Fine mapping and functional studies of risk variants for type 1 diabetes at chromosome 16p13.13

3D genome organization and epigenetic regulation in autoimmune diseases

Three-dimensional (3D) genomics is an emerging field of research that investigates the relationship between gene regulatory function and the spatial structure of chromatin. Chromatin folding can be studied using chromosome conformation capture (3C) technology and 3C-based derivative sequencing technologies, including chromosome conformation capture-on-chip (4C), chromosome conformation capture carbon copy (5C), and high-throughput chromosome conformation capture (Hi-C), which allow scientists to capture 3D conformations from a single site to the entire genome. A comprehensive analysis of the relationships between various regulatory components and gene function also requires the integration of multi-omics data such as genomics, transcriptomics, and epigenomics. 3D genome folding is involved in immune cell differentiation, activation, and dysfunction and participates in a wide range of diseases, including autoimmune diseases. We describe hierarchical 3D chromatin organization in this review and conclude with characteristics of C-techniques and multi-omics applications of the 3D genome. In addition, we describe the relationship between 3D genome structure and the differentiation and maturation of immune cells and address how changes in chromosome folding contribute to autoimmune diseases.

CLEC16A-An Emerging Master Regulator of Autoimmunity and Neurodegeneration

CLEC16A is emerging as an important genetic risk factor for several autoimmune disorders and for Parkinson disease (PD), opening new avenues for translational research and therapeutic development. While the exact role of CLEC16A in health and disease is still being elucidated, the gene plays a critical role in the regulation of autophagy, mitophagy, endocytosis, intracellular trafficking, immune function, and in biological processes such as insulin secretion and others that are important to cellular homeostasis. As shown in both human and animal modeling studies, CLEC16A hypofunction predisposes to both autoinflammatory phenotype and neurodegeneration. While the two are clearly related, further functional studies are needed to fully understand the mechanisms involved for optimized therapeutic interventions. Based on recent data, mitophagy-inducing drugs may be warranted, and such therapy should be tested in clinical trials as these drugs would tackle the underlying pathogenic mechanism (s) and could treat or prevent symptoms of autoimmunity and neurodegeneration in individuals with CLEC16A risk variants. Accordingly, interventions directed at reversing the dysregulated mitophagy and the consequences of loss of function of CLEC16A without activating other detrimental cellular pathways could present an effective therapy. This review presents the emerging role of CLEC16A in health and disease and provides an update on the disease processes that are attributed to variants located in the CLEC16A gene, which are responsible for autoimmune disorders and neurodegeneration with emphasis on how this information is being translated into practical and effective applications in the clinic.

Immune Regulation in Time and Space: The Role of Local- and Long-Range Genomic Interactions in Regulating Immune Responses

Mammals face and overcome an onslaught of endogenous and exogenous challenges in order to survive. Typical immune cells and barrier cells, such as epithelia, must respond rapidly and effectively to encountered pathogens and aberrant cells to prevent invasion and eliminate pathogenic species before they become overgrown and cause harm. On the other hand, inappropriate initiation and failed termination of immune cell effector function in the absence of pathogens or aberrant tissue gives rise to a number of chronic, auto-immune, and neoplastic diseases. Therefore, the fine control of immune effector functions to provide for a rapid, robust response to challenge is essential. Importantly, immune cells are heterogeneous due to various factors relating to cytokine exposure and cell-cell interaction. For instance, tissue-resident macrophages and T cells are phenotypically, transcriptionally, and functionally distinct from their circulating counterparts. Indeed, even the same cell types in the same environment show distinct transcription patterns at the single cell level due to cellular noise, despite being robust in concert. Additionally, immune cells must remain quiescent in a naive state to avoid autoimmunity or chronic inflammatory states but must respond robustly upon activation regardless of their microenvironment or cellular noise. In recent years, accruing evidence from next-generation sequencing, chromatin capture techniques, and high-resolution imaging has shown that local- and long-range genome architecture plays an important role in coordinating rapid and robust transcriptional responses. Here, we discuss the local- and long-range genome architecture of immune cells and the resultant changes upon pathogen or antigen exposure. Furthermore, we argue that genome structures contribute functionally to rapid and robust responses under noisy and distinct cellular environments and propose a model to explain this phenomenon.

Type I interferons as key players in pancreatic β-cell dysfunction in type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by pancreatic islet inflammation (insulitis) and specific pancreatic β-cell destruction by an immune attack. Although the precise underlying mechanisms leading to the autoimmune assault remain poorly understood, it is well accepted that insulitis takes place in the context of a conflicting dialogue between pancreatic β-cells and the immune cells. Moreover, both host genetic background (i.e., candidate genes) and environmental factors (e.g., viral infections) contribute to this inadequate dialogue. Accumulating evidence indicates that type I interferons (IFNs), cytokines that are crucial for both innate and adaptive immune responses, act as key links between environmental and genetic risk factors in the development of T1D. This chapter summarizes some relevant pathways involved in β-cell dysfunction and death, and briefly reviews how enteroviral infections and genetic susceptibility can impact insulitis. Moreover, we present the current evidence showing that, in β-cells, type I IFN signaling pathway activation leads to several outcomes, such as long-lasting major histocompatibility complex (MHC) class I hyperexpression, endoplasmic reticulum (ER) stress, epigenetic changes, and induction of posttranscriptional as well as posttranslational modifications. MHC class I overexpression, when combined with ER stress and posttranscriptional/posttranslational modifications, might lead to sustained neoantigen presentation to immune system and β-cell apoptosis. This knowledge supports the concept that type I IFNs are implicated in the early stages of T1D pathogenesis. Finally, we highlight the promising therapeutic avenues for T1D treatment directed at type I IFN signaling pathway.

Next steps in the identification of gene targets for type 1 diabetes

The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. Graphical abstract.

Genetic variants in class II transactivator are associated with chronic hepatitis B virus infection in the Han Chinese population

Class II transactivator (CIITA) is a master regulator of MHC gene expression and plays a role in inducing the expression of other immune system genes, including IL-4, IL-10 and Fas ligand, as well as more than 60 other immunologically significant genes. We used CIITA as a candidate gene to analyse whether any single-nucleotide polymorphisms (SNPs) are associated with chronic hepatitis B virus (HBV) infection. In total, 773 patients with chronic HBV infection were enrolled in this hospital-based case-control study. The patients were divided into groups according to their clinical characteristics: 596 patients had chronic hepatitis B (CHB), and 177 patients had hepatocellular carcinoma (HCC). A total of 313 patients with self-limited HBV infection were selected as the control group. CIITA gene variants were screened using Haploview 4.2 software; improved multiplex ligation detection reaction technology was then used for genotype detection, and HaploReg v4.1 was employed to predict the functions of 15 variants. The results showed that SNPs in introns in the CIITA gene, namely, rs13333382 (TT + TA vs. AA: p = .003, odds ratio (OR) = 0.65, 95% confidence interval (CI) = 0.49-0.87) and rs4780335 (CC + CG vs. GG: p = 9.40 × 10^-5 , OR = 0.55, 95% CI = 0.41-0.74), were positively associated with self-limited HBV infection in the dominant genetic model. Additionally, SNP rs1139564 (TT + TC vs. CC: p = .002, OR = 1.61, 95% CI = 1.19-2.16) in the 3' untranslated region may increase the risk of CHB. According to in silico analysis, all three statistically significant variants act as transcription factor binding motifs. However, we did not find that these 15 mutations are associated with HCC risk. Therefore, we believe that CIITA is a susceptibility gene for CHB rather than for HCC.

Replication study of susceptibility variants associated with allergic rhinitis and allergy in Han Chinese

Background

Allergic rhinitis (AR) is believed to be a complex genetic disease. The last decade has been marked by the publication of more than 20 genome-wide association studies (GWASs) of AR and associated allergic phenotypes and allergic diseases, which have shown allergic diseases and traits to share a large number of genetic susceptibility loci. The aim of present study was therefore to investigate the highly replicated allergy related genes and variants as candidates for AR in Han Chinese subjects.

Methods

A total of 762 AR patients and 760 control subjects were recruited, and a total of 58 susceptible variants previously reported to be associated with allergic traits were choose for replication.

Results

Logistic regression analyses revealed that in the co-dominant-effect model as assessed by the AIC, compared with wild-type carriers, significant AR risk were associated with rs9865818 in LPP (P = 0.029, OR = 1.469 for GG vs. AA); rs6554809 in DNAH5 (P = 0.000, OR = 1.597 for TC vs. CC); rs1438673 in WDR36-CAMK4 loci (P = 0.037, OR = 1.396 for CC vs.TT), rs7775228 in HLA region (P = 0.000, OR = 1.589 for TC vs.TT), rs7203459 in CLEC16A (P = 0.025, OR = 0.731 for TC vs. TT).

Conclusion

We replicated Han Chinese AR-specific susceptibility loci in LPP, DNAH5, HLA, CLEC16A and WDR36-CAMK4. Further understanding the molecular mechanisms underlying these associations may provide new insights into the etiology of allergic disease.

Clarifying the function of genes at the chromosome 16p13 locus in type 1 diabetes: CLEC16A and DEXI

More than a decade after the discovery of a novel type 1 diabetes risk locus on chromosome 16p13, there remains complexity and controversy over the specific gene(s) that regulate diabetes pathogenesis. A new study by Nieves-Bonilla et al. shows that one of these genes, DEXI, is unlikely to contribute to type 1 diabetes pathogenesis and positions the endolysosomal E3 ubiquitin ligase CLEC16A as the primary culprit by which this gene locus influences diabetes risk.

The type 1 diabetes candidate gene Dexi does not affect disease risk in the nonobese diabetic mouse model

Genome wide association studies have implicated more than 50 genomic regions in type 1 diabetes (T1D). A T1D region at chromosome 16p13.13 includes the candidate genes CLEC16A and DEXI. Conclusive evidence as to which gene is causal for the disease-association of this region is missing. We previously reported that Clec16a deficiency modified immune reactivity and protected against autoimmunity in the nonobese diabetic (NOD) mouse model for T1D. However, the diabetes-associated SNPs at 16p13.13 were described to also impact on DEXI expression and others have argued that DEXI is the causal gene in this disease locus. To help resolve whether DEXI affects disease, we generated Dexi knockout (KO) NOD mice. We found that Dexi deficiency had no effect on the frequency of diabetes. To test for possible interactions between Dexi and Clec16a, we intercrossed Dexi KO and Clec16a knockdown (KD) NOD mice. Dexi KO did not modify the disease protection afforded by Clec16a KD. We conclude that Dexi plays no role in autoimmune diabetes in the NOD model. Our data provide strongly suggestive evidence that CLEC16A, not DEXI, is causal for the T1D association of variants in the 16p13.13 region.

DEXI, a candidate gene for type 1 diabetes, modulates rat and human pancreatic beta cell inflammation via regulation of the type I IFN/STAT signalling pathway

AIMS/HYPOTHESIS

The initial stages of type 1 diabetes are characterised by an aberrant islet inflammation that is in part regulated by the interaction between type 1 diabetes susceptibility genes and environmental factors. Chromosome 16p13 is associated with type 1 diabetes and CLEC16A is thought to be the aetiological gene in the region. Recent gene expression analysis has, however, indicated that SNPs in CLEC16A modulate the expression of a neighbouring gene with unknown function named DEXI, encoding dexamethasone-induced protein (DEXI). We therefore evaluated the role of DEXI in beta cell responses to 'danger signals' and determined the mechanisms involved.

METHODS

Functional studies based on silencing or overexpression of DEXI were performed in rat and human pancreatic beta cells. Beta cell inflammation and apoptosis, driven by a synthetic viral double-stranded RNA, were evaluated by real-time PCR, western blotting and luciferase assays.

RESULTS

DEXI-silenced beta cells exposed to a synthetic double-stranded RNA (polyinosinic:polycytidylic acid [PIC], a by-product of viral replication) showed reduced activation of signal transducer and activator of transcription (STAT) 1 and lower production of proinflammatory chemokines that was preceded by a reduction in IFNβ levels. Exposure to PIC increased chromatin-bound DEXI and IFNβ promoter activity. This effect on IFNβ promoter was inhibited in DEXI-silenced beta cells, suggesting that DEXI is implicated in the regulation of IFNβ transcription. In a mirror image of knockdown experiments, DEXI overexpression led to increased levels of STAT1 and proinflammatory chemokines.

CONCLUSIONS/INTERPRETATION

These observations support DEXI as the aetiological gene in the type 1 diabetes-associated 16p13 genomic region, and provide the first indication of a link between this candidate gene and the regulation of local antiviral immune responses in beta cells. Moreover, our results provide initial information on the function of DEXI.

Progress in understanding type 1 diabetes through its genetic overlap with other autoimmune diseases

Type 1 diabetes mellitus (T1DM) is the most common autoimmune disease in pediatrics with a prevalence of roughly 1 in 500 children in the USA. Genome-wide association studies have identified more than 50 variants associated with increased risk for type 1 diabetes. Comparison of these variants with those identified in other autoimmune diseases reveals three important findings: (1) there is a high degree of overlap in implicated variants in diseases with similar pathophysiology, (2) in diseases with differing pathophysiology the same variants are often implicated in opposite roles, (3) in diseases with differing pathophysiology that have many non-overlapping or oppositely implicated variants there are still several variants which are overlapping or shared. Thus, the genetic overlap between T1DM and other autoimmune diseases forms the basis for our understanding of druggable targets in type 1 diabetes.

Multiple Sclerosis Risk Allele in CLEC16A Acts as an Expression Quantitative Trait Locus for CLEC16A and SOCS1 in CD4+ T Cells

For multiple sclerosis, genome wide association studies and follow up studies have identified susceptibility single nucleotide polymorphisms located in or near CLEC16A at chromosome 16p13.13, encompassing among others CIITA, DEXI and SOCS1 in addition to CLEC16A. These genetic variants are located in intronic or intergenic regions and display strong linkage disequilibrium with each other, complicating the understanding of their functional contribution and the identification of the direct causal variant(s). Previous studies have shown that multiple sclerosis-associated risk variants in CLEC16A act as expression quantitative trait loci for CLEC16A itself in human pancreatic β-cells, for DEXI and SOCS1 in thymic tissue samples, and for DEXI in monocytes and lymphoblastoid cell lines. Since T cells are major players in multiple sclerosis pathogenesis, we have performed expression analyses of the CIITA-DEXI-CLEC16A-SOCS1 gene cluster in CD4+ and CD8+ T cells isolated from multiple sclerosis patients and healthy controls. We observed a higher expression of SOCS1 and CLEC16A in CD4+ T cells in samples homozygous for the risk allele of CLEC16A rs12927355. Pair-wise linear regression analysis revealed high correlation in gene expression in peripheral T cells of CIITA, DEXI, CLEC16A and SOCS1. Our data imply a possible regulatory role for the multiple sclerosis-associated rs12927355 in CLEC16A.

Diabetes mellitus: The epidemic of the century

The epidemic nature of diabetes mellitus in different regions is reviewed. The Middle East and North Africa region has the highest prevalence of diabetes in adults (10.9%) whereas, the Western Pacific region has the highest number of adults diagnosed with diabetes and has countries with the highest prevalence of diabetes (37.5%). Different classes of diabetes mellitus, type 1, type 2, gestational diabetes and other types of diabetes mellitus are compared in terms of diagnostic criteria, etiology and genetics. The molecular genetics of diabetes received extensive attention in recent years by many prominent investigators and research groups in the biomedical field. A large array of mutations and single nucleotide polymorphisms in genes that play a role in the various steps and pathways involved in glucose metabolism and the development, control and function of pancreatic cells at various levels are reviewed. The major advances in the molecular understanding of diabetes in relation to the different types of diabetes in comparison to the previous understanding in this field are briefly reviewed here. Despite the accumulation of extensive data at the molecular and cellular levels, the mechanism of diabetes development and complications are still not fully understood. Definitely, more extensive research is needed in this field that will eventually reflect on the ultimate objective to improve diagnoses, therapy and minimize the chance of chronic complications development.