The Psoriasis Center of Research Translation at Case Western Reserve University (CORT) will advance translational discovery and application in psoriasis using a cutting-edge systems biology approach that integrates patient-centered data within a rich and synergistic /collaborative institutional environment. We will leverage extensive preclinical, clinical and translational resources with the expertise and experience of our CWRU interdisciplinary research team, which encompasses bioinformatics, micro/myocobiome, psoriasis patient care, cutaneous immunology and transgenic models. The overall goal of the CORT is to combine new bioinformatic methodologies with advanced murine and human experimental approaches to translate scientific findings into clinical applications that more nimbly advance therapy for psoriasis and related inflammatory comorbidities. Our highly innovative, synergistic and cross-disciplinary CORT model will use a collaborative research project (CRP) as a central hub with bi- directional input from 2 highly interactive research cores, to refine and test hypotheses, identify and test drug leads and advance understanding of psoriasis and related inflammatory comorbidities. To do so, the CRP will integrate input from the: 1) Preclinical Modeling Core (PMC), that will provide and customize our many validated, unique transgenic psoriasiform animal models and translatable human xenograft approaches, essential to translating new mediator/pathway roles and drug leads; 2) Applied Meta-`Omics Core (AMC), that will apply multi-platform (transcriptome, metabolome, micro/mycobiome) bioinformatics to individual patient and murine samples to identify novel pathway-specific targets. Iterative experimental testing of these targets and feedback from the PMC and CRP will identify key novel pathways critical for psoriasis pathogenesis likely to benefit from intervention by new drugs or repurposed existing drugs for psoriasis therapy. Our patient-centered translational approach will exploit and enhance a novel, comprehensive and highly annotated database of ~850 psoriasis/psoriatic arthritis single-patient case records that combines clinical information derived from CLEARPATH (an Ohio medical provider consortium-based unified EMR repository for research access), with inflammation markers that stratify subsets. Into each patient's EMR, we will directly integrate his/her meta'Omics data created by the AMC working with the CRP, to create an 'Omics-integrated EMR (EMRi) data set. These cohesive multi-platform personal data records will identify psoriasis patient endotypes based upon unique perturbations identified from their ?meta'Omics? analyses. Our overarching hypothesis is that by powerfully combining existing and developing psoriasis basic science datasets, patient records, bioinformatics and computational systems biology with bi-directional mouse and human studies, we will identify new therapeutic targets and repurposed drugs that can be expeditiously moved to clinical trials, improving psoriasis treatment and patient care.

Public Health Relevance

The Psoriasis CORT at Case Western Reserve University and University Hospitals Cleveland Medical Center uses emerging capabilities of data analyses that can assemble many aspects of a single psoriasis patient in great detail, including their gene expression in skin and blood cells, the skin microbes (both bacterial and fungal) and the clinical features that are recorded in their electronic medical record (EMR). Using advanced computer algorithms to compare in-house patient data against externally available large databases, we can identify drugs already approved by the FDA that may be repurposed to treat psoriasis, and validate/invalidate them in animal models and patient cells.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Specialized Center (P50)
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Special Emphasis Panel (ZAR1)
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Cibotti, Ricardo
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Case Western Reserve University
Schools of Medicine
United States
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Damiani, Giovanni; Conic, Rosalynn R Z; de Vita, Valerio et al. (2018) When IL-17 inhibitors fail: Real-life evidence to switch from secukinumab to adalimumab or ustekinumab. Dermatol Ther :e12793
Wang, QuanQiu; McCormick, Thomas S; Ward, Nicole L et al. (2017) Combining mechanism-based prediction with patient-based profiling for psoriasis metabolomics biomarker discovery. AMIA Annu Symp Proc 2017:1734-1743