Development of Predictive Psoriasis Response Endotypes Using Single Cell Transcriptomics

Overview

The investigators propose to improve the possibility of reaching skin resolution by identifying certain markers or gene patterns that may predict patient response to certain psoriasis drugs ahead of time, thus eliminating or reducing the trial-and-error approach often employed. The ability to rule out (or in) specific therapeutics based on predictive efficacy would lead to a more personalized approach for psoriasis treatment. To do this, the investigators will be asking participants to try two different already on the market FDA-approved psoriasis drugs for 8 weeks at a time. The investigators will be monitoring participants skin for improvements as well as taking blood and skin samples at least three times. Investigators may also ask to take stool samples and/or skin swabs.

Psoriasis is a chronic systemic skin disease in which pro-inflammatory molecules contribute to the development of scaled inflamed skin and other disease-associated comorbidities such as increased risk of depression, heart attack, stroke, and metabolic syndrome. Some lesion-derived cytokines/chemokines are released into systemic circulation and increase lesional severity. Given their importance in the pathogenesis of psoriasis, the interleukins 12 (IL-12) and 23 (IL-23) are significant targets of biologic therapies. Importantly, psoriasis patients exhibit variable responses to treatments targeting interleukins; one size does not fit all for these therapeutics. Our preliminary data demonstrates individual skin improvement (Responders) as well as lack of skin improvement (Non-Responders) in patients treated with monoclonal antibody therapy specifically targeting the shared (p40) subunit common to IL-12 and IL-23 (ustekinumab/Stelara). Interestingly, some Non-Responders to ustekinumab respond well to inhibition of the IL-23 pathway via the unique p19 subunit. We hypothesize that the pattern of differentially expressed genes (DEGs) among Responders and Non-Responders following anti-IL-12 and anti-IL-23 therapy may enable us to predict the likelihood of patient response to p40 antagonism as well as antagonism of the p19 subunit of IL-23. Single cell transcriptome analysis will be used to generate gene expression patterns that identify variable patient response patterns (endotypes).