18th International HLA and Immunogenetics Workshop: Report on the SNP‐HLA Reference Consortium (SHLARC) component

Abstract

The SNP‐HLA Reference Consortium (SHLARC), a component of the 18th International HLA and Immunogenetics Workshop, is aimed at collecting diverse and extensive human leukocyte antigen (HLA) data to create custom reference panels and enhance HLA imputation techniques. Genome‐wide association studies (GWAS) have significantly contributed to identifying genetic associations with various diseases. The HLA genomic region has emerged as the top locus in GWAS, particularly in immune‐related disorders. However, the limited information provided by single nucleotide polymorphisms (SNPs), the hallmark of GWAS, poses challenges, especially in the HLA region, where strong linkage disequilibrium (LD) spans several megabases. HLA imputation techniques have been developed using statistical inference in response to these challenges. These techniques enable the prediction of HLA alleles from genotyped GWAS SNPs. Here we present the SHLARC activities, a collaborative effort to create extensive, and multi‐ethnic reference panels to enhance HLA imputation accuracy.

A multi‐ethnic reference panel to impute HLA classical and non‐classical class I alleles in admixed samples: Testing imputation accuracy in an admixed sample from Brazil

“…Our findings contribute to the SHLARC ongoing efforts to enhance the power of HLA association studies by providing the immunogenetics community with large and diverse reference panels for HLA imputation 12,34 . In this study, we assessed the accuracy of different reference panels, built with samples from different genetic backgrounds, in predicting HLA alleles in randomly selected samples and an independent Brazilian dataset.…”

Construction and efficacy testing of DNA vaccines containing HLA-A*02:01-restricted SARS-CoV-2 T-cell epitopes predicted by immunoinformatics

“…Immunoinformatics-based T-cell epitope prediction algorithms such as those implemented by the IEDB allow in silico prediction of potentially immunogenic epitopes of specified length(s) and MHC specificities. In this study, we selected one of the most prevalent HLA-A subtypes, namely, HLA-A*02:01 [26,27], and selected an epitope length of 14 amino acid residues for prediction (Supplementary Tables S1).…”

“…In the present study, we used the Immune Epitope Database (IEDB) epitope prediction platform [25] and scanned the entire SARS-CoV-2 (Wuhan-hu-1) proteome for potential CD8 + T-cell epitopes that are present in one of the most prevalent HLA-A subtypes (HLA-A*02:01) [26,27]. The immunogenicity of the predicted epitopes in natural infections was tested by analyzing the recognition of chemically synthesized epitope peptides by peripheral blood mononuclear cells (PBMCs) from convalescent SARS-CoV-2 (Wuhan-hu-1)-infected patients.…”

Unveiling the Significance of HLA and KIR Diversity in Underrepresented Populations

“…However, due to the high prevalence of HLA polymorphisms and the high variation across populations, HLA allele imputation requires a large amount of information from each population. It relies on reference panels of known SNPs, HLA haplotypes, and genotypes that allow for linking SNPs and HLA alleles, which are specific to each population; obviously, this approach is not suitable in many cases, especially in underrepresented populations [ 35 ]. The vast majority of GWASs have been conducted in European populations [ 36 , 37 ], and imputations increases in complexity when the population has high admixture, as is the case for Latin Americans.…”