Identification of Novel Serological Autoantibodies in Takayasu Arteritis Patients Using HuProt Arrays

Abstract

To identify novel autoantibodies of Takayasu arteritis (TAK) using HuProt array-based approach. A two-phase approach was adopted. In Phase I, serum samples collected from 40 TAK patients, 15 autoimmune disease patients, and 20 healthy subjects were screened to identify TAK-specific autoantibodies using human protein (HuProt) arrays. In Phase II, the identified candidate autoantibodies were validated with TAK-focused arrays using an additional cohort comprised of 109 TAK patients, 110 autoimmune disease patients, and 96 healthy subjects. Subsequently, the TAK-specific autoantibodies validated in Phase II were further confirmed using Western blot analysis. We identified and validated eight autoantibodies as potential TAK-specific diagnostic biomarkers, including anti-SPATA7, -QDPR, -SLC25A2, -PRH2, -DIXDC1, -IL17RB, -ZFAND4, and -NOLC1 antibodies, with AUC of 0.803, 0.801, 0.780, 0.696, 0.695, 0.678, 0.635 and 0.613, respectively. SPATA7 could distinguish TAK from healthy and disease controls with 73.4% sensitivity at 85.4% specificity, while QDPR showed 71.6% sensitivity at 86.4% specificity. SLC25A22 showed the highest sensitivity of 80.7%, but at lower specificity of 67.0%. In addition, PRH2, IL17RB and NOLC1 showed good specificities of 88.3%, 85.9% and 86.9%, respectively, but at lower sensitivities (<50%). Finally, DIXDC1 and ZFAND4 showed moderate performance as compared with the other autoantibodies. Using a decision tree model, we could reach a specificity of 94.2% with AUC of 0.843, a significantly improved performance as compared to that by each individual biomarker. The performance of three autoantibodies, namely anti-SPATA7, -QDPR and -PRH2, were successfully confirmed with Western blot analysis. Using this two-phase strategy, we identified and validated eight novel autoantibodies as TAK–specific biomarker candidates, three of which could be readily adopted in a clinical setting.

Identification of Anti-SNRPA as a Novel Serological Biomarker for Systemic Sclerosis Diagnosis

“…To ensure reproducibility and avoid potential overfitting problems, we fabricated SSc-focused arrays with 2 × 6 subarray format using the re-prepared 113 candidate autoantigens in the Phase II validation and subjected them to the immune reactivity with a much larger cohort, comprising 700 serum samples, including 400 patients with SSc, 100 healthy subjects, 40 patients with chronic diseases, and 160 patients with various autoimmune diseases. Same as our previous profiling assay based on focused array for other diseases, ,, all of the serum samples were separately profiled in each block on the focused arrays.…”

“…After data acquisition and biostatistics analysis as before, ,, the SNRPA protein has the best performance as SSc-specific autoantigen and was therefore selected for further validation. Anti-SNRPA could distinguish SSc samples from both healthy and disease controls with a 11.25% sensitivity in SSc and a 96.67% specificity, for which 290 were negative among the 300 controls, respectively, meaning that the positive rate of anti-SNRPA autoantibody was only 3.33% in the controls ( P < 0.01).…”

Medium-vessel and large-vessel vasculitis in children

“…These include serum and stool markers of inflammation, such as IL-6 and S100A12 as well as chemokines, complement and other novel biomarkers (Table 2). One study describes eight novel TAK-associated autoantibodies using HuProt array-based approach, which could act as potential Takayasu arteritis biomarkers [23]. In a different study, elevated levels of IgM and IgG were associated with a higher risk of 1-year recurrence in Takayasu arteritis; the correlation of immunoglobulins of interest, as it offers a potentially low cost and a readily available biomarker in Takayasu arteritis; however, further research is needed to validate these findings [24 ▪ ].…”

Outcome Measures and Biomarkers for Disease Assessment in Takayasu Arteritis

“…A recent paper analyzed serum proteomics using protein microarray in TAK vs. healthy controls. Although eight proteins could distinguish TAK from healthy controls, none of these were significantly different between 31 patients with active TAK and 78 with inactive TAK [ 145 ]. Another study screened the sera of five patients with TAK and three healthy controls using a chemokine array and identified twelve chemokines to be increased and four to be decreased in TAK than in controls.…”