Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis

Abstract

Objective. Approximately 30-40% of rheumatoid arthritis (RA) patients who are initially started on low-dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.Methods. RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.Results. Based on the ratio of transcript values (i.e., the difference in log 2 -transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2-regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10 −25 ) and at 4 weeks after treatment initiation (P = 4.9 × 10 −28 ).Conclusion. Testing for changes in gene expression between pretreatment and 4 weeks post-treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.

Identification of molecules associated with response to abatacept in patients with rheumatoid arthritis

“…Comparing the background at the start of ABA treatment, the percentage of MTX users was different in responders and non-responders. Recently, it has been reported that the expression level of the type 1 IFN is higher in patients that do not respond to methotrexate [42]. As there was no difference in the type I IFN scores among MTX users and non-users in both responders and non-responders in this study (data not shown), the cause of the difference in type I IFN expressions between the responders and the non-responders is not attributed to the percentage of MTX use.…”

The 4-H of Biomarkers in Arthritis: A Lot of Help, Occasional Harm, Some Hype, Increasing Hope

“…However, gene expression profiles from whole blood RNA showed an overrepresentation of type I interferon pathway genes in nonresponders. This signature explained 78% of the AUC, a significant improvement over clinical assessment 19 . Recently, combining clinical and genomic variables (specifically, genotypes of adenosine triphosphatebinding cassette transporter implicated in active MTX efflux from cells) yielded a model with an AUC of 80% 20 , illustrating how various sources of biomarkers can synergize productively.…”

“…Next-generation Biomarkers: HOPE and HYPE • Response to treatment Today, predicting response to MTX (methotrexate) remains impossible. Clinical covariates such as age, smoking status, antibodies, joint counts, and patient evaluations only explained 63% of the area under the receiver operating characteristics (ROC) curve (AUC) to predict MTX nonresponse 19 . However, gene expression profiles from whole blood RNA showed an overrepresentation of type I interferon pathway genes in nonresponders.…”

<p>Towards Precision Medicine in Systemic Lupus Erythematosus</p>

“…In rheumatoid arthritis gene signature has been shown to assist response prediction. 77 In the current treatment of lupus longterm clinical and immunological remission is only achieved in a proportion of patients. The inherent pathophysiological complexity of lupus described at the cellular and molecular level cannot be overstated.…”