Background: Diminished expression of human leukocyte antigen DR on circulating monocytes (mHLA-DR) is a reliable indicator of immunosuppression in critically ill patients, predictive of both adverse outcome and septic complications. The objective of the present work was to test, in an interlaboratory clinical study, a standardized protocol for mHLA-DR measurement by flow cytometry.Methods: mHLA-DR was assessed in fresh whole blood according to a standardized staining protocol. Cells were analyzed on different flow cytometers (FC500, Navios, FACS Canto II) in different laboratories (Lyon and Grenoble). Results were expressed as numbers of antibodies bound per cell (AB/C).Results: Correlations between results were excellent (Pearson and interclass correlation coefficients > 0.98). Coefficients of variations for intra-assay precision ranged from 1.9 to 3.2%. Conclusion: The present report highlights the robustness of this standardized flow cytometric protocol for mHLA-DR measurement in multicentric clinical studies. V C 2012 International Clinical Cytometry Society

Background Informing kidney transplant recipients of their prognosis and disease progression is of primary importance in a patient-centred vision of care. By participating in decisions from the outset, transplant recipients may be more adherent to complex medical regimens due to their enhanced understanding. Methods We proposed to include repeated measurements of serum creatinine (SCr), in addition to baseline characteristics, in order to obtain dynamic predictions of the graft failure risk that could be updated continuously during patient follow-up. Adult recipients from the French Données Informatisées et VAlidées en Transplantation (DIVAT) cohort transplanted for the first or second time from a heart-beating or living donor and alive with a functioning graft at 1 year post-transplantation were included. Results The model was composed of six baseline parameters, in addition to the SCr evolution. We validated the dynamic predictions by evaluating both discrimination and calibration accuracy. The area under the receiver operating characteristic curve varied from 0.72 to 0.76 for prediction times at 1 and 6 years post-transplantation, respectively, while calibration plots showed correct accuracy. We also provided an online application tool (https://shiny.idbc.fr/DynPG). Conclusion We have created a tool that, for the first time in kidney transplantation, predicts graft failure risk both at an individual patient level and dynamically. We believe that this tool would encourage willing patients into participative medicine.

Motivation The HLA system plays a pivotal role in both clinical applications and immunology research. Typing HLA genes in patient and donor is indeed required in hematopoietic stem cell and solid-organ transplantation, and the histocompatibility complex region exhibits countless genetic associations with immune-related pathologies. Since the discovery of HLA antigens, the HLA system nomenclature and typing methods have constantly evolved, which leads to difficulties in using data generated with older methodologies. Results Here, we present Easy-HLA, a web-based software suite designed to facilitate analysis and gain knowledge from HLA typing, regardless of nomenclature or typing method. Easy-HLA implements a computational and statistical method of HLA haplotypes inference based on published reference populations containing over 600 000 haplotypes to upgrade missing or partial HLA information: ‘HLA-Upgrade’ tool infers high-resolution HLA typing and ‘HLA-2-Haplo’ imputes haplotype pairs and provides additional functional annotations (e.g. amino acids and KIR ligands). We validated both tools using two independent cohorts (total n = 2500). For HLA-Upgrade, we reached a prediction accuracy of 92% from low- to high-resolution of European genotypes. We observed a 96% call rate and 76% accuracy with HLA-2-Haplo European haplotype pairs prediction. In conclusion, Easy-HLA tools facilitate large-scale immunogenetic analysis and promotes the multi-faceted HLA expertise beyond allelic associations by providing new functional immunogenomics parameters. Availability and implementation Easy-HLA is a web application freely available (free account) at: https://hla.univ-nantes.fr. Supplementary information Supplementary data are available at Bioinformatics online.

Background: Asthma is a complex chronic inflammatory disease of the airways. Association studies between HLA and asthma were first reported in the 1970s, and yet, the precise role of HLA alleles in asthma is not fully understood. Numerous genome-wide association studies were recently conducted on asthma, but were always limited to simple genetic markers (single nucleotide polymorphisms) and not complex HLA gene polymorphisms (alleles/haplotypes), therefore not capturing the biological relevance of this complex locus for asthma pathogenesis. Objective: To run the first HLA-centric association study with asthma and specific asthma-related phenotypes in a large cohort of African-ancestry individuals. Methods: We collected high-density genomics data for the Consortium on Asthma among African-ancestry Populations in the Americas (N 5 4993) participants. Using computer-intensive machine-learning attribute bagging methods to infer HLA alleles, and Easy-HLA to infer HLA 5-gene haplotypes, we conducted a high-throughput HLA-centric association study of asthma susceptibility and total serum IgE (tIgE) levels in subjects with and without asthma. Results: Among the 1607 individuals with asthma, 972 had available tIgE levels, with a mean tIgE level of 198.7 IU/mL. We could not identify any association with asthma susceptibility. However, we showed that HLA-DRB1*09:01 was associated with increased tIgE levels (P 5 8.5 3 10 24 ; weighted effect size, 0.51 [0.15-0.87]). Conclusions: We identified for the first time an HLA allele associated with tIgE levels in African-ancestry individuals with asthma. Our report emphasizes that by leveraging powerful computational machine-learning methods, specific/extreme phenotypes, and population diversity, we can explore HLA gene polymorphisms in depth and reveal the full extent of complex disease associations.

The identity of histocompatibility loci, besides human leukocyte antigen (HLA), remains elusive. The major histocompatibility complex (MHC) class I MICA gene is a candidate histocompatibility locus. Here, we investigate its role in a French multicenter cohort of 1,356 kidney transplants. MICA mismatches were associated with decreased graft survival (hazard ratio (HR), 2.12; 95% confidence interval (CI): 1.45–3.11; P < 0.001). Both before and after transplantation anti-MICA donor-specific antibodies (DSA) were strongly associated with increased antibody-mediated rejection (ABMR) (HR, 3.79; 95% CI: 1.94–7.39; P < 0.001; HR, 9.92; 95% CI: 7.43–13.20; P < 0.001, respectively). This effect was synergetic with that of anti-HLA DSA before and after transplantation (HR, 25.68; 95% CI: 3.31–199.41; P = 0.002; HR, 82.67; 95% CI: 33.67–202.97; P < 0.001, respectively). De novo-developed anti-MICA DSA were the most harmful because they were also associated with reduced graft survival (HR, 1.29; 95% CI: 1.05–1.58; P = 0.014). Finally, the damaging effect of anti-MICA DSA on graft survival was confirmed in an independent cohort of 168 patients with ABMR (HR, 1.71; 95% CI: 1.02–2.86; P = 0.041). In conclusion, assessment of MICA matching and immunization for the identification of patients at high risk for transplant rejection and loss is warranted.

The impact of natural killer (NK) cell alloreactivity on hematopoietic stem cell transplantation (HSCT) outcome is still debated due to the complexity of graft parameters, HLA class I environment, the nature of killer cell immunoglobulin-like receptor (KIR)/KIR ligand genetic combinations studied, and KIR+ NK cell repertoire size. KIR genes are known to be polymorphic in terms of gene content, copy number variation, and number of alleles. These allelic polymorphisms may impact both the phenotype and function of KIR+ NK cells. We, therefore, speculate that polymorphisms may alter donor KIR+ NK cell phenotype/function thus modulating post-HSCT KIR+ NK cell alloreactivity. To investigate KIR allele polymorphisms of all KIR genes, we developed a next-generation sequencing (NGS) technology on a MiSeq platform. To ensure the reliability and specificity of our method, genomic DNA from well-characterized cell lines were used; high-resolution KIR typing results obtained were then compared to those previously reported. Two different bioinformatic pipelines were used allowing the attribution of sequencing reads to specific KIR genes and the assignment of KIR alleles for each KIR gene. Our results demonstrated successful long-range KIR gene amplifications of all reference samples using intergenic KIR primers. The alignment of reads to the human genome reference (hg19) using BiRD pipeline or visualization of data using Profiler software demonstrated that all KIR genes were completely sequenced with a sufficient read depth (mean 317× for all loci) and a high percentage of mapping (mean 93% for all loci). Comparison of high-resolution KIR typing obtained to those published data using exome capture resulted in a reported concordance rate of 95% for centromeric and telomeric KIR genes. Overall, our results suggest that NGS can be used to investigate the broad KIR allelic polymorphism. Hence, these data improve our knowledge, not only on KIR+ NK cell alloreactivity in HSCT but also on the role of KIR+ NK cell populations in control of viral infections and diseases.

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The antibody-dependent cellular cytotoxicity (ADCC) effector function of natural killer (NK) cells is one of the known mechanisms of action for rituximab-based anti-cancer immunotherapy. Inhibition of the ADCC function of NK cells through interactions between inhibitory killer cell immunoglobulin-like receptors (KIRs) and HLA class I ligands is associated with resistance of cancers to rituximab. In this study, we deeply investigated the impact of KIR, HLA class I, and CD16 genotypes on rituximab-dependent NK cell responses in both an in vitro cellular model from healthy blood donors and ex vivo rituximab-treated non-Hodgkin lymphoma (NHL) patients. We highlight that an HLA environment with limited KIR ligands is beneficial to promoting a higher frequency of KIR + NK cells including both educated and uneducated NK cells, two NK cell compartments that demonstrate higher rituximab-dependent degranulation than KIR − NK cells. In contrast, a substantial KIR ligand environment favors a higher frequency of poorly effective KIR − NK cells and numerous functional KIR/HLA inhibitions of educated KIR + NK cells. These phenomena explain why NHL patients with limited KIR ligands respond better to rituximab. In this HLA environment, CD16 polymorphism appears to have a collateral effect. Furthermore, we show the synergic effect of KIR2DS1, which strongly potentiates NK cell ADCC from C2 − blood donors against C2 + target cells. Taken together, these results pave the way for stronger prediction of rituximab responses for NHL patients. HLA class I typing and peripheral blood KIR + NK cell frequency could be simple and useful markers for predicting rituximab response.