Novel Autoantibodies in Idiopathic Small Fiber Neuropathy.

OBJECTIVE: Small fiber neuropathy (SFN) is clinically and etiologically heterogeneous. Although autoimmunity has been postulated to be pathophysiologically important in SFN, few autoantibodies have been described. We aimed to identify autoantibodies associated with idiopathic SFN (iSFN) by a novel high-throughput protein microarray platform that captures autoantibodies expressed in the native conformational state. METHODS: Sera from 58 SFN patients and 20 age- and gender-matched healthy controls (HCs) were screened against >1,600 immune-related antigens. Fluorescent unit readout and postassay imaging were performed, followed by composite data normalization and protein fold change (pFC) analysis. Analysis of an independent validation cohort of 33 SFN patients against the same 20 HCs was conducted to identify reproducible proteins in both cohorts. RESULTS: Nine autoantibodies were screened with statistical significance and pFC criteria in both cohorts, with at least 50% change in serum levels. Three proteins showed consistently high fold changes in main and validation cohorts: MX1 (FC = 2.99 and 3.07, respectively, p = 0.003, q = 0.076), DBNL (FC = 2.11 and 2.16, respectively, p = 0.009, q < 0.003), and KRT8 (FC = 1.65 and 1.70, respectively, p = 0.043, q < 0.003). Further subgroup analysis into iSFN and SFN by secondary causes (secondary SFN) in the main cohort showed that MX1 is higher in iSFN compared to secondary SFN (FC = 1.61 vs 0.106, p = 0.009). INTERPRETATION: Novel autoantibodies MX1, DBNL, and KRT8 are found in iSFN. MX1 may allow diagnostic subtyping of iSFN patients. ANN NEUROL 2022;91:66-77.

Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA.

Anti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three independent cohorts were enrolled. In Cohort-1, 24 plasma samples (6 ADAb-positive and 6 ADAb-negative patients at baseline and week 24 of adalimumab therapy, respectively) were assayed with immune-related microarray containing 1,636 correctly folded functional proteins. Next, we executed statistically powered autoantibody profiling analysis of 50 samples in Cohort-2 (24 ADAb-positive and 26 ADAb-negative patients). Subsequently, immunofluorescence assay was performed on 48 samples in Cohort-3 to correlate with ADAb titers and drug levels. The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median = 0.024 µg/ml) compared with ADAb-negative patients (median = 6.38 µg/ml, p < 0.001). ROC analysis based on the ADAb status revealed the top 20 autoantibodies with AUC ≥ 0.7 in differentiating both groups in Cohort-1. Analysis of Cohort-2 dataset identified a panel of 8 biomarkers (TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, PTPN20, and KLHL12) with 80.6% specificity, 77.4% sensitivity, and 79.0% accuracy in discriminating poor from EULAR responders. Immunofluorescence assay validated that anti-TROVE2 antibody could highly predict ADAb development and poor EULAR response (AUC 0.79 and 0.89, respectively). Multivariate regression analysis proved anti-TROVE2 antibody to be an independent predictor for developing ADAb. Immune-related protein microarray and replication analysis identified anti-TROVE2 antibody as a useful biomarker for predicting ADAb development and therapeutic response in adalimumab-treated patients.

Detection of putative autoantibodies in systemic lupus erythematous using a novel native-conformation protein microarray platform.

OBJECTIVE: Conventional immunoassays detect autoantibodies related to systemic lupus erythematosus (SLE) via recognition of epitopes on autoantigens expressed in their denatured rather than native conformational state, casting difficulty in evaluating the genuine pathogenicity of the autoantibodies. We aimed to use a novel high-throughput protein microarray platform to identify autoantibodies against native autoantigens in SLE sera. METHODS: Sera from SLE patients and those of gender-, age-, and ethnicity-matched healthy controls (HC) were screened against more than 1,600 immune-related antigens of native conformation. The relative fluorescent unit readout from post-assay imaging were subjected to bioinformatics pre-processing and composite normalization. A penetrance fold change (pFC) analysis between SLE and HC samples shortlisted 50 autoantigens that were subjected to an unsupervised cluster analysis. Correlations between the pFC of putative autoantigens and clinical parameters including SLE disease activity index (SLEDAI-2K) and recent SLE flares were explored. RESULTS: 381 autoantigens were identified when 15 SLE and 15 HC serum samples were compared. The top 20 autoantigens which elicited autoantibody responses in SLE sera filtered based on the highest pFC were further analyzed. Autoantigens which the putative autoantibodies reacted against are those involved in chromatin organization such as DEK, regulation of transcription activity including REOX4 and ELF4, and negative regulation of NFkB activity such as TRIB3. Additionally, the pFC of these autoantibodies significantly and positively correlated with SLEDAI-2K and recent SLE flares. CONCLUSION: A high-throughput protein microarray platform allows detection and quantification of putative lupus-related autoantibodies which are of potential pathophysiological and prognostic significance in SLE patients.

A Novel Method to Identify Autoantibodies against Putative Target Proteins in Serum from beta-Thalassemia Major: A Pilot Study.

Abnormal immune reactivity in patients with beta-thalassemia (beta-thal) major can be associated with poor prognosis. Immunome protein-array analysis represents a powerful approach to identify novel biomarkers. The Sengenics Immunome Protein Array platform was used for high-throughput quantification of autoantibodies in 12 serum samples collected from nine beta-thal major patients and three non-thalassemia controls, which were run together with two pooled normal sera (Sengenics Internal QC samples). To obtain more accurate and reliable results, the evaluation of the biological relevance of the shortlisted biomarkers was analyzed using an Open Target Platform online database. Elevated autoantibodies directed against 23 autoantigens on the immunome array were identified and analyzed using a penetrance fold change-based bioinformatics method. Understanding the autoantibody profile of beta-thal major patients would help to further understand the pathogenesis of the disease. The identified autoantigens may serve as potential biomarkers for the prognosis of beta-thal major.