Identification of five new HLA-C alleles by next-generation sequencing.

Five novel HLA-C alleles detected by next-generation sequencing: HLA-C*02:02:73, -C*03:04:106, -C*06:382, -C*07:1114Q and -C*12:408.

A novel HLA-C*03 variant, HLA-C*03:620, identified in a Chinese individual.

HLA-C*03:620 differs from the HLA-C*03:04:01:02 allele by one nucleotide substitution in the exon 3.

Characterisation of the novel HLA-C*15:274 allele using short and long-read sequencing technologies.

The novel HLA-C*15:274 allele, first described in a potential bone marrow donor from Brazil.

Insights into PCSK9-LDLR Regulation and Trafficking via the Differential Functions of MHC-I Proteins HFE and HLA-C.

PCSK9 is implicated in familial hypercholesterolemia via targeting the cell surface PCSK9-LDLR complex toward lysosomal degradation. The M2 repeat in the PCSK9's C-terminal domain is essential for its extracellular function, potentially through its interaction with an unidentified "protein X". The M2 repeat was recently shown to bind an R-x-E motif in MHC-class-I proteins (implicated in the immune system), like HLA-C, and causing their lysosomal degradation. These findings suggested a new role of PCSK9 in the immune system and that HLA-like proteins could be "protein X" candidates. However, the participation of each member of the MHC-I protein family in this process and their regulation of PCSK9's function have yet to be determined. Herein, we compared the implication of MHC-I-like proteins such as HFE (involved in iron homeostasis) and HLA-C on the extracellular function of PCSK9. Our data revealed that the M2 domain regulates the intracellular sorting of the PCSK9-LDLR complex to lysosomes, and that HFE is a new target of PCSK9 that inhibits its activity on the LDLR, whereas HLA-C enhances its function. This work suggests the potential modulation of PCSK9's functions through interactions of HFE and HLA-C.

Characterisation of the novel HLA-C*08:275 allele, first identified in a Brazilian individual.

The novel HLA-C*08:275 allele, first described in a potential bone marrow donor from Brazil.

Discovery of the novel HLA-C*12:02:53 allele in a Taiwanese individual.

Nucleotide substitution in codon 238 of HLA-C*12:02:02:01 results in a novel allele, HLA-C*12:02:53.

Identification of the novel HLA-C allele, HLA-C*12:351Q, using next-generation sequencing.

The novel allele HLA-C*12:351Q differs from HLA-C*12:02:02:01 by a single nucleotide deletion in exon 5.

HLA-B and C Expression Contributes to COVID-19 Disease Severity within a South African Cohort.

Globally, SARS-CoV-2 has negatively impacted many lives and industries due to its rapid spread, severe outcomes, and the need for the implementation of lockdown strategies across the world. SARS-CoV-2 disease severity varies among different populations. Host genetics have been associated with various diseases, and their ability to alter disease susceptibility and severity. In addition, Human Leukocyte Antigen (HLA) expression levels and alleles vary significantly among ethnic groups, which might impact the host's response to SARS-CoV-2. Our previous study highlighted that HLA-A might have an effect on COVID-19 disease severity across ethnicities. Therefore, in this study, we aim to examine the effect of HLA-B and C expression levels on COVID-19 disease severity. To achieve this, we used real-time PCR to measure the HLA mRNA expression levels of SARS-CoV-2-infected individuals from a South African cohort and compared them across ethnic groups, disease outcomes, gender, comorbidities, and age. Our results show (1) that the effect of HLA-B mRNA expression levels was associated with differences in disease severity when we compare symptomatic vs. asymptomatic (p < 0.0001). While HLA-C mRNA expression levels were not associated with COVID-19 disease severity. (2) In addition, we observed that HLA-B and HLA-C mRNA expression levels were significantly different between South African Black individuals and South African Indian individuals (p < 0.0001, p < 0.0001). HLA-B mRNA expression levels among symptomatic South African Black individuals were significantly higher than symptomatic South African Indian individuals (p < 0.0001). In addition, the HLA-B mRNA expression levels of symptomatic South African Black individuals were significantly higher than asymptomatic South African Black individuals (p > 0.0001). HLA-C mRNA expression levels among symptomatic South African Black individuals were significantly higher than among symptomatic South African Indian individuals (p = 0.0217). (3) HLA-C expression levels were significantly different between males and females (p = 0.0052). In addition, the HLA-C expression levels of asymptomatic males are higher than asymptomatic females (p = 0.0375). (4) HLA-B expression levels were significantly different between individuals with and without comorbidities (p = 0.0009). In addition, we observed a significant difference between individuals with no comorbidities and non-communicable diseases (p = 0.0034), in particular, hypertension (p = 0.0487). (5) HLA-B expression levels were significantly different between individuals between 26-35 and 56-65 years (p = 0.0380). Our work is expected to strengthen the understanding of the relationship between HLA and COVID-19 by providing insights into HLA-B and C expression levels across ethnic populations in South Africa among COVID-19-symptomatic and asymptomatic individuals. Our results highlight that HLA-B mRNA expression levels contribute to COVID-19 severity as well as variation in ethnicities associated with COVID-19. Further studies are needed to examine the effect of HLA expression levels across various ethnic groups with contributing factors.

Detection of the HLA-C*07:04:29 allele in a Chinese individual.

HLA-C*07:04:29 differs from HLA-C*07:04:01:01 by a single substitution in exon 4.

Identification of the novel HLA-C allele, HLA-C*07:02:150.

A novel HLA-C*07 allele, now officially designated HLA-C*07:02:150, was identified by next-generation sequencing.

The novel HLA-C*07:02:147 allele characterised by two different sequencing-based typing techniques.

The novel allele HLA-C*07:02:147 differs from HLA-C*07:02:01:01 by one synonymous nucleotide substitution in exon 2.

The novel HLA-C*03:94:02 allele identified by next-generation sequencing in a Chinese individual.

HLA-C*03:94:02 differs from HLA-C*03:94:01 by a single nucleotide substitution in exon 2 (codon 17 GGA->GGG).

Detection of the novel HLA-B*55:01:31, HLA-C*07:1113 alleles and confirmation of HLA-C*12:392.

Novel HLA-B*55:01:31, HLA-C*07:1113 alleles and confirmatory HLA-C*12:392 allele were detected during the HLA typing process.

Recognition of the HLA-C*07:359 allele in Taiwanese individuals.

One nucleotide substitution in codon 264 of HLA-C*07:02:01:01 results in a novel allele, HLA-C*07:359.

Characterization of the novel HLA-C*06:376N allele by Pacific Biosciences HiFi sequencing in a Chinese individual.

HLA-C*06:376N differs from HLA-C*06:02:01:01 by seven nucleotide changes in exon 2, intron 2, and exon 3.

Novel genetic variants of HLA gene associated with Thai Behcet's disease (BD) patients using next generation sequencing technology.

Behçet's disease (BD) manifests as an autoimmune disorder featuring recurrent ulcers and multi-organ involvement, influenced by genetic factors associated with both HLA and non-HLA genes, including TNF-α and ERAP1. The study investigated the susceptible alleles of both Class I and II molecules of the HLA gene in 56 Thai BD patients and 192 healthy controls through next-generation sequencing using a PacBio kit. The study assessed 56 BD patients, primarily females (58.9%), revealing diverse manifestations including ocular (41.1%), vascular (35.7%), skin (55.4%), CNS (5.4%), and GI system (10.7%) involvement. This study found associations between BD and HLA-A*26:01:01 (OR 3.285, 95% CI 1.135-9.504, P-value 0.028), HLA-B*39:01:01 (OR 6.176, 95% CI 1.428-26.712, P-value 0.015), HLA-B*51:01:01 (OR 3.033, 95% CI 1.135-8.103, P-value 0.027), HLA-B*51:01:02 (OR 6.176, 95% CI 1.428-26.712, P-value 0.015), HLA-C*14:02:01 (OR 3.485, 95% CI 1.339-9.065, P-value 0.01), HLA-DRB1*14:54:01 (OR 1.924, 95% CI 1.051-3.522, P-value 0.034), and HLA-DQB1*05:03:01 (OR 3.00, 95% CI 1.323-6.798, P-value 0.008). However, after Bonferroni correction none of these alleles were found to be associated with BD. In haplotype analysis, we found a strong linkage disequilibrium in HLA-B*51:01:01, HLA-C*14:02:01 (P-value 0.0, Pc-value 0.02). Regarding the phenotype, a significant association was found between HLA-DRB1*14:54:01 (OR 11.67, 95% CI 2.86-47.57, P-value 0.001) and BD with ocular involvement, apart from this, no distinct phenotype-HLA association was documented. In summary, our study identifies specific HLA associations in BD. Although limited by a small sample size, we acknowledge the need for further investigation into HLA relationships with CNS, GI, and neurological phenotypes in the Thai population.

The novel HLA-C*06:372 allele, identified in a stem cell donor of an old order mennonite ethnicity.

HLA-C*06:372 differs from HLA-C*06:02:01:01 by a single substitution in exon 4.

[Establishment and validation of prediction models for human leukocyte antigen haplotypes and human leukocyte antigen genotypes].

Objective: To establish prediction models for human leukocyte antigen (HLA) haplotypes and HLA genotypes, and verify the prediction accuracy. Methods: The prediction models were established based on the characteristic of HLA haplotype inheritance and linkage disequilibrium (LD), as well as the invention patents and software copyrights obtained. The models include algorithm and reference databases such as HLA A-C-B-DRB1-DQB1 high-resolution haplotypes database, B-C and DRB1-DQB1 LD database, G group alleles table, and NMDP Code alleles table. The prediction algorithm involves data processing, comparison with reference data, filtering results, probability calculation and ranking, confidence degree estimation, and output of prediction results. The accuracy of the predictions was verified by comparing them with the correct results, and the relationship between prediction accuracy and the probability distribution and confidence degree of the predicted results was analyzed. Results: The HLA haplotypes and genotypes prediction models were established. The prediction algorithm included the prediction of A-C-B-DRB1-DQB1 haplotypes according to HLA-A, B, DRB1, C, DQB1 genotypes, the prediction of C and DQB1 high-resolution results according to A, B and DRB1 high-resolution results, and the prediction of A, B, DRB1, C and DQB1 high resolution results according to the A, B and DRB1 intermediate or low resolution results. Validation results of "Predicting A-C-B-DRB1-DQB1 haplotypes basing on HLA-A, B, DRB1, C, DQB1 genotypes" model: for 787 data, the accuracy was 94.0% (740/787) with 740 correct predictions, 34 incorrect predictions, and 13 instances with no predicted results. For 847 data, the accuracy was 100% (847/847). The 2 411 and 2 594 haplotype combinations predicted from 787 and 847 data were grouped according to confidence degree, the accuracy was 100% (48/48, 114/114) for a confidence degree of 1, 96.2% (303/315) and 97.8% (409/418) for a confidence degree of 2 respectively. Validation results of "Predicting A, B, DRB1 and C, DQB1 high-resolution genotypes basing on HLA-A, B, DRB1 high, intermediate, or low resolution genotypes" model: when predicting C and DQB1 high resolution genotypes basing on A, B, and DRB1 high resolution genotypes, 89.3% (1 459/1 634) of the predictions were correct. The accuracy for the top 2 predicted probability (GPP) ranking was 79.2% (1 156/1 459), and for the top 10, it was 95.0% (1 386/1 459). Furthermore, when GPP≥90% and GPP 50%-90%, the prediction accuracy was 81.3% (209/257) and 72.8% (447/614) respectively. The accuracy of predicting C and DQB1 high resolution genotypes basing on the results of A, B, and DRB1 high resolution genotypes from the China Marrow Donor Program was 87.0% (20/23). The accuracy of predicting A, B, DRB1, C, and DQB1 high resolution genotypes basing on the results of A, B, and DRB1 intermediate or low-resolution genotypes was 70.0% (7/10) and 52.5% (21/40) respectively. When predicting whether the patient is likely to have a HLA 10/10 matched donor, the accuracy of the top 2 GPP combinations with a proportion of ≥50% was 85.7% (6/7). Conclusions: When using A, B, DRB1, C, DQB1 genotypes to predict A-C-B-DRB1-DQB1 haplotype combinations, the results with a confidence degree of 1 and 2 are reliable. When predicting C and DQB1 genotypes according to A, B and DRB1 genotypes, the top 10 results ranked by GPP are reliable, and the top 2 results with GPP≥50% are more reliable.

Immunogenetic Background of Chronic Lymphoproliferative Disorders in Romanian Patients-Case Control Study.

BACKGROUND AND OBJECTIVES: The implications of the genetic component in the initiation and development of chronic lymphoproliferative disorders have been the subject of intense research efforts. Some of the most important genes involved in the occurrence and evolution of these pathologies are the HLA genes. The aim of this study is to analyze, for the first time, possible associations between chronic lymphoproliferative diseases and certain HLA alleles in the Romanian population. MATERIALS AND METHODS: This study included 38 patients with chronic lymphoproliferative disorders, diagnosed between 2021 and 2022 at Fundeni Clinical Institute, Bucharest, Romania, and 50 healthy controls. HLA class I and class II genes (HLA-A/B/C, HLA-DQB1/DPB1/DRB1) were investigated by doing high resolution genotyping using sequence specific primers (SSP). RESULTS: Several HLA alleles were strongly associated with chronic lymphoproliferative disorders. The most important finding was that the HLA-C*02:02 (p = 0.002, OR = 1.101), and HLA-C*12:02 (p = 0.002, OR = 1.101) have a predisposing role in the development of chronic lymphoproliferative disorders. Moreover, we identified that HLA-A*11:01 (p = 0.01, OR = 0.16), HLA-B*35:02 (p = 0.037, OR = 0.94), HLA-B*81:01 (p = 0.037, OR = 0.94), HLA-C*07:02 (p = 0.036, OR = 0.34), HLA-DRB1*11:01 (p = 0.021, OR = 0.19), and HLA-DRB1*13:02 (p = 0.037, OR = 0.94), alleles have protective roles. CONCLUSIONS: Our study indicates that HLA-C*02:02 and HLA-C*12:02 are positively associated with chronic lymphoproliferative disorders for our Romanian patients while HLA-DRB1*11:01, HLA-DRB1*13:02, and HLA-B*35:02 alleles have a protective role against these diseases.