Quantitative SARS-CoV-2 antibody assays against the spike (S) protein are useful for monitoring immune response after infection or vaccination. We compared the results of three chemiluminescent immunoassays (CLIAs) (Abbott, Roche, Siemens) and a surrogate virus neutralization test (sVNT, GenScript) using 191 sequential samples from 32 COVID-19 patients. All assays detected >90% of samples collected 14 days after symptom onset (Abbott 97.4%, Roche 96.2%, Siemens 92.3%, and GenScript 96.2%), and overall agreement among the four assays was 91.1% to 96.3%. When we assessed time-course antibody levels, the Abbott and Siemens assays showed higher levels in patients with severe disease (p < 0.05). Antibody levels from the three CLIAs were correlated (r = 0.763–0.885). However, Passing–Bablok regression analysis showed significant proportional differences between assays and converting results to binding antibody units (BAU)/mL still showed substantial bias. CLIAs had good performance in predicting sVNT positivity (Area Under the Curve (AUC), 0.959–0.987), with Abbott having the highest AUC value (p < 0.05). SARS-CoV-2 S protein antibody levels as assessed by the CLIAs were not interchangeable, but showed reliable performance for predicting sVNT results. Further standardization and harmonization of immunoassays might be helpful in monitoring immune status after COVID-19 infection or vaccination.

IntroductionThe differential immune responses after two additional BNT162b2 (BNT) booster doses between ChAdOx1 nCoV-10 (ChAd)-primed and BNT-primed groups have not been elucidated. The aim of this study was to compare vaccine-induced humoral and cellular immune responses and evaluate breakthrough infection between the two vaccination strategies.MethodsIn 221 healthy subjects (111 in the ChAd group), longitudinal immune responses were monitored at 3, 4, and 6 months after the 2nd dose and 1, 3, and 6 months after the 3rd dose. Humoral immunity was measured by two fully automated chemiluminescent immunoassays (Elecsys and Abbott) and a surrogate virus neutralization test (sVNT). Cellular immunity was assessed by two interferon-γ (IFN-γ) release assays (QuantiFERON SARS-CoV-2 and Covi-FERON).ResultsAfter the 2nd dose of BNT vaccination, total antibody levels were higher in the ChAd group, but IgG antibody and sVNT results were higher in the BNT group. Following the 3rd dose vaccination, binding antibody titers were significantly elevated in both groups (ChAD-BNT; 15.4 to 17.8-fold, BNT-BNT; 22.2 to 24.6-fold), and the neutralizing capacity was increased by 1.3-fold in both cohorts. The ChAd-BNT group had lower omicron neutralization positivity than the BNT-BNT group (P = 0.001) at 6 months after the 3rd dose. Cellular responses to the spike antigen also showed 1.7 to 3.0-fold increases after the 3rd dose, which gradually declined to the levels equivalent to before the 3rd vaccination. The ChAd cohort tended to have higher IFN-γ level than the BNT cohort for 3-6 months after the 2nd and 3rd doses. The frequency of breakthrough infection was higher in the ChAd group (44.8%) than in the BNT group (28.1%) (P = 0.0219). Breakthrough infection induced increased humoral responses in both groups, and increase of cellular response was significant in the ChAd group.DiscussionOur study showed differential humoral and cellular immune responses between ChAd-BNT-BNT heterologous and BNT-BNT-BNT homologous vaccination cohorts. The occurrence of low antibody levels in the ChAd-primed cohort in the humoral immune response may be associated with an increased incidence of breakthrough infections. Further studies are needed on the benefits of enhanced cellular immunity in ChAd-primed cohorts.

The effects of COVID-19 vaccination on alloimmunization and clinical impact in transplant candidates remain largely unknown. In a 61-year-old man who had no donor-specific antibodies (DSA) and was planned to undergo ABOincompatible kidney transplantation (ABOi KT), DSAs (anti-A24, anti-B51, and anti-Cw14) developed after COVID-19 vaccination. After desensitization therapy, antibody level was further increased, leading to flow cytometric crossmatch-positive status. Donor-specific T cell immunity using interferongamma ELISPOT was continuously negative, whereas SARS-CoV-2 specific T cell immunity was intact. After confirming the C1q-negative status of DSA, the patient received ABOi KT. The patient had stable graft function and suppressed alloimmunity up to 2 months after KT. COVID-19 vaccination might relate to alloimmunization in transplant candidates, and desensitization through immune monitoring can help guide transplantation.

Background: After kidney transplantation, approximately 30% of patients develop BK viremia and 7% develop BK nephropathy. We performed transcriptome-based clustering at the single-cell level to identify these patients to be effective in monitoring and treating allograft dysfunction after transplantation. Methods: Single-cell libraries were generated using the 10× Genomics Chromium Platform from peripheral blood mononuclear cells from each of one posttransplant stable patient, two patients with BK viremia, and three patients with BK virus-associated nephropathy (BKVAN). We analyzed multiplexing data in Cell-Ranger pipeline and used R and "Seurat" packages for downstream analysis. Results: A total of 5,811 differentially expressed genes (DEGs) in 17 cell clusters were identified using 5,473 stable cells, 9,068 BK viremia cells, and 17,238 BKVAN cells for analysis. In the BK virus infection group, CENPF, MKI67, TOP2A, UBE2C, and HIST1H1B were overexpressed in gamma-delta T cells (logarithm two of fold change [log 2 FC] difference, 8.2-63.8), and TSC22D1, C2orf88, RGS18, and ACRBP in platelets than in the stable group (log 2 FC difference, 3.5-153). Among them, CENPF, MKI67, and TOP2A were more expressed in gamma-delta T cells of BKVAN group than in BK viremia group (log 2 FC difference, 53.5-56.5), whereas PF4, PPBP, and GNG11 in platelets were more overexpressed in BK viremia group than in the BKVAN group (log 2 FC difference, 27.6-70.9). In the stable group, LGALS3, CTSD, CD68, CST3, and GRN were overexpressed in FCGR3A monocytes (log 2 FC difference, 12.0-244.7) and TVP23A in CD16 monocytes (log 2 FC difference, 14.1 or more) than in the BK infection group. Conclusions: In patients with reactivated BK virus, the relationship to specific genomes can determine progression to nephropathy. In the case of gamma-delta T cells, the expression level was very low, so the difference in expression of each sample could be confirmed through single-cell RNA analysis. The developed marker is expected to enable more careful management of patients after kidney transplantation.

Background: Patients with operational tolerance do not use immunosuppressants after renal transplantation, but they show stable post-transplant results as stable patients with immunosuppressants. We analyzed differently expressed mRNAs and proteins by targeting immune genes to single cells in patients with rejection, stable, and tolerance after kidney transplantation to see if the post-kidney transplantation stability could be distinguished from genetic signatures. Methods: This experiment was conducted with peripheral blood mononuclear cells (PBMC) of four post-transplant rejection patients, four post-transplant stable patients, and five post-transplant tolerance patients. Through targeted multi-omic analysis, 10,180 (rejection group), 7,180 (stable group), and 16,784 (tolerance group) single-cell transcriptomes were analyzed. We added 20 different types of ab-seq to the targeted panel to complement for the relationship between proteins and transcripts. Results: We found 17 subclusters in the PBMC samples of three groups and confirmed the expression of mRNA and protein targeted by the immune panel among the subpopulations. We found the difference in the expression level of each group of NK cells, CD4 T cells, CD8 T cells, B cells, Treg cells, B memory cells and B naive cell populations. In 420 target genes including 20 Ab-seq, 70 transcripts and proteins were expressed differently in rejection and stable, 45 in stable and tolerance, and 96 differently in rejection and tolerance. Compared with the other two groups of patients, in tolerance patients, CD56(Ab) was highly expressed in B cells, CD4 T cells, and Treg cells, and CD196(Ab) was highly expressed in B memory cells and B naive cells. CD8(Ab) was highly expressed in NK cells. Conclusions: Analysis of transcript expression at the single cell level characterizes the phenotype of cells and defines their functional properties. We found that the operational tolerance group expressed markers that differed from the rejection and stable group.