Search

The COVID-19 pandemic continues to affect individuals across the globe, with some individuals experiencing more severe disease than others. The relatively high frequency of re-infections and breakthrough infections observed with SARS-CoV-2 highlights the importance of extending our understanding of immunity to COVID-19. Here, we aim to shed light on the importance of antibody titres and epitope utilization in protection from re-infection. Health care workers are highly exposed to SARS-CoV-2 and are therefore also more likely to become re-infected. We utilized quantitative, multi-antigen, multi-epitope SARS-CoV-2 protein microarrays to measure IgG and IgA titres against various domains of the nucleocapsid and spike proteins. Potential re-infections in a large, diverse health care worker cohort (N = 300) during the second wave of the pandemic were identified by assessing the IgG anti-N titres before and after the second wave. We assessed epitope coverage and antibody titres between the 'single infection' and 're-infection' groups. Clear differences were observed in the breadth of the anti-N response before the second wave, with the epitope coverage for both IgG (p = 0.019) and IgA (p = 0.015) being significantly increased in those who did not become re-infected compared to those who did. Additionally, the IgG anti-N (p = 0.004) and anti-S titres (p = 0.018) were significantly higher in those not re-infected. These results highlight the importance of the breadth of elicited antibody epitope coverage following natural infection in protection from re-infection and disease in the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has been identified as the causative agent for causing the clinical syndrome of COVID -19. Accurate detection of SARS-CoV-2 infection is not only important for management of infected individuals but also to break the chain of transmission. South Africa is the current epicenter of SARS-CoV-2 infection in Africa. To optimize the diagnostic algorithm for SARS-CoV-2 in the South African setting, the study aims to evaluate the diagnostic performance of the EUROIMMUN Anti-SARS-CoV-2 assays. This study reported the performance of EUROIMMUN enzyme-linked immunosorbent assay (ELISA) for semi-quantitative detection of IgA and IgG antibodies in serum and plasma samples targeting the recombinant S1 domain of the SARS-CoV-2 spike protein as antigen. Samples were collected from 391 individuals who had tested positive for SARS-CoV-2 and 139 SARS CoV-2 negative controls. Samples were stratified by number of days' post-PCR diagnosis and symptoms. The sensitivity of EUROIMMUN IgG was 64.1% (95% CI: 59.1–69.0%) and 74.3% (95% CI: 69.6–78.6%) for IgA and the specificity was lower for IgA [84.2% (95% CI: 77–89.2%)] than IgG [95.2% (95% CI: 90.8–98.4%)]. The EUROIMMUN Anti-SARS-CoV-2 ELISA Assay sensitivity was higher for IgA but low for IgG and improved for both assays in symptomatic individuals and at later timepoints post PCR diagnosis. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]