Building a fluorescence-based cellular screening platform to identify small molecules targeting mutant UBA1, this project addresses an acute unmet need in VEXAS syndrome and lays groundwork for broader rheumatic disease therapies.
Using single-molecule imaging to visualize B cell receptor signaling across gut compartments, this project uncovers how intestinal B cell education breaks down in IBD, revealing new targets for therapeutic intervention.
Identifying a novel molecular regulator of tolerogenic dendritic cell function, this project uncovers how its loss triggers spontaneous multiorgan autoimmunity and exacerbates lupus — revealing a clinically relevant pathway in immune tolerance.
A self-replicating RNA platform delivers anti-inflammatory cytokines directly to the airways, offering targeted local immune suppression without systemic toxicity — a mechanistically distinct approach to treating lupus lung disease.
Targeting the calcineurin-NFAT protein-protein interaction rather than enzyme active sites, this project develops a novel class of inhibitors to treat steroid-refractory ulcerative colitis with fewer side effects.
By profiling genetic and molecular drivers of pemphigus vulgaris across patient skin and blood, this project uncovers genotype-driven inflammatory loops and actionable targets for personalized therapy.
Integrating clinical, imaging, and biological data from large real-world MS cohorts, this project builds a machine learning model to predict disability progression early and enable personalized treatment decisions.
Using cancer patients experiencing immunotherapy-triggered autoimmunity as a unique human model, this project uncovers the molecular and epigenetic mechanisms by which self-reactive T cells escape immune tolerance.
Investigating how foreign sugar modifications on anti-TNF biologics trigger immune responses in pediatric IBD patients, this project aims to personalize biologic therapy selection and inform safer drug design.
Combining machine learning with microbiome and metabolomic data from 4,000+ IBD patients, this project develops tools to predict disease flares, identify therapeutic targets, and enable personalized flare prevention.
