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

Virus-induced diabetes mellitus, revisiting infection etiology in light of SARS-CoV-2

Diabetes mellitus (DM) is comprised of two predominant subtypes: type 1 diabetes mellitus (T1DM), accounting for approximately 5 % of cases worldwide and resulting from autoimmune destruction of insulin-producing β-cells, and type 2 (T2DM), accounting for approximately 95 % of cases globally and characterized by the inability of pancreatic β-cells to meet the demand for insulin due to a relative β-cell deficit in the setting of peripheral insulin resistance. Both types of DM involve derangement of glucose metabolism and are metabolic diseases generally considered to be initiated by a combination of genetic and environmental factors. Viruses have been reported to play a role as infectious etiological factors in the initiation of both types of DM in predisposed individuals. Among the reported viral infections causing DM in humans, the most studied include coxsackie B virus, cytomegalovirus and hepatitis C virus. The recent COVID-19 pandemic has highlighted the diabetogenic potential of SARS-CoV-2, rekindling interest in the field of virus-induced diabetes (VID). This review discusses the reported mechanisms of viral-induced DM, addressing emerging concepts in VID, as well as highlighting areas where knowledge is lacking, and further investigation is warranted.

Genome-wide discovery for diabetes-dependent triglycerides-associated loci

PURPOSE

We aimed to discover loci associated with triglyceride (TG) levels in the context of type 2 diabetes (T2D). We conducted a genome-wide association study (GWAS) in 424,120 genotyped participants of the UK Biobank (UKB) with T2D status and TG levels.

METHODS

We stratified the cohort based on T2D status and conducted association analyses of TG levels for genetic variants with minor allele count (MAC) at least 20 in each stratum. Effect differences of genetic variants by T2D status were determined by Cochran's Q-test and we validated the significantly associated variants in the Mass General Brigham Biobank (MGBB).

RESULTS

Among 21,176 T2D and 402,944 non-T2D samples from UKB, stratified GWAS identified 19 and 315 genomic risk loci significantly associated with TG levels, respectively. Only chr6p21.32 exhibited genome-wide significant heterogeneity (I2 = 98.4%; pheterogeneity = 2.1x10-15), with log(TG) effect estimates of -0.066 (95%CI: -0.082, -0.050) and 0.002 (95%CI: -0.002, 0.006) for T2D and non-T2D, respectively. The lead variant rs9274619:A (allele frequency 0.095) is located 2Kb upstream of the HLA-DQB1 gene, between HLA-DQB1 and HLA-DQA2 genes. We replicated this finding among 25,137 participants (6,951 T2D cases) of MGBB (pheterogeneity = 9.5x10-3). Phenome-wide interaction association analyses showed that the lead variant was strongly associated with a concomitant diagnosis of type 1 diabetes (T1D) as well as diabetes-associated complications.

CONCLUSION

In conclusion, we identified an intergenic variant near HLA-DQB1/DQA2 significantly associates with decreased triglycerides only among those with T2D and highlights an immune overlap with T1D.

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.

Influence of Insulin Receptor Single Nucleotide Polymorphisms on Glycaemic Control and Formation of Anti-Insulin Antibodies in Diabetes Mellitus

Single nucleotide polymorphisms (SNPs) in insulin and insulin receptor genes may influence the interaction between the two molecules, as may anti-insulin antibodies (IAs), commonly found in patients with type 1 diabetes mellitus (T1D) or type 2 diabetes mellitus (T2D) treated with exogenous insulin. We examined the impact of two SNPs in the human insulin gene (INS), rs3842752 and rs689, and two in the insulin receptor gene (INSR) rs2245649 and rs2229429, on disease susceptibility, glycaemic control, and IAs formation in 100 T1D patients and 101 T2D patients treated with insulin. 79 individuals without diabetes were typed as healthy controls. The minor alleles of rs3842752 and rs689 in INS protected against T1D (OR: 0.50, p = 0.01 and OR: 0.44; p = 0.002, respectively). The minor alleles of both rs2245649 and rs2229429 in INSR were risk factors for poor glycaemic control (HbA1c ≥ 80 mmol/mol) in T1D (OR: 5.35, p = 0.009 and OR: 3.10, p = 0.01, respectively). Surprisingly, the minor alleles of rs2245649 and rs2229429 in INSR associated strongly with the absence of IAs in T1D (OR = 0.28, p = 0.008 and OR = 0.30, p = 0.002, respectively). In conclusion, the minor alleles of the investigated INS SNPs protect against T1D, and the minor alleles of the investigated INSR SNPs are associated with poor glycaemic control and the absence of IAs in T1D.

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.

Class I MHC Polymorphisms Associated with Type 2 Diabetes in the Mexican Population

Type 2 diabetes (T2D) has been linked to the expression of Human Leukocyte Antigens, principally to the Major Histocompatibility Complex Class II, with only scarce reports of Major Histocompatibility Complex Class I in specific populations. The objective of the present work was to explore the presence of polymorphisms in the MHC Class I related to T2D in the Mexican population using the Genome-Wide Association Studies Slim Initiative in Genomic Medicine of the Americas (GWAS SIGMA) database. This database contains information on 3848 Mexican individuals with T2D and 4366 control individuals from the same population without a clinical or hereditary history of the disease. The searching criteria considered a p-value of <0.005 and an odds ratio (OR) of >1.0. Ten novel, statistically significant nucleotide variants were identified: four polymorphisms associated with HLA-A (A*03:01:01:01) and six with HLA-C (C*01:02:01:01). These alleles have a high prevalence in Latin American populations and could potentially be associated with autoimmunity mechanisms related to the development of T2D complications.

Epitope Mapping of Pathogenic Autoantigens on Sjögren’s Syndrome-Susceptible Human Leukocyte Antigens Using In Silico Techniques

Sjögren’s syndrome (SjS) is characterized by lymphocytic infiltration and the dysfunction of the salivary and lacrimal glands. The autoimmune response is driven by the effector T cells and their cytokines. The activation of the effector helper T cells is mediated by autoantigen presentation by human leukocyte antigen (HLA) class II molecules of antigen-presenting cells. Studies using familial aggregation, animal models, and genome-wide association demonstrate a significant genetic correlation between specific risk HLAs and SjS. One of the key HLA alleles is HLA-DRB1*0301; it is one of the most influential associations with primary SjS, having the highest odds ratio and occurrence across different ethnic groups. The specific autoantigens attributed to SjS remain elusive, especially the specific antigenic epitopes presented by HLA-DRB1*0301. This study applied a high throughput in silico mapping technique to identify antigenic epitopes of known SjS autoantigens presented by high-risk HLAs. Furthermore, we identified specific binding HLA-DRB1*0301 epitopes using structural modeling tools such as Immune Epitope Database and Analysis Resource IEDB, AutoDock Vina, and COOT. By deciphering the critical epitopes of autoantigens presented by HLA-DRB1*0301, we gain a better understanding of the origin of the antigens, determine the T cell receptor function, learn the mechanism of disease progression, and develop therapeutic applications.

Alterations in Biomarkers Related to Glycemia, Lipid Metabolism, and Inflammation up to 20 Years Before Diagnosis of Type 1 Diabetes in Adults: Findings From the AMORIS Cohort

OBJECTIVE

Type 1 diabetes is described to have an acute onset, but autoantibodies can appear several years preceding diagnosis. This suggests a long preclinical phase, which may also include metabolic parameters. Here we assessed whether elevations in glycemic, lipid, and other metabolic biomarkers were associated with future type 1 diabetes risk in adults.

RESEARCH DESIGN AND METHODS

We studied 591,239 individuals from the Swedish AMORIS cohort followed from 1985-1996 to 2012. Through linkage to national patient, diabetes, and prescription registers, we identified incident type 1 diabetes. Using Cox regression models, we estimated hazard ratios for biomarkers at baseline and incident type 1 diabetes. We additionally assessed trajectories of biomarkers during the 25 years before type 1 diabetes diagnosis in a nested case-control design.

RESULTS

We identified 1,122 type 1 diabetes cases during follow-up (average age of patient at diagnosis: 53.3 years). The biomarkers glucose, fructosamine, triglycerides, the ratio of apolipoprotein (apo)B to apoA-I, uric acid, alkaline phosphatase, and BMI were positively associated with type 1 diabetes risk. Higher apoA-I was associated with lower type 1 diabetes incidence. Already 15 years before diagnosis, type 1 diabetes cases had higher mean glucose, fructosamine, triglycerides, and uric acid levels compared with control subjects.

CONCLUSIONS

Alterations in biomarker levels related to glycemia, lipid metabolism, and inflammation are associated with clinically diagnosed type 1 diabetes risk, and these may be elevated many years preceding diagnosis.

Analysis of HLA Variants and Graves' Disease and Its Comorbidities Using a High Resolution Imputation System to Examine Electronic Medical Health Records

Hyperthyroidism is a prevalent endocrine disorder, and genetics play a major role in the development of thyroid-associated diseases. In particular, the inheritance of HLA has been demonstrated to induce the highest susceptibility to Graves' disease (GD). However, thus far, no studies have reported the contribution of HLA to the development of GD and the complications that follow. Thus, in the present study, to the best of our knowledge, for the first time, a powerful imputation method, HIBAG, was used to predict the HLA subtypes among populations with available genome-wide SNP array data from the China Medical University Hospital (CMUH). The disease status was extracted from the CMUH electronic medical records; a total of 2,998 subjects with GD were identified as the cases to be tested and 29,083 subjects without any diagnosis of thyroid disorders were randomly selected as the controls. A total of 12 HLA class I genotypes (HLA-A*02:07-*11:01, HLA-B*40:01-*46:01 and *46:01-*46:01, and HLA-C*01:02-*01:02, *01:02-*03:04, and *01:02-*07:02) and 17 HLA class II genotypes (HLA-DPA1*02:02-*02:02, HLA-DPB1*02:01-*05:01, *02:02-*05:01, and *04:01-*05:01, HLA-DQA1*03:02, HLA-DRB1*09:01-*15:01, and *09:01-*09:01) were found to be associated with GD in the Taiwanese population. Moreover, the HLA subtypes HLA-A*11:01, HLA-B*46:01, HLA-DPA1*01:03, and HLA-DPB1*05:01 were found to be associated with heart disease, stroke, diabetes, and hypertension among subjects with GD. Our data suggest that several HLA alleles are markedly associated with GD and its comorbidities, including heart disease, hypertension, and diabetes.

Down Syndrome Is a Metabolic Disease: Altered Insulin Signaling Mediates Peripheral and Brain Dysfunctions

Down syndrome (DS) is the most frequent chromosomal abnormality that causes intellectual disability, resulting from the presence of an extra complete or segment of chromosome 21 (HSA21). In addition, trisomy of HSA21 contributes to altered energy metabolism that appears to be a strong determinant in the development of pathological phenotypes associated with DS. Alterations include, among others, mitochondrial defects, increased oxidative stress levels, impaired glucose, and lipid metabolism, finally resulting in reduced energy production and cellular dysfunctions. These molecular defects seem to account for a high incidence of metabolic disorders, i.e., diabetes and/or obesity, as well as a higher risk of developing Alzheimer’s disease (AD) in DS. A dysregulation of the insulin signaling with reduced downstream pathways represents a common pathophysiological aspect in the development of both peripheral and central alterations leading to diabetes/obesity and AD. This is further strengthened by evidence showing that the molecular mechanisms responsible for such alterations appear to be similar between peripheral organs and brain. Considering that DS subjects are at high risk to develop either peripheral or brain metabolic defects, this review will discuss current knowledge about the link between trisomy of HSA21 and defects of insulin and insulin-related pathways in DS. Drawing the molecular signature underlying these processes in DS is a key challenge to identify novel drug targets and set up new prevention strategies aimed to reduce the impact of metabolic disorders and cognitive decline.