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1.
An Expanded Genome-Wide Association Study of Fructosamine Levels Identifies RCN3 as a Replicating Locus and Implicates FCGRT as the Effector Transcript.
Riveros-Mckay, F, Roberts, D, Di Angelantonio, E, Yu, B, Soranzo, N, Danesh, J, Selvin, E, Butterworth, AS, Barroso, I
Diabetes. 2022;(2):359-364
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Abstract
Fructosamine is a measure of short-term glycemic control, which has been suggested as a useful complement to glycated hemoglobin (HbA1c) for the diagnosis and monitoring of diabetes. To date, a single genome-wide association study (GWAS) including 8,951 U.S. White and 2,712 U.S. Black individuals without a diabetes diagnosis has been published. Results in Whites and Blacks yielded different association loci, near RCN3 and CNTN5, respectively. In this study, we performed a GWAS on 20,731 European-ancestry blood donors and meta-analyzed our results with previous data from U.S. White participants from the Atherosclerosis Risk in Communities (ARIC) study (Nmeta = 29,685). We identified a novel association near GCK (rs3757840, βmeta = 0.0062; minor allele frequency [MAF] = 0.49; Pmeta = 3.66 × 10-8) and confirmed the association near RCN3 (rs113886122, βmeta = 0.0134; MAF = 0.17; Pmeta = 5.71 × 10-18). Colocalization analysis with whole-blood expression quantitative trait loci data suggested FCGRT as the effector transcript at the RCN3 locus. We further showed that fructosamine has low heritability (h2 = 7.7%), has no significant genetic correlation with HbA1c and other glycemic traits in individuals without a diabetes diagnosis (P > 0.05), but has evidence of shared genetic etiology with some anthropometric traits (Bonferroni-corrected P < 0.0012). Our results broaden knowledge of the genetic architecture of fructosamine and prioritize FCGRT for downstream functional studies at the established RCN3 locus.
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2.
The pockets guide to HLA class I molecules.
Nguyen, AT, Szeto, C, Gras, S
Biochemical Society transactions. 2021;(5):2319-2331
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Abstract
Human leukocyte antigens (HLA) are cell-surface proteins that present peptides to T cells. These peptides are bound within the peptide binding cleft of HLA, and together as a complex, are recognised by T cells using their specialised T cell receptors. Within the cleft, the peptide residue side chains bind into distinct pockets. These pockets ultimately determine the specificity of peptide binding. As HLAs are the most polymorphic molecules in humans, amino acid variants in each binding pocket influences the peptide repertoire that can be presented on the cell surface. Here, we review each of the 6 HLA binding pockets of HLA class I (HLA-I) molecules. The binding specificity of pockets B and F are strong determinants of peptide binding and have been used to classify HLA into supertypes, a useful tool to predict peptide binding to a given HLA. Over the years, peptide binding prediction has also become more reliable by using binding affinity and mass spectrometry data. Crystal structures of peptide-bound HLA molecules provide a means to interrogate the interactions between binding pockets and peptide residue side chains. We find that most of the bound peptides from these structures conform to binding motifs determined from prediction software and examine outliers to learn how these HLAs are stabilised from a structural perspective.
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Genetic determinants of the humoral immune response in MS.
Gasperi, C, Andlauer, TFM, Keating, A, Knier, B, Klein, A, Pernpeintner, V, Lichtner, P, Gold, R, Zipp, F, Then Bergh, F, et al
Neurology(R) neuroimmunology & neuroinflammation. 2020;(5)
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Abstract
OBJECTIVE In this observational study, we investigated the impact of genetic factors at the immunoglobulin heavy chain constant locus on chromosome 14 and the major histocompatibility complex region on intrathecal immunoglobulin G, A, and M levels as well as on B cells and plasmablasts in the CSF and blood of patients with multiple sclerosis (MS). METHODS Using regression analyses, we tested genetic variants on chromosome 14 and imputed human leukocyte antigen (HLA) alleles for associations with intrathecal immunoglobulins in 1,279 patients with MS or clinically isolated syndrome and with blood and CSF B cells and plasmablasts in 301 and 348 patients, respectively. RESULTS The minor alleles of variants on chromosome 14 were associated with higher intrathecal immunoglobulin G levels (β = 0.58 [0.47 to 0.68], lowest adjusted p = 2.32 × 10-23), and lower intrathecal immunoglobulin M (β = -0.56 [-0.67 to -0.46], p = 2.06 × 10-24) and A (β = -0.42 [-0.54 to -0.31], p = 7.48 × 10-11) levels. Alleles from the HLA-B*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02 haplotype were associated with higher (lowest p = 2.14 × 10-7) and HLA-B*44:02 with lower (β = -0.35 [-0.54 to -0.17], p = 1.38 × 10-2) immunoglobulin G levels. Of interest, different HLA alleles were associated with lower intrathecal immunoglobulin M (HLA-C*02:02, β = -0.45 [-0.61 to -0.28], p = 1.01 × 10-5) and higher immunoglobulin A levels (HLA-DQA1*01:03-DQB1*06:03-DRB1*13:01 haplotype, β = 0.40 [0.21 to 0.60], p = 4.46 × 10-3). The impact of HLA alleles on intrathecal immunoglobulin G and M levels could mostly be explained by associations with CSF B cells and plasmablasts. CONCLUSION Although some HLA alleles seem to primarily drive the extent of humoral immune responses in the CNS by increasing CSF B cells and plasmablasts, genetic variants at the immunoglobulin heavy chain constant locus might regulate intrathecal immunoglobulins levels via different mechanisms.
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Opsonization-Enhanced Antigen Presentation by MR1 Activates Rapid Polyfunctional MAIT Cell Responses Acting as an Effector Arm of Humoral Antibacterial Immunity.
Boulouis, C, Gorin, JB, Dias, J, Bergman, P, Leeansyah, E, Sandberg, JK
Journal of immunology (Baltimore, Md. : 1950). 2020;(1):67-77
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Abstract
Mucosa-associated invariant T (MAIT) cells are innate-like antimicrobial T cells recognizing a breadth of important pathogens via presentation of microbial riboflavin metabolite Ags by MHC class Ib-related (MR1) molecules. However, the interaction of human MAIT cells with adaptive immune responses and the role they may play in settings of vaccinology remain relatively little explored. In this study we investigated the interplay between MAIT cell-mediated antibacterial effector functions and the humoral immune response. IgG opsonization of the model microbe Escherichia coli with pooled human sera markedly enhanced the capacity of monocytic APC to stimulate MAIT cells. This effect included greater sensitivity of recognition and faster response kinetics, as well as a markedly higher polyfunctionality and magnitude of MAIT cell responses involving a range of effector functions. The boost of MAIT cell responses was dependent on strongly enhanced MR1-mediated Ag presentation via increased FcγR-mediated uptake and signaling primarily mediated by FcγRI. To investigate possible translation of this effect to a vaccine setting, sera from human subjects before and after vaccination with the 13-valent-conjugated Streptococcus pneumoniae vaccine were assessed in a MAIT cell activation assay. Interestingly, vaccine-induced Abs enhanced Ag presentation to MAIT cells, resulting in more potent effector responses. These findings indicate that enhancement of Ag presentation by IgG opsonization allows innate-like MAIT cells to mount a faster, stronger, and qualitatively more complex response and to function as an effector arm of vaccine-induced humoral adaptive antibacterial immunity.
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The farther the better: Investigating how distance from human self affects the propensity of a peptide to be presented on cell surface by MHC class I molecules, the case of Trypanosoma cruzi.
Vergni, D, Gaudio, R, Santoni, D
PloS one. 2020;(12):e0243285
Abstract
More than twenty years ago the reverse vaccinology paradigm came to light trying to design new vaccines based on the analysis of genomic information in order to select those pathogen peptides able to trigger an immune response. In this context, focusing on the proteome of Trypanosoma cruzi, we investigated the link between the probabilities for pathogen peptides to be presented on a cell surface and their distance from human self. We found a reasonable but, as far as we know, undiscovered property: the farther the distance between a peptide and the human-self the higher the probability for that peptide to be presented on a cell surface. We also found that the most distant peptides from human self bind, on average, a broader collection of HLAs than expected, implying a potential immunological role in a large portion of individuals. Finally, introducing a novel quantitative indicator for a peptide to measure its potential immunological role, we proposed a pool of peptides that could be potential epitopes and that can be suitable for experimental testing. The software to compute peptide classes according to the distance from human self is free available at http://www.iasi.cnr.it/~dsantoni/nullomers.
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A large peptidome dataset improves HLA class I epitope prediction across most of the human population.
Sarkizova, S, Klaeger, S, Le, PM, Li, LW, Oliveira, G, Keshishian, H, Hartigan, CR, Zhang, W, Braun, DA, Ligon, KL, et al
Nature biotechnology. 2020;(2):199-209
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Abstract
Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.
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Conserved epitopes with high HLA-I population coverage are targets of CD8+ T cells associated with high IFN-γ responses against all dengue virus serotypes.
Adikari, TN, Di Giallonardo, F, Leung, P, Grifoni, A, Sette, A, Weiskopf, D, Bull, RA, Luciani, F
Scientific reports. 2020;(1):20497
Abstract
Cytotoxic CD8+ T cells are key for immune protection against viral infections. The breadth and cross-reactivity of these responses are important against rapidly mutating RNA viruses, such as dengue (DENV), yet how viral diversity affect T cell responses and their cross-reactivity against multiple variants of the virus remains poorly defined. In this study, an integrated analysis was performed to map experimentally validated CD8+ T cell epitopes onto the distribution of DENV genome sequences across the 4 serotypes worldwide. Despite the higher viral diversity observed within HLA-I restricted epitopes, mapping of 609 experimentally validated epitopes sequences on 3985 full-length viral genomes revealed 19 highly conserved epitopes across the four serotypes within the immunogenic regions of NS3, NS4B and NS5. These conserved epitopes were associated with a higher magnitude of IFN-γ response when compared to non-conserved epitopes and were restricted to 13 HLA class I genotypes, hence providing high coverage among human populations. Phylogeographic analyses showed that these epitopes are largely conserved in most of the endemic regions of the world, and with only some of these epitopes presenting distinct mutated variants circulating in South America and Asia.This study provides evidence for the existence of highly immunogenic and conserved epitopes across serotypes, which may impact design of new universal T-cell-inducing vaccine candidates that minimise detrimental effects of viral diversification and at the same time induce responses to a broad human population.
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The p.Arg435His Variation of IgG3 With High Affinity to FcRn Is Associated With Susceptibility for Pemphigus Vulgaris-Analysis of Four Different Ethnic Cohorts.
Recke, A, Konitzer, S, Lemcke, S, Freitag, M, Sommer, NM, Abdelhady, M, Amoli, MM, Benoit, S, El-Chennawy, F, Eldarouti, M, et al
Frontiers in immunology. 2018;:1788
Abstract
IgG3 is the IgG subclass with the strongest effector functions among all four IgG subclasses and the highest degree of allelic variability among all constant immunoglobulin genes. Due to its genetic position, IgG3 is often the first isotype an antibody switches to before IgG1 or IgG4. Compared with the other IgG subclasses, it has a reduced half-life which is probably connected to a decreased affinity to the neonatal Fc receptor (FcRn). However, a few allelic variants harbor an amino acid replacement of His435 to Arg that reverts the half-life of the resulting IgG3 to the same level as the other IgG subclasses. Because of its functional impact, we hypothesized that the p.Arg435His variation could be associated with susceptibility to autoantibody-mediated diseases like pemphigus vulgaris (PV) and bullous pemphigoid (BP). Using a set of samples from German, Turkish, Egyptian, and Iranian patients and controls, we were able to demonstrate a genetic association of the p.Arg435His variation with PV risk, but not with BP risk. Our results suggest a hitherto unknown role for the function of IgG3 in the pathogenesis of PV.
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Single nucleotide polymorphisms in ZNRD1-AS1 increase cancer risk in an Asian population.
Wang, PY, Li, JH, Liu, YM, Lv, Q, Xie, N, Zhang, HH, Xie, SY
Oncotarget. 2017;(6):10064-10070
Abstract
Single nucleotide polymorphisms (SNPs) in human zinc ribbon domain containing 1 antisense RNA 1 (ZNRD1-AS1) have been associated with cancer development. In this meta-analysis, we more precisely estimated the associations between three expression quantitative trait loci SNPs in ZNRD1-AS1 (rs3757328, rs6940552, and rs9261204) and cancer susceptibility. The data for three SNPs were extracted from eligible studies, which included 5,293 patients and 5,440 controls. Overall, no significant associations between SNPs in ZNRD1-AS1 (rs3757328, rs6940552, and rs9261204) and cancer risk were observed. However, in further subgroup analyses based on cancer type, we found that the A allele of rs3757328 increased the risk of some cancer in both allele contrast (OR = 1.15, 95% CI = 1.05 - 1.25) and recessive models (OR = 1.79; 95% CI = 1.33 - 2.41). The A allele of rs6940552 and the G allele of rs9261204 also increased the risk of some cancer in an Asian population in allele contrast (OR = 1.17, 95% CI = 1.08 - 1.26, and OR = 1.25, 95% CI = 1.16 - 1.34, respectively) and recessive models (OR = 1.44, 95% CI = 1.18 - 1.77, and OR = 1.49; 95% CI = 1.23 - 1.80, respectively). Thus, rs3757328, rs6940552, and rs9261204 in ZNRD1-AS1 are all associated with increased some cancer risk in an Asian population.
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HLA class I binding prediction via convolutional neural networks.
Vang, YS, Xie, X
Bioinformatics (Oxford, England). 2017;(17):2658-2665
Abstract
MOTIVATION Many biological processes are governed by protein-ligand interactions. One such example is the recognition of self and non-self cells by the immune system. This immune response process is regulated by the major histocompatibility complex (MHC) protein which is encoded by the human leukocyte antigen (HLA) complex. Understanding the binding potential between MHC and peptides can lead to the design of more potent, peptide-based vaccines and immunotherapies for infectious autoimmune diseases. RESULTS We apply machine learning techniques from the natural language processing (NLP) domain to address the task of MHC-peptide binding prediction. More specifically, we introduce a new distributed representation of amino acids, name HLA-Vec, that can be used for a variety of downstream proteomic machine learning tasks. We then propose a deep convolutional neural network architecture, name HLA-CNN, for the task of HLA class I-peptide binding prediction. Experimental results show combining the new distributed representation with our HLA-CNN architecture achieves state-of-the-art results in the majority of the latest two Immune Epitope Database (IEDB) weekly automated benchmark datasets. We further apply our model to predict binding on the human genome and identify 15 genes with potential for self binding. AVAILABILITY AND IMPLEMENTATION Codes to generate the HLA-Vec and HLA-CNN are publicly available at: https://github.com/uci-cbcl/HLA-bind . CONTACT xhx@ics.uci.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.