Date of Award
January 2024
Document Type
Thesis
Degree Name
Medical Doctor (MD)
Department
Medicine
First Advisor
William Damsky
Abstract
Targeted systemic therapy selection in psoriasis and eczema does not account for patient specific, treatment-relevant immunologic heterogeneity. The goal of this project was to develop a rapid, non-invasive method of obtaining and analyzing epidermal protein biomarkers and evaluate its ability to molecularly subclassify psoriasis and eczema and identify biomarkers that correlate with treatment response. Our first aim was to optimize and validate a method of noninvasive, full-thickness epidermal sampling and subsequent protein detection. Our second aim was to identify protein biomarkers that could reliably discriminate between psoriasis and eczema, and to characterize intra-disease proteomic heterogeneity within psoriasis and eczema, respectively. Our third aim was to identify protein biomarkers in eczema that correlated with lack of response to dupilumab. We enrolled patients with psoriasis (n=44 samples) and eczema (n=31 samples); patients underwent noninvasive sampling of lesional skin and protein levels were measured using high-throughput protein assays. Differentially expressed proteins were compared between psoriasis and eczema samples, and supervised and unsupervised machine learning approached were applied to protein data within each diagnosis to molecularly subclassify patients. The sampling approach was found to be painless, nonscarring, and enabled rapid turnaround from time of sample collection to data output. We used this approach to accurately differentiate psoriasis and eczema using a limited set of proteins and to identify cases of eczema/psoriasis overlap with non-canonical molecular profiles; specifically, we identified a subset of low NOS2 expressing psoriasis patients with molecular profiles enriched for Type 2 immunity biomarkers including IL-4, CCL17, and CCL22. Additionally, we identified patient-specific cytokine biomarkers in eczema, including IFN-γ, CXCL9, IL-9, and CXCL14, that were correlated with nonresponse to IL-13 blockade. These results suggest that our approach has potential to realize the goal of personalized medicine in inflammatory skin disease.
Recommended Citation
Murphy, Michael, "Non-Invasive Epidermal Proteome-Based Subclassification Of Psoriasis And Eczema And Identification Of Treatment Relevant Biomarkers" (2024). Yale Medicine Thesis Digital Library. 4267.
https://elischolar.library.yale.edu/ymtdl/4267
Comments
This thesis is restricted to Yale network users only. It will be made publicly available on 06/01/2027