Pos0422 metabolomic Fingerprint to Discriminate Remission From Active Disease and Healthy Controls in Psoriatic Arthritis

Abstract

BackgroundAmong the unmet needs in psoriatic arthritis (PsA), the discovery of molecular players and biomarkers of disease activity or clinical remission achievement, remains unsolved. Metabolomics is a valuable technology in identifying biomarkers, by the study of a set of small molecules produced by the catabolism or anabolism of an organism in response to physiological or pathological states, allowing to better understand the disease-related variations downstream of the genome and proteome.ObjectivesIn this pilot study, we have compared the serum metabolomics profile of patients with psoriatic arthritis with active or clinically inactive disease state compared with healty controls, using Nuclear Magnetic Resonance Spectroscopy (1H-NMR).MethodsFrom a cohort of 300 PsA patients according to CASPAR criteria, we selected 30 PsA with active disease state by DAPSA > 14 score (no bDMARDs ongoing) (A), 38 patients (peripheral arthritis subset) with >1-year remission by antiTNFα assessed by DAPSA ≤ 4 (B) and 32 healthy controls (C) matching for mean age and gender ratio. The sera metabolomics profile of 100 subjects was analyzed with a Varian UNITY INOVA 500 MHz NMR spectrometer, combined with Multivariate statistical Analysis (MVA). Principal Component Analysis (PCA) and Orthogonal Partial Least-Squares Discriminant Analysis (OPLS-DA) were applied. The model’s goodness was evaluated using a permutation test (Q2 intercept value <0.005).ResultsThe represented OPLS-DA models (Figure 1) exhibited a clear separation between subjects with active disease (red dots) and healthy controls (green dots), and patients with active disease or clinical remission state (blue dots), indicating significant differences in the serum metabolomics profile between all compared conditions. Interestingly, the OPLS-DA model shows how the PsA patients in the remission state have a profile which does not completely overlap with healthy subjects. The validity of the OPLS-DA models was evaluated through a permutation test using 500 times (Table 1) and indicate the great statistical validity of the OPLS-DA reported models.ConclusionThe metabolomic profile of PsA patients with different disease state and healthy subjects reveal a high grade of dissimilarity between all compared conditions: remarkably, the metabolomic profile of patients with the drug-induced clinical remission appears still different from a healthy condition, perhaps reflecting molecular modifications induced by the great response to TNFalpha inhibition sustaining the clinical remission of PsA disease. Supplementary analysis of single-spectra is ongoing to obtain a list of metabolites differentially expressed in all conditions, and on this field further explorations are needed to validate metabolomics biomarkers that can accurately and reliably measure PsA disease activity or remission achievement, as well as to identify the metabolic fingerprint of antiTNFα-treatment success.Figure 1.OPLS-DA scores plots of1H NMR spectra of sera samples.Red dots: (A) active PsA patients; blue dots: (B) remission PsA patients; green dots: (C) healthy controls.Table 1.Parameters for OPLS-DA modelsOPLS-DA modelsPermutation (500 times)*active PsA patientsvshealthy controlsComponentsaR2XcumbR2YcumcQ2cumdR2 interceptQ2 intercept1P+1O0.4060.6650.5170.330-0.336active PsA patientsvsremission PsA patients1P+2O0.4810.8240.5040.461-0.424remission PsA patientsvshealthy controls1P+1O0.3890.6110.4290.318-0.331aThe number of Predictive and Orthogonal components used to create the statistical models.b,cR2X and R2Y indicated the cumulative explained fraction of the variation of the X block and Y block for the extracted components.dQ2cum values indicated cumulative predicted fraction of the variation of the Y block for the extracted components.*An Q2 intercept value less than 0.005 are indicative of a valid model.AcknowledgementsAll staff of the Rheumatology Unit of the AOU of Cagliari, patients and volunteer donors.Disclosure of InterestsNone Declared.

Molecular profiling of clinical remission in psoriatic arthritis reveals dysregulation of FOS and CCDC50 genes: a gene expression study

“…To date, no successful models of TNFi prediction in PsA are available clinically ( 38 ), and the research field of biomarker discovery related to molecular remission achievement is only at an early stage ( 39 – 41 ). Whole-blood transcriptomic profiling performed in this study suggests that TNFi-induced clinical remission in PsA is similar to a healthy condition, but not identical, differing for a list of 125 transcripts and particularly for the FOS and CCDC50 gene expression amount.…”