Defining and treating genetic abnormalities in psoriasis/atopic dermatitis-overlap dermatoses

University Of California, San Francisco, San Francisco CA

Investigators

Abstract

Defining and treating genetic abnormalities in psoriasis/atopic dermatitis-overlap dermatoses Project Summary/Narrative Immunomodulatory therapies now robustly improve cases of the inflammatory skin diseases psoriasis and atopic dermatitis, based on selective targeting of cytokine pathways. However, no biomarkers are available to diagnose or predict treatment regimens for the frequent, ambiguous rashes harboring overlapping clinicopathologic features of both diseases. The objective of this proposal is to use high-resolution, quantitative biomarkers specific for psoriasis and atopic dermatitis to understand the etiology of these overlap cases, which we term “PSO-AD” rashes. We will also use observational studies to determine if PSO-AD rashes predictably respond to targeted drugs based on their biomarker profile. Our long-term objective is to develop a biomarker that can predict the medication most likely to elicit clinical improvement in a given patient's PSO-AD rash. Our central hypothesis is that PSO-AD rashes arise from a spectrum of genetic abnormalities and that cases closely resembling psoriasis or atopic dermatitis will respond to the corresponding targeted medication. The rationale underlying this proposal is our preliminary data defining highly specific biomarkers for psoriasis and atopic dermatitis and evidence that based on these markers, therapies can be rationally chosen for PSO-AD overlap cases. We will pursue these aims using innovative technical approaches that include spatial transcriptomics (to validate that epidermal pathology arises from T cell pathology) and targeted bulk RNA-seq methods that can assess PSO-AD cost effectively on the patient level. Our proposal is significant because it advances the first companion diagnostic to targeted biologic medications.The expected outcome of this proposal is a biomarker set that predicts drug response in PSO-AD rashes. These data will have a positive impact on treatment because they will reduce the substantial clinical delays and economic impact stemming from failed ad hoc treatment of PSO-AD rashes.