Session Type: Abstract Submissions (ACR)
Background/Purpose: The strong association of AS with HLA-B27 implicates a T cell response restricted by this Class I MHC molecule, predicting that specific T Cell Receptor (TCR) sequences would be shared among AS patients.
Methods: We have developed a technology for large scale sequencing of TCR to assess the repertoire profile. All TCR sequences are amplified from peripheral blood and ~1 million TCR sequences are obtained to generate a comprehensive profile of TCR repertoire. We applied this technology to profile B27+ AS (n=128), B27- AS (n=24), B27- mechanical back pain (n=24), healthy controls (n=25) and SLE patients (n=176).
Results: We used a TCR repertoire data from the controls (HC and SLE) to filter out clonotypes present in an appreciable number of these samples. After rigorous control of multiple testing using train and test data sets, two clonotypes were discovered to have significantly different frequencies in B27+ AS population and controls (41% vs 5% and 54% vs19%, p <0.0001). These clones were further tested in 24 patients with mechanical back pain and 24 B27- AS patients. The frequency of both clonotypes in the MBP population was similar to that in controls (4% vs 5% and 25% vs 19%). In B27- AS one clonotype had frequency similar to controls (8% vs 5%), and one had a higher frequency than controls (42% vs. 25% p =0.016). The table below shows the frequency of both clonotypes in the different populations.
Diagnosis n Clone 1: no. positive (%) Clone 2: no. positive(%)
B27+ AS 128 54 (41%) 69 (54%)
B27- AS 24 2 (8%) 10 (42%)
MBP 24 1 (4%) 6 (25%)
Controls 201 11 (5%) 38 (19%)
Conclusion: We provide evidence that there is a distinctive set of shared clonotypes in the T cell repertoire in AS patients. This sheds light on the immunological role of HLA B27 in AS and demonstrates promising specificity for potential diagnostic utility.
R. D. Inman,
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/discovery-of-two-public-t-cell-receptor-clonotypes-in-b27-ankylosing-spondylitis-by-deep-repertoire-sequence-analysis/