Next-Generation Sequencing Reveals That HLA-DRB3, -DRB4, and -DRB5 May Be Associated With Islet Autoantibodies and Risk for Childhood Type 1 Diabetes

HLA Associations of Intrathecal IgG Production against Specific Viruses in Multiple Sclerosis

OBJECTIVE

Specific human leucocyte antigen (HLA) alleles are not only associated with higher risk to develop multiple sclerosis (MS) and other autoimmune diseases, but also with the severity of various viral and bacterial infections. Here, we analyzed the most specific biomarker for MS, that is, the polyspecific intrathecal IgG antibody production against measles, rubella, and varicella zoster virus (MRZ reaction), for possible HLA associations in MS.

METHODS

We assessed MRZ reaction from 184 Swiss patients with MS and clinically isolated syndrome (CIS) and 89 Swiss non-MS/non-CIS control patients, and performed HLA sequence-based typing, to check for associations of positive MRZ reaction with the most prevalent HLA alleles. We used a cohort of 176 Swedish MS/CIS patients to replicate significant findings.

RESULTS

Whereas positive MRZ reaction showed a prevalence of 38.0% in MS/CIS patients, it was highly specific (97.7%) for MS/CIS. We identified HLA-DRB1*15:01 and other tightly linked alleles of the HLA-DR15 haplotype as the strongest HLA-encoded risk factors for a positive MRZ reaction in Swiss MS/CIS (odds ratio [OR], 3.90, 95% confidence interval [CI] 2.05-7.46, padjusted = 0.0004) and replicated these findings in Swedish MS/CIS patients (OR 2.18, 95%-CI 1.16-4.02, padjusted = 0.028). In addition, female MS/CIS patients had a significantly higher probability for a positive MRZ reaction than male patients in both cohorts combined (padjusted <0.005).

INTERPRETATION

HLA-DRB1*15:01, the strongest genetic risk factor for MS, and female sex, 1 of the most prominent demographic risk factors for developing MS, predispose in MS/CIS patients for a positive MRZ reaction, the most specific CSF biomarker for MS. ANN NEUROL 2024;95:1112-1126.

Evaluation of HLA typing content of next-generation sequencing datasets from family trios and individuals of arab ethnicity

Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling.

HLA Gene Polymorphisms in Romanian Patients with Chronic Lymphocytic Leukemia

Materials and Methods

This study included 66 patients with CLL, diagnosed between 2020 and 2022, and 100 healthy controls. HLA class I and class II genes (HLA-A/B/C, HLA-DQA1/DQB1/DPA1/DPB1, and HLA-DRB1/3/4/5) were investigated using next-generation sequencing technology.

Results

Several HLA alleles were strongly associated with CLL. The most important finding was that HLA-DRB1∗04:02:01 (p=0.001, OR = 1.05) and HLA-DRB3∗02:01:01 (p=0.009, OR = 1.03) have a predisposing role in CLL development. Moreover, we identified that HLA-A∗24:02:01 0.01 (p=0.01, OR = 0.38), HLA-DQA1∗05:05:01 (p=0.01, OR = 0.56), HLA-DQB1∗03:02:01 (p=0.03, OR = 0.40), and HLA-DRB4∗01:03:01 (p=0.03, OR = 0.54 alleles have protective roles. Correlations between HLA expression and gender showed that women had a higher expression of protective HLA alleles when compared to men.

Conclusions

Our data are the first to indicate that in Romanian patients with CLL, the HLA-A∗24:02:01 and HLA-DQA1∗05:05:01 alleles have a protective role against CLL development, whereas HLA-DRB1∗04:02:01 and HLA-DRB3∗02:01:01alleles are positively associated with CLL.

Genetic and Epigenetic Aspects of Type 1 Diabetes Mellitus: Modern View on the Problem

Omics technologies accumulated an enormous amount of data that advanced knowledge about the molecular pathogenesis of type 1 diabetes mellitus and identified a number of fundamental problems focused on the transition to personalized diabetology in the future. Among them, the most significant are the following: (1) clinical and genetic heterogeneity of type 1 diabetes mellitus; (2) the prognostic significance of DNA markers beyond the HLA genes; (3) assessment of the contribution of a large number of DNA markers to the polygenic risk of disease progress; (4) the existence of ethnic population differences in the distribution of frequencies of risk alleles and genotypes; (5) the infancy of epigenetic research into type 1 diabetes mellitus. Disclosure of these issues is one of the priorities of fundamental diabetology and practical healthcare. The purpose of this review is the systemization of the results of modern molecular genetic, transcriptomic, and epigenetic investigations of type 1 diabetes mellitus in general, as well as its individual forms. The paper summarizes data on the role of risk HLA haplotypes and a number of other candidate genes and loci, identified through genome-wide association studies, in the development of this disease and in alterations in T cell signaling. In addition, this review assesses the contribution of differential DNA methylation and the role of microRNAs in the formation of the molecular pathogenesis of type 1 diabetes mellitus, as well as discusses the most currently central trends in the context of early diagnosis of type 1 diabetes mellitus.

Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer

Immune checkpoint inhibitors (ICI) are important treatment options for metastatic non-small cell lung cancer (mNSCLC). However, not all patients benefit from ICIs and can experience immune-related adverse events (irAEs). Limited understanding exists for germline determinants of ICI efficacy and toxicity, but Human Leukocyte Antigen (HLA) genes have emerged as a potential predictive biomarker. We performed HLA typing on 85 patients with mNSCLC, on ICI therapy and analyzed the impact of HLA Class II genotype on progression free survival (PFS), overall survival (OS), and irAEs. Most patients received pembrolizumab (83.5%). HLA-DRB4 genotype was seen in 34/85 (40%) and its presence correlated with improved OS in both univariate (p = 0.022; 26.3 months vs 10.2 months) and multivariate analysis (p = 0.011, HR 0.49, 95% CI [0.29, 0.85]). PFS did not reach significance (univariate, p = 0.12, 8.2 months vs 5.1 months). Eleven patients developed endocrine irAEs. HLA-DRB4 was the predominant genotype among these patients (9/11, 81.8%). Cumulative incidence of endocrine irAEs was higher in patients with HLA-DRB4 (p = 0.0139). Our study is the first to suggest that patients with metastatic NSCLC patients on ICI therapy with HLA-DRB4 genotype experience improved survival outcomes. Patients with HLA-DRB4 had the longest median OS (26.3 months). Additionally, we found a correlation between HLA-DRB4 and the occurrence of endocrine irAEs.

Investigation of molecular interaction and conformational stability of disease concomitant to HLA-DRβ3

Human leucocyte antigen DRβ3 is associated with specific autoimmune thyroid disease and plays a vital role in the progression of Grave's disease. The available crystallographic structure of the HLA DRA, DRβ3*0101, was selected and used to generate mutation at position 57 from valine amino acid to Aspartic acid (D), Glutamic acid (E), Alanine (A), and Serine (S) amino acids by computational modeling approach. Mutant models were minimized, and stable conformation was chosen based on the lowest root mean square deviation value. Molecular docking assessed the best binding affinity of ligands C1, C2, C3, and C4 with wild-type and mutant HLA-DRβ3 models. Molecular dynamics simulation studies were executed to evaluate the stability of selected hits with wild-type and mutant dock complexes. The C3 has shown good binding affinity with wild-type and selected mutants; V57A, V57E, and V57D. Structural and molecular dynamics insights reveal the differences between wild-type and mutant-type HLA-DRβ3, which could help design novel antagonist molecules against autoimmune thyroid disorder.Communicated by Ramaswamy H. Sarma.

High-resolution HLA class II sequencing of Swedish multiple sclerosis patients

Multiple sclerosis (MS) is a chronic neurological disease believed to be caused by autoimmune pathogenesis. The aetiology is likely explained by a complex interplay between inherited and environmental factors. Genetic investigations into MS have been conducted for over 50 years, yielding >100 associations to date. Globally, the strongest linkage is with the human leukocyte antigen (HLA) HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 haplotype. Here, high-resolution sequencing of HLA was used to determine the alleles of DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 as well as their extended haplotypes and genotypes in 100 Swedish MS patients. Results were compared to 636 population controls. The heterogeneity in HLA associations with MS was demonstrated; among 100 patients, 69 extended HLA-DR-DQ genotypes were found. Three extended HLA-DR-DQ genotypes were found to be correlated to MS; HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 haplotype together with (A) HLA-DRB4*01:01:01//DRB4*01:01:01:01-DRB1*07:01:01-DQA1*02:01//02:01:01-DQB1*02:02:01, (B) HLA-DRBX*null-DRB1*08:01:01-DQA1*04:01:01-DQB1*04:02:01, and (C) HLA-DRB3*01:01:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01. At the allelic level, HLA-DRB3*01:01:02 was considered protective against MS. However, when combined with HLA-DRB3*01:01:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01, this extended haplotype was considered a predisposing risk factor. This highlights the limitations as included with investigations of single alleles relative to those of extended haplotypes/genotypes. In conclusion, with 69 genotypes presented among 100 patients, high-resolution sequencing was conducted to underscore the wide polymorphisms present among MS patients. Additional studies in larger cohorts will be of importance to define MS among the patient group not associated with HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01.

Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: a bioinformatics analytic workflow

Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.

Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections

The human leukocyte antigen (HLA) system is one of the most crucial host factors influencing disease progression in bacterial and viral infections. This review provides the basic concepts of the structure and function of HLA molecules in humans. Here, we highlight the main findings on the associations between HLA class I and class II alleles and susceptibility to important infectious diseases such as tuberculosis, leprosy, melioidosis, Staphylococcus aureus infection, human immunodeficiency virus infection, coronavirus disease 2019, hepatitis B, and hepatitis C in populations worldwide. Finally, we discuss challenges in HLA typing to predict disease outcomes in clinical implementation. Evaluation of the impact of HLA variants on the outcome of bacterial and viral infections would improve the understanding of pathogenesis and identify those at risk from infectious diseases in distinct populations and may improve the individual treatment.

The increased risk of multiple sclerosis associated with HLA-DRB1*15:01 and smoking is modified by alcohol consumption

Previous studies have observed an inverse association between alcohol consumption and multiple sclerosis (MS) risk. We aimed to investigate possible interactions between alcohol consumption, MS-associated human leukocyte antigen (HLA) genes and smoking regarding MS risk. We used a Swedish population-based case-control study (2059 incident cases, 2887 controls) matched by age, sex, and residential area. Subjects with different genotypes and alcohol consumption habits were compared regarding MS risk, by calculating odds ratios with 95% confidence intervals using logistic regression models. Interaction on the additive scale between non-drinking and both genotype and smoking were assessed by calculating the attributable proportion due to interaction (AP). There was a dose-dependent inverse association between alcohol consumption and MS risk (p for trend < 0.0001). A potentiating effect was observed between non-drinking and presence of DRB1*15:01 (AP 0.3, 95% CI 0.2-0.5) which was of similar magnitude irrespective of smoking habits. Non-drinking also interacted with smoking to increase MS risk (AP 0.2, 95% CI 0.06-0.4). Non-drinking interacts with DRB1*15:01 and smoking to increase the risk of MS. Better understanding of the mechanisms behind our findings may help to define ways to achieve protection against MS by other means than alcohol consumption.

Diabetes: discovery of insulin, genetic, epigenetic and viral infection mediated regulation

Diabetes mellitus, commonly referred to as diabetes, is a combination of many metabolic diseases. Insulin deficiency in our body is the main cause of diabetes. Insulin is one of the most well studied proteins, yet the genesis of its discovery was not getting much attention so far. Nevertheless, the history of the discovery of insulin is an exemplary of solving observational and scientific riddles, drudgery, patience and even professional turmoil. It is an inspiration for all medical personnel and scientists who are practising in the field of molecular medicine. Additionally, the genetic and epigenetic regulation of different types of diabetes needs to be addressed because of the widespread nature of the disease. Diabetes not only involves genetic predisposition but environmental factors, lifestyle etc. can be the major contributor for its inception. Nonetheless, viral infections at an early age are also found to trigger the onset of type I diabetes. In this review article, the history of the discovery of insulin is detailed along with the justification for the genetic and epigenetic regulatory mechanisms of diabetes and explained how viral infections can also trigger the onset of diabetes.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.

Next-generation sequencing and clinical histocompatibility testing

Histocompatibility testing is essential for donor identification and risk assessment in solid organ and hematopoietic stem cell transplant. Additionally, it is useful for identifying donor specific alleles for monitoring donor specific antibodies in post-transplant patients. Next-generation sequence (NGS) based human leukocyte antigen (HLA) typing has improved many aspects of histocompatibility testing in hematopoietic stem cell and solid organ transplant. HLA disease association testing and research has also benefited from the advent of NGS technologies. In this review we discuss the current impact and future applications of NGS typing on clinical histocompatibility testing for transplant and non-transplant purposes.

Etiology of Autoimmune Islet Disease: Timing Is Everything

Life is about timing. -Carl LewisThe understanding of autoimmune type 1 diabetes is increasing, and examining etiology separate from pathogenesis has become crucial. The components to explain type 1 diabetes development have been known for some time. The strong association with HLA has been researched for nearly 50 years. Genome-wide association studies added another 60+ non-HLA genetic factors with minor contribution to risk. Insulitis has long been known to be present close to clinical diagnosis. T and B cells recognizing β-cell autoantigens are detectable prior to diagnosis and in newly diagnosed patients. Islet autoantibody tests against four major autoantigens have been standardized and used as biomarkers of islet autoimmunity. However, to clarify the etiology would require attention to time. Etiology may be defined as the cause of a disease (i.e., type 1 diabetes) or abnormal condition (i.e., islet autoimmunity). Timing is everything, as neither the prodrome of islet autoimmunity nor the clinical onset of type 1 diabetes tells us much about the etiology. Rather, the islet autoantibody that appears first and persists would mark the diagnosis of an autoimmune islet disease (AID). Events after the diagnosis of AID would represent the pathogenesis. Several islet autoantibodies without (stage 1) or with impaired glucose tolerance (stage 2) or with symptoms (stage 3) would define the pathogenesis culminating in clinical type 1 diabetes. Etiology would be about the timing of events that take place before the first-appearing islet autoantibody.

The KAG motif of HLA-DRB1 (β71, β74, β86) predicts seroconversion and development of type 1 diabetes

BACKGROUND

HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated.

METHODS

We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions.

FINDINGS

Three amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10-64). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10-4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10-14) after adjusting potential confounders.

INTERPRETATIONS

DNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65.

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Allele and haplotype frequencies of human leukocyte antigen-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 by next generation sequencing-based typing in Koreans in South Korea

Allele frequencies and haplotype frequencies of HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 have been rarely reported in South Koreans using unambiguous, phase-resolved next generation DNA sequencing. In this study, HLA typing of 11 loci in 173 healthy South Koreans were performed using next generation DNA sequencing with long-range PCR, TruSight^® HLA v2 kit, Illumina MiSeqDx platform system, and Assign^™ for TruSight^™ HLA software. Haplotype frequencies were calculated using the PyPop software. Direct counting methods were used to investigate the association with DRB1 for samples with only one copy of a particular secondary DRB locus. We compared these allele types with the ambiguous allele combinations of the IPD-IMGT/HLA database. We identified 20, 40, 26, 31, 19, 16, 4, and 16 alleles of HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1, respectively. The number of HLA-DRB3/4/5 alleles was 4, 5, and 3, respectively. The haplotype frequencies of most common haplotypes were as follows: A*33:03:01-B*44:03:01-C*14:03-DRB1*13:02:01-DQB1*06:04:01-DPB1*04:01:01 (2.89%), A*33:03:01-B*44:03:01-C*14:03 (4.91%), DRB1*08:03:02-DQA1*01:03:01-DQB1*06:01:01-DPA1*02:02:02-DPB1*05:01:01 (5.41%), DRB1*04:05:01-DRB4*01:03:01 (12.72%), DQA1*01:03:01-DQB1*06:01:01 (13.01%), and DPA1*02:02:02-DPB1*05:01:01 (30.83%). In samples with only one copy of a specific secondary DRB locus, we examined its association with DRB1. We, thus, resolved 10 allele ambiguities in HLA-B, -C (each exon 2+3), -DRB1, -DQB1, -DQA1, and -DPB1 (each exon 2) of the IPD-IMGT/HLA database. Korean population was geographically close to Japanese and Han Chinese populations in the genetic distances by multidimensional scaling (MDS) plots. The information obtained by HLA typing of the 11 extended loci by next generation sequencing may be useful for more exact diagnostic tests on various transplantations and the genetic population relationship studies in South Koreans.

Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries

Preferential fat accumulation in visceral vs. subcutaneous depots makes obese individuals more prone to metabolic complications. Body fat distribution (FD) is regulated by genetics. FD patterns vary across ethnic groups independent of obesity. Asians have more and Africans have less visceral fat compared with Europeans. Consequently, Asians tend to be more susceptible to type 2 diabetes even with lower BMIs when compared with Europeans. To date, genome-wide association studies (GWAS) have identified more than 460 loci related to FD traits. However, the majority of these data were generated in European populations. In this review, we aimed to summarize recent advances in FD genetics with a focus on comparisons between European and non-European populations (Asians and Africans). We therefore not only compared FD-related susceptibility loci identified in three ethnicities but also discussed whether known genetic variants might explain the FD pattern heterogeneity across different ancestries. Moreover, we describe several novel candidate genes potentially regulating FD, including NID2, HECTD4 and GNAS, identified in studies with Asian populations. It is of note that in agreement with current knowledge, most of the proposed FD candidate genes found in Asians belong to the group of developmental genes.

Nine residues in HLA-DQ molecules determine with susceptibility and resistance to type 1 diabetes among young children in Sweden

HLA-DQ molecules account over 50% genetic risk of type 1 diabetes (T1D), but little is known about associated residues. Through next generation targeted sequencing technology and deep learning of DQ residue sequences, the aim was to uncover critical residues and their motifs associated with T1D. Our analysis uncovered (αa1, α44, α157, α196) and (β9, β30, β57, β70, β135) on the HLA-DQ molecule. Their motifs captured all known susceptibility and resistant T1D associations. Three motifs, “DCAA-YSARD” (OR = 2.10, p = 1.96*10⁻²⁰), “DQAA-YYARD” (OR = 3.34, 2.69*10⁻⁷²) and “DQDA-YYARD” (OR = 3.71, 1.53*10⁻⁶) corresponding to DQ2.5 and DQ8.1 (the latter two motifs) associated with susceptibility. Ten motifs were significantly associated with resistance to T1D. Collectively, homozygous DQ risk motifs accounted for 43% of DQ-T1D risk, while homozygous DQ resistant motifs accounted for 25% protection to DQ-T1D risk. Of the identified nine residues five were within or near anchoring pockets of the antigenic peptide (α44, β9, β30, β57 and β70), one was the N-terminal of the alpha chain (αa1), one in the CD4-binding region (β135), one in the putative cognate TCR-induced αβ homodimerization process (α157), and one in the intra-membrane domain of the alpha chain (α196). Finding these critical residues should allow investigations of fundamental properties of host immunity that underlie tolerance to self and organ-specific autoimmunity.

Identification of hub genes related to the progression of type 1 diabetes by computational analysis

BACKGROUND

Type 1 diabetes (T1D) is a serious threat to childhood life and has fairly complicated pathogenesis. Profound attempts have been made to enlighten the pathogenesis, but the molecular mechanisms of T1D are still not well known.

METHODS

To identify the candidate genes in the progression of T1D, expression profiling by high throughput sequencing dataset GSE123658 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and gene ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI), modules, target gene - miRNA regulatory network and target gene - TF regulatory network analysis were constructed and analyzed using HIPPIE, miRNet, NetworkAnalyst and Cytoscape. Finally, validation of hub genes was conducted by using ROC (Receiver operating characteristic) curve and RT-PCR analysis. A molecular docking study was performed.

RESULTS

A total of 284 DEGs were identified, consisting of 142 up regulated genes and 142 down regulated genes. The gene ontology (GO) and pathways of the DEGs include cell-cell signaling, vesicle fusion, plasma membrane, signaling receptor activity, lipid binding, signaling by GPCR and innate immune system. Four hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell-cell signaling, cytokine signaling in immune system, signaling by GPCR and innate immune system. ROC curve and RT-PCR analysis showed that EGFR, GRIN2B, GJA1, CAP2, MIF, POLR2A, PRKACA, GABARAP, TLN1 and PXN might be involved in the advancement of T1D. Molecular docking studies showed high docking score.

CONCLUSIONS

DEGs and hub genes identified in the present investigation help us understand the molecular mechanisms underlying the advancement of T1D, and provide candidate targets for diagnosis and treatment of T1D.

The transcriptome-wide association search for genes and genetic variants which associate with BMI and gestational weight gain in women with type 1 diabetes

BACKGROUND

Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes; however, the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG.

METHODS

We have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1 Mb around identified loci) with the mentioned phenotypes.

RESULTS

In Analysis 1 we have found 175 BMI associated genes and 19 variants (p < 10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p = 3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p < 10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p = 9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR < 0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort.

CONCLUSIONS

Here, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.

High-resolution genotyping indicates that children with type 1 diabetes and celiac disease share three HLA class II loci in DRB3, DRB4 and DRB5 genes

Type 1 diabetes (T1D) and celiac disease (CD) share common genetic loci, mainly within the human leukocyte antigen (HLA) class II complex. Extended genotyping of HLA class II alleles and their potential risk for developing both diseases remains to be studied. The present study compared extended HLA-class II gene polymorphisms in children with T1D, CD, and a subgroup diagnosed with both diseases (T1D w/CD). Next-generation targeted sequencing (NGTS) of HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1, and DPB1 alleles from DNA collected from 68 T1D, 219 CD, and seven T1D w/CD patients were compared with 636 HLA-genotyped Swedish children from the general population selected as controls. In comparison to controls, the DRB4*01:03:01 allele occurred more frequently in T1D w/CD (odds ratio (OR) = 7.84; 95% confidence interval (95% CI) = (2.24, 34.5), P = 0.0002) and T1D (OR = 3.86; 95% CI, (2.69, 5.55), P = 1.07 × 10^-14 ), respectively. The DRB3*01:01:02 allele occurred more frequently in CD as compared to controls (OR = 7.87; 95% CI, (6.17, 10.03), P = 4.24 × 10^-71 ), but less frequently in T1D (OR = 2.59; 95% CI, (1.76, 3.81), P = 7.29 × 10^-07 ) and T1D w/CD (OR = 0.87; 95% CI, (0.09, 3.96), P ≤ 0.999). The frequency of the DRB4*01:03:01-DRB1*04:01:01-DQA1*03:01:01-DQB1*03:02:01 (DR4-DQ8) haplotype was higher in T1D w/CD (OR = 12.88; 95% CI (4.35, 38.14) P = 3.75 × 10^-9 ), and moderately higher in T1D (OR = 2.13; 95% CI (1.18, 3.83) P = 0.01) compared with controls, but comparable in CD (OR = 1.45; 95% CI (0.94, 2.21), P = 0.08) and controls. Children with T1D and CD are associated with DRB4*01:03:01, DRB3*01:01:02, and DRB3*02:02:01 of which DRB4*01:03:01 confers the strongest risk allele for developing T1D w/CD.

Next-Generation HLA Sequence Analysis Uncovers Seven HLA-DQ Amino Acid Residues and Six Motifs Resistant to Childhood Type 1 Diabetes

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, and β70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10^-24, 3.54 × 10^-15, and 1.03 × 10^-21, respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at β57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10^-15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, β167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-β heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

Characterization of plasma lipidomics in adolescent subjects with increased risk for type 1 diabetes in the DiPiS cohort

INTRODUCTION

Type 1 diabetes (T1D) is caused by the destruction of pancreatic islet beta cells resulting in total loss of insulin production. Recent studies have suggested that the destruction may be interrelated to plasma lipids.

OBJECTIVES

Specific lipids have previously been shown to be decreased in children who develop T1D before four years of age. Disturbances of plasma lipids prior to clinical diagnosis of diabetes, if true, may provide a novel way to improve prediction, and monitor disease progression.

METHODS

A lipidomic approach was utilized to analyze plasma from 67 healthy adolescent subjects (10-15 years of age) with or without islet autoantibodies but all with increased genetic risk for T1D. The study subjects were enrolled at birth in the Diabetes Prediction in Skåne (DiPiS) study and after 10-15 years of follow-up we performed the present cross-sectional analysis. HLA-DRB345, -DRB1, -DQA1, -DQB1, -DPA1 and -DPB1 genotypes were determined using next generation sequencing. Lipidomic profiles were determined using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Lipidomics data were analyzed according to genotype.

RESULTS

Variation in levels of several specific phospholipid species were related to level of autoimmunity but not development of T1D. Five glycosylated ceramides were increased in insulin autoantibody (IAA) positive adolescent subjects compared to adolescent subjects without this autoantibody. Additionally, HLA genotypes seemed to influence levels of long chain triacylglycerol (TG).

CONCLUSION

Lipidomic profiling of adolescent subjects in high risk of T1D may improve sub-phenotyping in this high risk population.

Decreased HLA-DQ expression on peripheral blood cells in children with varying number of beta cell autoantibodies

The risk for type 1 diabetes is strongly associated with HLA-DQ and the appearance of beta cell autoantibodies against either insulin, glutamate decarboxylase (GAD65), insulinoma-associated protein-2 (IA-2), or zinc transporter 8 (ZnT8). Prolonged exposure to autoantibodies may be related to T cell exhaustion known to occur in chronic infections or autoimmune disorders. It was hypothesized that autoantibody exposure may affect HLA-DQ expression on peripheral blood cells and thereby contribute to T cell exhaustion thought to be associated with the pathogenesis of type 1 diabetes. The aim of this study was to determine whether autoantibody exposure as an expression of autoimmunity burden was related to peripheral blood cell HLA-DQ cell surface expression in either 1) a cross-sectional analysis or 2) cumulative as area under the trajectory of autoantibodies during long term follow-up in the Diabetes Prediction in Skåne (DiPiS) study. Children (n = 67), aged 10–15 years were analyzed for complete blood count, HLA-DQ cell surface median fluorescence intensity (MFI), autoantibody frequency, and HLA genotypes by Next Generation Sequencing. Decreased HLA-DQ cell surface MFI with an increasing number of autoantibodies was observed in CD16⁺, CD14⁺CD16⁻, CD4⁺ and CD8⁺ cells but not in CD19⁺ cells and neutrophils. HLA-DQ cell surface MFI was associated with HLA-DQ2/8 in CD4⁺ T cells, marginally in CD14⁺CD16⁻ monocytes and CD8⁺ T cells. These associations appeared to be related to autoimmunity burden. The results suggest that HLA-DQ cell surface expression was related to HLA and autoimmunity burden.

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PBMC HLA-DQ surface expression in beta cell autoimmunity is poorly understood.

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Children, 10–15 years of age without or with beta cell autoantibodies were analyzed.

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HLA-DQ cell surface expression decreased with increasing number of autoantibodies.

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HLA-DQ cell surface expression was related to HLA and autoimmunity burden.

HLA-A, -B, -C, -DRB1, -DQA1, and -DQB1 allele and haplotype frequencies defined by next generation sequencing in a population of East Croatia blood donors

Next-generation sequencing (NGS) is increasingly used in transplantation settings, but also as a method of choice for in-depth analysis of population-specific HLA genetic architecture and its linkage to various diseases. With respect to complex ethnic admixture characteristic for East Croatian population, we aimed to investigate class-I (HLA-A, -B, -C) and class-II (HLA-DRB1, -DQA1, -DQB1) HLA diversity at the highest, 4-field resolution level in 120 healthy, unrelated, blood donor volunteers. Genomic DNA was extracted and HLA genotypes of class I and DQA1 genes were defined in full-length, -DQB1 from intron 1 to 3′ UTR, and -DRB1 from intron 1 to intron 4 (Illumina MiSeq platform, Omixon Twin algorithms, IMGT/HLA release 3.30.0_5). Linkage disequilibrium statistics, Hardy-Weinberg departures, and haplotype frequencies were inferred by exact tests and iterative Expectation-Maximization algorithm using PyPop 0.7.0 and Arlequin v3.5.2.2 software. Our data provide first description of 4-field allele and haplotype frequencies in Croatian population, revealing 192 class-I and class-II alleles and extended haplotypic combinations not apparent from the existing 2-field HLA reports from Croatia. This established reference database complements current knowledge of HLA diversity and should prove useful in future population studies, transplantation settings, and disease-associated HLA screening.

HLA Class II Allele Analyses Implicate Common Genetic Components in Type 1 and Non-Insulin-Treated Type 2 Diabetes

CONTEXT

Common genetic susceptibility may underlie the frequently observed co-occurrence of type 1 and type 2 diabetes in families. Given the role of HLA class II genes in the pathophysiology of type 1 diabetes, the aim of the present study was to test the association of high density imputed human leukocyte antigen (HLA) genotypes with type 2 diabetes.

OBJECTIVES AND DESIGN

Three cohorts (Ntotal = 10 413) from Leipzig, Germany were included in this study: LIFE-Adult (N = 4649), LIFE-Heart (N = 4815) and the Sorbs (N = 949) cohort. Detailed metabolic phenotyping and genome-wide single nucleotide polymorphism (SNP) data were available for all subjects. Using 1000 Genome imputation data, HLA genotypes were imputed on 4-digit level and association tests for type 2 diabetes, and related metabolic traits were conducted.

RESULTS

In a meta-analysis including all 3 cohorts, the absence of HLA-DRB5 was associated with increased risk of type 2 diabetes (P = 0.001). In contrast, HLA-DQB*06:02 and HLA-DQA*01:02 had a protective effect on type 2 diabetes (P = 0.005 and 0.003, respectively). Both alleles are part of the well-established type 1 diabetes protective haplotype DRB1*15:01~DQA1*01:02~DQB1*06:02, which was also associated with reduced risk of type 2 diabetes (OR 0.84; P = 0.005). On the contrary, the DRB1*07:01~DQA1*02:01~DQB1*03:03 was identified as a risk haplotype in non-insulin-treated diabetes (OR 1.37; P = 0.002).

CONCLUSIONS

Genetic variation in the HLA class II locus exerts risk and protective effects on non-insulin-treated type 2 diabetes. Our data suggest that the genetic architecture of type 1 diabetes and type 2 diabetes might share common components on the HLA class II locus.

Geographical variation in the incidence of type 1 diabetes in the Nordic countries: A study within NordicDiabKids

BACKGROUND

The incidence of type 1 diabetes (T1D) is high in the Nordic countries with geographic differences between as well as within countries.

OBJECTIVE

To describe the geographical distribution of the incidence of T1D among children in four Nordic countries, an area where the population is considered genetically similar.

METHODS

Data on children 0 to 14 years of age and diagnosed with T1D 2006 to 2011 was collected from four Nordic national pediatric quality diabetes registries. Data included year of diagnosis (2006-2011), sex, and age at diagnosis. Figures for number of children at risk during 2006 to 2011-as well as total population, proportion with foreign background and size of populated areas of geographic regions-were collected from official statistics.

RESULTS

The total incidence during the study period for all four countries was 35.7/100 000 person years but differed between the countries (range 18.2-44.1; P < .001). The incidence difference between the countries was most obvious in the highest age group, 10 to 14 years of age, whereas there was no difference in the youngest age group 0 to 5 years of age. Iceland had similar incidence in the entire country, whereas the other countries had areas with different incidence. Densely populated areas, such as major cities, had the lowest incidence.

CONCLUSION

The incidence of T1D differed between the Nordic countries and also between the neighboring countries and generally decreased with population density. This indicates that environmental factors may contribute to the level of incidence of T1D.

Childhood thyroid autoimmunity and relation to islet autoantibodies in children at risk for type 1 diabetes in the diabetes prediction in skåne (DiPiS) study

BACKGROUND

The aim was to determine prevalence and age at seroconversion of thyroid autoimmunity in relation to islet autoantibodies, gender and HLA-DQ genotypes in children with increased risk for type 1 diabetes followed from birth.

METHODS

In 10-year-old children (n = 1874), blood samples were analysed for autoantibodies against thyroid peroxidase (TPOAb), thyroglobulin (TGAb), glutamic acid decarboxylase 65 (GADA), Zink transporter 8 (ZnT8R/W/QA), insulinoma-associated protein-2 (IA-2A), insulin (IAA) and HLA-DQ genotypes. Prospectively collected samples from 2 years of age were next analysed for TPOAb, and TGAb and, finally, in confirming samples at 11-16 years of age along with TSH and FT4. Frequencies were tested with Chi-square or Fischer's exact tests, autoantibody levels with Wilcoxon and correlations between autoantibody levels with Spearman's rank correlation test.

RESULTS

The prevalence of thyroid autoimmunity was 6.9%, overrepresented in girls (p < .001) also having higher TPOAb levels at 10 years (p = .049). TPOAb was associated with GADA (p = .002), ZnT8R/W/QA (p = .001) and IA-2A (p = .001) while TGAb were associated with ZnT8R/W/QA (p = .021). In boys only, TPOAb were associated with GADA (p = .002), IA-2A (p = .001), ZnT8R/W/QA (p = .001) and IAA (p = .009), and TGAb with GADA (p = .013), IA-2A (p = .005) and ZnT8R/W/QA (p = .003). Levels of IA-2A correlated to both TPOAb (p = .021) and to TGAb (p = .011). In boys only, levels of GADA and TGAb correlated (p = .009 as did levels of IA-2A and TPOAb (p = .013). The frequency and levels of thyroid autoantibodies increased with age. At follow-up, 22.3% had abnormal thyroid function or were treated with thyroxine.

CONCLUSIONS

Thyroid autoimmunity and high TPOAb levels were more common in girls. In contrast, in boys only, there was a strong association with as well as correlation between levels of thyroid and islet autoantibodies. It is concluded that while girls may develop autoimmune thyroid disease (AITD) independent of islet autoantibodies, the risk for thyroid disease in boys may be linked to concomitant islet autoimmunity.

HLA high-resolution typing by next-generation sequencing in Pandemrix-induced narcolepsy

The incidence of narcolepsy type 1 (NT1) increased in Sweden following the 2009–2010 mass-vaccination with the influenza Pandemrix-vaccine. NT1 has been associated with Human leukocyte antigen (HLA) DQB1*06:02 but full high-resolution HLA-typing of all loci in vaccine-induced NT1 remains to be done. Therefore, here we performed HLA typing by sequencing HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 in 31 vaccine-associated NT1 patients and 66 of their first-degree relatives (FDR), and compared these data to 636 Swedish general population controls (GP). Previously reported disease-related alleles in the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01extended haplotype were increased in NT1 patients (34/62 haplotypes, 54.8%) compared to GP (194/1272 haplotypes, 15.3%, p = 6.17E^-16). Indeed, this extended haplotype was found in 30/31 patients (96.8%) and 178/636 GP (28.0%). In total, 15 alleles, four extended haplotypes, and six genotypes were found to be increased or decreased in frequency among NT1 patients compared to GP. Among subjects with the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02-DQB1*06:02 haplotype, a second DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype (p = 2.02E^-2), but not homozygosity for DRB1*15:01:01-DQB1*06:02:01 (p = 7.49E^-1) conferred association to NT1. Alleles with increased frequency in DQA1*01:02:01 (p = 1.07E^-2) and DQA1*03:02//*03:03:01 (p = 3.26E^-2), as well as with decreased frequency in DRB3*01:01:02 (p = 8.09E^-3), DRB1*03:01:01 (p = 1.40E^-2), and DQB1*02:01:01 (p = 1.40E^-2) were found among patients compared to their FDR. High-resolution HLA sequencing in Pandemrix-associated NT1 confirmed the strong association with the DQB1*06:02:01-containing haplotype but also revealed an increased association to the not previously reported extended HLA-DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype. High-resolution HLA typing should prove useful in dissecting the immunological mechanisms of vaccination-associated NT1.

The influence of human leukocyte antigen-DRB1*15:01 and its interaction with smoking in MS development is dependent on DQA1*01:01 status

BACKGROUND

HLA-DRB1*15:01, absence of HLA-A*02:01, and smoking interact to increase multiple sclerosis (MS) risk.

OBJECTIVE

To analyze whether MS-associated human leukocyte antigen (HLA) alleles, apart from DRB1*15:01 and absence of A*02:01, interact with smoking in MS development, and to explore whether the established HLA-smoking interaction is affected by the DQA1*01:01 allele, which confers a protective effect only in the presence of DRB1*15:01.

METHODS

In two Swedish population-based case-control studies (5838 cases, 5412 controls), subjects with different genotypes and smoking habits were compared regarding MS risk, by calculating odds ratios with 95% confidence intervals employing logistic regression. Interaction on the additive scale between different genotypes and smoking was evaluated.

RESULTS

The DRB1*08:01 allele interacted with smoking to increase MS risk. The interaction between DRB1*15:01 and both the absence of A*02:01 and smoking was confined to DQA1*01:01 negative subjects, whereas no interactions occurred among DQA1*01:01 positive subjects.

CONCLUSION

Multifaceted interactions take place between different class II alleles and smoking in MS development. The influence of DRB1*15:01 and its interaction with the absence of A*02:01 and smoking is dependent on DQA1*01:01 status which may be due to differences in the responding T-cell repertoires.

Genetic aspects of type 1 diabetes

Type 1 diabetes mellitus (T1DM) is characterized by autoimmune destruction of pancreatic beta-cells in genetically predisposed individuals, eventually resulting in severe insulin deficiency. It is the most common form of diabetes in children and adolescents. Genetic susceptibility plays a crucial role in development of T1DM. The human leukocyte antigen complex plays a key role in the pathogenesis of T1DM. Furthermore, genome-wide association studies and linkage analysis have recently made a significant contribution to current knowledge relative to the impact of genetics on T1DM development and progression. This review focuses on current knowledge of genetics as a pathogenesis for T1DM. It also discusses mechanisms by which genes influence the risk of developing T1DM as well as the clinical and research applications of genetic risk scores in T1DM.

Eleven Amino Acids of HLA-DRB1 and Fifteen Amino Acids of HLA-DRB3, 4, and 5 Include Potentially Causal Residues Responsible for the Risk of Childhood Type 1 Diabetes

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the β49-55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (β14, β25, β71, and β73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10^-18), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10^-11), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population.

Adeno-associated virus neutralising antibodies in type 1 diabetes mellitus

Recombinant Adeno-associated viruses (AAVs) are an attractive vector for gene therapy delivery which may be blocked by AAV neutralising antibodies (NAbs). As Type 1 Diabetes (T1DM) is an endocrine disease of immunological origin, it is likely that NAb profiles are altered in the disease. In this study NAb to AAV2, AAV5, AAV6, and AAV8 in 72 subjects with T1DM and 45 non-diabetic patients were measured over a 4-year follow-up period. AAV2 NAb titres were significantly lower in non-diabetic subjects (P = 0.036). The T1DM group had more AAV8 NAb activity at baseline (P = 0.019), whilst after 4 years follow-up the T1DM group displayed developed increased AAV 5 (P = 0.03), 6 (P = 0.03) and 8 (P = 0.002) activity relative to the control group, however, overall AAV5 and 8 NAb levels were very low in patients <40. AAV NAb titre activity and prevalence generally appears higher in T1DM, however, low levels of AAV 5 and 8, particular in younger adult age groups at which T1DM can be targeted, could make these attractive vectors to target the disease.

Comparative analysis of gene expression profiles in children with type 1 diabetes mellitus

Type 1 diabetes (T1D) is an autoimmune disease that is typically diagnosed in children. The aim of the present study was to identify potential genes involved in the pathogenesis of childhood T1D. Two datasets of mRNA expression in children with T1D were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) in children with T1D were identified. Functional analysis was performed and a protein‑protein interaction (PPI) network was constructed, as was a transcription factor (TF)‑target network. The expression of selected DEGs was further assessed using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis. Electronic validation and diagnostic value analysis of the identified DEGs [cytokine inducible SH2 containing protein (CISH), SR‑related CTD associated factor 11 (SCAF11), estrogen receptor 1 (ESR1), Rho GTPase activating protein 25 (ARHGAP25), major histocompatibility complex, class II, DR β4 (HLA‑DRB4) and interleukin 23 subunit α (IL23A)] was performed in the GEO dataset. Compared with the normal control group, a total of 1,467 DEGs with P<0.05 were identified in children with T1D. CISH and SCAF11 were determined to be the most up‑ and downregulated genes, respectively. Heterogeneous nuclear ribonucleoprotein D (HNRNPD; degree=33), protein kinase AMP‑activated catalytic subunit α1 (PRKAA1; degree=11), integrin subunit α4 (ITGA4; degree=8) and ESR1 (degree=8) were identified in the PPI network as high‑degree genes. ARHGAP25 (degree=12), HNRNPD (degree=10), HLA‑DRB4 (degree=10) and IL23A (degree=9) were high‑degree genes identified in the TF‑target network. RT‑qPCR revealed that the expression of HNRNPD, PRKAA1, ITGA4 and transporter 2, ATP binding cassette subfamily B member was consistent with the results of the integrated analysis. Furthermore, the results of the electronic validation were consistent with the bioinformatics analysis. SCAF11, CISH and ARHGAP25 were identified to possess value as potential diagnostic markers for children with T1D. In conclusion, identifying DEGs in children with T1D may contribute to our understanding of its pathogenesis, and such DEGs may be used as diagnostic biomarkers for children with T1D.

Identification of diagnostic biomarker in patients with gestational diabetes mellitus based on transcriptome-wide gene expression and pattern recognition

Gestational diabetes mellitus (GDM) is becoming a growing threat for all pregnancies. In this study, we set up an automatic screening method combining both transcriptomic databases and support vector machine (SVM)-based pattern recognition to select biomarkers that can be used in predicting and preventing GDM for gravidas. We screened 63 samples (32 GDM samples and 31 normal controls) in GEO database for the GDM-specific biomarkers. Differentially expressed genes between patients with GDM and normal controls were picked out using edgeR package. Enrichment analysis was performed using database for annotation, visualization, and integrated discovery. The regulatory gene network was constructed based on the KEGG pathway database. Genes in the hub of the network were selected as specific biomarkers of GDM and further validated through document investigation. Finally, the GDM prediction model was verified using the SVMs. In total, 189 probes corresponding to 69 genes that differentially expressed between GDM and controls were screened out by edgeR package. Nineteen pathways were clustered by KEGG enrichment analysis and were integrated into a regulatory network containing 572 nodes and 1874 edges. The intersection of 50 hub genes extracted from the network and 69 differential genes picked out by edgeR was a collection of six genes, including members of HLA superfamily. In the SVM model, the six genes had a good capacity of predicting GDM in both the training data set (area under curve [AUC] is 0.781) and the testing data set (AUC is 0.710) and had been reported to be associated with GDM. We found that the collection of six genes can be potentially applied as a biomarker for GDM diagnosis.

DRB4*01:01 Has a Distinct Motif and Presents a Proinsulin Epitope That Is Recognized in Subjects with Type 1 Diabetes

DRB4*01:01 (DRB4) is a secondary HLA-DR product that is part of the high-risk DR4/DQ8 haplotype that is associated with type 1 diabetes (T1D). DRB4 shares considerable homology with HLA-DR4 alleles that predispose to autoimmunity, including DRB1*04:01 and DRB1*04:04. However, the DRB4 protein sequence includes distinct residues that would be expected to alter the characteristics of its binding pockets. To identify high-affinity peptides that are recognized in the context of DRB4, we used an HLA class II tetramer-based approach to identify epitopes within multiple viral Ags. We applied a similar approach to identify antigenic sequences within glutamic acid decarboxylase 65 and pre-proinsulin that are recognized in the context of DRB4. Seven sequences were immunogenic, eliciting high-affinity T cell responses in DRB4⁺ subjects. DRB1*04:01-restricted responses toward many of these peptides have been previously described, but responses to a novel pre-proinsulin 9-28 peptide were commonly observed in subjects with T1D. Furthermore, T cells that recognized this peptide in the context of DRB4 were present at significantly higher frequencies in patients with T1D than in healthy controls, implicating this as a disease-relevant specificity that may contribute to the breakdown of β cell tolerance in genetically susceptible individuals. We then deduced a DRB4 motif and confirmed its key features through structural modeling. This modeling suggested that the core epitope within the pre-proinsulin 9-28 peptide has a somewhat unusual binding motif, with tryptophan in the fourth binding pocket of DRB4, perhaps influencing the availability of this complex for T cell selection.

Association of protein tyrosine phosphatase non-receptor type 22 gene functional variant C1858T, HLA-DQ/DR genotypes and autoantibodies with susceptibility to type-1 diabetes mellitus in Kuwaiti Arabs

The incidence of type-1 Diabetes Mellitus (T1DM) has increased steadily in Kuwait during recent years and it is now considered amongst the high-incidence countries. An interaction between susceptibility genes, immune system mediators and environmental factors predispose susceptible individuals to T1DM. We have determined the prevalence of protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene functional variant (C1858T; R620W, rs2476601), HLA-DQ and DR alleles and three autoantibodies in Kuwaiti children with T1DM to evaluate their impact on genetic predisposition of the disease. This study included 253 Kuwaiti children with T1DM and 214 ethnically matched controls. The genotypes of PTPN22 gene functional variant C1858T (R620W; rs2476601) were detected by PCR-RFLP method and confirmed by DNA sequencing. HLA-DQ and DR alleles were determined by sequence-specific PCR. Three autoantibodies were detected in the T1DM patients using radio-immunoassays. A significant association was detected between the variant genotype of the PTPN22 gene (C1858T, rs2476601) and T1DM in Kuwaiti Arabs. HLA-DQ2 and DQ8 alleles showed a strong association with T1DM. In T1DM patients which carried the variant TT-genotype of the PTPN22 gene, 93% had at least one DQ2 allele and 60% carried either a DQ2 or a DQ8 allele. Amongst the DR alleles, the DR3-DRB5, DR3-3, DR3-4 and DR4-4 showed a strong association with T1DM. Majority of T1DM patients who carried homozygous variant (TT) genotype of the PTPN22 gene had either DR3-DRB5 or DRB3-DRB4 genotypes. In T1DM patients who co-inherited the high risk HLA DQ, DR alleles with the variant genotype of PTPN22 gene, the majority were positive for three autoantibodies. Our data demonstrate that the variant T-allele of the PTPN22 gene along with HLA-DQ2 and DQ8 alleles constitute significant determinants of genetic predisposition of T1DM in Kuwaiti children.

The Better Diabetes Diagnosis (BDD) study - A review of a nationwide prospective cohort study in Sweden

The incidence of type 1 diabetes (T1D) in Sweden is one of the highest in the world. However, the possibility of other types of diabetes must also be considered. In addition, individuals with T1D constitute a heterogeneous group. A precise classification of diabetes is a prerequisite for optimal outcome. For precise classification, knowledge on the distribution of genetic factors, biochemical markers and clinical features in individuals with new onset of diabetes is needed. The Better Diabetes Diagnosis (BDD), is a nationwide study in Sweden with the primary aim to facilitate a more precise classification and diagnosis of diabetes in order to enable the most adequate treatment for each patient. Secondary aims include identification of risk factors for diabetes-related co-morbidities. Since 2005, data on almost all children and adolescents with newly diagnosed diabetes in Sweden are prospectively collected and including heredity of diabetes, clinical symptoms, levels of C peptide, genetic analyses and detection of autoantibodies. Since 2011, analyses of HLA profile, autoantibodies and C peptide levels are part of clinical routine in Sweden for all pediatric patients with suspected diagnosis of diabetes. In this review, we present the methods and main results of the BDD study so far and discuss future aspects.

Genetics of type 1 diabetes

Type 1 diabetes (T1D) results from immune-mediated loss of pancreatic beta cells leading to insulin deficiency. It is the most common form of diabetes in children, and its incidence is on the rise. This article reviews the current knowledge on the genetics of T1D. In particular, we discuss the influence of HLA and non-HLA genes on T1D risk and disease progression through the preclinical stages of the disease, and the development of genetic scores that can be applied to disease prediction. Racial/ethnic differences, challenges and future directions in the genetics of T1D are also discussed.

High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis

We investigated association between HLA class I and class II alleles and haplotypes, and KIR loci and their HLA class I ligands, with multiple sclerosis (MS) in 412 European-American MS patients and 419 ethnically-matched controls, using next generation sequencing. The DRB1*15:01~DQB1*06:02 haplotype was highly predisposing (odds ratio (OR) = 3.98; 95% confidence interval (CI) = 3−5.31; p-value (p) = 2.22E−16), as was DRB1*03:01~DQB1*02:01 (OR = 1.63; CI = 1.19–2.24; p = 1.41E−03). Hardy-Weinberg (HW) analysis in MS patients revealed a significant DRB1*03:01~DQB1*02:01 homozyote excess (15 observed, 8.6 expected; p = 0.016). The OR for this genotype (5.27; CI = 1.47–28.52; p = 0.0036) suggests a recessive MS risk model. Controls displayed no HW deviations. The C*03:04~B*40:01 haplotype (OR = 0.27; CI = 0.14–0.51; p = 6.76E−06) was highly protective for MS, especially in haplotypes with A*02:01 (OR = 0.15; CI = 0.04–0.45; p = 6.51E−05). By itself, A*02:01 is moderately protective, (OR = 0.69; CI = 0.54–0.87; p = 1.46E−03), and haplotypes of A*02:01 with the HLA-B Thr80 Bw4 variant (Bw4T) more so (OR = 0.53; CI = 0.35–0.78; p = 7.55E−04). Protective associations with the Bw4 KIR ligand resulted from linkage disequilibrium (LD) with DRB1*15:01, but the Bw4T variant was protective (OR = 0.64; CI = 0.49–0.82; p = 3.37E−04) independent of LD with DRB1*15:01. The Bw4I variant was not associated with MS. Overall, we find specific class I HLA polymorphisms to be protective for MS, independent of the strong predisposition conferred by DRB1*15:01.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes

AIM

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies.

METHODS

Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D.

RESULTS

In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10^-92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime.

CONCLUSION

Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations.

Early prediction of autoimmune (type 1) diabetes

Underlying type 1 diabetes is a genetic aetiology dominated by the influence of specific HLA haplotypes involving primarily the class II DR-DQ region. In genetically predisposed children with the DR4-DQ8 haplotype, exogenous factors, yet to be identified, are thought to trigger an autoimmune reaction against insulin, signalled by insulin autoantibodies as the first autoantibody to appear. In children with the DR3-DQ2 haplotype, the triggering reaction is primarily against GAD signalled by GAD autoantibodies (GADA) as the first-appearing autoantibody. The incidence rate of insulin autoantibodies as the first-appearing autoantibody peaks during the first years of life and declines thereafter. The incidence rate of GADA as the first-appearing autoantibody peaks later but does not decline. The first autoantibody may variably be followed, in an apparently non-HLA-associated pathogenesis, by a second, third or fourth autoantibody. Although not all persons with a single type of autoantibody progress to diabetes, the presence of multiple autoantibodies seems invariably to be followed by loss of functional beta cell mass and eventually by dysglycaemia and symptoms. Infiltration of mononuclear cells in and around the islets appears to be a late phenomenon appearing in the multiple-autoantibody-positive with dysglycaemia. As our understanding of the aetiology and pathogenesis of type 1 diabetes advances, the improved capability for early prediction should guide new strategies for the prevention of type 1 diabetes.

Different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease

Celiac disease is associated with the HLA-DR3-DQA1*05:01-DQB1*02:01 and DR4-DQA1*03:01-DQB1*03:02 haplotypes. In addition, there are currently over 40 non-HLA loci associated with celiac disease. This study extends previous analyses on different HLA haplotypes in celiac disease using next generation targeted sequencing. Included were 143 patients with celiac disease and 135 non-celiac disease controls investigated at median 9.8 years (1.4-18.3 years). PCR-based amplification of HLA and sequencing with Illumina MiSeq technology were used for extended sequencing of the HLA class II haplotypes HLA-DRB1, DRB3, DRB4, DRB5, DQA1 and DQB1, respectively. Odds ratios were computed marginally for every allele and haplotype as the ratio of allelic frequency in patients and controls as ratio of exposure rates (RR), when comparing a null reference with equal exposure rates in cases and controls. Among the extended HLA haplotypes, the strongest risk haplotype for celiac disease was shown for DRB3*01:01:02 in linkage with DQA1*05:01-DQB1*02:01 (RR = 6.34; P-value < .0001). In a subpopulation analysis, DRB3*01:01:02-DQA1*05:01-DQB1*02:01 remained the most significant in patients with Scandinavian ethnicity (RR = 4.63; P < .0001) whereas DRB1*07:01:01-DRB4*01:03:01-DQA1*02:01-DQB1*02:02:01 presented the highest risk of celiac disease among non-Scandinavians (RR = 7.94; P = .011). The data also revealed 2 distinct celiac disease risk DR3-DQA1*05:01-DQB*02:01 haplotypes distinguished by either the DRB3*01:01:02 or DRB3*02:02:01 alleles, indicating that different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease. The associated risk of celiac disease for DR3-DRB3*01:01:02-DQA1*05:01-DQB1*02:01 is predominant among patients of Scandinavian ethnicity.

Toward solving the etiological mystery of primary biliary cholangitis

Primary biliary cholangitis (PBC) is considered a model autoimmune disease due to its signature anti‐mitochondrial antibody (AMA) autoantibody, female predominance, and relatively specific portal infiltration and cholestasis. The identification and cloning of the major mitochondrial autoantigens recognized by AMA have served as an immunologic platform to identify the earliest events involved in loss of tolerance. Despite the relatively high concordance rate in identical twins, genome‐wide association studies have not proven clinically useful and have led to suggestions of epigenetic events. To understand the natural history and etiology of PBC, several murine models have been developed, including spontaneous models, models induced by chemical xenobiotic immunization, and by “designer” mice with altered interferon metabolism. Herein, we describe five such models, including 1) NOD.c3c4 mice, 2) dominant negative form of transforming growth factor receptor type II mice, 3) interleukin‐2R α^−/− mice, 4) adenylate‐uridylate‐rich element Del^−/− mice, and 5) 2‐octynoic acid‐conjugated bovine serum albumin immunized mice. Individually there is no perfect murine model, but collectively the models point to loss of tolerance to PDC‐E2, the major mitochondrial autoantigen, as the earliest event that occurs before clinical disease is manifest. Although there is no direct association of AMA titer and PBC disease progression, it is noteworthy that the triad of PBC monocytes, biliary apotopes, and AMA leads to an intense proinflammatory cytokine burst. Further, the recurrence of PBC after liver transplantation indicates that, due to major histocompatibility complex restriction, disease activity must include not only adaptive immunity but also innate immune mechanisms. We postulate that successful treatment of PBC may require a personalized approach with therapies designed for different stages of disease. (Hepatology Communications 2017;1:275–287)

Type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM), also known as autoimmune diabetes, is a chronic disease characterized by insulin deficiency due to pancreatic β-cell loss and leads to hyperglycaemia. Although the age of symptomatic onset is usually during childhood or adolescence, symptoms can sometimes develop much later. Although the aetiology of T1DM is not completely understood, the pathogenesis of the disease is thought to involve T cell-mediated destruction of β-cells. Islet-targeting autoantibodies that target insulin, 65 kDa glutamic acid decarboxylase, insulinoma-associated protein 2 and zinc transporter 8 - all of which are proteins associated with secretory granules in β-cells - are biomarkers of T1DM-associated autoimmunity that are found months to years before symptom onset, and can be used to identify and study individuals who are at risk of developing T1DM. The type of autoantibody that appears first depends on the environmental trigger and on genetic factors. The pathogenesis of T1DM can be divided into three stages depending on the absence or presence of hyperglycaemia and hyperglycaemia-associated symptoms (such as polyuria and thirst). A cure is not available, and patients depend on lifelong insulin injections; novel approaches to insulin treatment, such as insulin pumps, continuous glucose monitoring and hybrid closed-loop systems, are in development. Although intensive glycaemic control has reduced the incidence of microvascular and macrovascular complications, the majority of patients with T1DM are still developing these complications. Major research efforts are needed to achieve early diagnosis, prevent β-cell loss and develop better treatment options to improve the quality of life and prognosis of those affected.