Evidence of gene-gene interaction and age-at-diagnosis effects in type 1 diabetes

Renalase inhibition defends against acute and chronic β cell stress by regulating cell metabolism

OBJECTIVE

Renalase (Rnls) is annotated as an oxidase enzyme. It has been implicated in Type 1 diabetes (T1D) risk via genome-wide association studies (GWAS). We previously discovered through CRISPR screening and validation experiments that Rnls inhibition prevents or delays T1D in multiple mouse models of diabetes in vivo, and protects pancreatic β cells against autoimmune killing, ER and oxidative stress in vitro. The molecular biochemistry and functions of Rnls are largely uncharted. Here we studied the mechanisms of Rnls inhibition that underlie β cell protection during diabetogenic stress.

METHODS

Akita mice were treated with oral Pargyline (PG) in vivo to bind and inhibit Rnls, and pancreas or islets were harvested for β cell mass and β cell function analyses. Genetic and pharmacological tools were used to inhibit Rnls in β cell lines. RNA sequencing, metabolomics and metabolic function experiments were conducted in vitro in NIT-1 mouse β cell lines and human stem cell-derived β cells.

RESULTS

In vivo, PG improved glycemia and mildly preserved β cell mass and function in females. Genetic strategies to mutate (Rnlsmut) or knockout (Rnls KO) Rnls induced a robust metabolic shift towards glycolysis in both mouse and human β cell lines, in vitro. Stress protection was abolished when glycolysis was blocked with 2-deoxyglucose (2-DG). Pharmacological Rnls inhibition with PG did not strongly mimic these newly identified metabolic mechanisms.

CONCLUSIONS

Our work illustrates a role for Rnls in regulating cell metabolism. We show that inhibiting Rnls protects against chronic stress in vivo, and shields against acute stress in β cell lines in vitro by rewiring cell metabolism towards glycolysis.

Genomic variants associated with age at diagnosis of childhood-onset type 1 diabetes

Age at diagnosis (AAD) of Type 1 diabetes (T1D) is determined by the age at onset of the autoimmune attack and by the rate of beta cell destruction that follows. Twin studies found that T1D AAD is strongly influenced by genetics, notably in young children. In young UK, Finnish, Sardinian patients AAD-associated genomic variants were previously identified, which may vary across populations and with time. In 1956 children of European ancestry born in mainland France in 1980-2008 who declared T1D before 15 years, we tested 94 T1D-associated SNPs for their association with AAD using nonparametric Kruskal-Wallis test. While high-risk HLA genotypes were not found to be associated with AAD, fourteen SNPs located in 12 non-HLA loci showed a strong association (2.9 × 10-12 < P < 1.4 × 10-3 after FDR correction). Four of these loci have been associated with AAD in previous cohorts (GSDMB, IL2, TNFAIP3, IL1), supporting a partially shared genetic influence on AAD of T1D in the studied European populations. In contrast, the association of 8 new loci CLEC16A, TYK2, ERBB3, CCR7, FCRL3, DNAH2, FGF3/4, and HPSE2 with AAD is novel. The 12 protein-coding genes located within these loci are involved in major immune pathways or in predisposition to other autoimmune diseases, which suggests a prominent role for these genes in the early immune mechanisms of beta cell destruction.

Association between HLA alleles and haplotypes with age at diagnosis of type 1 diabetes in an admixed Brazilian population: A nationwide study

To investigate the potential relationship between HLA alleles and haplotypes and the age at diagnosis of type 1 diabetes (T1DAgeD) in an admixed Brazilian population. This nationwide study was conducted in public clinics across 12 Brazilian cities. We collected demographic and genetic data from 1,600 patients with T1D. DNA samples were utilised to determine genomic ancestry (GA) and perform HLA typings for DRB1, DQA1 and DQB1. We explored allele and haplotype frequencies and GA in patients grouped by T1DAgeD categories (<6 years, ≥6-<11 years, ≥11-<19 years and ≥19 years) through univariate and multivariate analyses and primary component analyses. Additionally, we considered self-reported colour-race and identified a familiar history of T1D in first-degree relatives. The homozygosity index for DRB1~DQA1~DQB1 haplotypes exhibited the highest variation among T1DAgeD groups, and the percentages of Sub-Saharan African and European ancestries showed opposite trends in principal component analysis (PCA) analyses. Regarding the association of alleles and haplotypes with T1DAgeD, risk alleles such as HLA-DQB1*03:02g, -DQA1*03:01g, -02:01g, DRB1*04:05g and -04:02g were more frequently observed in heterozygosity or homozygosity in T1D patients with an early disease onset. Conversely, alleles such as DRB1*07:01g, -13:03g, DQB1*06:02g and DQA1*02:01 were more prevalent in older T1D patients. The combination DR3/DR4.5 was significantly associated with early disease onset. However, gender, GA, familiar history of T1D and self-reported colour-race identity did not exhibit significant associations with the onset of T1D. It is worth noting that the very common risk haplotype DRB1*03:01g~DQA1*05:01g~DQB1*02:01g did not differentiate between T1DAgeD groups. In the admixed Brazilian population, the high-risk haplotype DRB1*04:05~DQA1*03:01~DQB1*03:02 was more prevalent in individuals diagnosed before 6 years of age. In contrast, the protective alleles DQA1*01:02g, DQB1*06:02g, DRB1*07:01g and DRB1*13:03g and haplotypes DRB1*13:03g~DQA1*05:01g~DQB1*03:01g and DRB1*16:02g~DQA1*01:02g~DQB1*05:02g were more frequently observed in patients diagnosed in adulthood. Notably, these associations were independent of factors such as sex, economic status, GA, familiar history of T1D and region of birth in Brazil. These alleles and haplotypes contribute to our understanding of the disease onset heterogeneity and may have implications for early interventions when detected in association with well-known genomic risk or protection factors for T1D.

Renalase inhibition regulates β cell metabolism to defend against acute and chronic stress

Renalase (Rnls), annotated as an oxidase enzyme, is a GWAS gene associated with Type 1 Diabetes (T1D) risk. We previously discovered that Rnls inhibition delays diabetes onset in mouse models of T1D in vivo , and protects pancreatic β cells against autoimmune killing, ER and oxidative stress in vitro . The molecular biochemistry and functions of Rnls are entirely uncharted. Here we find that Rnls inhibition defends against loss of β cell mass and islet dysfunction in chronically stressed Akita mice in vivo . We used RNA sequencing, untargeted and targeted metabolomics and metabolic function experiments in mouse and human β cells and discovered a robust and conserved metabolic shift towards glycolysis, amino acid abundance and GSH synthesis to counter protein misfolding stress, in vitro . Our work illustrates a function for Rnls in mammalian cells, and suggests an axis by which manipulating intrinsic properties of β cells can rewire metabolism to protect against diabetogenic stress.

Research progress of autoimmune diseases based on induced pluripotent stem cells

Autoimmune diseases can damage specific or multiple organs and tissues, influence the quality of life, and even cause disability and death. A 'disease in a dish' can be developed based on patients-derived induced pluripotent stem cells (iPSCs) and iPSCs-derived disease-relevant cell types to provide a platform for pathogenesis research, phenotypical assays, cell therapy, and drug discovery. With rapid progress in molecular biology research methods including genome-sequencing technology, epigenetic analysis, '-omics' analysis and organoid technology, large amount of data represents an opportunity to help in gaining an in-depth understanding of pathological mechanisms and developing novel therapeutic strategies for these diseases. This paper aimed to review the iPSCs-based research on phenotype confirmation, mechanism exploration, drug discovery, and cell therapy for autoimmune diseases, especially multiple sclerosis, inflammatory bowel disease, and type 1 diabetes using iPSCs and iPSCs-derived cells.

The rare DRB1*04:08-DQ8 haplotype is the main HLA class II genetic driver and discriminative factor of Early-onset Type 1 diabetes in the Portuguese population

Introduction

Early-onset Type 1 diabetes (EOT1D) is considered a disease subtype with distinctive immunological and clinical features. While both Human Leukocyte Antigen (HLA) and non-HLA variants contribute to age at T1D diagnosis, detailed analyses of EOT1D-specific genetic determinants are still lacking. This study scrutinized the involvement of the HLA class II locus in EOT1D genetic control.

Methods

We conducted genetic association and regularized logistic regression analyses to evaluate genotypic, haplotypic and allelic variants in DRB1, DQA1 and DQB1 genes in children with EOT1D (diagnosed at ≤5 years of age; n=97), individuals with later-onset disease (LaOT1D; diagnosed 8-30 years of age; n=96) and nondiabetic control subjects (n=169), in the Portuguese population.

Results

Allelic association analysis of EOT1D and LaOT1D unrelated patients in comparison with controls, revealed that the rare DRB1*04:08 allele is a distinctive EOT1D susceptibility factor (corrected p-value=7.0x10-7). Conversely, the classical T1D risk allele DRB1*04:05 was absent in EOT1D children while was associated with LaOT1D (corrected p-value=1.4x10-2). In corroboration, HLA class II haplotype analysis showed that the rare DRB1*04:08-DQ8 haplotype is specifically associated with EOT1D (corrected p-value=1.4x10-5) and represents the major HLA class II genetic driver and discriminative factor in the development of early onset disease.

Discussion

This study uncovered that EOT1D holds a distinctive spectrum of HLA class II susceptibility loci, which includes risk factors overlapping with LaOT1D and discriminative genetic configurations. These findings warrant replication studies in larger multicentric settings encompassing other ethnicities and may impact target screening strategies and follow-up of young children with high T1D genetic risk as well as personalized therapeutic approaches.

Gene Interactions in Human Disease Studies-Evidence Is Mounting

Despite monumental advances in molecular technology to generate genome sequence data at scale, there is still a considerable proportion of heritability in most complex diseases that remains unexplained. Because many of the discoveries have been single-nucleotide variants with small to moderate effects on disease, the functional implication of many of the variants is still unknown and, thus, we have limited new drug targets and therapeutics. We, and many others, posit that one primary factor that has limited our ability to identify novel drug targets from genome-wide association studies may be due to gene interactions (epistasis), gene-environment interactions, network/pathway effects, or multiomic relationships. We propose that many of these complex models explain much of the underlying genetic architecture of complex disease. In this review, we discuss the evidence from multiple research avenues, ranging from pairs of alleles to multiomic integration studies and pharmacogenomics, that supports the need for further investigation of gene interactions (or epistasis) in genetic and genomic studies of human disease. Our goal is to catalog the mounting evidence for epistasis in genetic studies and the connections between genetic interactions and human health and disease that could enable precision medicine of the future.

The missing heritability in type 1 diabetes

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.

Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease in which immune cells destroy insulin-producing beta cells. The aetiology of this complex disease is dependent on the interplay of multiple heterogeneous cell types in the pancreatic environment. Here, we provide a single-cell atlas of pancreatic islets of 24 T1D, autoantibody-positive and nondiabetic organ donors across multiple quantitative modalities including ~80,000 cells using single-cell transcriptomics, ~7,000,000 cells using cytometry by time of flight and ~1,000,000 cells using in situ imaging mass cytometry. We develop an advanced integrative analytical strategy to assess pancreatic islets and identify canonical cell types. We show that a subset of exocrine ductal cells acquires a signature of tolerogenic dendritic cells in an apparent attempt at immune suppression in T1D donors. Our multimodal analyses delineate cell types and processes that may contribute to T1D immunopathogenesis and provide an integrative procedure for exploration and discovery of human pancreatic function.

Renalase gene Glu37Asp polymorphism affects susceptibility to diabetic retinopathy in type 2 diabetes mellitus

AIMS

Renalase (RNLS) is an enzyme with monoamine oxidase activity that metabolizes circulating catecholamines. The RNLS gene Asp37Glu missense polymorphism (rs2296545) has been associated with hypertension, cardiac hypertrophy and dysfunction, and stroke. The purpose of our study was to investigate the potential involvement of this polymorphism in the microvascular complications of type 2 diabetes (T2DM).

METHODS

In this case-control study, the polymorphism was genotyped in 860 patients with T2DM and 400 healthy controls. The genotype and allele distribution was compared in subgroups of patients: with diabetic nephropathy (DN+) (n = 405) versus DN- (independently of the presence of DR) and, similarly, patients with diabetic retinopathy (DR+) (n = 328) versus DR- (independently of the presence of DN).

RESULTS

No significant association was detected between analyzed polymorphism and DN. In contrast, the retinopathy subgroup showed a significantly higher frequency of G allele (OR 1.4, 95% CI 1.16-1.72, p = 0.0005) and GG genotype (OR 1.86, 95% CI 1.26-2.75, p = 0.001) than DR- patients. The effect of RNLS Glu37Asp polymorphism on DR remained significant after adjustments for age, gender, BMI, and duration of T2DM (p = 0.005).

CONCLUSIONS

This is the first study to investigate RNLS gene polymorphism in microvascular complications of T2DM. The results suggest that RNLS rs2296545 SNP might be considered a risk factor for diabetic retinopathy in T2DM patients. This can provide new insight into the role of renalase gene in the pathophysiology of microvascular complications of diabetes.

Statistical Learning Methods Applicable to Genome-Wide Association Studies on Unbalanced Case-Control Disease Data

Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health records have enabled the collection of thousands of phenotypes from large cohorts, in particular for diseases with low prevalence. The unbalanced binary traits pose serious challenges to traditional statistical methods in terms of both genomic selection and disease prediction. For example, the well-established linear mixed models (LMM) yield inflated type I error rates in the presence of unbalanced case-control ratios. In this article, we review multiple statistical approaches that have been developed to overcome the inaccuracy caused by the unbalanced case-control ratio, with the advantages and limitations of each approach commented. In addition, we also explore the potential for applying several powerful and popular state-of-the-art machine-learning approaches, which have not been applied to the GWAS field yet. This review paves the way for better analysis and understanding of the unbalanced case-control disease data in GWAS.

Genome-wide search for genes affecting the age at diagnosis of type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease affecting individuals in the early years of life. Although previous studies have identified genetic loci influencing T1D diagnosis age, these studies did not investigate the genome with high resolution.

OBJECTIVE AND METHODS

We performed a genome-wide meta-analysis for age at diagnosis with cohorts from Finland (Finnish Diabetic Nephropathy Study), the United Kingdom (UK Genetic Resource Investigating Diabetes) and Sardinia. Through SNP associations, transcriptome-wide association analysis linked T1D diagnosis age and gene expression.

RESULTS

We identified two chromosomal regions associated with T1D diagnosis age: multiple independent variants in the HLA region on chromosome 6 and a locus on chromosome 17q12. We performed gene-level association tests with transcriptome prediction models from two whole blood datasets, lymphocyte cell line, spleen, pancreas and small intestine tissues. Of the non-HLA genes, lower PNMT expression in whole blood, and higher IKZF3 and ZPBP2, and lower ORMDL3 and GSDMB transcription levels in multiple tissues were associated with lower T1D diagnosis age (FDR = 0.05). These genes lie on chr17q12 which is associated with T1D, other autoimmune diseases, and childhood asthma. Additionally, higher expression of PHF20L1, a gene not previously implicated in T1D, was associated with lower diagnosis age in lymphocytes, pancreas, and spleen. Altogether, the non-HLA associations were enriched in open chromatin in various blood cells, blood vessel tissues and foetal thymus tissue.

CONCLUSION

Multiple genes on chr17q12 and PHF20L1 on chr8 were associated with T1D diagnosis age and only further studies may elucidate the role of these genes for immunity and T1D onset.

A non-coding RNASEH1 gene variant associates with type 1 diabetes and interacts with HLA tagSNPs in families from Colombia

OBJECTIVES

RNASEH1 gene has recently been associated with type 1 diabetes (T1D) in Colombia. The purpose of this study was to fine mapping the putative functional variant in RNASEH1 and testing its interaction with HLA tagSNPs.

METHODS

Two-hundred nuclear families with T1D were included in this study. Probands were tested for GAD65 and IA-2 autoantibodies. Genotyping was performed using 20 coding tagSNPs uncovered through Sanger sequencing (N = 96), in addition to 23 tagSNPs chosen from 1000genomes to cover the extent of the gene region. Also, 45 tagSNPs for classic HLA alleles associated with T1D were also genotyped. The transmission disequilibrium test (TDT) was used to test for association and a multiple testing correction was made using permutation. Interaction between RNASEH1 variants and HLA was evaluated by means of the M-TDT test.

RESULTS

We identified 20 variants (15 were novel) in the 96 patients sequenced. None of these variants were in linkage disequilibrium. In total, 43 RNASEH1 variants were genotyped in the 200 families. Association between T1D and rs7607888 was identified (P = .002). Haplotype analysis involving rs7607888 variant revealed even stronger association with T1D (most significative P = .0003). HLA tagSNPs displayed stronger associations (OR = 6.39, 95% CI = 4.33-9.44, P-value = 9.74E-28). Finally, we found several statistically significant interactions of HLA variants with rs7607888 (P-value ranged from 8.77E-04 to 5.33E-12).

CONCLUSION

Our results verify the association of rs7607888 in RNASEH1 gene with T1D. It is also shown in the interaction between RNASEH1 and HLA for conveying risk to T1D in Northwest Colombia. Work is underway aiming to identify the actual classic HLA alleles associated with the tagSNPs tested here.

Genome-scale in vivo CRISPR screen identifies RNLS as a target for beta cell protection in type 1 diabetes

Type 1 diabetes (T1D) is caused by the autoimmune destruction of pancreatic beta cells. Pluripotent stem cells can now be differentiated into beta cells, thus raising the prospect of a cell replacement therapy for T1D. However, autoimmunity would rapidly destroy newly transplanted beta cells. Using a genome-scale CRISPR screen in a mouse model for T1D, we show that deleting RNLS, a genome-wide association study candidate gene for T1D, made beta cells resistant to autoimmune killing. Structure-based modelling identified the U.S. Food and Drug Administration-approved drug pargyline as a potential RNLS inhibitor. Oral pargyline treatment protected transplanted beta cells in diabetic mice, thus leading to disease reversal. Furthermore, pargyline prevented or delayed diabetes onset in several mouse models for T1D. Our results identify RNLS as a modifier of beta cell vulnerability and as a potential therapeutic target to avert beta cell loss in T1D.

Microbiota derived factors as drivers of type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease caused by complex interactions between host genetics and environmental factors, culminating in the T-cell mediated destruction of the insulin producing cells in the pancreas. The rapid increase in disease frequency over the past 50 years or more has been too rapid to attribute to genetics. Dysbiosis of the gut microbiota is currently being widely investigated as a major contributor to environmental change driving increased T1D onset. In this chapter, we discuss the major changes in gut microbiota composition and function linked to T1D risk as well as the potential origin of these changes including infant diet, antibiotic use and host genetics. We examine the interaction between inflammation and gut barrier function and the dysbiotic gut microbiota that have been linked to T1D.

Genetic Variants Predisposing Most Strongly to Type 1 Diabetes Diagnosed Under Age 7 Years Lie Near Candidate Genes That Function in the Immune System and in Pancreatic β-Cells

OBJECTIVE

Immunohistological analyses of pancreata from patients with type 1 diabetes suggest distinct autoimmune islet β-cell pathology between those diagnosed at <7 years (<7 group) and those diagnosed at age ≥13 years (≥13 group), with both B- and T-lymphocyte islet inflammation common in children in the <7 group, whereas B cells are rare in the ≥13 group. Based on these observations, we sought to identify differences in genetic susceptibility between these prespecified age-at-diagnosis groups to inform on the etiology of the most aggressive form of type 1 diabetes that initiates in the first years of life.

RESEARCH DESIGN AND METHODS

Using multinomial logistic regression models, we tested if known type 1 diabetes loci (17 within the HLA and 55 non-HLA loci) had significantly stronger effect sizes in the <7 group compared with the ≥13 group, using genotype data from 27,071 individuals (18,485 control subjects and 3,121 case subjects diagnosed at <7 years, 3,757 at 7-13 years, and 1,708 at ≥13 years).

RESULTS

Six HLA haplotypes/classical alleles and six non-HLA regions, one of which functions specifically in β-cells (GLIS3) and the other five likely affecting key T-cell (IL2RA, IL10, IKZF3, and THEMIS), thymus (THEMIS), and B-cell development/functions (IKZF3 and IL10) or in both immune and β-cells (CTSH), showed evidence for stronger effects in the <7 group.

CONCLUSIONS

A subset of type 1 diabetes-associated variants are more prevalent in children diagnosed under the age of 7 years and are near candidate genes that act in both pancreatic β- and immune cells.

The associations between three genome-wide risk variants for serum C-peptide of T1D and autoantibody-positive T1D risk, and clinical characteristics in Chinese population

AIMS

Recent meta-genome-wide association studies identified several genetic variants associated with beta-cell function in type 1 diabetes (T1D). The aim of this study was to investigate the associations between these variants and T1D risk, C-peptide levels, islet-specific autoantibodies, and lipid levels in Chinese Han population.

METHODS

A total of 1005 unrelated autoantibody-positive T1D cases and 1417 healthy controls were included, which were genotyped for rs559047, rs9260151, and rs3135002. T1D individuals were measured for both C-peptide and lipid levels. Logistic regression models were used to examine these associations.

RESULTS

We found that rs3135002 A allele showed a genome-wide significant association with T1D risk (OR = 0.22, 95% CI = 0.17-0.30; P = 7.49 × 10^-27), and significant heterogeneity of effect size was observed between early-onset and later-onset T1D subgroups (I² = 80% and P = 0.026). Rs559047 had a nominal association with fasting C-peptide levels in newly diagnosed T1D individuals (P = 0.036). Moreover, rs3135002 A allele was significantly associated with GADA positivity (OR = 0.52, 95% CI = 0.30-0.91, P = 0.02). In addition, nominal correlations were observed with HDL levels for rs559047 (P = 0.042), while LDL levels for rs9260151 (P = 0.032) in T1D individuals.

CONCLUSIONS

Our results indicate that there are both similarities and differences for the associations of genetic variants among T1D development, progression, and related autoimmunity, metabolic traits.

New insights on the genetics of type 1 diabetes

PURPOSE OF REVIEW

The genetic risk for type 1 diabetes has been studied for over half a century, with the strong genetic associations of type 1 diabetes forming critical evidence for the role of the immune system in pathogenesis. In this review, we discuss some of the original research leading to recent developments in type 1 diabetes genetics.

RECENT FINDINGS

We examine the translation of polygenic scores for type 1 diabetes into tools for prediction and diagnosis of type 1 diabetes, in particular, when used in combination with other biomarkers and clinical features, such as age and islet-specific autoantibodies. Furthermore, we review the description of age associations with type 1 diabetes genetic risk, and the investigation of loci linked to type 2 diabetes in progression of type 1 diabetes. Finally, we consider current limitations, including the scarcity of data from racial and ethnic minorities, and future directions.

SUMMARY

The development of polygenic risk scores has allowed the integration of type 1 diabetes genetics into diagnosis and prediction. Emerging information on the role of specific genes in subgroups of individuals with the disease, for example, early-onset, mild autoimmunity, and so forth, is facilitating our understanding of the heterogeneity of type 1 diabetes, with the ultimate goal of using genetic information in research and clinical practice.

The Effect of Age on the Progression and Severity of Type 1 Diabetes: Potential Effects on Disease Mechanisms

PURPOSE OF REVIEW

To explore the impact of age on type 1 diabetes (T1D) pathogenesis.

RECENT FINDINGS

Children progress more rapidly from autoantibody positivity to T1D and have lower C-peptide levels compared to adults. In histological analysis of post-mortem pancreata, younger age of diagnosis is associated with reduced numbers of insulin containing islets and a hyper-immune CD20^hi infiltrate. Moreover compared to adults, children exhibit decreased immune regulatory function and increased engagement and trafficking of autoreactive CD8⁺ T cells, and age-related differences in β cell vulnerability may also contribute to the more aggressive immune phenotype observed in children. To account for some of these differences, HLA and non-HLA genetic loci that influence multiple disease characteristics, including age of onset, are being increasingly characterized. The exception of T1D as an autoimmune disease more prevalent in children than adults results from a combination of immune, metabolic, and genetic factors. Age-related differences in T1D pathology have important implications for better tailoring of immunotherapies.

The Role of NOD Mice in Type 1 Diabetes Research: Lessons from the Past and Recommendations for the Future

For more than 35 years, the NOD mouse has been the primary animal model for studying autoimmune diabetes. During this time, striking similarities to the human disease have been uncovered. In both species, unusual polymorphisms in a major histocompatibility complex (MHC) class II molecule confer the most disease risk, disease is caused by perturbations by the same genes or different genes in the same biological pathways and that diabetes onset is preceded by the presence of circulating autoreactive T cells and autoantibodies that recognize many of the same islet antigens. However, the relevance of the NOD model is frequently challenged due to past failures translating therapies from NOD mice to humans and because the appearance of insulitis in mice and some patients is different. Nevertheless, the NOD mouse remains a pillar of autoimmune diabetes research for its usefulness as a preclinical model and because it provides access to invasive procedures as well as tissues that are rarely procured from patients or controls. The current article is focused on approaches to improve the NOD mouse by addressing reasons why immune therapies have failed to translate from mice to humans. We also propose new strategies for mixing and editing the NOD genome to improve the model in ways that will better advance our understanding of human diabetes. As proof of concept, we report that diabetes is completely suppressed in a knock-in NOD strain with a serine to aspartic acid substitution at position 57 in the MHC class II Aβ. This supports that similar non-aspartic acid substitutions at residue 57 of variants of the human class II HLA-DQβ homolog confer diabetes risk.

The chromosome 6q22.33 region is associated with age at diagnosis of type 1 diabetes and disease risk in those diagnosed under 5 years of age

AIMS/HYPOTHESIS

The genetic risk of type 1 diabetes has been extensively studied. However, the genetic determinants of age at diagnosis (AAD) of type 1 diabetes remain relatively unexplained. Identification of AAD genes and pathways could provide insight into the earliest events in the disease process.

METHODS

Using ImmunoChip data from 15,696 cases, we aimed to identify regions in the genome associated with AAD.

RESULTS

Two regions were convincingly associated with AAD (p < 5 × 10-8): the MHC on 6p21, and 6q22.33. Fine-mapping of 6q22.33 identified two AAD-associated haplotypes in the region nearest to the genes encoding protein tyrosine phosphatase receptor kappa (PTPRK) and thymocyte-expressed molecule involved in selection (THEMIS). We examined the susceptibility to type 1 diabetes at these SNPs by performing a meta-analysis including 19,510 control participants. Although these SNPs were not associated with type 1 diabetes overall (p > 0.001), the SNP most associated with AAD, rs72975913, was associated with susceptibility to type 1 diabetes in those individuals diagnosed at less than 5 years old (p = 2.3 × 10-9).

CONCLUSION/INTERPRETATION

PTPRK and its neighbour THEMIS are required for early development of the thymus, which we can assume influences the initiation of autoimmunity. Non-HLA genes may only be detectable as risk factors for the disease in individuals diagnosed under the age 5 years because, after that period of immune development, their role in disease susceptibility has become redundant.

The Genetic Architecture of Type 1 Diabetes

Type 1 diabetes (T1D) is classically characterised by the clinical need for insulin, the presence of disease-associated serum autoantibodies, and an onset in childhood. The disease, as with other autoimmune diseases, is due to the interaction of genetic and non-genetic effects, which induce a destructive process damaging insulin-secreting cells. In this review, we focus on the nature of this interaction, and how our understanding of that gene-environment interaction has changed our understanding of the nature of the disease. We discuss the early onset of the disease, the development of distinct immunogenotypes, and the declining heritability with increasing age at diagnosis. Whilst Human Leukocyte Antigens (HLA) have a major role in causing T1D, we note that some of these HLA genes have a protective role, especially in children, whilst other non-HLA genes are also important. In adult-onset T1D, the disease is often not insulin-dependent at diagnosis, and has a dissimilar immunogenotype with reduced genetic predisposition. Finally, we discuss the putative nature of the non-genetic factors and how they might interact with genetic susceptibility, including preliminary studies of the epigenome associated with T1D.

β-cell specific T-lymphocyte response has a distinct inflammatory phenotype in children with Type 1 diabetes compared with adults

AIM

To examine the hypothesis that the quality, magnitude and breadth of helper T-lymphocyte responses to β cells differ in Type 1 diabetes according to diagnosis in childhood or adulthood.

METHODS

We studied helper T-lymphocyte reactivity against β-cell autoantigens by measuring production of the pro-inflammatory cytokine interferon-γ and the anti-inflammatory cytokine interleukin-10, using enzyme-linked immunospot assays in 61 people with Type 1 diabetes (within 3 months of diagnosis, positive for HLA DRB1*0301 and/or *0401), of whom 33 were children/adolescents, and a further 91 were unaffected siblings.

RESULTS

Interferon-γ responses were significantly more frequent in children with Type 1 diabetes compared with adults (85 vs 61%; P = 0.04). Insulin and proinsulin peptides were preferentially targeted in children (P = 0.0001 and P = 0.04, respectively) and the breadth of the interferon-γ response was also greater, with 70% of children having an interferon-γ response to three or more peptides compared with 14% of adults (P < 0.0001). Islet β-cell antigen-specific interleukin-10 responses were similar in children and adults in terms of frequency, breadth and magnitude, with the exception of responses to glutamic acid decarboxylase 65, which were significantly less frequent in adults.

CONCLUSIONS

At diagnosis of Type 1 diabetes, pro-inflammatory autoreactivity is significantly more prevalent, focuses on a wider range of targets, and is more focused on insulin/proinsulin in children than adults. We interpret this as indicating a more aggressive immunological response in the younger age group that is especially characterized by loss of tolerance to proinsulin. These findings highlight the existence of age-related heterogeneity in Type 1 diabetes pathogenesis that could have relevance to the development of immune-based therapies.

Polymorphism of the renalase gene in gestational diabetes mellitus

Renalase is considered as a novel candidate gene for type 2 diabetes. In this study, we aimed to investigate the relationship of serum renalase and two single nucleotide polymorphisms with gestational diabetes mellitus. One hundred and ninety-eight normotensive pregnant females (n = 99 gestational diabetes mellitus; n = 99 euglycemic pregnant controls) were classified according to the International Association of the Diabetes and Pregnancy Study criteria. Fasting and 2-h post glucose load blood levels and anthropometric assessment was performed. Serum renalase was measured using enzyme-linked immunosorbent assay, whereas DNA samples were genotyped for renalase single nucleotide polymorphisms rs2576178 and rs10887800 using Polymerase chain reaction-Restriction fragment length polymorphism method. In an age-matched case control study, no difference was observed in the serum levels of renalase (p > 0.05). The variant rs10887800 showed an association with gestational diabetes mellitus and remained significant after multiple adjustments (p < 0.05), whereas rs2576178 showed weak association (p = 0.030) that was lost after multiple adjustments (p = 0.09). We inferred a modest association of the rs10887800 polymorphism with gestational diabetes. Although gestational diabetes mellitus is self-reversible, yet presence of this minor G allele might predispose to metabolic syndrome phenotypes in near the future.

A method for identifying genetic heterogeneity within phenotypically defined disease subgroups

Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximizing power in comparison to standard variant-by-variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post hoc identification of the contributing genetic variants. We demonstrate the method on a range of simulated and test data sets, for which expected results are already known. We investigate subgroups of individuals with type 1 diabetes (T1D) defined by autoantibody positivity, establishing evidence for differential genetic architecture with positivity for thyroid-peroxidase-specific antibody, driven generally by variants in known T1D-associated genomic regions.

Prediction and prevention of type 1 diabetes: update on success of prediction and struggles at prevention

Type 1 diabetes mellitus (T1DM) is the archetypal example of a T cell-mediated autoimmune disease characterized by selective destruction of pancreatic β cells. The pathogenic equation for T1DM presents a complex interrelation of genetic and environmental factors, most of which have yet to be identified. On the basis of observed familial aggregation of T1DM, it is certain that there is a decided heritable genetic susceptibility for developing T1DM. The well-known association of T1DM with certain human histocompatibility leukocyte antigen (HLA) alleles of the major histocompatibility complex (MHC) was a major step toward understanding the role of inheritance in T1DM. Type 1 diabetes is a polygenic disease with a small number of genes having large effects (e.g., HLA) and a large number of genes having small effects. Risk of T1DM progression is conferred by specific HLA DR/DQ alleles [e.g., DRB1*03-DQB1*0201 (DR3/DQ2) or DRB1*04-DQB1*0302 (DR4/DQ8)]. In addition, the HLA allele DQB1*0602 is associated with dominant protection from T1DM in multiple populations. A concordance rate lower than 100% between monozygotic twins indicates a potential involvement of environmental factors on disease development. The detection of at least two islet autoantibodies in the blood is virtually pre-diagnostic for T1DM. The majority of children who carry these biomarkers, regardless of whether they have an a priori family history of the disease, will develop insulin-requiring diabetes. Facilitating pre-diagnosis is the timing of seroconversion which is most pronounced in the first 2 yr of life. Unfortunately the significant progress in improving prediction of T1DM has not yet been paralleled by safe and efficacious intervention strategies aimed at preventing the disease. Herein we summarize the chequered history of prediction and prevention of T1DM, describing successes and failures alike, and thereafter examine future trends in the exciting, partially explored field of T1DM prevention.

Serum Renalase Levels Correlate with Disease Activity in Lupus Nephritis

Introduction

Lupus nephritis (LN) is among the most serious complications of systemic lupus erythematosus (SLE), which causes significant morbidity and mortality. Renalase is a novel, kidney-secreted cytokine-like protein that promotes cell survival. Here, we aimed to investigate the relationship of serum renalase levels with LN and its role in the disease progression of LN.

Methods

For this cross-sectional study, 67 LN patients and 35 healthy controls were enrolled. Seventeen active LN patients who received standard therapies were followed up for six months. Disease activity was determined by the SLE Disease Activity–2000 (SLEDAI-2K) scoring system and serum renalase amounts were determined by ELISA. Predictive value of renalase for disease activity was assessed. Furthermore, the expression of renalase in the kidneys of patients and macrophage infiltration was assessed by immunohistochemistry.

Results

Serum renalase amounts were significantly higher in LN patients than in healthy controls. Moreover, patients with proliferative LN had more elevated serum renalase levels than Class V LN patients. In proliferative LN patients, serum renalase levels were significantly higher in patients with active LN than those with inactive LN. Serum renalase levels were positively correlated with SLEDAI-2K, 24-h urine protein excretion, ds-DNA and ESR but inversely correlated with serum albumin and C3. Renalase amounts decreased significantly after six-months of standard therapy. The performance of renalase as a marker for diagnosis of active LN was 0.906 with a cutoff value of 66.67 μg/ml. We also observed that the amount of renalase was significantly higher in glomerular of proliferative LN along with the co-expression of macrophages.

Conclusion

Serum renalase levels were correlated with disease activity in LN. Serum renalase might serve as a potential indicator for disease activity in LN. The marked increase of glomerular renalase and its association with macrophages suggest that it might play an important role in disease progression of LN.

Immunogenetics of type 1 diabetes: A comprehensive review

Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing beta cells in the pancreas. Prevention of T1D will require the ability to detect and modulate the autoimmune process before the clinical onset of disease. Genetic screening is a logical first step in identification of future patients to test prevention strategies. Susceptibility to T1D includes a strong genetic component, with the strongest risk attributable to genes that encode the classical Human Leukocyte Antigens (HLA). Other genetic loci, both immune and non-immune genes, contribute to T1D risk; however, the results of decades of small and large genetic linkage and association studies show clearly that the HLA genes confer the most disease risk and protection and can be used as part of a prediction strategy for T1D. Current predictive genetic models, based on HLA and other susceptibility loci, are effective in identifying the highest-risk individuals in populations of European descent. These models generally include screening for the HLA haplotypes "DR3" and "DR4." However, genetic variation among racial and ethnic groups reduces the predictive value of current models that are based on low resolution HLA genotyping. Not all DR3 and DR4 haplotypes are high T1D risk; some versions, rare in Europeans but high frequency in other populations, are even T1D protective. More information is needed to create predictive models for non-European populations. Comparative studies among different populations are needed to complete the knowledge base for the genetics of T1D risk to enable the eventual development of screening and intervention strategies applicable to all individuals, tailored to their individual genetic background. This review summarizes the current understanding of the genetic basis of T1D susceptibility, focusing on genes of the immune system, with particular emphasis on the HLA genes.

Genome-wide gene-gene interaction analysis for next-generation sequencing

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study.

Renalase: its role as a cytokine, and an update on its association with type 1 diabetes and ischemic stroke

PURPOSE OF REVIEW

Remarkable progress has been achieved over the past 2 years in understanding the cellular actions of renalase, its pathophysiology and potential therapeutic utility.

RECENT FINDINGS

There has been a paradigm shift in our thinking about the mechanisms underlying the cellular actions of renalase. We now understand that, independent of its enzymatic properties, renalase functions as a signaling molecule, a cytokine that interacts with a yet-to-be identified plasma membrane receptor(s) to activate protein kinase B and the mitogen-activated protein kinase pathway. These signaling properties are critical to its cytoprotective effects. New information regarding renalase's enzymatic function as an α-nicotinamide adenine dinucleotide oxidase/anomerase will be reviewed. Lastly, we will discuss the association of certain single nucleotide polymorphisms in the renalase gene with type 1 diabetes and with ischemic stroke, and the clinical implications of these findings.

SUMMARY

The consistent association of renalase single nucleotide polymorphisms and the development of type 1 diabetes is a great interest particularly because we now understand that renalase functions as a cytokine. Future work on renalase should focus on exploring the identity of its receptor(s), and its potential role as an immune modulator.

Immunogenetics of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) is an autoimmune disease arising through a complex interaction of both genetic and immunologic factors. Similar to the majority of autoimmune diseases, T1DM usually has a relapsing remitting disease course with autoantibody and T cellular responses to islet autoantigens, which precede the clinical onset of the disease process. The immunological diagnosis of autoimmune diseases relies primarily on the detection of autoantibodies in the serum of T1DM patients. Although their pathogenic significance remains uncertain, they have the practical advantage of serving as surrogate biomarkers for predicting the clinical onset of T1DM. Type 1 diabetes is a polygenic disease with a small number of genes having large effects (i.e. HLA), and a large number of genes having small effects. Risk of T1DM progression is conferred by specific HLA DR/DQ alleles [e.g., DRB1*03-DQB1*0201 (DR3) or DRB1*04-DQB1*0302 (DR4)]. In addition, HLA alleles such as DQB1*0602 are associated with dominant protection from T1DM in multiple populations. A discordance rate of greater than 50% between monozygotic twins indicates a potential involvement of environmental factors on disease development. Viral infections may play a role in the chain of events leading to disease, albeit conclusive evidence linking infections with T1DM remains to be firmly established. Two syndromes have been described in which an immune-mediated form of diabetes occurs as the result of a single gene defect. These syndromes are termed autoimmune polyglandular syndrome type I (APS-I) or autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED), and X-linked poyendocrinopathy, immune dysfunction and diarrhea (XPID). These two syndromes are unique models to understand the mechanisms involved in the loss of tolerance to self-antigens in autoimmune diabetes and its associated organ-specific autoimmune disorders. A growing number of animal models of these diseases have greatly helped elucidate the immunologic mechanisms leading to autoimmune diabetes.

Renalase, kidney and cardiovascular disease: are they related or just coincidentally associated?

Cardiovascular diseases, including hypertension are the leading cause of death in the developed countries. Diabetes and chronic kidney disease became also more prevalent reaching almost the level of epidemy. Researchers are looking eagerly for the new risk and/or pathogenetic factors, as well as therapeutic option in these disease. It has been suggested that human kidney releases a protein named renalase into the bloodstream. It is supposed to be an enzyme which breaks down catecholamines in the blood circulation and regulate blood pressure. However, there were several doubts whether renalase exerts monoaminooxidase activity, or if it is monoaminooxidase at all. Recently, a hypothesis that it is also a cytokine was postulated. Studies on renalase polymorphisms in hypertension, cardiovascular disease or diabetes are inconsistent. Similarly, there are several discrepancies in the animal on the possible role of renalase in hypertension and cardiovascular diseases. Some studies report a protective role of renalase in acute kidney injury, whereas others showed that renalase levels were mainly dependent on kidney function, indicating rather a role of kidney in excretion of this substance. Moreover, validated assays are needed to evaluate renalase levels and activity. On one hand a deeper and more accurate link between renalase and cardiovascular diseases require further profound research, on the other hand whether or not renalase protein could be a new therapeutic target in these pathologies should also be considered. Whether renalase, discovered in 2005, might be a Holy Grail of hypertension, linking kidney and cardiovascular diseases, remains to be proven.

Pathway-guided identification of gene-gene interactions

Assessing gene-gene interactions (GxG) at the gene level can permit examination of epistasis at biologically functional units with amplified interaction signals from marker-marker pairs. While current gene-based GxG methods tend to be designed for two or a few genes, for complex traits, it is often common to have a list of many candidate genes to explore GxG. We propose a regression model with pathway-guided regularization for detecting interactions among genes. Specifically, we use the principal components to summarize the SNP-SNP interactions between a gene pair, and use an L1 penalty that incorporates adaptive weights based on biological guidance and trait supervision to identify important main and interaction effects. Our approach aims to combine biological guidance and data adaptiveness, and yields credible findings that may be likely to shed insights in order to formulate biological hypotheses for further molecular studies. The proposed approach can be used to explore the GxG with a list of many candidate genes and is applicable even when sample size is smaller than the number of predictors studied. We evaluate the utility of the proposed method using simulation and real data analysis. The results suggest improved performance over methods not utilizing pathway and trait guidance.

Association of cytokines in individuals sensitive and insensitive to dust mites in a Brazilian population

Introduction

Allergic reaction to dust mites is a relatively common condition among children, triggering cutaneous and respiratory responses that have a great impact on the health of this population. Anaphylactic hypersensitivity is characterized by an exacerbated response involving the production of regulatory cytokines responsible for stimulating the production of IgE antibodies.

Objective

To investigate an association of variants in cytokine genes (IL1A⁻⁸⁸⁹, IL1B^{−511, +3962}, IL1R¹⁹⁷⁰, IL1RA¹¹¹⁰⁰, IL4RA⁺¹⁹⁰², IL12⁻¹¹⁸⁸, IFNG⁺⁸⁷⁴, TGFB1^{codon 10, codon 25}, TNFA^{−308, −238}, IL2^{−330, +166}, IL4^{−1098, −590, −33}, IL6^{−174, nt565}, and IL10^{−1082, −819, −592}) between patients sensitive to dust mites and a control group.

Methods

A total of 254 patients were grouped as atopic and non-atopic according to sensitivity as evaluated by the Prick Test and to cytokine genotyping by the polymerase chain reaction-sequence specific primers (PCR-SSP) method using the Cytokine Genotyping Kit.

Results

A comparison between individuals allergic to Dermatophagoides farinae, Dermatophagoides pteronyssinus, and Blomia tropicalis and a non-atopic control group showed significant differences between allele and genotype frequencies in the regulatory regions of cytokine genes, with important evidence for IL4⁻⁵⁹⁰ in T/C (10.2% vs. 43.1%, odd ratio [OR] = 0.15, p = 5.2 10⁻⁸, pc = 0.0000011, and 95% confidence interval [95%CI] = 0.07–0.32) and T/T genotypes (42.9% vs. 13.8%, OR = 4.69, p = 2.5 10⁻⁶, pc = 0.000055, and 95%CI = 2.42–9.09). Other associations were observed in the pro-inflammatory cytokines IL1A⁻⁸⁸⁹ (T/T, C, and T) and IL2⁻³³⁰ (G/T and T/T) and the anti-inflammatory cytokines IL4RA⁺¹⁹⁰² (A and G), IL4⁻⁵⁹⁰ (T/C, T/T, C, and T), and IL10⁻⁵⁹² (A/A, C/A, A, and C).

Conclusion

Our results suggest a possible association between single nucleotide polymorphisms (SNPs) in cytokine genes and hypersensitivity to dust mites.

Genetic analysis in young-age-of-onset Graves' disease reveals new susceptibility loci

CONTEXT

Genetic and environmental factors play an essential role in the pathogenesis of Graves' Disease (GD). Children with GD have less exposure time to environmental factors and therefore are believed to harbor stronger genetic susceptibility than adults.

OBJECTIVE

The aim of the study was to identify susceptibility loci that predispose to GD in patients with young-age-of-onset (YAO) GD.

SETTING AND DESIGN

One hundred six patients with YAO GD (onset <30 y) and 855 healthy subjects were studied. Cases and controls were genotyped using the Illumina Infinium Immunochip, designed to genotype 196,524 polymorphisms. Case control association analyses were performed using the PLINK computer package. Ingenuity Pathway Analysis program (QIAGEN) was used to carry out pathway analyses.

RESULTS

Immunochip genetic association analysis identified 30 single-nucleotide polymorphisms in several genes that were significantly associated with YAO GD, including major histocompatibility complex class I and class II genes, BTNL2, NOTCH4, TNFAIP3, and CXCR4. Candidate gene analysis revealed that most of the genes previously shown to be associated with adult-onset GD were also associated with YAO GD. Pathway analysis demonstrated that antigen presentation, T-helper cell differentiation, and B cell development were the major pathways contributing to the pathogenesis of YAO GD.

CONCLUSIONS

Genetic analysis identified novel susceptibility loci in YAO GD adding a new dimension to the understanding of GD etiology.

Analysis of gene-gene interactions using gene-trait similarity regression

OBJECTIVE

Gene-gene interactions (G×G) are important to study because of their extensiveness in biological systems and their potential in explaining missing heritability of complex traits. In this work, we propose a new similarity-based test to assess G×G at the gene level, which permits the study of epistasis at biologically functional units with amplified interaction signals.

METHODS

Under the framework of gene-trait similarity regression (SimReg), we propose a gene-based test for detecting G×G. SimReg uses a regression model to correlate trait similarity with genotypic similarity across a gene. Unlike existing gene-level methods based on leading principal components (PCs), SimReg summarizes all information on genotypic variation within a gene and can be used to assess the joint/interactive effects of two genes as well as the effect of one gene conditional on another.

RESULTS

Using simulations and a real data application to the Warfarin study, we show that the SimReg G×G tests have satisfactory power and robustness under different genetic architecture when compared to existing gene-based interaction tests such as PC analysis or partial least squares. A genome-wide association study with approx. 20,000 genes may be completed on a parallel computing system in 2 weeks.

Congenic mice reveal genetic epistasis and overlapping disease loci for autoimmune diabetes and listeriosis

The nonobese diabetic (NOD) mouse strain serves as a genomic standard for assessing how allelic variation for insulin-dependent diabetes (Idd) loci affects the development of autoimmune diabetes. We previously demonstrated that C57BL/6 (B6) mice harbor a more diabetogenic allele than NOD mice for the Idd14 locus when introduced onto the NOD genetic background. New congenic NOD mouse strains, harboring smaller B6-derived intervals on chromosome 13, now localize Idd14 to an ~18-Mb interval and reveal a new locus, Idd31. Notably, the B6 allele for Idd31 confers protection against diabetes, but only in the absence of the diabetogenic B6 allele for Idd14, indicating genetic epistasis between these two loci. Moreover, congenic mice that are more susceptible to diabetes are more resistant to Listeria monocytogenes infection. This result co-localizes Idd14 and Listr2, a resistance locus for listeriosis, to the same genomic interval and indicates that congenic NOD mice may also be useful for localizing resistance loci for infectious disease.

Polymorphisms in the TLR3 gene are associated with risk for type 1 diabetes mellitus

INTRODUCTION

Viral pathogens seem to play a role in triggering the autoimmune destruction that leads to the development of type 1 diabetes mellitus (T1DM). Toll-like receptor 3 (TLR3) has been shown to recognize double-stranded RNA, a molecular signature of most viruses. It is expressed at high levels in pancreatic β-cells and immune cells, suggesting a role for it in the pathogenesis of T1DM. Therefore, the aim of this study was to investigate whether TLR3 polymorphisms are associated with T1DM.

METHODS

Frequencies of the TLR3 rs11721827, rs13126816, rs5743313, rs7668666, and rs3775291 polymorphisms were analyzed in 449 T1DM patients and in 507 nondiabetic subjects. Haplotypes constructed from the combination of these polymorphisms were inferred using a Bayesian statistical method.

RESULTS

The rs3775291 and rs13126816 polymorphisms were associated with T1DM, and the strongest association was observed for the additive model (odds ratio (OR)=2.3, 95% CI 1.3-4.2 and OR=2.1, 95% CI 1.3-3.1 respectively). In the same way, the frequency of T1DM was higher as more risk alleles of the five polymorphisms were present (P-trend=0.001). Moreover, in T1DM patients, the minor alleles of the rs5743313 and rs117221827 polymorphisms were associated with an early age at diagnosis and worse glycemic control.

CONCLUSION

The TLR3 rs3775291 and rs13126816 polymorphisms are associated with risk for T1DM, while the rs5743313 and rs11721827 polymorphisms are associated with age at T1DM diagnosis and poor glycemic control. The number of risk alleles of the five TLR3 polymorphisms in the haplotypes seems to influence the risk for T1DM, suggesting that these polymorphisms might interact in the susceptibility for the disease.

A strategy to find gene combinations that identify children who progress rapidly to type 1 diabetes after islet autoantibody seroconversion

We recently developed a novel approach capable of identifying gene combinations to obtain maximal disease risk stratification. Type 1 diabetes has a preclinical phase including seroconversion to autoimmunity and subsequent progression to diabetes. Here, we applied our gene combination approach to identify combinations that contribute either to islet autoimmunity or to the progression from islet autoantibodies to diabetes onset. We examined 12 type 1 diabetes susceptibility genes (INS, ERBB3, PTPN2, IFIH1, PTPN22, KIAA0350, CD25, CTLA4, SH2B3, IL2, IL18RAP, IL10) in a cohort of children of parents with type 1 diabetes and prospectively followed from birth. The most predictive combination was subsequently applied to a smaller validation cohort. The combinations of genes only marginally contributed to the risk of developing islet autoimmunity, but could substantially modify risk of progression to diabetes in islet autoantibody-positive children. The greatest discrimination was provided by risk allele scores of five genes, INS, IFIH1, IL18RAP, CD25, and IL2 genes, which could identify 80 % of islet autoantibody-positive children who progressed to diabetes within 6 years of seroconversion and discriminate high risk (63 % within 6 years; 95 % CI 45-81 %) and low risk (11 % within 6 years; 95 % CI 0.1-22 %; p = 4 × 10(-5)) antibody-positive children. Risk stratification by these five genes was confirmed in a second cohort of islet autoantibody children. These findings highlight genes that may affect the rate of the beta-cell destruction process once autoimmunity has initiated and may help to identify islet autoantibody-positive subjects with rapid progression to diabetes.

Analysis of the expression of candidate genes for type 1 diabetes susceptibility in T cells

Type 1 diabetes is characterized by T-cell-mediated autoimmune destruction of pancreatic β-cells. Currently, approximately 50 type 1 diabetes susceptibility genes or chromosomal regions have been identified. However, the functions of type 1 diabetes susceptibility genes in T cells are elusive. In this study, we evaluated the correlation between type 1 diabetes susceptibility genes and T-cell signaling. The expression levels of 22 candidate type 1 diabetes susceptibility genes in T cells from nonobese diabetic (NOD), control C57BL/6 (B6), and NOD-control F1 hybrid mice were analyzed in response to 2 key immunoregulatory cytokines: interleukin-2 (IL-2) and transforming growth factor β (TGF-β). Exogenous gene expression studies were also performed in EL4 and Jurkat E6.1 T-cell lines. Significant differences in the expression of Clec16a, Dlk1, Il2, Ptpn22, Rnls, and Zac1 (also known as Plagl1) were observed in T cells derived from the 3 strains of mice, and TGF-β differentially influenced the expression of Ctla4, Foxp3, Il2, Ptpn22, Sh2b3, and Zac1. We found that TGF-β induced Zac1 expression in both primary T cells and EL4 cells and that exogenous expression of Zac1 and ZAC1 in T-cell lines altered the expression of Il2 and DLK1, respectively. The results of our study indicate the possibility that additional genetic pathways underlying type 1 diabetes susceptibility, including those involving Clec16a, Dlk1, Rnls, Sh2b3, and Zac1 under IL-2 and TGF-β signaling in T cells, may be shared between human and NOD mice.

From genetics of inflammatory bowel disease towards mechanistic insights

Advancements in human genetics now poise the field to illuminate the pathophysiology of complex genetic disease. In particular, genome-wide association studies (GWAS) have generated insights into the mechanisms driving inflammatory bowel disease (IBD) and implicated genes shared by multiple autoimmune and autoinflammatory diseases. Thus, emerging evidence suggests a central role for the mucosal immune system in mediating immune homeostasis and highlights the complexity of genetic and environmental interactions that collectively modulate the risk of disease. Nevertheless, the challenge remains to determine how genetic variation can precipitate and sustain the inappropriate inflammatory response to commensals that is observed in IBD. Here, we highlight recent advancements in immunogenetics and provide a forward-looking view of the innovations that will deliver mechanistic insights from human genetics.

Characteristics of rapid vs slow progression to type 1 diabetes in multiple islet autoantibody-positive children

AIMS/HYPOTHESIS

Islet autoantibody-positive children progress to type 1 diabetes at variable rates. In our study, we asked whether characteristic autoantibody and/or gene profiles could be defined for phenotypes showing extreme progression.

METHODS

Autoantibodies to insulin (IAA), GAD (GADA), insulinoma-associated antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A) were measured in follow-up sera, and genotyping for type 1 diabetes susceptibility genes (HLA-DR/HLA-DQ, INS variable number of tandem repeats [VNTR] and single nucleotide polymorphisms at PTPN22, PTPN2, ERBB3, IL2, SH2B3, CTLA4, IFIH1, KIAA0350 [also known as CLEC16A], CD25, IL18RAP, IL10, COBL) was performed on the DNA samples of children born to a parent with type 1 diabetes and prospectively followed from birth for up to 22 years.

RESULTS

Of the 1,650 children followed, 23 developed multiple autoantibodies and progressed to diabetes within 3 years (rapid progressors), while 24 children developed multiple autoantibodies and remained non-diabetic for more than 10 years from seroconversion (slow progressors). Rapid and slow progressors were similar with respect to HLA-DR/HLA-DQ genotypes, development of IAA, GADA and ZnT8A, and progression to multiple autoantibodies. In contrast, IA-2A development was considerably delayed in the slow progressors. Furthermore, both groups were effectively distinguished by the combined presence or absence of type 1 diabetes susceptibility alleles of non-HLA genes, most notably IL2, CD25, INS VNTR, IL18RAP, IL10, IFIH1 and PTPN22, and discrimination was improved among children carrying high-risk HLA-DR/HLA-DQ genotypes.

CONCLUSIONS/INTERPRETATION

Our data suggest that genotypes of non-HLA type 1 diabetes susceptibility genes influence the likelihood or rate of diabetes progression among children with multiple islet autoantibodies.

Complex multi-block analysis identifies new immunologic and genetic disease progression patterns associated with the residual β-cell function 1 year after diagnosis of type 1 diabetes

The purpose of the present study is to explore the progression of type 1 diabetes (T1D) in Danish children 12 months after diagnosis using Latent Factor Modelling. We include three data blocks of dynamic paraclinical biomarkers, baseline clinical characteristics and genetic profiles of diabetes related SNPs in the analyses. This method identified a model explaining 21.6% of the total variation in the data set. The model consists of two components: (1) A pattern of declining residual β-cell function positively associated with young age, presence of diabetic ketoacidosis and long duration of disease symptoms (P = 0.0004), and with risk alleles of WFS1, CDKN2A/2B and RNLS (P = 0.006). (2) A second pattern of high ZnT8 autoantibody levels and low postprandial glucagon levels associated with risk alleles of IFIH1, TCF2, TAF5L, IL2RA and PTPN2 and protective alleles of ERBB3 gene (P = 0.0005). These results demonstrate that Latent Factor Modelling can identify associating patterns in clinical prospective data – future functional studies will be needed to clarify the relevance of these patterns.

Viruses and type 1 diabetes: a new look at an old story

Epidemiological data suggesting an infectious origin of diabetes pre-date the discovery of insulin; indeed it was the variation in mortality rates from diabetes that led Gunderson to hypothesise that a virus with 'selective affinity for the pancreas' may cause 'acute diabetes' in youth (1). He noted an increase in deaths from diabetes in young people aged 10-20 yr in Norway from 1900 to 1921 following epidemics of parotitis, with a lag time of 3-4 yr between infection and death. In Norway, Denmark,France, and America, the increase in deaths from diabetes exceeded the expected number based on population growth; lending further weight to the proposal that diabetes was caused by infection. Since that time,a large body of epidemiological, clinical and experimental research, in humans, cellular and animal models, has provided further insights into the contribution of infections in the development of type 1 diabetes.Epidemiological evidence for a viral aetiology of diabetes A substantial body of epidemiological data point to a significant contribution of the environment in the development of type 1 diabetes,although much of the evidence is not specific to viruses per se. These data include rising rates of type 1 diabetes in both developed and developing countries in recent decades (2, 3) and a reduced contribution of high risk human leucocyte antigen (HLA) genotypes (4, 5), indicating that non-genetic factors are important. Similarly, the pairwise concordance between monozygotic twins for type 1 diabetes of less than 40%, and the observation that the incidence of diabetes in migrant children reflects that of their adopted country (6, 7), provide circumstantial evidence that environmental agents contribute to the disease. Space-time clustering in the presentation of type 1 diabetes (8-10) and clustering of births in children who subsequently develop diabetes (11) support a direct role for infections in the initiation and acceleration of the disease process.

Genetic interactions among Idd3, Idd5.1, Idd5.2, and Idd5.3 protective loci in the nonobese diabetic mouse model of type 1 diabetes

In the NOD mouse model of type 1 diabetes, insulin-dependent diabetes (Idd) loci control the development of insulitis and diabetes. Independently, protective alleles of Idd3/Il2 or Idd5 are able to partially protect congenic NOD mice from insulitis and diabetes, and to partially tolerize islet-specific CD8(+) T cells. However, when the two regions are combined, mice are almost completely protected, strongly suggesting the existence of genetic interactions between the two loci. Idd5 contains at least three protective subregions/causative gene candidates, Idd5.1/Ctla4, Idd5.2/Slc11a1, and Idd5.3/Acadl, yet it is unknown which of them interacts with Idd3/Il2. Through the use of a series of novel congenic strains containing the Idd3/Il2 region and different combinations of Idd5 subregion(s), we defined these genetic interactions. The combination of Idd3/Il2 and Idd5.3/Acadl was able to provide nearly complete protection from type 1 diabetes, but all three Idd5 subregions were required to protect from insulitis and fully restore self-tolerance. By backcrossing a Slc11a1 knockout allele onto the NOD genetic background, we have demonstrated that Slc11a1 is responsible for the diabetes protection resulting from Idd5.2. We also used Slc11a1 knockout-SCID and Idd5.2-SCID mice to show that both loss-of-function alleles provide protection from insulitis when expressed on the SCID host alone. These results lend further support to the hypothesis that Slc11a1 is Idd5.2.