HLA-B*15:47:01 allele with undefined serological equivalent considered as B Blank.

We report a discordance between complement-dependent cytotoxicity and next-generation sequencing molecular typing revealing HLA-B*15:47:01 allele with undefined serological equivalent confirmed by high-level immunization against the B15 serotype. Due to the high-level immunization against HLA-B15 and B70 antigens, we considered the HLA-B*15:47:01 allele to be B Blank and not as B15 or B70 serological specificity.

MICA and NKG2D variants as risk factors in spondyloarthritis: a case-control study.

The major histocompatibility complex class I polypeptide-related sequence A (MICA) glycoprotein mediates the activation of the natural killer group 2D receptor (NKG2D) expressed on NK and CD8+ T cells. A methionine or valine at position 129 in exon 3 results in strong (MICA129 met) or weak (MICA129 val) binding to NKG2D. The MICA A5.1 allele causes a premature stop codon. Various NKG2D polymorphisms are associated with low (NKC3 C/C and NKC4 C/C) or high (NKC3 G/G and NKC4 T/T) levels of NK cell cytotoxic activity. In 162 patients with spondyloarthritis (115 with ankylosing spondyloarthritis, 46 with psoriatic arthritis and 1 with reactive arthritis) compared to 124 healthy controls, MICA-129 with methionine allele was more frequent in patients with spondyloarthritis (odds ratio (OR) (95% confidence interval) = 4.84 (2.75‒8.67)), whereas MICA-129 val/val, MICA A5.1 and NKC3 C/C variants were less frequent (OR = 0.20 (0.11‒0.37), 0.15 (0.06‒0.36) and 0.24 (0.13‒0.44), respectively). After adjustment for HLA-B*27 status, only NKC3 C/C remained linked to spondyloarthritis (adjusted OR = 0.14 (0.06‒0.33)). Homozygosity for MICA A5.1 is linked to ankylosing spondyloarthritis, and NKC3 C/C and MICA-129 val/val to psoriatic arthritis. MICA and NKC3 polymorphisms (related to a low NK cell cytotoxic activity) constituted a genetic association with spondyloarthritis.

Cryopreservation and thawing of hematopoietic stem cell CD34-induced apoptosis through caspase pathway activation: Key role of granulocytes.

INTRODUCTION: Cell damage inescapably occurs during both the freezing and the thawing graft processes for autologous hematopoietic stem cell (HSC) transplantation. To estimate HSC injury, a quality control is performed including: (i) CD34+ quantification; (ii) percentage of CD34+ viability and (iii) evaluation of HSC functional ability to form colony forming unit-granulocyte macrophage (CFU-GM). Apoptosis involves complex pathways such as caspase enzymes. Here, we assess the extent of apoptosis that is caspase-dependent before and after cryoconservation of CD34+, using a Fluorescent Labeled Inhibitor of CAspases (FLICA). METHODS: Caspase pathway activation status was evaluated in 46 patients (multiple myeloma [n = 24], lymphoma [n = 22]), by flow cytometry, using a 7-aminoactinomycin-D (7AAD)/FLICA staining test, in CD34+, CD3+, CD14+ and CD56+ cells. Viable 7AAD-/FLICA+ cells were then correlated with various parameters. RESULTS: We showed a significant caspase pathway activation, with 23% CD34+/7AAD-/FLICA+ cells after thawing, compared with the 2% described in fresh CD34+ cells (P < 0.0001). Moreover, caspase pathway was significantly activated in thawing CD3+, CD56+ and CD14+ cells. We also report a significant correlation between the rate of CD34+/7AAD-/FLICA+ cells and post-thawing granulocytes count (P = 0.042) and their potential to be differentiated into CFU-GM (P = 0.004). DISCUSSION: Our results show substantial cell death, induced by the increase of caspase pathway activation, secondary to the thawing process, and across all study cell types. This observation may affect the immune response quality during recipient aplasia, without detecting a clinical impact. Moreover, caspase pathway activation through CD3+ and CD56+ subpopulations could modify the therapeutic result of donor lymphocytes infusion (DLI).

The association between killer-cell immunoglobulin-like receptor (KIR) and KIR ligand genotypes and the likelihood of BK virus replication after kidney transplantation.

BK virus is a common opportunistic post-transplantation viral infection. Although some risk factors have been studied in this context, the contribution of NK cells has not been assessed in detail. In a group of kidney transplant recipients, we studied the association between (i) the likelihood of BK virus replication during the two-year period after kidney transplantation and (ii) the genotypes of the killer cell immunoglobulin-like receptor (KIR) repertoire and their human leukocyte antigen (HLA) ligands. Other clinical factors (such as defective organ recovery and immunosuppressive treatment) were also assessed. BK virus replication was observed in 43 of the 103 recipients (41%). Patients with BK virus replication in the plasma were more likely to display defective organ recovery in the first seven days post-transplantation. BK virus replication was not associated with Missing KIR ligands. However, BK virus replication was more frequent in patients with responsive NK cells (i.e. when a ligand for activating KIRs was not homozygous in the recipient and present in the donor). Our results suggest that defective organ recovery and the recipient's activating KIR repertoire may be related (depending on HLA ligands present in the couple recipient / donor) to the reactivation of BK virus replication after kidney transplantation.

Characterization of the novel HLA-B*07:491 allele by next generation sequencing.

HLA-B*07:491 differs from HLA-B*07:02:01 by one nucleotide substitution in codon 218 in exon 4.

Characterisation of the novel HLA-B*58:02:04 allele by next-generation sequencing.

HLA-B*58:02:04 differs from HLA-B*58:02:01 by one synonymous nucleotide in codon 215 in exon 4.

Platelet transfusions in haploidentical haematopoietic stem cell allograft candidates: Protecting HLA-A and HLA-B antigens through eplet analysis.

In patients awaiting an allogeneic haematopoietic stem cell transplantation, platelet transfusion is a risk factor for anti-HLA class I immunization because the resulting donor-specific antibodies complicate the allograft process. The objective of the present study was to determine the feasibility of a novel eplet-based strategy for identifying HLA class I mismatches between potential donors and the recipient when pre-allograft platelet transfusions were required. We included 114 recipient/haploidentical relative pairs. For each pair, we entered HLA-class I typing data into the HLA Eplet Mismatch calculator, defined the list of mismatched eplets (for the recipient versus donor direction) and thus identified the shared HLAs to be avoided. Using this list of HLAs, we defined the theoretical availability of platelet components (PCs) by calculating the virtual panel-reactive antibody (vPRA). We also determined the number of PCs actually available in France by querying the regional transfusion centre's database. The mean ± standard deviation number of highly/moderately exposed eplets to be avoided in platelet transfusions was 5.8 ± 3.3, which led to the prohibition of 38.5 ± 2 HLAs-A and -B. Taking into account the mismatched antigens and the eplet load, the mean ± standard deviation theoretical availability of PCs (according to the vPRA) was respectively 34.49% ± 1.95% for HLA-A and 80% ± 2.3% for HLA-B. A vPRA value below 94.9% for highly or moderately exposed eplets would predict that 10 PCs were actually available nationally. Although epitope protection of HLA molecules is feasible, it significantly restricts the choice of PCs.

Characterization of the novel HLA-DPB1*1359:01 allele by next generation sequencing.

HLA-DPB1*1359:01 differs from HLA-DPB1*03:01:01 by one nucleotide substitution in codon 77 in exon 2.

Characterization of the novel HLA-C*05:282Q allele by next generation sequencing.

HLA-C*05:282Q differs from HLA-C*05:01:01 by one nucleotide substitution in codon -24 in exon 1.

Characterization of the novel HLA-DQB1*06:03:47 allele by next generation sequencing.

HLA-DQB1*06:03:47 differs from HLA-DQB1*06:03:01 by one synonymous nucleotide substitution in codon 158 in exon 3.

Characterization of the novel HLA-DRB1*14:255 allele by next generation sequencing.

HLA-DRB1*14:255 differs from HLA-DRB1*14:54:01 by one nucleotide substitution in codon 205 in exon 4.

Characterization of the novel HLA-C*03:613 allele by next generation sequencing.

HLA-C*03:613 differs from HLA-C*03:02:02 by one nucleotide substitution in codon 190 in exon 4.

Characterization of the novel HLA-C*04:438 allele by next generation sequencing.

HLA-C*04:438 differs from HLA-C*04:01:01 by one nucleotide substitution in codon 237 in exon 4.

Characterization of the novel HLA-DQA1*01:80 allele by next generation sequencing.

HLA-DQA1*01:80 differs from HLA-DQA1*01:04:01 by one nucleotide substitution in codon -18 in exon 1.

HLA graph, a free and ready-to-use bioinformatics tool to explore anti-HLA eplets reactivity pattern.

INTRODUCTION: HLA antigens are highly polymorphic, and their immunogenicity is dependent on the configurations of polymorphic amino acids. Monitoring anti-HLA immunization is essential in organ transplantation, as antibodies directed against HLA molecules are a major cause of rejection. Anti-HLA antibodies are not specific for HLA antigens, but recognize B-cell epitopes present on HLA molecules. METHODS: To better understand antibody reactivity patterns, we calculated the Spearman correlation of the mean fluorescence intensity (MFI) of anti-HLA antibodies identified by a single-antigen assay performed using a Luminex® immunobeads assay on a large number of samples. Then, we built a computer tool analyzing antibody reactivity patterns with an accessibility by a web browser linked to the International Epitope Registry. We also extended our model to Onelambda® and Lifecodes® single-antigen class I and class II assays. RESULTS AND DISCUSSION: The resulting MFI correlations reflect HLA antibody cross-reactivity and eplets similarity. We built HLA Graph, a computer tool that analyzes the eplets involved in antibody reactivity profiles. HLA Graph is usable with Onelambda® and Lifecodes® single-antigen class I and class II assays. The interpretation of reactivity against alleles not tested by the antibody assays and against the alpha and beta chains of HLA-DQ and HLA-DP loci were also developed. CONCLUSION: HLA Graph is a free and ready-to-use bioinformatics tool that can be used by all laboratories performing anti-HLA antibody identification by immunobead assay.

Utility of assessing CD3+ cell chimerism within the first months after allogeneic hematopoietic stem-cell transplantation for acute myeloid leukemia.

After allogeneic hematopoietic stem-cell transplantation (alloHSCT), the chimerism assay is used to monitor cell engraftment and quantify the respective proportions of donor/recipient cells in blood or bone-marrow samples. Here, we aimed to better assess the utility of determining CD3+ cell chimerism within the first 6 months post alloHSCT. One hundred and thirty five patients diagnosed with acute myeloid leukemia were enrolled in this study. We observed significantly lower overall survival and relapse free survival for patients without full donor chimerism (<95%, <98%, <99%) in whole blood at Day 30, as well as at Day 90 after alloHSCT, than for patients with full donor chimerism. This outcome was not observed when assessing selected CD3+ cells. However, at Day 90, patients with discordant whole blood versus selected CD3+ cell chimerism showed both significantly lower overall survival and relapse free survival, giving an interest to assess selected cells chimerism.

Characterization of the novel HLA-C*01:214 allele by sequencing-based typing.

HLA-C*01:214 differs from HLA-C*01:02:01:01 by one nucleotide substitution in codon -10 in exon 1.

Characterization of the novel HLA-C*04:450 allele by next-generation sequencing.

HLA-C*04:450 differs from HLA-C*04:01:01 by one nucleotide substitution in codon 328 in exon 7.

Characterization of the novel HLA-DRB1*04:326 allele by next generation sequencing.

HLA-DRB1*04:326 differs from HLA-DRB1*04:01:01 by one nucleotide substitution in codon 23 in exon 2.