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Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis.

ABSTRACT: Genetic biomarkers are sought to personalize treatment of patients with rheumatoid arthritis (RA), given their variable response to TNF inhibitors (TNFi). However, no genetic biomaker is yet sufficiently validated. Here, we report a validation study of 18 previously reported genetic biomarkers, including 11 from GWAS of response to TNFi. The validation was attempted in 581 patients with RA that had not been treated with biologic antirheumatic drugs previously. Their response to TNFi was evaluated at 3, 6 and 12 months in two ways: change in the DAS28 measure of disease activity, and according to the EULAR criteria for response to antirheumatic drugs. Association of these parameters with the genotypes, obtained by PCR amplification followed by single-base extension, was tested with regression analysis. These analyses were adjusted for baseline DAS28, sex, and the specific TNFi. However, none of the proposed biomarkers was validated, as none showed association with response to TNFi in our study, even at the time of assessment and with the outcome that showed the most significant result in previous studies. These negative results are notable because this was the first independent validation study for 12 of the biomarkers, and because they indicate that prudence is needed in the interpretation of the proposed biomarkers of response to TNFi even when they are supported by very low p values. The results also emphasize the requirement of independent replication for validation, and the need to search protocols that could increase reproducibility of the biomarkers of response to TNFi.

SUBMITTER: Lopez-Rodriguez R

PROVIDER: S-EPMC5937760 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis.

Lopez-Rodriguez Rosario R Perez-Pampin Eva E Marquez Ana A Blanco Francisco J FJ Joven Beatriz B Carreira Patricia P Ferrer Miguel Angel MA Caliz Rafael R Valor Lara L Narvaez Javier J Cañete Juan D JD Ordoñez Maria Del Carmen MDC Manrique-Arija Sara S Vasilopoulos Yiannis Y Balsa Alejandro A Pascual-Salcedo Dora D Moreno-Ramos Manuel J MJ Alegre-Sancho Juan Jose JJ Navarro-Sarabia Federico F Moreira Virginia V Garcia-Portales Rosa R Raya Enrique E Magro-Checa Cesar C Martin Javier J Gomez-Reino Juan J JJ Gonzalez Antonio A

PloS one 20180507 5

Genetic biomarkers are sought to personalize treatment of patients with rheumatoid arthritis (RA), given their variable response to TNF inhibitors (TNFi). However, no genetic biomaker is yet sufficiently validated. Here, we report a validation study of 18 previously reported genetic biomarkers, including 11 from GWAS of response to TNFi. The validation was attempted in 581 patients with RA that had not been treated with biologic antirheumatic drugs previously. Their response to TNFi was evaluate ...[more]

PMID: 29734345

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Project description:In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction model for response to TNFi therapy, containing metabolites and clinical parameters. Associations between metabolites and disease activity may help elucidate additional pathologic mechanisms behind RA.

Project description:OBJECTIVE:To compare the effectiveness and safety of three non-tumour necrosis factor (TNF) ? inhibitors (rituximab, abatacept, and tocilizumab) in the treatment of rheumatoid arthritis. DESIGN:Population based prospective study. SETTING:53 university and 54 non-university clinical centres in France. PARTICIPANTS:3162 adults (>18 years) with rheumatoid arthritis according to 1987 American College of Rheumatology criteria, enrolled in one of the three French Society of Rheumatology registries; who had no severe cardiovascular disease, active or severe infections, or severe immunodeficiency, with follow-up of at least 24 months. INTERVENTION:Initiation of intravenous rituximab, abatacept, or tocilizumab for rheumatoid arthritis. MAIN OUTCOME MEASURE:The primary outcome was drug retention without failure at 24 months. Failure was defined as all cause death; discontinuation of rituximab, abatacept, or tocilizumab; initiation of a new biologic or a combination of conventional disease modifying antirheumatic drugs; or increase in corticosteroid dose >10 mg/d compared with baseline at two successive visits. Because of non-proportional hazards, treatment effects are presented as life expectancy difference without failure (LEDwf), which measures the difference between average duration of survival without failure. RESULTS:Average durations of survival without failure were 19.8 months for rituximab, 15.6 months for abatacept, and 19.1 months for tocilizumab. Average durations were greater with rituximab (LEDwf 4.1, 95% confidence interval 3.1 to 5.2) and tocilizumab (3.5, 2.1 to 5.0) than with abatacept, and uncertainty about tocilizumab compared with rituximab was substantial (-0.7, -1.9 to 0.5). No evidence was found of difference between treatments for mean duration of survival without death, presence of cancer or serious infections, or major adverse cardiovascular events. CONCLUSION:Among adults with refractory rheumatoid arthritis followed-up in routine practice, rituximab and tocilizumab were associated with greater improvements in outcomes at two years compared with abatacept.

Dataset Information

Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis.

Publications

Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis.

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