scholarly journals Accuracy of programs for the determination of HLA alleles from NGS data

2017 ◽  
Author(s):  
Antti Larjo ◽  
Robert Eveleigh ◽  
Elina Kilpeläinen ◽  
Tony Kwan ◽  
Tomi Pastinen ◽  
...  
Keyword(s):  
Human Leukocyte ◽  
Hla Typing ◽  
Ensemble Prediction ◽  
Hla Alleles ◽  
Leukocyte Antigen ◽  
Peptide Antigens ◽  
Hla Genes ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

AbstractThe human leukocyte antigen (HLA) genes code for proteins that play a central role in the function of the immune system by presenting peptide antigens to T cells. As HLA genes show extremely high genetic polymorphism, HLA typing on the allele level is demanding and is based on DNA sequencing. Determination of HLA alleles is warranted as many HLA alleles are major genetic factors that confer susceptibility to autoimmune diseases and is important for the matching of HLA alleles in transplantation. Here, we compared the accuracy of several published HLA-typing algorithms that are based on next generation sequencing (NGS) data. As genome screens are becoming increasingly routine in research, we wanted to test how well HLA alleles can be deduced from genome screens not designed for HLA typing. The accuracies were assessed using datasets consisting of NGS data produced using the ImmunoSEQ platform, including the full 4 Mbp HLA segment, from 94 stem cell transplantation patients and exome sequences from the 1000 Genomes collection. When used with the default settings none of the methods gave perfect results for all the genes and samples. However, we found that ensemble prediction of the results or modifications of the settings could be used to improve accuracy. Most of the algorithms did not perform very well for the exome-only data. The results indicate that the use of these algorithms for accurate HLA allele determination based on NGS data is not straightforward.

scholarly journals Familial Pemphigus Vulgaris Occured in a Father and Son as the First Confirmed Cases

2016 ◽  
Vol 2016 ◽  
pp. 1-4
Author(s):  
Ali Haydar Eskiocak ◽  
Birgul Ozkesici ◽  
Soner Uzun
Keyword(s):  
Genetic Predisposition ◽  
Human Leukocyte ◽  
Pemphigus Vulgaris ◽  
Hla Typing ◽  
Enzyme Linked Immunosorbent Assay ◽  
Leukocyte Antigen ◽  
Hla Genes ◽  
Mother And Daughter ◽  
First Occurrence ◽  
Father And Son

Pemphigus vulgaris (PV) is a chronic autoimmune bullous disease of the skin and mucous membranes. Although there is some evidence pointing towards a genetic predisposition by some human leukocyte antigen (HLA) genes, familial occurrence of PV is very rare. Most of the familial PV cases so far reported have been in mother and daughter and in siblings. PV in father and son, as presented here, has not been reported in the literature before, except an unconfirmed report. The diagnosis of PV was established by histologic, cytologic studies and enzyme linked immunosorbent assay (ELISA) in Case1and by ELISA and BIOCHIP indirect immunofluorescence test in Case2. The son was responsive to moderate doses of methylprednisolone, with the treatment continuing with tapered doses. The father was in a subclinic condition; consequently, only close follow-up was recommended. HLA typing studies revealed identical HLA alleles of HLA-DR4 (DRB1⁎04) and HLA-DQB1⁎03in both of our cases; this had been found to be associated with PV in prior studies. Familial occurrences of PV and related HLA genes indicate the importance of genetic predisposition. The first occurrence of confirmed familial PV in father and son is reported here.

scholarly journals arcasHLA: high resolution HLA typing from RNA seq

2018 ◽  
Author(s):  
Rose Orenbuch ◽  
Ioan Filip ◽  
Devon Comito ◽  
Jeffrey Shaman ◽  
Itsik Pe'er ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Mhc Class Ii ◽  
Critical Role ◽  
Human Leukocyte ◽  
Hla Typing ◽  
Sequencing Data ◽  
Leukocyte Antigen ◽  
Hla Genes ◽  
Biological Dataset ◽  
High Level

Human leukocyte antigen (HLA) locus makes up the major compatibility complex (MHC) and plays a critical role in host response to disease, including cancers and autoimmune disorders. In the clinical setting, HLA typing is necessary for determining tissue compatibility. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between the HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional splicing and bias due to amplification. Here, we present arcasHLA: a fast and accurate in silico tool that infers HLA genotypes from RNA sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two field precision for MHC class I genes, and over 99.7% for MHC class II. Importantly, arcasHLA takes as its input pre-aligned BAM files, and outputs three-field resolution for all HLA genes in less than 2 minutes. Finally, we discuss evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies. arcasHLA is available at https://github.com/RabadanLab/arcasHLA.

scholarly journals SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes

2019 ◽  
Vol 28 (5) ◽  
pp. 627-635 ◽  
Author(s):  
Jessika Nordin ◽  
Adam Ameur ◽  
Kerstin Lindblad-Toh ◽  
Ulf Gyllensten ◽  
Jennifer R. S. Meadows
Keyword(s):  
Human Leukocyte ◽  
Class Ii ◽  
Hla Typing ◽  
Class I ◽  
Sequencing Data ◽  
High Confidence ◽  
Leukocyte Antigen ◽  
Hla Dqa1 ◽  
Inference Methods ◽  
Ngs Data

AbstractThere is a need to accurately call human leukocyte antigen (HLA) genes from existing short-read sequencing data, however there is no single solution that matches the gold standard of Sanger sequenced lab typing. Here we aimed to combine results from available software programs, minimizing the biases of applied algorithm and HLA reference. The result is a robust HLA population resource for the published 1000 Swedish genomes, and a framework for future HLA interrogation. HLA 2nd-field alleles were called using four imputation and inference methods for the classical eight genes (class I: HLA-A, HLA-B, HLA-C; class II: HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1). A high confidence population set (SweHLA) was determined using an n−1 concordance rule for class I (four software) and class II (three software) alleles. Results were compared across populations and individual programs benchmarked to SweHLA. Per gene, 875 to 988 of the 1000 samples were genotyped in SweHLA; 920 samples had at least seven loci called. While a small fraction of reference alleles were common to all software (class I = 1.9% and class II = 4.1%), this did not affect the overall call rate. Gene-level concordance was high compared to European populations (>0.83%), with COX and PGF the dominant SweHLA haplotypes. We noted that 15/18 discordant alleles (delta allele frequency >2) were previously reported as disease-associated. These differences could in part explain across-study genetic replication failures, reinforcing the need to use multiple software solutions. SweHLA demonstrates a way to use existing NGS data to generate a population resource agnostic to individual HLA software biases.

scholarly journals Frequency of HLA Alleles in a Group of Severe COVID‐19 Irani-an Patients

2021 ◽  
Author(s):  
Ramin Hamidi Farahani ◽  
Emran Esmaeilzadeh ◽  
Amir Nezami Asl ◽  
Mohammad Foad Heidari ◽  
Ebrahim Hazrati
Keyword(s):  
Reference Group ◽  
Human Leukocyte ◽  
Severe Form ◽  
Hla Typing ◽  
Allele Frequency Distribution ◽  
Hla Alleles ◽  
Leukocyte Antigen ◽  
Potential Association ◽  
Related Proteins ◽  
Iranian Patients

Background: Human Leukocyte Antigen (HLA) system composed of a group of related proteins with important functions in the immune system. Several studies have reported that there is a significant association between specific HLA alleles and the susceptibility to different infectious diseases. This study aimed to detect the specific HLA alleles that cause higher susceptibility to COVID-19, we analyzed the HLA allele frequency distribution in Iranian patients with a severe form of COVID-19. Methods: Overall, 48 severe cases of COVID-19 that were hospitalized and required intensive care unit (ICU) admission between Oct and Dec 2020 were included in this study. Genomic DNA was extracted from the peripheral blood samples and HLA typing (Locus A, B, and DR) was performed for the patients. Results: After analyzing and comparing the results with a reference group of 500 Iranian individuals, a significant association was found for HLA-B*38, HLA-A*68, HLA-A*24, and HLA-DRB1*01. Conclusion: These results may be valuable for studying the potential association of specific HLA alleles with susceptibility to COVID-19 and mortality due to the disease.

scholarly journals SweHLA: the high confidence HLA typing bio-resource drawn from 1 000 Swedish genomes

2019 ◽  
Author(s):  
Jessika Nordin ◽  
Adam Ameur ◽  
Kerstin Lindblad-Toh ◽  
Ulf Gyllensten ◽  
Jennifer R.S. Meadows
Keyword(s):  
Human Leukocyte ◽  
Class Ii ◽  
Hla Typing ◽  
Class I ◽  
Sequencing Data ◽  
High Confidence ◽  
Leukocyte Antigen ◽  
Gene Level ◽  
Inference Methods ◽  
Ngs Data

AbstractThere is a need to accurately call human leukocyte antigen (HLA) genes from existing short-read sequencing data, however there is no single solution that matches the gold standard of lab typing. Here we aimed to combine results from available software, minimising the biases of applied algorithm and HLA reference. The result is a robust HLA population resource for the published 1 000 Swedish genomes, and a framework for future HLA interrogation. HLA 2-field alleles were called using four imputation and inference methods for the classical eight genes (class I: HLA-A, -B, -C; class II: HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1). A high confidence population set (SweHLA) was determined using an n-1 concordance rule for class I (four software) and class II (three software) alleles. Results were compared across populations and individual programs benchmarked to SweHLA. Per allele, 875 to 988 of the 1 000 samples were genotyped in SweHLA; 920 samples had at least seven loci. While a small fraction of reference alleles were common to all software (class I=1.9% and class II=4.1%), this did not affect the overall call rate. Gene-level concordance was high compared to European populations (>0.83%), with COX and PGF the dominant SweHLA haplotypes. We noted that 15/18 discordant alleles (delta allele frequency > 2) were previously reported as disease-associated. These differences could in part explain across-study genetic replication failures, reinforcing the need to use multiple software. SweHLA demonstrates a way to use existing NGS data to generate a population resource agnostic to individual HLA software biases.

scholarly journals Human Leukocyte Antigen (HLA) Influence on Prognosis of Autoimmune Hearing Loss

2021 ◽  
Vol 11 (1) ◽  
pp. 31-37
Author(s):  
George Psillas ◽  
Paris Binos ◽  
Grigorios G Dimas ◽  
Michalis Daniilidis ◽  
Jiannis Constantinidis
Keyword(s):  
Hearing Loss ◽  
Human Leukocyte Antigen ◽  
Clinical Symptoms ◽  
Human Leukocyte ◽  
Hla Typing ◽  
Response To Treatment ◽  
Hla B27 ◽  
Hla Alleles ◽  
Leukocyte Antigen ◽  
Autoimmune Hearing Loss

Background: To evaluate the effect of human leukocyte antigen (HLA) on hearing outcome in patients suffering from autoimmune hearing loss (AIHL). Materials and Methods: The diagnosis of AIHL was essentially based on clinical symptoms, such as recurrent, sudden, fluctuating, or quickly progressing (<12 months) sensorineural hearing loss (uni-/bilateral). The molecular typing of HLA alleles was achieved by using polymerase chain reaction procedures. Patients underwent a tapering schema of steroid treatment and audiometric features were recorded. A logistic regression model was used to identify which HLA typing alleles were statistically significant in patients’ response to treatment. Results: Forty patients with AIHL were found to be carriers of HLA B27, B35, B51, C4, C7, and DRB1*04 alleles. No statistically significant influence of HLA B27, B35, B51, C4, C7, DRB1*04 HLA alleles typing was detected for the prognosis of AIHL. In these patients, the onset of AIHL was mainly progressive (53.8%), 29.2% of them had moderate hearing loss, and most of the cases had both bilateral hearing loss (62.5%) and downsloping audiogram (40%). Conclusion: The presence of HLA B27, B35, B51, C4, C7, and DRB1*04 alleles had no significant effect on a favorable outcome of AIHL. However, larger samples of patients are necessary in order to improve the knowledge about the HLA influence on the clinical course of AIHL.

scholarly journals Practical Use of Methods for Imputation of HLA Alleles from SNP Genotype Data

2016 ◽  
Author(s):  
Allan Motyer ◽  
Damjan Vukcevic ◽  
Alexander Dilthey ◽  
Peter Donnelly ◽  
Gil McVean ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Imputation Accuracy ◽  
Human Leukocyte ◽  
Hla Typing ◽  
Genotype Data ◽  
Hla Alleles ◽  
Imputation Methods ◽  
Hla Genes ◽  
Disease Associations

AbstractThe human leukocyte antigen (HLA) genes play an essential role in immune function. Typing of HLA alleles is critical for transplantation and is informative for many disease associations. The high cost of accurate lab-based HLA typing has precluded its use in large-scale disease-association studies. The development of statistical methods to type alleles using linkage disequilibrium with nearby SNPs, called HLA imputation, has allowed large cohorts of individuals to be typed accurately, so that massive numbers of affected individuals and controls may be studied. This has resulted in many important findings. Several HLA imputation methods have been widely used, however their relative performance has not been adequately addressed. We have conducted a comprehensive study to evaluate the most widely used HLA imputation methods. We assembled a multi-ethnic panel of 10,561 individuals with SNP genotype data and lab-based typing of alleles at 11 HLA genes at two-field resolution, and used it to train and validate each method. Use of this panel leads to imputation accuracy far superior to what is currently publicly available. We present a highly-accurate new imputation method, HLA*IMP:03. We address the question of optimal use of HLA imputations in tests of genetic association, showing that it is usually not necessary to apply a probability threshold to achieve maximal power. We also investigated the effect on accuracy of SNP density and population stratification at the continental level and show that neither of these are a significant concern.

scholarly journals PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation

2021 ◽  
Vol 11 (11) ◽  
pp. 1230
Author(s):  
Jittima Piriyapongsa ◽  
Chanathip Sukritha ◽  
Pavita Kaewprommal ◽  
Chalermpong Intarat ◽  
Kwankom Triparn ◽  
...  
Keyword(s):  
Human Leukocyte ◽  
Web Based ◽  
Leukocyte Antigen ◽  
Genome Wide ◽  
Immune Mediated ◽  
Hla Genotypes ◽  
One Stop ◽  
Potential Risks ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

The increasing availability of next generation sequencing (NGS) for personal genomics could promote pharmacogenomics (PGx) discovery and application. However, current tools for analysis and interpretation of pharmacogenomic variants from NGS data are inadequate, as none offer comprehensive analytic functions in a simple, web-based platform. In addition, no tools exist to analyze human leukocyte antigen (HLA) genes for determining potential risks of immune-mediated adverse drug reaction (IM-ADR). We describe PharmVIP, a web-based PGx tool, for one-stop comprehensive analysis and interpretation of genome-wide variants obtained from NGS platforms. PharmVIP comprises three main interpretation modules covering analyses of pharmacogenes involved in pharmacokinetics, pharmacodynamics and IM-ADR. The Guideline module provides Clinical Pharmacogenetics Implementation Consortium (CPIC) drug guideline recommendations based on the translation of genotypic data in genes having guidelines. The HLA module reports HLA genotypes, potential adverse drug reactions, and the relevant drug guidelines. The Pharmacogenes module is employed for prioritizing variants according to variant effect on gene function. Detailed, customizable reports are provided as exportable files and as an interactive web version. PharmVIP is a new integrated NGS workflow for the PGx community to facilitate discovery and clinical application.

scholarly journals Human Leukocyte Antigen and Red Blood Cells Impact Umbilical Cord Blood CD34+ Cell Viability after Thawing

2019 ◽  
Vol 20 (19) ◽  
pp. 4875 ◽  
Author(s):  
Vanegas ◽  
Galindo ◽  
Páez-Gutiérrez ◽  
González-Acero ◽  
Medina-Valderrama ◽  
...  
Keyword(s):  
Human Leukocyte Antigen ◽  
Cell Viability ◽  
Cord Blood ◽  
Red Blood Cells ◽  
Umbilical Cord ◽  
Umbilical Cord Blood ◽  
Blood Cells ◽  
Human Leukocyte ◽  
Hla Typing ◽  
Leukocyte Antigen

Hematopoietic progenitor cell (HPC) transplantation is a treatment option for malignant and nonmalignant diseases. Umbilical cord blood (UCB) is an important HPC source, mainly for pediatric patients. It has been demonstrated that human leukocyte antigen (HLA) matching and cell dose are the most important features impacting clinical outcomes. However, UCB matching is performed using low resolution HLA typing and it has been demonstrated that the unnoticed mismatches negatively impact the transplant. Since we found differences in CD34+ viability after thawing of UCB units matched for two different patients (p = 0.05), we presumed a possible association between CD34+ cell viability and HLA. We performed a multivariate linear model (n = 67), comprising pre-cryopreservation variables and high resolution HLA genotypes separately. We found that pre-cryopreservation red blood cells (RBC), granulocytes, and viable CD34+ cell count significantly impacted CD34+ viability after thawing, along with HLA-B or -C (R2 = 0.95, p = 0.01; R2 = 0.56, p = 0.007, respectively). Although HLA-B*40:02 may have a negative impact on CD34+ cell viability, RBC depletion significantly improves it.

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