Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes

Genome-wide association studies - A summary for the clinical gastroenterologist

Genome-wide association studies (GWAS) have been applied to various gastrointestinal and liver diseases in recent years. A large number of susceptibility genes and key biological pathways in disease development have been identified. So far, studies in inflammatory bowel diseases, and in particular Crohn’s disease, have been especially successful in defining new susceptibility loci using the GWAS design. The identification of associations related to autophagy as well as several genes involved in immunological response will be important to future research on Crohn’s disease. In this review, key methodological aspects of GWAS, the importance of proper cohort collection, genotyping issues and statistical methods are summarized. Ways of addressing the shortcomings of the GWAS design, when it comes to rare variants, are also discussed. For each of the relevant conditions, findings from the various GWAS are summarized with a focus on the affected biological systems.

From genes to function: the next challenge to understanding multiple sclerosis

Susceptibility to multiple sclerosis is jointly determined by genetic and environmental factors, and progress has been made in defining some of these genetic associations, as well as their possible interactions with the environment. However, definitive proof for the involvement of specific genetic determinants in the disease will only come from studies that examine their functional roles in disease pathogenesis. New and combined approaches are needed to analyse the complexity of gene regulation and the functional contribution of each genetic determinant to disease susceptibility or pathophysiology. These studies should proceed in parallel with the use of genetically defined human populations to explore how both genetic and environmental factors affect the function of the pathways in individuals with and without disease, and how these determine the inherited risk of multiple sclerosis.

The genetics of autoimmune diseases: a networked perspective

Modern tools for genetic analysis are producing a large impact on our understanding of autoimmunity. More than 30 genome-wide association studies (GWAS) have been published to date in several autoimmune diseases (AID) and hundreds of common variants have been identified that confer risk or protection. While statistical adjustments are essential to refine the list of potential associations with each disease, valuable information can be extracted by the systematic collection of moderately significant variants present in more than one trait. In this article, a compilation of all GWAS published to date in seven common AID is provided and a network-based analysis of shared susceptibility genes at different levels of significance is presented. While involvement of the MHC region in chromosome 6p21 is not in question for most AID, the complex genetic architecture of this locus poses a significant analytical challenge. On the other hand, by considering the contribution of non-MHC-related genes, similarities and differences among AID can be readily computed thus gaining insights into possible pathogenic mechanisms. Statistically significant excess sharing of non-MHC genes was found between type I diabetes (T1D) and all other AID studied, a result also seen for RA. A smaller but significant degree of sharing was observed for multiple sclerosis (MS), Celiac disease (CeD) and Crohn's disease (CD). The availability of GWAS data allows for a systematic analysis of similarities and differences among several AID. Using this class of approaches the unique genetic landscape for each autoimmune disease can start to be defined.

Adenovirus E3 MHC inhibitory genes but not TNF/Fas apoptotic inhibitory genes expressed in beta cells prevent autoimmune diabetes

To mimic events and molecules involved in type 1 insulin-dependent diabetes mellitus (T1D), we previously designed a transgenic (tg) mouse model where the viral nucleoprotein (NP) gene of lymphocytic choriomeningitis virus (LCMV) was expressed in the thymus to delete high affinity antiself (virus) T cells and in insulin-producing beta cells of the islets of Langerhans. Such tg mice, termed RIP-LCMV, fail to spontaneously develop diabetes. In contrast, when these mice are challenged with LCMV, they develop diabetes as they display hyperglycemia, low to absent levels of pancreatic insulin, and abundant mononuclear cell infiltrates in the islets. However, expressing the adenovirus early region (E3) gene in beta cells along with the LCMV transgene aborted the T1D. The present study utilizes this combined tg model (RIP LCMV x RIP E3) to define the requirement(s) of either pro-apoptotic TNF and Fas pathways or MHC class I up-regulation on beta cells for virus-induced T1D. Inhibitors to either pathway (TNF/Fas or MHC class I) are encoded in the E3 gene complex. To accomplish this task either the E3 region encoding the inhibitors of TNF and Fas pathways or the region encoding gp-19, a protein that inhibits transport of MHC class I molecules out of the endoplasmic reticulum were deleted in the RIP LCMV x RIP E3 model. Thus only the gp-19 is required to abort the virus-induced T1D. In contrast, removal of TNF- and Fas-pathway inhibitory genes had no effect on E3-mediated prevention of T1D.

Coexpression network based on natural variation in human gene expression reveals gene interactions and functions

Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including CHCHD2 and TMEM111, and provided experimental evidence that TMEM111 is part of the endoplasmic reticulum-associated secretory pathway. We also found that IFIH1, a susceptibility gene of type 1 diabetes, interacts with YES1, which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes.

Structures and Assumptions: Strategies to Harness Gene × Gene and Gene × Environment Interactions in GWAS

Genome-wide association studies, in which as many as a million single nucleotide polymorphisms (SNP) are measured on several thousand samples, are quickly becoming a common type of study for identifying genetic factors associated with many phenotypes. There is a strong assumption that interactions between SNPs or genes and interactions between genes and environmental factors substantially contribute to the genetic risk of a disease. Identification of such interactions could potentially lead to increased understanding about disease mechanisms; drug × gene interactions could have profound applications for personalized medicine; strong interaction effects could be beneficial for risk prediction models. In this paper we provide an overview of different approaches to model interactions, emphasizing approaches that make specific use of the structure of genetic data, and those that make specific modeling assumptions that may (or may not) be reasonable to make. We conclude that to identify interactions it is often necessary to do some selection of SNPs, for example, based on prior hypothesis or marginal significance, but that to identify SNPs that are marginally associated with a disease it may also be useful to consider larger numbers of interactions.

Finding the missing heritability of complex diseases

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

Sequence variations of GRM6 in patients with high myopia

PURPOSE

Mutations in the glutamate receptor metabotropic 6 gene (GRM6) have been identified in patients with congenital stationary night blindness (CSNB1B). High myopia is usually observed in CSNB1B patients. This study tested if any mutations in GRM6 were solely responsible for high myopia.

METHODS

DNA was prepared from the venous leukocytes of 96 Chinese patients with high myopia (refraction of spherical equivalent of at least -6.00 diopters [D]) and 96 controls (refraction of spherical equivalent between -0.50 D and +2.00 D with normal visual acuity). The coding regions and adjacent intronic sequence of GRM6 were amplified by a polymerase chain reaction (PCR) and then analyzed by cycle sequencing. Detected variations were evaluated in normal controls by heteroduplex-single-strand-conformation (SSCP) polymorphism analysis or restriction fragment polymorphism (RFLP).

RESULTS

Four novel variations predicted to have potential functional changes were identified: c.67-82delCAGGCGGGCCTGGCGCinsT (p.Gln23_Arg28delinsCys), c.858-5a>g (r.spl?), c.1172G>A (p.Arg391Gln), and c.1537G>A (p.Val513Met). Except for c.1172G>A, the other three were not detected in the 96 controls. In addition, five rare variations-(c.72G>A, c.504+10g>t, c.726-50g>c, c.1359C>T, and c.1383C>T)-and one common variation (c.2437-6g>a) without predicted functional consequences and nine known single nucleotide polymorphisms (SNPs) were also detected.

CONCLUSION

Three novel variations with potential functional consequences were identified in the GRM6 of patients with high myopia, suggesting a potential role in the development of myopia in rare cases.

A cis-acting regulatory variant in the IL2RA locus

The mechanism for the association of type 1 diabetes (T1D) with IL2RA remains to be clarified. Neither of the two distinct, transmission-disequilibrium confirmed loci mapping to this gene can be explained by a coding variant. An effect on the levels of the soluble protein product sIL-2RA has been reported but its cause and relationship to disease risk is not clear. To look for an allelic effect on IL2RA transcription in cis, we examined RNA from 48 heterozygous lymphocyte samples for differential allele expression. Of the 48 samples, 32 showed statistically significant allelic imbalance. No known single nucleotide polymorphism (SNP) had perfect correlation with this transcriptional effect but the one that showed the most significant (p = 1.6 x 10(-5)) linkage disequilibrium with it was the SNP rs3118470. We had previously shown rs3118470 to confer T1D susceptibility in a Canadian dataset, independently of rs41295061 as the major reported locus (p = 5 x 10(-3), after accounting for rs41295061 by conditional regression). Lower IL2RA levels consistently originated from the T1D predisposing allele. We conclude that an as yet unidentified variant or haplotype, best marked by rs3118470, is responsible for this independent effect and increases T1D risk through diminished expression of the IL-2R, likely by interfering with the proper development of regulatory T cells.

Closing the gap between genotype and phenotype

Making causative connections between genotypic and phenotypic variation is a major challenge for geneticists engaged in the study of human disease. A study drawing this connection for a type 1 diabetes risk locus now demonstrates the importance of focusing on specific quantitative traits and studying them in normal subjects.

Innate receptors and microbes in induction of autoimmunity

Cells of the adaptive immune system (T and B cells) causing autoimmunity require activation signals that are normally provided by the innate immune system. Innate signaling receptors are obvious candidates for participation in the induction of autoimmunity, and the nature of these receptors suggests that microbes could be the triggers. Recent publications describing the development of autoimmunity in sterile conditions and in animals deficient in innate signaling question the requirement of these receptors for initiation of autoimmunity. In addition, the role of the non-pathogenic (commensal) microbiota as a regulator of autoimmunity has come into the spotlight. In this review we discuss recent reports that deal with the link between innate signaling receptors and 'adaptive' autoimmunity.

Cytoplasmic nucleic acid sensors in antiviral immunity

The innate immune system uses pattern recognition receptors (PRRs) to sense invading microbes and initiate a rapid protective response. PRRs bind and are activated by structural motifs, such as nucleic acids or bacterial and fungal cell wall components, collectively known as pathogen-associated molecular patterns. PRRs that recognize pathogen-derived nucleic acids are present in vesicular compartments and in the cytosol of most cell types. Here, we review recent studies of these cytosolic sensors, focusing on the nature of the ligands for DNA-dependent activator of interferon (DAI)-regulatory factors, absent in melanoma 2 (AIM2), and the retinoic acid-inducible gene I-like helicase (RLH) family of receptors, the basis of ligand recognition and the signaling pathways triggered by the activation of these receptors. An increased understanding of these molecular aspects of innate immunity will guide the development of novel antiviral therapeutics.

The genetics of quantitative traits: challenges and prospects

A major challenge in current biology is to understand the genetic basis of variation for quantitative traits. We review the principles of quantitative trait locus mapping and summarize insights about the genetic architecture of quantitative traits that have been obtained over the past decades. We are currently in the midst of a genomic revolution, which enables us to incorporate genetic variation in transcript abundance and other intermediate molecular phenotypes into a quantitative trait locus mapping framework. This systems genetics approach enables us to understand the biology inside the 'black box' that lies between genotype and phenotype in terms of causal networks of interacting genes.

Multiple sclerosis and polymorphisms of innate pattern recognition receptors TLR1-10, NOD1-2, DDX58, and IFIH1

Genetic factors are critical in multiple sclerosis (MS), and it is conceivable that the pattern recognition receptors of the innate immune system are of pathogenic importance. We therefore developed two novel assays capable of analyzing 42 single-nucleotide polymorphisms in the human genes encoding TLR1-10, NOD1-2, DDX58, and IFIH1. Using these assays, we genotyped 963 MS patients and 960 controls, and analyzed for possible associations to MS diagnosis, clinical course, severity, and age at onset. Our results support previous findings of associations between the IFIH1-locus and MS (IFIH1-rs3747517 and IFIH1-rs1990760 trend test: P=0.002 and P=0.014, respectively).

The genetic contribution to non-syndromic human obesity

The last few years have seen major advances in common non-syndromic obesity research, much of it the result of genetic studies. This Review outlines the competing hypotheses about the mechanisms underlying the genetic and physiological basis of obesity, and then examines the recent explosion of genetic association studies that have yielded insights into obesity, both at the candidate gene level and the genome-wide level. With obesity genetics now entering the post-genome-wide association scan era, the obvious question is how to improve the results obtained so far using single nucleotide polymorphism markers and how to move successfully into the other areas of genomic variation that may be associated with common obesity.

Exploring the unknown: assumptions about allelic architecture and strategies for susceptibility variant discovery

Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.

IFIH1 gene polymorphisms in type 1 diabetes: genetic association analysis and genotype-phenotype correlation in the Belgian population

The evaluation of susceptibility loci in a registry-based setting could be an important addition to the current predictive and screening models in T1D. Therefore, the aim of this study was to evaluate the importance of one of these loci, IFIH1. T1D patients (n=1981), control subjects (n=2092) and 430 families were genotyped for HLA-DQ and IFIH1 nsSNP rs1990760 (Ala946Thr). In the association analysis, the allelic frequencies, A (62.4% vs. 61.3%) and G (37.6% vs. 38.7%) were similar in cases and controls (chi(2) = 0.98, p = 0.32), the genotypic frequencies reveals a weak association with T1D (chi(2) = 6.79, p = 0.03), no significant transmission distortions in families (%T; A = 51.4%, G = 48.0 %, chi(2) = 1.76, p = 0.19) and no interaction with HLA-DQ-linked risk. Furthermore, no genotype-phenotype correlation was observed. In conclusion, IFIH1 has no important role in T1D risk assessment in a registry-based Belgian population.

Connections between antiviral defense and autoimmunity

Recent advances have revealed a fundamental contradiction in antiviral immunity: innate immune sensors that detect nucleic acids mediate both protective immunity to infection and pathological autoimmune disease. Thus, the study of the mechanics of nucleic acid detection will provide insight into how these systems are inappropriately triggered in autoimmunity, and, conversely, the study of autoimmune disease triggered by these sensors will tell us more about how they are linked to activation of adaptive immunity.

Common vs. rare allele hypotheses for complex diseases

There has been growing debate over the nature of the genetic contribution to individual susceptibility to common complex diseases such as diabetes, osteoporosis, and cancer. The 'Common Disease, Common Variant (CDCV)' hypothesis argues that genetic variations with appreciable frequency in the population at large, but relatively low 'penetrance' (or the probability that a carrier of the relevant variants will express the disease), are the major contributors to genetic susceptibility to common diseases. The 'Common Disease, Rare Variant (CDRV)' hypothesis, on the contrary, argues that multiple rare DNA sequence variations, each with relatively high penetrance, are the major contributors to genetic susceptibility to common diseases. Both hypotheses have their place in current research efforts.

Molecular genetics of atrial fibrillation

Atrial fibrillation (AF) is the most common persistent cardiac dysrhythmia and the number one cause of arrhythmia-related hospitalizations. In addition, AF is a major contributor to stroke. With life expectancies increasing, the growing global disability from AF has crippling implications for society. Several family studies have shown a strong polygenetic predisposition for AF but, so far, most of the linkage analysis and candidate gene studies have discovered only monogenic, rare, deleterious mutations. Recent breakthroughs in high-throughput genotyping technology have allowed improved scanning of the genome with greater statistical power to detect susceptibility alleles for AF. Using this technology, a region on 4q25 has now been identified and validated in thousands of cases as a common susceptibility factor for AF with an odds ratio of over 3.0 for homozygotes. The Paired-like homeodomain transcription factor 2 (PITX2) gene, which is involved in embryonic cardiac development, has now been identified as the causal variant for the 4q25 susceptibility locus. Additional susceptibility variants are anticipated that will have direct ramifications for prognosis and treatment of this highly pervasive and clinically significant disorder.

Identification of loss of function mutations in human genes encoding RIG-I and MDA5: implications for resistance to type I diabetes

Retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated gene 5 (MDA5) are essential for detecting viral RNA and triggering antiviral responses, including production of type I interferon. We analyzed the phenotype of non-synonymous mutants of human RIG-I and MDA5 reported in databases by functional complementation in cell cultures. Of seven missense mutations of RIG-I, S183I, which occurs within the second caspase recruitment domain repeat, inactivated this domain and conferred a dominant inhibitory function. Of 10 mutants of MDA5, two exhibited loss of function. A nonsense mutation, E627*, resulted in deletion of the C-terminal region and double-stranded RNA (dsRNA) binding activity. Another loss of function mutation, I923V, which occurs within the C-terminal domain, did not affect dsRNA binding activity, suggesting a novel and essential role for this residue in the signaling. Remarkably, these mutations are implicated in resistance to type I diabetes. However, the A946T mutation of MDA5, which has been implicated in type I diabetes by previous genetic analyses, affected neither dsRNA binding nor IFN gene activation. These results provide new insights into the structure-function relationship of RIG-I-like receptors as well as into human RIG-I-like receptor polymorphisms, antiviral innate immunity, and autoimmune diseases.