SAT0642 PROTEIN BIOMARKERS TO DIFFERENTIATE PSORIATIC ARTHRITIS FROM PSORIASIS. (June 2019)

• Record Type: Journal Article
• Authors: Magee, Conor; Pu, Yitong; Kwasnik, Anna; Ardle, Angela MC; Hernandez, Belinda; Farkas, Flora; Ikumi, Natsumi; Szentpetery, Agnes; Shakerdi, Loai; Gallagher, Phil; Kirby, Brian; Pennington, Stephen; Fitzgerald, Oliver
• Is Part Of: Annals of the rheumatic diseases. Volume 78(2019)Supplement 2
• Page Start: 1418
• Page End: 1420
• Publication Date: 2019-06
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2019-eular.3242
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: The BIOmarkers of COMorbidities (BIOCOM) in Psoriasis (Pso) study is a longitudinal study in which we aim to identify clinical, genetic and protein biomarker features associated with the development of co-morbidities, notably psoriatic arthritis (PsA), in patients with psoriasis (Pso). Pso usually precedes the development of PsA with an average interval of 10 years. Thus, patients with Pso are an ideal group in which to study the early events in the evolution to PsA. Objectives: To use a targeted proteomics approach to identify a serum protein, or panel of proteins, which can predict the development of PsA in patients with Pso. As a first step, we initially sought to identify serum proteins capable of discriminating between patients with Pso only and patients with established PsA. Methods: 30 patients with Pso and 30 patients with established PsA were selected from the BIOCOM-Pso database. Serum samples from these patients, taken at their initial assessment, were digested using an established in-house standard operating protocol (SOP). Once digested, a targeted proteomics approach using liquid chromatography – mass spectrometry (LC-MS) and a multiple reaction monitoring (MRM) assay called PAPRICA was used to measure candidate biomarker proteins. These 206 proteins (423 peptides) were previously identified as being potential biomarkers in a number of different inflammatory rheumatological conditions. Results: The demographics of the 2 patient groups are shown in Table 1 . Targeted proteomics data from the PsA and Pso patients was subjected to univariate and multivariate analysis using a leave one out cross validation approach. The initial results revealed that the application of the PAPRICA method to the BIOCOM-Pso samples resulted in a dataset in which 88 of the 206 PAPRICA proteins could be reliably measured (CV Area < 20%; Signal to Noise ratio > 5; Library Dot Product > 0.8). This subset of the PAPRICA proteins was not able to discriminate between PsA and Pso and none of the associated peptides were significantly different between the two groups (p value < 0.05). Conclusion: Analysis of a subset of 88 of the 206 biomarker proteins in the PAPRICA method, in patients with PsA and Pso, did not reveal peptides (proteins) that were statistically different between these two groups. Multivariate analysis generated a model that was unable to discriminate between patients with PsA and Pso. The possibility that the full PAPRICA assay may be able to discriminate between PsA and Pso will be explored, as will supplementing the PAPRICA method with additional biomarkers including proteins that may be identified in an unbiased proteome wide screen of PsA vs Pso serum samples. Disclosure of Interests: None declared