Background/Purpose: Although not yet fully possible, ideally, since patients with rapidly progressing joint destruction need tight initial control, predicting the progression of joint destruction would be pivotal in establishing a treatment strategy for individual RA patients. We developed a SNP algorithm with the aim of enabling the prediction of yearly radiographic progression by means of genome-wide SNP analysis using multiple medical cohorts.

Methods: One-hundred twenty-four RA patients whose disease duration was 5 years or less were enrolled in this study from 6 hospitals in different regions of Japan. All patients were treated with biologics after the failure of DMARDs therapy. Radiographic progression of joint destruction was estimated by Sharp score per year of disease duration. We defined three groups, rapid, intermediate, and slow radiographic progression, according to Sharp score per year of disease duration. Twenty-three patients had a yearly Sharp score of >50 (rapid radiographic progression), 76 had a yearly score of 50-10 (intermediate radiographic progression) and 25 had a yearly score of <10 (slow radiographic progression). Case-control analyses between 278,347 SNPs and radiographic progression (rapid vs. intermediate+slow or rapid+intermediate vs. slow) were examined by Fisher’s exact test. We selected 10 SNPs closely associated with radiographic progression (p < 0.0001). We then scored a relationship between each SNP and radiographic progression, the estimated total score of the 10 SNPs (estimated scoring in each SNP was as follows: homo allele in the majority in rapid radiographic progression group: +1 point, hetero allele: 0 point, and homo allele in the majority of intermediate+slow radiographic progression group: -1 point), and examined relationships between the rapid and intermediate+slow group, and the total score.

Results: Accuracy ((true positive+true negative)/total), specificity (true negative/(false positive+true negative)) and sensitivity (true positive/(true positive+false negative)) of the algorithm for distinguishing the rapid progression group from the intermediate+slow progression group ranged from 93-96%. Accuracy, specificity and sensitivity of the algorithm for distinguishing the rapid+intermediate progression group from the slow progression group ranged from 88-90%. It is therefore suggested that this SNP algorithm may enable the prediction of rapidly progressing severe joint destruction.

Conclusion: This highly accurate algorithm using SNP analysis may be useful in initially diagnosing rapid radiographic progression, and, in this way, may contribute to establishing a strategy of treatment for individual RA patients.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/algorithm-using-genome-wide-snp-analysis-for-prediction-of-radiographic-progression-per-year-in-ra-patients-from-multiple-medical-cohorts/