Genomic sequence of HLA-DPA1*01:03:01:81, -DPA1*01:03:01:89, -DPA1*01:03:01:90, -DPA1*01:03:01:91, -DPA1*01:03:01:93 and -DPA1*01:03:01:94 alleles in Spanish individuals.
Genomic sequence of HLA-DPA1*01:03:01:81, -DPA1*01:03:01:89, -DPA1*01:03:01:90, -DPA1*01:03:01:91, -DPA1*01:03:01:93 and -DPA1*01:03:01:94 alleles in Spanish individuals.
HLA-DPB1*05:01:22 differs from HLA-DPB1*05:01:01:01 by one nucleotide in exon 3.
HLA-DQB1*04:01:01:03 differs from HLA-DQB1*04:01:01:01 by a 10-nucleotide fragment insertion in intron 1.
Haploidentical haematopoietic stem cell transplantation (haplo-HSCT) is one of the most effective therapies for treating malignant haematological disorders. However, HLA disparities are significant barriers to the success of this process since they increase the risk of graft versus host disease (GvHD). HLA disparities quantification could help to anticipate the probability and degree of GvHD, but the best tool for such quantification remains a challenge. The aim of this study was to quantify the degree of HLA epitope incompatibilities using PIRCHE (Predicted Indirectly Recognisable HLA Epitopes) algorithm for immunogenicity prediction and their potential relationship with GvHD degree and clinical outcome. We studied 145 patients who underwent a haplo-HSCT with post-transplant cyclophosphamide (PTCy) from a related donor between 2013 and 2020 at our centre evaluating molecular HLA mismatches by PIRCHE-algorithm. Patients with PIRCHE Score (PS) I + II > 38 in GvH direction, developed acute GvHD grade II–IV earlier than their counterparts (HR: 1.71, 95% CI: 1.02–2.87, p = 0.032). In addition, PS-B > 1 in GvH direction was an independent risk factor for chronic GvHD, (HR: 2.51, 95% CI 1.17–5.36, p = 0.017). A higher incidence of relapse was found for patients with PS-II > 28 HvG (HR: 9.16, 95% CI: 2.47–33.92, p < 0.001) which also favoured a worse GvHD/relapse-free survival in patients with PS-II > 27 in HvG direction (HR: 1.88, 95% CI: 1.11–3.18, p = 0.017). These findings indicate that the alloreactivity inferred by epitope HLA disparities is associated with post-transplant outcomes. Thus, analysing PS could benefit the selection of the most suitable donors allowing patient stratification based on HLA mismatches in the context of haplo-HSCT with PTCy.
Several molecular mismatch assessment approaches exist, but data on their combined use are limited. In this study, we aimed to define distinct risk groups for rejection based on the combination of three molecular mismatch assessment approaches (i.e., eplet mismatch count, the number of highly immunogenic eplets and PIRCHE-II score) in 439 consecutive immunological standard risk transplantations. For each molecular mismatch assessment approach, ROC analyses were used to define cut-offs for prediction of (sub) clinical rejection according to Banff 2019 classification within the first year post-transplant as a reference. If all three scores were below the cut-off, the patient was assigned to the low-risk group (19% of patients); if all three scores were above the cut-off, the patient was assigned to the high-risk group (21% of patients). The one-year incidence of (sub) clinical rejection was 12% in the low-risk group and 33% in the high-risk group (p = 0.003). Internal validation of the assigned risk groups for prediction of other outcomes revealed a high consistency: clinical rejection (6% vs. 24%; p = 0.004), ATG-treated rejection (1% vs. 16%; p < 0.001) and development of de novo HLA-DSA at 5 years post-transplant (6% vs. 25%; p = 0.003). The molecular mismatch risk group was an independent predictor for (sub) clinical rejection (high-risk vs. low-risk: hazard ratio 3.11 [95%-CI 1.50–6.45]; p = 0.002). We conclude that combining molecular mismatch approaches allows us to distinguish low- and high-risk groups among standard renal allograft recipients. Independent validation in other patient populations and different ethnicities is required.
HLA-C*14:153 differs from HLA-C*14:02:01:01 by a non-synonymous nucleotide substitution in exon 2.
Discovery of a novel HLA class I allele, HLA-C*12:424, identified using two NGS methods.
HLA-DRB5*02:02:05 differs from HLA-DRB5*02:02:01 by one nucleotide substitution in codon 134 in exon 3.
The following sequences have been submitted to the Nomenclature Committee since the April, May and June 2024 nomenclature update [1] and, following agreed policy, have been assigned official allele designations [2]. Full details of all sequences will be published in a forthcoming report.
Below are listed the newly assigned sequences (Table 1) and confirmations of previously reported sequences (Table 2). The accession number of each sequence is given and these can be used to retrieve the sequence files from the EMBL, GenBank or DDBJ data libraries. Although accession numbers have been assigned by the data-libraries and most sequences are already available, there is still the possibility that an author may not yet have allowed the sequence to be released; in such a case you will have to contact the submitting author directly. Additional information pertaining to new sequences is often included in the publications describing these alleles; a listing of recent publications that describe new HLA sequences is given in Table 3. An additional 221 alleles were recently published but have not been included in Table 3 due to space considerations [3, 4].
All new and confirmatory sequences should now be submitted directly to the WHO Nomenclature Committee for Factors of the HLA System via the IPD-IMGT/HLA Database using the sequence submission tool provided [5, 6]. The IPD-IMGT/HLA Database may be accessed via the World Wide Web at: www.ebi.ac.uk/ipd/imgt/hla.
The authors declare no conflicts of interest.
Identification of the novel HLA-DPA1*02:141 allele that differs from HLA-DPA1*02:02:02:01 at one position in exon 4.
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