Background/Purpose:  Although not yet fully possible, ideally, since patients with rapidly progressing joint space narrowing/erosion exist, predicting progression of joint space narrowing/erosion would be pivotal in establishing treatment strategy for individual RA patients. Also, it is important to distinguish the effectiveness between TNF biologics and non-TNF biologics in joint space narrowing progression-type/erosion progression-type patients for determining the best treatment strategy. We developed SNP algorithms with an aim of enabling prediction of progression of joint space narrowing/erosion by means of genome-wide SNP analysis using multiple medical cohorts.

Methods:  One-hundred twenty-four RA patients with disease duration of 5 years or less from 6 different hospitals were enrolled. All patients were treated with biologics after the using DMARDs. We defined patients with rapid progression of joint space narrowing and with rapid progression of erosion by the ratio between joint space narrowing/erosion score in each patient. Twenty-five patients had joint space narrowing/erosion score of ≧ 5 (rapid progression of joint space narrowing), 99 had joint space narrowing/erosion score of < 5 (slow progression of joint space narrowing), 21 had an erosion/joint space narrowing score of ≧ 1 (rapid progression of erosion), and 103 had erosion/joint space narrowing score of < 1 (slow progression of erosion). Case-controlled analyses between 278,347 SNPs and progression of joint space narrowing/erosion (rapid vs. slow) were examined by Fisher’s exact tests. We selected 10 SNPs closely associated with progression of joint space narrowing/erosion (p < 0.0001). We then scored a relationship between each SNP and progression of joint space narrowing/erosion, the estimated total score of the 10 SNPs (estimated scoring in each SNP was as follows: homo allele in the majority in rapid progression group: +1 point, hetero allele: 0 point, and homo allele in the majority of slow progression group: -1 point), and examined relationships between the rapid and 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 progressing joint space narrowing group from the slow progressing group ranged from 80-88%. Accuracy, specificity and sensitivity of the algorithm for distinguishing the rapid progressing erosion group from the slow progressing group ranged from 86-95%. It is therefore suggested that this SNP algorithm may enable the prediction of rapidly progressing joint space narrowing/erosion. Though neither effectiveness of TNF-biologics nor non-TNF biologics correlated to the score of erosion progression-type and/or joint space narrowing progression-type patients (p > 0.05), with progressive type of erosion, tocilizumab treatment tended to be effective.

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

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/algorithms-using-genome-wide-snp-analysis-for-prediction-of-progression-of-joint-space-narrowing-or-erosion-in-rheumatoid-arthritis-patients-using-data-from-multiple-medical-cohorts/