Abstract
BackgroundDisease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment.ObjectivesTo develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis.MethodsCandidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing.Results130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities.ConclusionWe followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.
Highlights
rheumatoid arthritis (RA) is a common, chronic, idiopathic autoimmune disease with over 1.3 million people diagnosed in the US and over 4 million worldwide
We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels
Stage 2, Feasibility, involved two parts: Stage 2A included four studies to assess and prioritize biomarkers based on their relationships to clinical disease activity; Stage 2B was a pilot imaging study to verify that multi-biomarker disease activity scores could capture critical aspects of disease activity
Summary
RA is a common, chronic, idiopathic autoimmune disease with over 1.3 million people diagnosed in the US and over 4 million worldwide. Despite recent advances in treatment including the introduction of potent biologic agents, substantial disease activity persists in many patients, with accompanying progressive bone and soft tissue damage, extra-articular consequences, disability, and increased mortality. Several studies, such as TICORA, CAMERA, BeSt, and FinRACO, have demonstrated improved outcomes with tight control of disease activity, a strategy employing frequent disease activity measurement and treatment adjustment to reach a specific target disease activity level [1,2,3]. Treat to Target guidelines codify these results into specific recommendations for optimal care including frequent disease activity monitoring for all patients [4]. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment
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