Our group focuses on characterizing the molecular mechanisms that underlie phenotypes of rheumatoid arthritis (RA). In previous studies we have used machine learning to integrate rheumatoid arthritis gene expression profiles with synovial histology features to provide insight into RA disease subsets (Arthritis and Rheumatol, 2018). We noted the persistence of histologic and transcriptional evidence of subclinical synovial inflammation in some RA patients in clinical remission (Arthritis and Rheumatol, 2019). Our group has also uncovered synovial histology associations of morning stiffness (Arthritis and Rheumatol, 2020). We have developed methods to empower patients to participate in dense longitudinal genomics studies from home and used this approach to gain insights into the immune events that lead to rheumatoid arthritis flares (NEJM, 2020).
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