Identification and Evaluation of Serum Protein Biomarkers That Differentiate Psoriatic Arthritis From Rheumatoid Arthritis
| Autor: | Anna Kwasnik, Oliver FitzGerald, Wilco de Jager, Stephen R. Pennington, Agnes Szenpetery, Sytze de Roock, Angela Mc Ardle, Belinda Hernández, Andrew C. Parnell |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adult
Male Oncology medicine.medical_specialty Immunology Serum protein Arthritis Rheumatoid Diagnosis Differential Psoriatic arthritis Rheumatology Internal medicine medicine Humans Immunology and Allergy biology medicine.diagnostic_test business.industry Arthritis Psoriatic Area under the curve Blood Proteins Early Inflammatory Arthritis Middle Aged medicine.disease Cross-Sectional Studies Rheumatoid arthritis Immunoassay Cohort biology.protein Female Antibody business Biomarkers |
| Zdroj: | Arthritis & Rheumatology. 74:81-91 |
| ISSN: | 2326-5205 2326-5191 |
| DOI: | 10.1002/art.41899 |
| Popis: | OBJECTIVE To identify serum protein biomarkers that might distinguish patients with early inflammatory arthritis (IA) with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) and may be used to support appropriate early intervention. METHODS The serum proteome of patients with PsA and patients with RA was interrogated using nano-liquid chromatography mass spectrometry (nano-LC-MS/MS) (n = 64 patients), an aptamer-based assay (SomaScan) targeting 1,129 proteins (n = 36 patients), and a multiplexed antibody assay (Luminex) for 48 proteins (n = 64 patients). Multiple reaction monitoring (MRM) assays were developed to evaluate the performance of putative markers using the discovery cohort (n = 60 patients) and subsequently an independent cohort of PsA and RA patients (n = 167). RESULTS Multivariate machine learning analysis of the protein discovery data from the 3 platforms revealed that it was possible to differentiate PsA patients from RA patients with an area under the curve (AUC) of 0.94 for nano-LC-MS/MS, 0.69 for bead-based immunoassay measurements, and 0.73 for aptamer-based analysis. Subsequently, in the separate verification and evaluation studies, random forest models revealed that a subset of proteins measured by MRM could differentiate PsA and RA patients with AUCs of 0.79 and 0.85, respectively. CONCLUSION We present a serum protein biomarker panel that can separate patients with early-onset IA with PsA from those with RA. With continued evaluation and refinement using additional and larger patient cohorts, including those with other arthropathies, we suggest that the panel identified here could contribute to improved clinical decision making. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text