Combining SARS-CoV-2 interferon-gamma release assay with humoral response assessment to define immune memory profiles.

OBJECTIVES: In the post-SARS-CoV-2 pandemic era, "breakthrough infections" are still documented, due to variants of concerns (VoCs) emergence and waning humoral immunity. Despite widespread utilization, the definition of the anti-Spike (S) immunoglobulin-G (IgG) threshold to define protection has unveiled several limitations. Here, we explore the advantages of incorporating T-cell response assessment to enhance the definition of immune memory profile. METHODS: SARS-CoV-2 interferon-gamma release assay test (IGRA) was performed on samples collected longitudinally from immunocompetent healthcare workers throughout their immunization by infection and/or vaccination, anti-receptor-binding domain IgG levels were assessed in parallel. The risk of symptomatic infection according to cellular/humoral immune capacities during Omicron BA.1 wave was then estimated. RESULTS: Close to 40% of our samples were exclusively IGRA-positive, largely due to time elapsed since their last immunization. This suggests that individuals have sustained long-lasting cellular immunity, while they would have been classified as lacking protective immunity based solely on IgG threshold. Moreover, the Cox regression model highlighted that Omicron BA.1 circulation raises the risk of symptomatic infection while increased anti-receptor-binding domain IgG and IGRA levels tended to reduce it. CONCLUSION: The discrepancy between humoral and cellular responses highlights the significance of assessing the overall adaptive immune response. This integrated approach allows the identification of vulnerable subjects and can be of interest to guide antiviral prophylaxis at an individual level.

Data-Driven Chronic Allograft Phenotypes: A Novel and Validated Complement for Histologic Assessment of Kidney Transplant Biopsies.

BACKGROUND: No validated system currently exists to realistically characterize the chronic pathology of kidney transplants that represents the dynamic disease process and spectrum of disease severity. We sought to develop and validate a tool to describe chronicity and severity of renal allograft disease and integrate it with the evaluation of disease activity. METHODS: The training cohort included 3549 kidney transplant biopsies from an observational cohort of 937 recipients. We reweighted the chronic histologic lesions according to their time-dependent association with graft failure, and performed consensus k-means clustering analysis. Total chronicity was calculated as the sum of the weighted chronic lesion scores, scaled to the unit interval. RESULTS: We identified four chronic clusters associated with graft outcome, based on the proportion of ambiguous clustering. The two clusters with the worst survival outcome were determined by interstitial fibrosis and tubular atrophy (IFTA) and by transplant glomerulopathy. The chronic clusters partially overlapped with the existing Banff IFTA classification (adjusted Rand index, 0.35) and were distributed independently of the acute lesions. Total chronicity strongly associated with graft failure (hazard ratio [HR], 8.33; 95% confidence interval [CI], 5.94 to 10.88; P<0.001), independent of the total activity scores (HR, 5.01; 95% CI, 2.83 to 7.00; P<0.001). These results were validated on an external cohort of 4031 biopsies from 2054 kidney transplant recipients. CONCLUSIONS: The evaluation of total chronicity provides information on kidney transplant pathology that complements the estimation of disease activity from acute lesion scores. Use of the data-driven algorithm used in this study, called RejectClass, may provide a holistic and quantitative assessment of kidney transplant injury phenotypes and severity.

Using EasyMatch® to anticipate the identification of an HLA identical unrelated donor: A validated efficient time and cost saving method.

In the absence of an HLA matched familial donor, a search for an unrelated donor or cord blood unit is initiated through worldwide registries. Although a first look-up on available HLA information of donors in the "book" at BMDW (Bone Marrow Donor Worldwide) can provide a good estimation of the number of compatible donors, the variety of resolution typing levels requires confirmatory typing (CT) which are expensive and time consuming. In order to help recipient centers in their work. The French donor registry (France Greffe de Moelle/Agence de la Biomedecine) has recently developed a software program called "EasyMatch®" that uses haplotype frequencies to compute the likelihood of phenotypic match in donors according to various typing resolution levels. The goal of our study is to report a single monocentric user-experience with EasyMatch®, demonstrating that its routine use reduced the cost and the delay of the donor search in our center, allowing the definition of a new strategy to search compatible unrelated donors. The strategy was first established on a retrospective cohort of 217 recipients (185 adults and 32 children=before score) and then validated on a prospective cohort of 171 recipients (160 adults and 11 children=after score). For all patients, we calculated the delay between the registration day and the donor identification day, and the number of CT requested to the donor centre. Considering both groups, we could observe a significant decrease of the number of CT from 8 to 2 (p<0,001), and a significant decrease of the median delay to identify a suitable donor from 43 to 31days (p<0.0001). EasyMatch® estimates the number of potentially identical donors, but doesn't foresee availability of the donors. It provides us an easy tracking of mismatches, an estimation of the number of potential donors, the selection of population following ethnic origin of patients and a high prediction when probability is high or low. It affords a new approach of donor search in our daily work and improves the efficiency in the great challenge of the compatible donor identification.