Current Research and Scholarly Interests
Dr. Sweatt's research centers on using high-throughput molecular profiling and advanced bioinformatics tools, including machine learning and systems-based network analyses, to uncover novel phenotypes and improve understanding of pulmonary arterial hypertension (PAH). When previously supported by the NIH K12 Career Development Program and the American Thoracic Society (ATS) Foundation/Pulmonary Hypertension Association (PHA) Research Fellowship, he developed a machine learning approach to classify PAH patients solely on the basis of blood immune profiling, without initial guidance from clinical features. This agnostic strategy led to the discovery and validation of PAH immune phenotypes with distinct proteomic profiles that are independent of PAH etiology and stratify clinical risk. To build on this foundational research, he now serves as PI of a NIH K23 project which seeks to understand PAH immune phenotypes with respect to their evolution during disease progression, mechanistic underpinnings, and therapeutic implications.
In other collaborative PAH research, he has contributed the development of blood biomarkers that relate to disease pathobiology and therapies under investigation, ascertained novel molecular and echocardiographic features of right heart maladaptation, and characterized new clinical sub-phenotypes. He serves as co-investigator for a NIH R21 project investigating exosome biology in PAH using a novel microfluidics platform.
In recognition of his scientific contributions, Dr. Sweatt holds appointed positions on the American Thoracic Society (ATS) Pulmonary Circulation Program Committee, ATS Program Review Subcommittee, PAH ICON International Genetics Consortium, PHA Research Room Committee, ATS Early Career Working Group, and AHA 3CPR Early Career Committee, among others.
