Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

Objectives To identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention. Methods In an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167). Results Multivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85. Conclusion We report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.

[1]  G. Ferraccioli,et al.  SAT0085 A MATRIX RISK MODEL FOR PREDICTING 5-YEAR RADIOGRAPHIC PROGRESSION IN A COHORT OF EARLY RHEUMATOID ARTHRITIS TREATED ACCORDING TO T2T STRATEGY , 2019, SATURDAY, 15 JUNE 2019.

[2]  D. Foell,et al.  Molecular signature characterisation of different inflammatory phenotypes of systemic juvenile idiopathic arthritis , 2019, Annals of the rheumatic diseases.

[3]  D. Gladman,et al.  Serum-based soluble markers differentiate psoriatic arthritis from osteoarthritis , 2019, Annals of the rheumatic diseases.

[4]  S. Pennington,et al.  Clinical Features of Psoriatic Arthritis: a Comprehensive Review of Unmet Clinical Needs , 2018, Clinical Reviews in Allergy & Immunology.

[5]  Manuel Mayr,et al.  In Aptamers They Trust: Caveats of the SOMAscan Biomarker Discovery Platform From SomaLogic , 2018, Circulation.

[6]  J. Merola,et al.  Distinguishing rheumatoid arthritis from psoriatic arthritis , 2018, RMD Open.

[7]  H. Yamanaka,et al.  IL-23 and Th17 Disease in Inflammatory Arthritis , 2017, Journal of clinical medicine.

[8]  L. Coates,et al.  Psoriatic arthritis: state of the art review , 2017, Clinical medicine.

[9]  H. Mischak,et al.  Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups , 2017, Scientific Reports.

[10]  P. Hofman,et al.  Pros: Can tissue biopsy be replaced by liquid biopsy? , 2016, Translational lung cancer research.

[11]  Oliver FitzGerald,et al.  Developing clinically relevant biomarkers in inflammatory arthritis: A multiplatform approach for serum candidate protein discovery , 2016, Proteomics. Clinical applications.

[12]  O. FitzGerald,et al.  Striking difference of periarticular bone density change in early psoriatic arthritis and rheumatoid arthritis following anti-rheumatic treatment as measured by digital X-ray radiogrammetry. , 2016, Rheumatology.

[13]  O. FitzGerald,et al.  Psoriatic arthritis: complexities, comorbidities and implications for the clinic , 2016, Expert review of clinical immunology.

[14]  A. Ogdie,et al.  The Epidemiology of Psoriatic Arthritis. , 2015, Rheumatic diseases clinics of North America.

[15]  S. Pennington,et al.  Early biomarkers of joint damage in rheumatoid and psoriatic arthritis , 2015, Arthritis Research & Therapy.

[16]  S. Pennington,et al.  Psoriatic Arthritis Under a Proteomic Spotlight: Application of Novel Technologies to Advance Diagnosis and Management , 2015, Current Rheumatology Reports.

[17]  Andrew N Hoofnagle,et al.  From lost in translation to paradise found: enabling protein biomarker method transfer by mass spectrometry. , 2014, Clinical chemistry.

[18]  W. Kolch,et al.  On-Beads Digestion in Conjunction with Data-Dependent Mass Spectrometry: A Shortcut to Quantitative and Dynamic Interaction Proteomics , 2014, Biology.

[19]  J. Sørensen,et al.  Diagnostic delay in patients with rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis: results from the Danish nationwide DANBIO registry , 2014, Annals of the rheumatic diseases.

[20]  Susan E. Abbatiello,et al.  Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach* , 2014, Molecular & Cellular Proteomics.

[21]  P. Tak,et al.  Tumor necrosis factor inhibition modulates thrombospondin-1 expression in human inflammatory joint disease through altered NR4A2 activity. , 2013, The American journal of pathology.

[22]  D. Billheimer,et al.  Mass spectrometric immunoassay and MRM as targeted MS‐based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes , 2013, Proteomics. Clinical applications.

[23]  Robert Wilson,et al.  Sensitivity and specificity: twin goals of proteomics assays. Can they be combined? , 2013, Expert review of proteomics.

[24]  Daniel B. Shin,et al.  Prevalence and treatment patterns of psoriatic arthritis in the UK. , 2013, Rheumatology.

[25]  Ruedi Aebersold,et al.  Proteomics meets the scientific method , 2013, Nature Methods.

[26]  Michael J. Green,et al.  Sensitivity and specificity of the classification of psoriatic arthritis criteria in early psoriatic arthritis. , 2012, Arthritis and rheumatism.

[27]  Derek J. Bailey,et al.  Parallel Reaction Monitoring for High Resolution and High Mass Accuracy Quantitative, Targeted Proteomics* , 2012, Molecular & Cellular Proteomics.

[28]  V. Chandran Spondyloarthritis: CASPAR criteria in early psoriatic arthritis , 2012, Nature Reviews Rheumatology.

[29]  David C. Thompson,et al.  Biomarkers in rheumatology, now and in the future. , 2012, Rheumatology.

[30]  M. Mann,et al.  Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.

[31]  A. Mendelsohn,et al.  The burden of psoriatic arthritis: a literature review from a global health systems perspective. , 2010, P & T : a peer-reviewed journal for formulary management.

[32]  A. Silman,et al.  UvA-DARE (Digital Academic Repository) 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative Aletaha, , 2010 .

[33]  A. Silman,et al.  Rheumatoid arthritis classifi cation criteria : an American College of Rheumatology / European League Against Rheumatism collaborative initiative , 2010 .

[34]  Vinod Chandran,et al.  Soluble biomarkers differentiate patients with psoriatic arthritis from those with psoriasis without arthritis. , 2010, Rheumatology.

[35]  Vincent Gau,et al.  Matrix Effects—A Challenge toward Automation of Molecular Analysis , 2010 .

[36]  Brendan MacLean,et al.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments , 2010, Bioinform..

[37]  A. Gottlieb,et al.  Treatment recommendations for psoriatic arthritis , 2008, Annals of the rheumatic diseases.

[38]  R. Aebersold,et al.  Selected reaction monitoring for quantitative proteomics: a tutorial , 2008, Molecular systems biology.

[39]  E. Theander,et al.  The Swedish early psoriatic arthritis register-- 2-year followup: a comparison with early rheumatoid arthritis. , 2008, The Journal of rheumatology.

[40]  Dafna Gladman,et al.  Classification criteria for psoriatic arthritis: development of new criteria from a large international study. , 2006, Arthritis and rheumatism.

[41]  L Stafford,et al.  A prospective, clinical and radiological study of early psoriatic arthritis: an early synovitis clinic experience. , 2003, Rheumatology.

[42]  Alexander Fraser,et al.  Angiopoietins, growth factors, and vascular morphology in early arthritis. , 2003, The Journal of rheumatology.

[43]  M. Mann,et al.  Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. , 2003, Analytical chemistry.

[44]  P. Helliwell,et al.  Comparison of disability and quality of life in rheumatoid and psoriatic arthritis. , 2001, The Journal of rheumatology.

[45]  D. Gladman,et al.  Health-related quality of life of patients with psoriatic arthritis: a comparison with patients with rheumatoid arthritis. , 2001, Arthritis and rheumatism.

[46]  B. Kirkham,et al.  Early treatment of psoriatic arthritis is associated with improved patient-reported outcomes: findings from the etanercept PRESTA trial. , 2015, Clinical and experimental rheumatology.