specialties

Genetic epidemiology, molecular epidemiology, patient-oriented research, pulmonary epidemiology, surgery, translational research

Methods Specialties

Categorical data, clustered data, functional genomics, functional modeling, gene-expression profiling, longitudinal methods, microarray methods, multivariate analysis, survival analysis