HLA class II allele DRB1*16:02 is associated with anti-NMDAR encephalitis

2019 ◽  
Vol 90 (6) ◽  
pp. 652-658 ◽  
Author(s):  
Yaqing Shu ◽  
Wei Qiu ◽  
Junfeng Zheng ◽  
Xiaobo Sun ◽  
Junping Yin ◽  
...  
Keyword(s):  
Autoimmune Encephalitis ◽  
Bioinformatic Analysis ◽  
Class Ii ◽  
Hla Class Ii ◽  
Chinese Han ◽  
Binding Prediction ◽  
Computational Docking ◽  
Nmdar Encephalitis ◽  
Close Relationship ◽  
Peptide Binding Prediction

Background and objectiveAetiology and pathogenesis of anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis, the most common autoimmune encephalitis, is largely unknown. Since an association of the disease with the human leucocyte antigen (HLA) has not been shown so far, we here investigated whether anti-NMDAR encephalitis is associated with the HLA locus.MethodsHLA loci of 61 patients with anti-NMDAR encephalitis and 571 healthy controls from the Chinese Han population were genotyped and analysed for this study.ResultsOur results show that the DRB1*16:02 allele is associated with anti-NMDAR encephalitis (OR 3.416, 95% CI 1.817 to 6.174, p=8.9×10−5, padj=0.021), with a higher allele frequency in patients (14.75%) than in controls (4.82%). This association was found to be independent of tumour formation. Besides disease susceptibility, DRB1*16:02 is also related to the clinical outcome of patients during treatment, where patients with DRB1*16:02 showed a lower therapeutic response to the treatment than patients with other HLA alleles (p=0.033). Bioinformatic analysis using HLA peptide-binding prediction algorithms and computational docking suggested a close relationship between the NR1 subunit of NMDAR and the DRB1*16:02.ConclusionsThis study for the first time demonstrates an association between specific HLA class II alleles and anti-NMDAR encephalitis, providing novel insights into the pathomechanism of the disease.

P067 Evaluation of HLA class II peptide binding prediction models against a robust experimental method

2017 ◽  
Vol 78 ◽  
pp. 103
Author(s):  
Kirsten M. Anderson ◽  
Christina Roark ◽  
Tiana Stastny ◽  
Michael Aubrey ◽  
Brian Freed
Keyword(s):  
Experimental Method ◽  
Prediction Models ◽  
Peptide Binding ◽  
Class Ii ◽  
Hla Class Ii ◽  
Binding Prediction ◽  
Peptide Binding Prediction

scholarly journals Myelin oligodendrocyte glycoprotein-associated disorders are associated with HLA subtypes in a Chinese paediatric-onset cohort

2020 ◽  
Vol 91 (7) ◽  
pp. 733-739
Author(s):  
Xiaobo Sun ◽  
Wei Qiu ◽  
Jingqi Wang ◽  
Shisi Wang ◽  
Yuge Wang ◽  
...  
Keyword(s):  
Class Ii ◽  
Myelin Oligodendrocyte Glycoprotein ◽  
Target Sequence ◽  
Supporting Evidence ◽  
Adult Onset ◽  
Chinese Han ◽  
Binding Prediction ◽  
Computational Docking ◽  
Scale Scores

ObjectiveMyelin oligodendrocyte glycoprotein-associated disorders (MOGADs) are a rare new neurological autoimmune disease with unclear pathogenesis. Since a linkage of the disease to the human leucocyte antigen (HLA) has not been shown, we here investigated whether MOGAD is associated with the HLA locus.MethodsHLA genotypes of 95 patients with MOGADs, assessed between 2016 and 2018 from three academic centres, were compared with 481 healthy Chinese Han individuals. Patients with MOGADs included 51 paediatric-onset and 44 adult-onset cases. All patients were seropositive for IgG targeting the myelin oligodendrocyte glycoprotein (MOG).ResultsPaediatric-onset MOGAD was associated with the DQB1*05:02–DRB1*16:02 alleles (OR=2.43; OR=3.28) or haplotype (OR=2.84) of HLA class II genes. The prevalence of these genotypes in patients with paediatric-onset MOGAD was significantly higher than healthy controls (padj=0.0154; padj=0.0221; padj=0.0331). By contrast, adult-onset MOGAD was not associated with any HLA genotype. Clinically, patients with the DQB1*05:02–DRB1*16:02 haplotype exhibited significantly higher expanded disability status scale scores at onset (p=0.004) and were more likely to undergo a disease relapse (p=0.030). HLA–peptide binding prediction algorithms and computational docking analysis provided supporting evidence for the close relationship between the MOG peptide subunit and DQB1*05:02 allele. In vitro results indicated that site-specific mutations of the predicted target sequence reduced the antigen–antibody binding, especially in the paediatric-onset group with DQB1*05:02 allele.ConclusionsThis study demonstrates a possible association between specific HLA class II alleles and paediatric-onset MOGAD, providing evidence for the conjecture that different aetiology and pathogenesis likely underlie paediatric-onset and adult-onset cases of MOGAD.

scholarly journals DeepSeqPanII: an interpretable recurrent neural network model with attention mechanism for peptide-HLA class II binding prediction

2020 ◽  
Author(s):  
ZHONGHAO LIU ◽  
Jing Jin ◽  
Yuxin Cui ◽  
Zheng Xiong ◽  
Alireza Nasiri ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Network Structure ◽  
State Of The Art ◽  
Class Ii ◽  
Hla Class Ii ◽  
Binding Prediction ◽  
Neural Network Structure ◽  
Art Performance

Abstract Background: Human leukocyte antigen (HLA) complex molecules play an essential role in immune interactions by presenting peptides on the cell surface to T cells. With significant progress in deep learning, a series of neural network based models have been proposed and demonstrated with their good performances for peptide-HLA class I binding prediction. However, there still lack effective binding prediction models for HLA class II protein binding with peptides due to its inherent challenges. In this work, we present a novel sequence-based pan-specific neural network structure, DeepSeaPanII, for peptide-HLA class II binding prediction. Compared with existing pan-specific models, our model is an end-to-end neural network model without the need for pre- or post-processing on input samples. Results: The leave-one-allele-out cross validation and benchmark evaluation results show that our proposed network model achieved state-of-the-art performance in HLA-II peptide binding. Besides state-of-the-art performance in binding affinity prediction, DeepSeqPanII can also extract biological insight on the binding mechanism over the peptide and HLA sequences by its attention mechanism based binding core prediction capability. Conclusions: In this work, we present a novel neural network structure for peptide-HLA class II binding prediction. It has state-of-the-art performance and could display insightful information it learned benefiting from attention module we carefully designed. Without requiring additional data, this structure could be applied to other related sequence problems. The source code and trained models are freely available at https://github.com/pcpLiu/DeepSeqPanII.

scholarly journals Common Denominators in the Immunobiology of IgG4 Autoimmune Diseases: What Do Glomerulonephritis, Pemphigus Vulgaris, Myasthenia Gravis, Thrombotic Thrombocytopenic Purpura and Autoimmune Encephalitis Have in Common?

2021 ◽  
Vol 11 ◽  
Author(s):  
Inga Koneczny ◽  
Vuslat Yilmaz ◽  
Konstantinos Lazaridis ◽  
John Tzartos ◽  
Tobias L. Lenz ◽  
...  
Keyword(s):  
T Cells ◽  
Nervous System ◽  
Autoimmune Diseases ◽  
Myasthenia Gravis ◽  
Thrombotic Thrombocytopenic Purpura ◽  
Autoimmune Encephalitis ◽  
Pemphigus Vulgaris ◽  
Class Ii ◽  
Hla Class Ii ◽  
Thrombocytopenic Purpura

IgG4 autoimmune diseases (IgG4-AID) are an emerging group of autoimmune diseases that are caused by pathogenic autoantibodies of the IgG4 subclass. It has only recently been appreciated, that members of this group share relevant immunobiological and therapeutic aspects even though different antigens, tissues and organs are affected: glomerulonephritis (kidney), pemphigus vulgaris (skin), thrombotic thrombocytopenic purpura (hematologic system) muscle-specific kinase (MuSK) in myasthenia gravis (peripheral nervous system) and autoimmune encephalitis (central nervous system) to give some examples. In all these diseases, patients’ IgG4 subclass autoantibodies block protein-protein interactions instead of causing complement mediated tissue injury, patients respond favorably to rituximab and share a genetic predisposition: at least five HLA class II genes have been reported in individual studies to be associated with several different IgG4-AID. This suggests a role for the HLA class II region and specifically the DRβ1 chain for aberrant priming of autoreactive T-cells toward a chronic immune response skewed toward the production of IgG4 subclass autoantibodies. The aim of this review is to provide an update on findings arguing for a common pathogenic mechanism in IgG4-AID in general and to provide hypotheses about the role of distinct HLA haplotypes, T-cells and cytokines in IgG4-AID.

Associations of MultipleNOTCH4Exonic Variants with Systemic Sclerosis

2018 ◽  
Vol 46 (2) ◽  
pp. 184-189 ◽  
Author(s):  
Xiaodong Zhou ◽  
Hongye Li ◽  
Shicheng Guo ◽  
Jiucun Wang ◽  
Chunhua Shi ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Association Studies ◽  
Conditional Logistic Regression ◽  
Class Ii ◽  
Hla Class Ii ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Chinese Han ◽  
Chinese Cohort ◽  
Hla Class Ii Alleles

Objective.Findings from previous genome-wide association studies indicated an association of theNOTCH4gene with systemic sclerosis (SSc). This is a followup study to fine-map exonic variants ofNOTCH4in SSc.Methods.All exons ofNOTCH4were sequenced and analyzed in a total of 1006 patients with SSc and 1004 controls of US white ancestry with the Ion Torrent system. Identified SSc-associated variants were confirmed with Sanger sequencing, and then examined in a Chinese Han cohort consisting of 576 patients with SSc and 574 controls. TheNOTCH4variants were analyzed for association with SSc as a whole and with SSc clinical and autoantibody subtypes with and without the influence of specific HLA-class II alleles that had been previously identified as major genetic factors in SSc.Results.A total of 12 SSc-associated and SSc subtype–associated exonic variants ofNOTCH4were identified in the US cohort. Three of them are nonsynonymous single-nucleotide polymorphisms and 1 is a CTG tandem repeat that encodes for a poly-leucine, all of which are located in theNOTCH4extracellular domain (NECD). Conditional logistic regression analysis on SSc-associated HLA-class II alleles indicated an independent association of theNOTCH4variants with SSc autoantibody subtypes. Analysis of the Chinese cohort supported a genetic contribution ofNOTCH4to SSc and its subtypes.Conclusion.MultipleNOTCH4exonic variants were associated with SSc and/or SSc subtypes. Several of these variants encode nonsynonymous sequence changes occurring in the NECD, which implicates a potentially functional effect ofNOTCH4.

scholarly journals Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach

2011 ◽  
Vol 11 (1) ◽  
pp. 32 ◽  
Author(s):  
Atanas Patronov ◽  
Ivan Dimitrov ◽  
Darren R Flower ◽  
Irini Doytchinova
Keyword(s):  
Molecular Docking ◽  
Peptide Binding ◽  
Class Ii ◽  
Human Class ◽  
Binding Prediction ◽  
Class Ii Mhc ◽  
Docking Approach ◽  
Peptide Binding Prediction

Class II HLA-peptide binding prediction using structural principles

2009 ◽  
Vol 70 (3) ◽  
pp. 159-169 ◽  
Author(s):  
Arumugam Mohanapriya ◽  
Sajitha Lulu ◽  
Rajarathinam Kayathri ◽  
Pandjassarame Kangueane
Keyword(s):  
Peptide Binding ◽  
Class Ii ◽  
Binding Prediction ◽  
Structural Principles ◽  
Peptide Binding Prediction
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