[ Back to EurekAlert! ] Public release date: 13-Jun-2008
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Contact: Rory Berrie / Camilla Dormer
eularpressoffice@uk.cohnwolfe.com
44-077-892-70392
European League Against Rheumatism

Novel DNA microarray chip predicts functional impairment and remission in rheumatoid arthritis

Paris, France, Friday 13 June 2008: A new DNA microarray chip can predict severe disability and remission in patients with rheumatoid arthritis (RA), as presented today at EULAR 2008, the Annual Congress of the European League Against Rheumatism in Paris, France. The chip (called the 'ARTchip') has yielded two clinical-genetic models of RA outcomes, to assist physicians in anticipating likely disease progression and prognosis and thereby guide decisions on the best course of treatment for individual patients.

The DNA microarray chip was developed as a tool to study 71 gene polymorphisms (tiny variations in the DNA that can cause or have a role in RA disease activity) in 45 genes chosen specifically for their presumed role in RA.

Dr Alejandro Balsa, of University Hospital La Paz, Madrid, Spain, who led the study, said: "Prognostic markers, identified through our microarray chip, can be used to predict disease outcomes in RA patients which may help healthcare professionals to choose the best treatment for each patient depending on their level of disease activity."

Predicting Severe Disability

6% and 8% of patients in the study and validation populations had a Health Assessment Questionnaire (HAQ) score of 2 or more indicating severe disability due to RA. The results from the DNA array significantly improved the ability of clinical scores to predict functional impairment.

Results of the study showed that clinical scores in combination with the DNA array had a high level of accuracy when compared in the two independent populations (sensitivity (S): 41%, specificity (Sp): 95% and likelihood ratio (LR): 7.6 in the study group, and S: 21%, Sp: 95% and LR: 4.4 in the validation population).

Predicting Remission

Overall, 6% and 7% of patients in the study and validation groups, respectively fell into the disease remission category. The results from the clinical scores in combination with the DNA array also accurately predicted remission in patients with RA, with S: 76%, Sp: 86%, LR: 5.4 compared withand S: 76%, Sp: 75%, LR: 3.1 respectively.

A total of 632 patients fulfilling the American College of Rheumatology (ACR) criteria for RA, with disease onset after 1990 and at least five-year disease duration, were analysed. Baseline variables were recorded including age, gender, smoking, joint counts, acute phase reactants and the presence of anti-CCP antibodies and rheumatoid factor. Remission was defined as absence of joint symptoms without disease-modifying anti-rheumatic drug (DMARD) therapy. Severe disability was defined as an HAQ score of 2 or more. Genetic association analyses were performed with HelixTree. Multivariate logistic regression models and ROC curves, to determine sensitivity, specificity and likelihood ratio, were developed with SPSS software.

Predictive models were initially developed for 375 patients and further validated on 257 RA patients. More than three quarters of the studied cases (77%) were females, and had with 10.93.6 years' disease duration.

A DNA array (or DNA chip) is a technique commonly used in molecular biology where tiny spots of specific DNA are arranged on a solid substance (normally glass). This technique can be used to screen thousands of genes in a single test, for their association with a particular disease or a specific clinical phenotype. In this study, a DNA array was developed and used to identify SNPs that can help to predict the course of RA. Moreover, the study provides rheumatologists with a tool to predict RA aggressiveness, based on a weighted combination of clinical and genetic parameters.

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For further information on this study, or to request an interview with the study lead, please do not hesitate to contact the EULAR congress press office on:

Email: eularpressoffice@uk.cohnwolfe.com

Rory Berrie: Onsite tel: +44 (0) 7789 270 392
Camilla Dormer: Onsite tel: +44 (0) 7876 190 439

Abstract number: FRI0033

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