Genetic liability of type 1 diabetes and the onset age among 22,650 young Finnish twin pairs: a nationwide follow-up study

"My parents died of myocardial infarction: is that my destiny?"

This article presents an overview of clinical and molecular genetics of myocardial infarction (MI). Discussion includes the partial overlapping of risk factors for myocardial infarction and atherosclerosis, the impact of a positive family history on the risk of MI, the "familial" nongenetic, environmental factors, the inherited risk associated with the low-dose input of many genes, and a simple approach to stratify the individual risk in genetic counseling.

Twin studies in autoimmune disease: genetics, gender and environment

Twin studies are powerful tools to discriminate whether a complex disease is due to genetic or environmental factors. High concordance rates among monozygotic (MZ) twins support genetic factors being predominantly involved, whilst low rates are suggestive of environmental factors. Twin studies have often been utilised in the study of systemic and organ specific autoimmune diseases. As an example, type I diabetes mellitus has been investigated to establish that that disease is largely affected by genetic factors, compared to rheumatoid arthritis or scleroderma, which have a weaker genetic association. However, large twin studies are scarce or virtually non-existent in other autoimmune diseases which have been limited to few sets of twins and individual case reports. In addition to the study of the genetic and environmental contributions to disease, it is likely that twin studies will also provide data in regards to the clinical course of disease, as well as risk for development in related individuals. More importantly, genome-wide association studies have thus far reported genomic variants that only account for a minority of autoimmunity cases, and cannot explain disease discordance in MZ twins. Future research is therefore encouraged not only in the analysis of twins with autoimmune disease, but also in regards to epigenetic factors or rare variants that may be discovered with next-generation sequencing. This review will examine the literature surrounding twin studies in autoimmune disease including discussions of genetics and gender.

Abnormal DNA methylation in CD4+ T cells from people with latent autoimmune diabetes in adults

Aberrant DNA methylation in T cells has been linked to pathogenesis of autoimmune diseases. To investigate genomic and gene-specific DNA methylation levels in CD4(+) T cells from patients with latent autoimmune diabetes in adults (LADA), and to investigate changes in the expression of genes that regulate methylation as well as the autoimmune-related gene FOXP3 in these patients. Global CD4(+) T cell DNA methylation was measured in 15 LADA patients and 11 healthy controls using a methylation quantification kit. mRNA levels of DNA methytransferases (DNMTs), methyl-DNA binding domain proteins (MBDs) and FOXP3 were measured by real time PCR. Methylation of a FOXP3 regulatory element region was determined by bisulphite genomic sequencing. Genomic DNA methylation in CD4(+) T cells from LADA patients was significantly increased compared to controls. DNMT3b mRNA levels were higher in CD4(+) T cells from LADA patients than in controls. DNMT3b expression positively correlated with global DNA methylation in LADA CD4(+) T cells. FOXP3 expression was decreased, and the FOXP3 promoter region was hypermethylated in CD4(+) T cells from LADA patients compared with controls. DNA methylation levels are altered in CD4(+) T cells from LADA patients, which may contribute to disease onset and progression by affecting the expression of autoimmune-related genes.

Beyond the hormone: insulin as an autoimmune target in type 1 diabetes

Insulin is not only the hormone produced by pancreatic β-cells but also a key target antigen of the autoimmune islet destruction leading to type 1 diabetes. Despite cultural biases between the fields of endocrinology and immunology, these two facets should not be regarded separately, but rather harmonized in a unifying picture of diabetes pathogenesis. There is increasing evidence suggesting that metabolic factors (β-cell dysfunction, insulin resistance) and immunological components (inflammation and β-cell-directed adaptive immune responses) may synergize toward islet destruction, with insulin standing at the crossroad of these pathways. This concept further calls for a revision of the classical dichotomy between type 1 and type 2 diabetes because metabolic and immune mechanisms may both contribute to different extents to the development of different forms of diabetes. After providing a background on the mechanisms of β-cell autoimmunity, we will explain the role of insulin and its precursors as target antigens expressed not only by β-cells but also in the thymus. Available knowledge on the autoimmune antibody and T-cell responses against insulin will be summarized. A unifying scheme will be proposed to show how different aspects of insulin biology may lead to β-cell destruction and may be therapeutically exploited. We will argue about possible reasons why insulin remains the mainstay of metabolic control in type 1 diabetes but has so far failed to prevent or halt β-cell autoimmunity as an immune modulatory reagent.

Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis

Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ∼50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14⁺ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D–discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D–associated methylation variable positions (T1D–MVPs). We confirmed these T1D–MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D–discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D–MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D–MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D–MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease.

Type 1 diabetes (T1D) is a complex autoimmune disease affecting >30 million people worldwide. It is caused by a combination of genetic and non-genetic factors, leading to destruction of insulin-secreting cells. Although significant progress has recently been made in elucidating the genetics of T1D, the non-genetic component has remained poorly defined. Epigenetic modifications, such as methylation of DNA, are indispensable for genomic processes such as transcriptional regulation and are frequently perturbed in human disease. We therefore hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology, and we performed a genome-wide DNA methylation analysis of a specific subset of immune cells (monocytes) from monozygotic twins discordant for T1D. This revealed the presence of T1D–specific methylation variable positions (T1D–MVPs) in the T1D–affected co-twins. Since these T1D–MVPs were found in MZ twins, they cannot be due to genetic differences. Additional experiments revealed that some of these T1D–MVPs are found in individuals before T1D diagnosis, suggesting they arise very early in the process that leads to overt T1D and are not simply due to post-disease associated factors (e.g. medication or long-term metabolic changes). T1D–MVPs may thus potentially represent a previously unappreciated, and important, component of type 1 diabetes risk.

Gut microbiota, immunity, and disease: a complex relationship

Our immune system has evolved to recognize and eradicate pathogenic microbes. However, we have a symbiotic relationship with multiple species of bacteria that occupy the gut and comprise the natural commensal flora or microbiota. The microbiota is critically important for the breakdown of nutrients, and also assists in preventing colonization by potentially pathogenic bacteria. In addition, the gut commensal bacteria appear to be critical for the development of an optimally functioning immune system. Various studies have shown that individual species of the microbiota can induce very different types of immune cells (e.g., Th17 cells, Foxp3(+) regulatory T cells) and responses, suggesting that the composition of the microbiota can have an important influence on the immune response. Although the microbiota resides in the gut, it appears to have a significant impact on the systemic immune response. Indeed, specific gut commensal bacteria have been shown to affect disease development in organs other than the gut, and depending on the species, have been found to have a wide range of effects on diseases from induction and exacerbation to inhibition and protection. In this review, we will focus on the role that the gut microbiota plays in the development and progression of inflammatory/autoimmune disease, and we will also touch upon its role in allergy and cancer.

Selective IgA deficiency in autoimmune diseases

Selective immunoglobulin A deficiency (IgAD) is the most common primary immunodeficiency in Caucasians. It has previously been suggested to be associated with a variety of concomitant autoimmune diseases. In this review, we present data on the prevalence of IgAD in patients with Graves disease (GD), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), celiac disease (CD), myasthenia gravis (MG) and rheumatoid arthritis (RA) on the basis of both our own recent large-scale screening results and literature data. Genetic factors are important for the development of both IgAD and various autoimmune disorders, including GD, SLE, T1D, CD, MG and RA, and a strong association with the major histocompatibility complex (MHC) region has been reported. In addition, non-MHC genes, such as interferon-induced helicase 1 (IFIH1) and c-type lectin domain family 16, member A (CLEC16A), are also associated with the development of IgAD and some of the above diseases. This indicates a possible common genetic background. In this review, we present suggestive evidence for a shared genetic predisposition between these disorders.

Autoimmunity and inflammation: murine models and translational studies

Autoimmune and inflammatory diseases, including type 1 diabetes, multiple sclerosis, inflammatory bowel disease, and rheumatoid arthritis, constitute an important and growing public health burden. However, in many cases our understanding of disease biology is limited and available therapies vary greatly in their efficacy and safety. Animal models of autoimmune and inflammatory diseases have provided valuable tools to researchers investigating their aetiology, pathology, and novel therapeutic strategies. Although such models vary in the degree to which they reflect human autoimmune and inflammatory diseases and caution is required in the extrapolation of animal data to the clinical setting, therapeutic approaches first evaluated in established animal models, including collagen-induced arthritis, experimental autoimmune encephalomyelitis, and the nonobese diabetic mouse, have successfully progressed to clinical investigation and practice. Similarly, these models have proven useful in providing support for basic hypotheses regarding the underlying causes and pathology of autoimmune and inflammatory diseases. Here we review selected murine models of autoimmunity and inflammation and efforts to translate findings from these models into both basic insights into disease biology and novel therapeutic strategies.

Utilizing twins concordance rates to infer the predisposition to myasthenia gravis

Myasthenia gravis (MG) is an autoimmune disorder in which patients experience muscular fatigability due to the presence of anti-acetylcholine receptor (AChR) antibodies which inhibit signal transduction across the neuro-muscular junction. Like all complex disorders, disease is caused by an interaction between genetic and environmental factors. Although several genes have been identified which appear to be associated with MG, both classic twin studies and current multi-gene models are insufficient to explain either disease pathogenesis or inheritance. We examined the literature on MG to determine both mono- and dizygotic twin concordance rates, and used this data to (1) estimate the proportion of the population with underlying genetic predisposition to MG and the frequency of the environmental component and (2) derive the number of inherited genetic regions that are required to confer predisposition to MG. Using a MZ twin concordance rate of 35.5%, and a dizygotic rate of approximately 4-5% (based on family data), the probability of encountering environmental components necessary to develop MG in an individual with genetic predisposition is approximately 52.4%, making the frequency of predisposition (1:5240) roughly twice the rate of incidence. Furthermore, the number of genetic regions co-inherited between affected individuals is between two and four, which may be large haplotypes with interacting activity. Determining these haplotypes, by fully sequencing associated regions in cases and controls to identify mutations present, may therefore be a practically step toward the understanding of complex disease.

Genome-virome interactions: examining the role of common viral infections in complex disease

New technologies have widened our view of 'complex diseases': those with both genetic and environmental risk factors. In this Review, we explore recent genetic and virological evidence implicating host-virus interactions in three diseases: type 1 diabetes, inflammatory bowel disease and asthma. The viruses implicated in these diseases cause mucosal infections that affect most of the population but are asymptomatic or mild in many hosts. These findings place a new emphasis on common viral infections as important environmental factors in the pathogenesis of complex diseases, and they compel the field to pursue a better understanding of host interactions with the human virome.

Receptor for advanced glycation end-products (RAGE) provides a link between genetic susceptibility and environmental factors in type 1 diabetes

AIMS/HYPOTHESIS

This group of studies examines human genetic susceptibility conferred by the receptor for advanced glycation end-products (RAGE) in type 1 diabetes and investigates how this may interact with a western environment.

METHODS

We analysed the AGER gene, using 13 tag SNPs, in 3,624 Finnish individuals from the FinnDiane study, followed by AGER associations with a high risk HLA genotype (DR3)-DQA1*05-DQB1*02/DRB1*0401-DQB1*0302 (n = 546; HLA-DR3/DR4), matched in healthy newborn infants from the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study (n = 373) using allelic analysis. We also studied islets and circulating RAGE in NODLt mice.

RESULTS

The rs2070600 and rs17493811 polymorphisms predicted increased risk of type 1 diabetes, whereas the rs9469089 SNP was related to decreased risk, on a high risk HLA background. Children from the DIPP study also showed a decline in circulating soluble RAGE levels, at seroconversion to positivity for type 1 diabetes-associated autoantibodies. Islet RAGE and circulating soluble RAGE levels in prediabetic NODLt mice decreased over time and were prevented by the AGE lowering therapy alagebrium chloride. Alagebrium chloride also decreased the incidence of autoimmune diabetes and restored islet RAGE levels.

CONCLUSIONS/INTERPRETATION

These studies suggest that inherited AGER gene polymorphisms may confer susceptibility to environmental insults. Declining circulating levels of soluble RAGE, before the development of overt diabetes, may also be predictive of clinical disease in children with high to medium risk HLA II backgrounds and this possibility warrants further investigation in a larger cohort.

Protection against or triggering of Type 1 diabetes? Different roles for viral infections

The emergence of autoreactivity that ultimately destroys insulin-producing β-cells and causes Type 1 diabetes (T1D) is a result of genetic susceptibility and environmental factors, such as viral infections. The ability to induce strong cellular immune responses and to cause inflammation in the target organ makes viral infections prime candidates for the initiation of islet autoreactivity. Indeed, certain viruses have been linked to the occurrence of T1D based on epidemiological, serological and histological findings; and several rodent studies clearly demonstrate that viral infections can trigger autoimmunity. However, viruses have also been shown to efficiently prevent autoimmunity, which underlines the beneficial aspects of exposure to microbial agents as suggested by the hygiene hypothesis. Here, we will try to untangle some aspects of the complex interplay between viruses and the immune system and we will recapitulate by what rationale certain viruses have been associated with T1D.

Estimating missing heritability for disease from genome-wide association studies

Genome-wide association studies are designed to discover SNPs that are associated with a complex trait. Employing strict significance thresholds when testing individual SNPs avoids false positives at the expense of increasing false negatives. Recently, we developed a method for quantitative traits that estimates the variation accounted for when fitting all SNPs simultaneously. Here we develop this method further for case-control studies. We use a linear mixed model for analysis of binary traits and transform the estimates to a liability scale by adjusting both for scale and for ascertainment of the case samples. We show by theory and simulation that the method is unbiased. We apply the method to data from the Wellcome Trust Case Control Consortium and show that a substantial proportion of variation in liability for Crohn disease, bipolar disorder, and type I diabetes is tagged by common SNPs.

Progress and promise of genome-wide association studies for human complex trait genetics

Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.

Function and regulation of retinoic acid-inducible gene-I

Antiviral innate immunity is triggered by sensing viral nucleic acids. RIG-I (retinoic acid-inducible gene-I) is an intracellular molecule that responds to viral nucleic acids and activates downstream signaling, resulting in the induction of members of the type I interferon (IFN) family, which are regarded among the most important effectors of the innate immune system. Although RIG-I is expressed ubiquitously in the cytoplasm, its levels are subject to transcriptional and post-transcriptional regulation. RIG-I belongs to the IFN-stimulated gene (ISG) family, but certain cells regulate its expression through IFN-independent mechanisms. Several lines of evidence indicate that deregulated RIG-I signaling is associated with autoimmune disorders. Further studies suggest that RIG-I has functions in addition to those directly related to its role in RNA sensing and host defense. We have much to learn and discover regarding this interesting cytoplasmic sensor so that we can capitalize on its properties for the treatment of viral infections, immune disorders, cancer, and perhaps other conditions.

The three ZNT8 autoantibody variants together improve the diagnostic sensitivity of childhood and adolescent type 1 diabetes

AIMS

We tested whether autoantibodies to all three ZnT8RWQ variants, GAD65, insulinoma-associated protein 2 (IA-2), insulin and autoantibodies to islet cell cytoplasm (ICA) in combination with human leukocyte antigen (HLA) would improve the diagnostic sensitivity of childhood type 1 diabetes by detecting the children who otherwise would have been autoantibody-negative.

METHODS

A total of 686 patients diagnosed in 1996-2005 in Skåne were analyzed for all the seven autoantibodies [arginin 325 zinc transporter 8 autoantibody (ZnT8RA), tryptophan 325 zinc transporter 8 autoantibody (ZnT8WA), glutamine 325 Zinc transporter 8 autoantibody (ZnT8QA), autoantibodies to glutamic acid decarboxylase (GADA), Autoantibodies to islet-antigen-2 (IA-2A), insulin autoantibodies (IAA) and ICA] in addition to HLA-DQ genotypes.

RESULTS

Zinc transporter 8 autoantibody to either one or all three amino acid variants at position 325 (ZnT8RWQA) was found in 65% (449/686) of the patients. The frequency was independent of age at diagnosis. The ZnT8RWQA reduced the frequency of autoantibody-negative patients from 7.5 to 5.4%-a reduction by 28%. Only 2 of 108 (2%) patients who are below 5 years of age had no autoantibody at diagnosis. Diagnosis without any islet autoantibody increased with increasing age at onset. DQA1-B1(*)X-0604 was associated with both ZnT8RA (p = 0.002) and ZnT8WA (p = 0.01) but not with ZnT8QA (p = 0.07). Kappa agreement analysis showed moderate (>0.40) to fair (>0.20) agreement between pairs of autoantibodies for all combinations of GADA, IA-2A, ZnT8RWQA and ICA but only slight ( < 0.19) agreement for any combination with IAA.

CONCLUSIONS

This study revealed that (1) the ZnT8RWQA was common, independent of age; (2) multiple autoantibodies were common among the young; (3) DQA1-B1(*)X-0604 increased the risk for ZnT8RA and ZnT8WA; (4) agreement between autoantibody pairs was common for all combinations except IAA. These results suggest that ZnT8RWQA is a necessary complement to the classification and prediction of childhood type 1 diabetes as well as to randomize the subjects in the prevention and intervention of clinical trials.

Genetics of type 1 diabetes

BACKGROUND

Type 1 diabetes, a multifactorial disease with a strong genetic component, is caused by the autoimmune destruction of pancreatic β cells. The major susceptibility locus maps to the HLA class II genes at 6p21, although more than 40 non-HLA susceptibility gene markers have been confirmed.

CONTENT

Although HLA class II alleles account for up to 30%-50% of genetic type 1 diabetes risk, multiple non-MHC loci contribute to disease risk with smaller effects. These include the insulin, PTPN22, CTLA4, IL2RA, IFIH1, and other recently discovered loci. Genomewide association studies performed with high-density single-nucleotide-polymorphism genotyping platforms have provided evidence for a number of novel loci, although fine mapping and characterization of these new regions remain to be performed. Children born with the high-risk genotype HLADR3/4-DQ8 comprise almost 50% of children who develop antiislet autoimmunity by the age of 5 years. Genetic risk for type 1 diabetes can be further stratified by selection of children with susceptible genotypes at other diabetes genes, by selection of children with a multiple family history of diabetes, and/or by selection of relatives that are HLA identical to the proband.

SUMMARY

Children with the HLA-risk genotypes DR3/4-DQ8 or DR4/DR4 who have a family history of type 1 diabetes have more than a 1 in 5 risk for developing islet autoantibodies during childhood, and children with the same HLA-risk genotype but no family history have approximately a 1 in 20 risk. Determining extreme genetic risk is a prerequisite for the implementation of primary prevention trials, which are now underway for relatives of individuals with type 1 diabetes.

Genome-wide analysis of copy number variation in type 1 diabetes

Type 1 diabetes (T1D) tends to cluster in families, suggesting there may be a genetic component predisposing to disease. However, a recent large-scale genome-wide association study concluded that identified genetic factors, single nucleotide polymorphisms, do not account for overall familiality. Another class of genetic variation is the amplification or deletion of >1 kilobase segments of the genome, also termed copy number variations (CNVs). We performed genome-wide CNV analysis on a cohort of 20 unrelated adults with T1D and a control (Ctrl) cohort of 20 subjects using the Affymetrix SNP Array 6.0 in combination with the Birdsuite copy number calling software. We identified 39 CNVs as enriched or depleted in T1D versus Ctrl. Additionally, we performed CNV analysis in a group of 10 monozygotic twin pairs discordant for T1D. Eleven of these 39 CNVs were also respectively enriched or depleted in the Twin cohort, suggesting that these variants may be involved in the development of islet autoimmunity, as the presently unaffected twin is at high risk for developing islet autoimmunity and T1D in his or her lifetime. These CNVs include a deletion on chromosome 6p21, near an HLA-DQ allele. CNVs were found that were both enriched or depleted in patients with or at high risk for developing T1D. These regions may represent genetic variants contributing to development of islet autoimmunity in T1D.

Type-specific human papillomavirus detection in cervical smears in Romania

To study type 1 diabetes (T1D), excellent animal models exist, both spontaneously diabetic and virus-induced. Based on knowledge from these, this review focuses on the environmental factors leading to T1D, concentrated into four areas which are: (1) The thymus-dependent immune system: T1D is a T cell driven disease and the beta cells are destroyed in an inflammatory insulitis process. Autoimmunity is breakdown of self-tolerance and the balance between regulator T cells and aggressive effector T cells is disturbed. Inhibition of the T cells (by e.g. anti-CD3 antibody or cyclosporine) will stop the T1D process, even if initiated by virus. Theoretically, the risk from immunotherapy elicits a higher frequency of malignancy. (2) The activity of the beta cells: Resting beta cells display less antigenicity and are less sensitive to immune destruction. Beta-cell rest can be induced by giving insulin externally in metabolic doses or by administering potassium-channel openers. Both procedures prevent T1D in animal models, whereas no good human data exist due to the risk of hypoglycemia. (3) NKT cells: According to the hygiene hypothesis, stimulation of NKT cells by non-pathogen microbes gives rise to less T cell reaction and less autoimmunity. Glycolipids presented by CD1 molecules are central in this stimulation. (4) Importance of the intestine and gliadin intake: Gluten-free diet dramatically inhibits T1D in animal models, and epidemiological data are supportive of such an effect in humans. The mechanisms include less subclinical intestinal inflammation and permeability, and changed composition of bacterial flora, which can also be obtained by intake of probiotics. Gluten-free diet is difficult to implement, and short-term intake has no effect. Regarding the onset of the T1D disease process, slow-acting enterovirus and gliadin deposits are speculated to be etiological in genetically susceptible individuals, followed by the mentioned four pathogenetic factors acting in concert. Neutralization of any one of these factors is capable of stopping T1D development, as lessons are learned from the animal models.

An epidemiological perspective on the future of direct-to-consumer personal genome testing

Personal genome testing is offered via the internet directly to consumers. Most tests that are currently offered use data from genome-wide scans to predict risks for multiple common diseases and traits. The utility of these tests is limited, predominantly because they lack predictive ability and clear benefits for disease prevention that are specific for genetic risk groups. In the near future, personal genome tests will likely be based on whole genome sequencing, but will these technological advances increase the utility of personal genome testing? Whole genome sequencing theoretically provides information about the risks of both monogenic and complex diseases, but the practical utility remains to be demonstrated. The utility of testing depends on the predictive ability of the test, the likelihood of actionable test results, and the options available for the reduction of risks. For monogenic diseases, the likelihood of known mutations will be extremely low in the general population and it will be a challenge to recognize new causal variants among all rare variants that are found using sequencing. For complex diseases, the predictive ability of genetic tests will be mainly restricted by the heritability of the disease, but also by the genetic complexity of the disease etiology, which determines the extent to which the heritability can be understood. Given that numerous genetic and non-genetic risk factors interact in the causation of complex diseases, the predictive ability of genetic models will likely remain modest. Personal genome testing will have minimal benefits for individual consumers unless major breakthroughs are made in the near future.

Dietary iron intake in the first 4 months of infancy and the development of type 1 diabetes: a pilot study

AIMS

To investigate the impact of iron intake on the development of type 1 diabetes (T1DM).

METHODS

Case-control study with self-administered questionnaire among families of children with T1DM who were less than 10 years old at the time of the survey and developed diabetes between age 1 and 6 years. Data on the types of infant feeding in the first 4 months of life was collected from parents of children with T1DM (n = 128) and controls (n = 67) <10 years old. Because some cases had sibling controls, we used conditional logistic regression models to analyze the data in two ways. First we performed a case-control analysis of all 128 cases and 67 controls. Next, we performed a case-control analysis restricted to cases (n = 59) that had a sibling without diabetes (n = 59). Total iron intake was modeled as one standard deviation (SD) increase in iron intake. The SD for iron intake was 540 mg in the total sample and 539 mg in the restricted sample as defined above.

RESULTS

The median (min, max) total iron intake in the first 4 months of life was 1159 (50, 2399) mg in T1DM cases and 466 (50, 1224) mg among controls (P < 0.001). For each one standard deviation increase in iron intake, the odds ratio (95% confidence interval) for type 1 diabetes was 2.01 (1.183, 3.41) among all participants (128 cases and 67 controls) while it was 2.26 (1.27, 4.03) in a restricted sample of T1 D cases with a control sibling (59 cases and 59 controls) in models adjusted for birth weight, age at the time of the survey, and birth order.

CONCLUSION

In this pilot study, high iron intake in the first 4 months of infancy is associated with T1DM. Whether iron intake is causal or a marker of another risk factor warrants further investigation.

Synthetic associations in the context of genome-wide association scan signals

Genome-wide association studies (GWAS) have successfully identified a large number of genetic variants associated with complex traits, but these only explain a small proportion of the total heritability. It has been recently proposed that rare variants can create 'synthetic association' signals in GWAS, by occurring more often in association with one of the alleles of a common tag single nucleotide polymorphism. While the ultimate evaluation of this hypothesis will require the completion of large-scale sequencing studies, it is informative to place it in the broader context of what is known about the genetic architecture of complex disease. In this review, we draw from empirical and theoretical data to summarize evidence showing that synthetic associations do not underlie many reported GWAS associations.

T-cell regulation by casitas B-lineage lymphoma (Cblb) is a critical failsafe against autoimmune disease due to autoimmune regulator (Aire) deficiency

Autoimmune polyendocrinopathy syndrome type 1 (APS1) results from homozygous Aire mutations that cripple thymic deletion of organ-specific T cells. The clinical course in man and mouse is characterized by high variability both in the latent period before onset of autoimmune disease and in the specific organs affected, but the reasons for this are unknown. Here we test the hypothesis that the latent period reflects the failsafe action of discrete postthymic mechanisms for imposing self-tolerance in peripheral T cells. Aire-deficient mice were crossed with mice of a uniform major histocompatibility complex (MHC) haplotype and genetic background carrying specific genetic defects in one of four distinct peripheral tolerance mechanisms: activation-induced cell death (Fasl(gld/gld)), anergy and requirement for CD28 costimulation (Cblb(-/-)), inhibition of ICOS and T(FH) cells (Rc3h1(san/san)), or decreased numbers of Foxp3(+) T regulatory cells (Card11(unm/unm)). Cblb-deficiency was unique among these four in precipitating rapid clinical autoimmune disease when combined with Aire-deficiency, resulting in autoimmune exocrine pancreatitis with median age of survival of only 25 d. Massive lymphocytic infiltration selectively destroyed most of the exocrine acinar cells of the pancreas and submandibular salivary gland, and CD4(+) and CD8(+) subsets were necessary and sufficient to transfer the disease. Intrinsic regulation of peripheral T cells by CBL-B thus serves a uniquely critical role as a failsafe against clinical onset of autoimmune disease in AIRE deficiency, and multiple peripheral tolerance mechanisms may need to fail before onset of clinical autoimmunity to many organs.

HLA-DR genotypes influence age at disease onset in children and juveniles with type 1 diabetes mellitus

OBJECTIVE

To investigate HLA-DR genotype in association with chronological age or calendar year of disease onset and the time trend of genotype frequencies from 1969 to 2009. Additionally, to examine genotype frequency in relation to B-cell-, islet cell antibodies (ICA)-, autoantibodies to insulin-, insulinoma antigen 2 (IA2)-, glutamic acid decarboxylase-antibody positivity, thyroid antibody positivity, thyroid diseases or coeliac antibody positivity. Genotype associations with gender and ethnicity are also analyzed.

SUBJECTS AND METHODS

HLA-typed children and juveniles (n=1445) aged <or=20 years at disease onset from the German/Austrian DPV-database were examined. chi(2) statistics and mixed hierarchical logistic regression models were used to compare genotype frequencies and establish associations with age at disease manifestation, autoimmune antibodies/diseases, ethnicity and time trend.

RESULTS

Subjects aged <6 years predominantly carried the genotype HLA-DR3/4 (25.2%), whereas in subjects aged >12 years the most prevalent HLA-DR genotype was X/X (18.1%). IA2 positivity was associated with HLA-DR4/X and HLA-DR3/4 positivity (P=0.011), and hypothyroidism was linked to HLA-DR4/4 (P=0.0103). More females carried the HLA-DR4/4 genotype (18.2 vs 12.7% P=0.0048) or were thyroid antibody positive (24.5 vs 14.7% P=0.0001). Larger numbers of <6 year olds were coeliac antibody positive than >12 year olds (14.8 vs 9.1% P=0.0037). No associations between migration background and B-cell-, thyroid- or coeliac-antibody positivity, and no time trend were found.

CONCLUSION

HLA-DR genotype associated with age at disease onset, ICA positivity and hypothyroidism; female gender with thyroid antibody positivity and low age of diabetes onset with coeliac antibody positivity.

Mycobacterium avium subsp. paratuberculosis as a trigger of type-1 diabetes: destination Sardinia, or beyond?

Type 1 diabetes mellitus (T1DM) is a multifactorial autoimmune disease in which the insulin producing beta cell population is destroyed by the infiltrated T lymphocytes. Even though the exact cause of T1DM is yet to be ascertained, varying degree of genetic susceptibility and environmental factors have been linked to the disease progress and outcome. Mycobacterium avium subsp. paratuberculosis (MAP) is an obligate zoonotic pathogen that causes chronic infection of intestines in ruminants, the Johne's disease. MAP that can even survive pasteurization and chlorination has also been implicated to cause similar type of enteritis in humans called Crohn's disease. With the increasing recognition of the link between MAP and Crohn's disease, it has been postulated that MAP is an occult antigen which besides Crohn's could as well be thought to trigger T1DM. Epitope homologies between mycobacterial proteins (Hsp 65) and pancreatic glutamic acid decarboxylase (GAD 65) and infant nutrition studies implicate MAP as one of the triggers for T1DM. PCR and ELISA analyses in diabetic patients from Sardinia suggest that MAP acts as a possible trigger for T1DM. Systematic mechanistic insights are needed to prove this link. Unfortunately, no easy animal model(s) or in-vitro systems are available to decipher the complex immunological network that is triggered in MAP infection leading to T1DM.

The genetic interpretation of area under the ROC curve in genomic profiling

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator.

Genome-wide association studies in human populations have facilitated the creation of genomic profiles that combine the effects of many associated genetic variants to predict risk of disease. However, genomic profiles are inherently constrained in their ability to classify diseased from non-diseased individuals dictated by the genetic epidemiology of the disease. In this paper, we use a genetic interpretation to provide insight into the constraints on genomic profiles for risk prediction. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability available as an online calculator.

Multi-locus models of genetic risk of disease

Background

Evidence for genetic contribution to complex diseases is described by recurrence risks to relatives of diseased individuals. Genome-wide association studies allow a description of the genetics of the same diseases in terms of risk loci, their effects and allele frequencies. To reconcile the two descriptions requires a model of how risks from individual loci combine to determine an individual's overall risk.

Methods

We derive predictions of risk to relatives from risks at individual loci under a number of models and compare them with published data on disease risk.

Results

The model in which risks are multiplicative on the risk scale implies equality between the recurrence risk to monozygotic twins and the square of the recurrence risk to sibs, a relationship often not observed, especially for low prevalence diseases. We show that this theoretical equality is achieved by allowing impossible probabilities of disease. Other models, in which probabilities of disease are constrained to a maximum of one, generate results more consistent with empirical estimates for a range of diseases.

Conclusions

The unconstrained multiplicative model, often used in theoretical studies because of its mathematical tractability, is not a realistic model. We find three models, the constrained multiplicative, Odds (or Logit) and Probit (or liability threshold) models, all fit the data on risk to relatives. Currently, in practice it would be difficult to differentiate between these models, but this may become possible if genetic variants that explain the majority of the genetic variance are identified.

Genetic overlap between autism, schizophrenia and bipolar disorder

There is strong evidence that genetic factors make substantial contributions to the etiology of autism, schizophrenia and bipolar disorders, with heritability estimates being at least 80% for each. These illnesses have complex inheritance, with multiple genetic and environmental factors influencing disease risk; however, in psychiatry, complex genetics is further compounded by phenotypic complexity. Autism, schizophrenia and bipolar disorder are effectively syndromic constellations of symptoms that define groups of patients with broadly similar outcomes and responses to treatment. As such the diagnostic categories are likely to be heterogeneous and the boundaries between them somewhat arbitrary. Recent applications of whole-genome technologies have discovered rare copy number variants and common single-nucleotide polymorphisms that are associated with risk of developing these disorders. Furthermore, these studies have shown an overlap between the genetic loci and even alleles that predispose to the different phenotypes. The findings have several implications. First, they show that copy number variations are likely to be important risk factors for autism and schizophrenia, whereas common single-nucleotide polymorphism alleles have a role in all disorders. Second, they imply that there are specific genetic loci and alleles that increase an individual's risk of developing any of these disorders. Finally, the findings suggest that some of the specific genetic loci implicated so far encode proteins, such as neurexins and neuroligins, that function in synaptic development and plasticity, and therefore may represent a common biological pathway for these disorders.

Sporadic cases are the norm for complex disease

The results of genome-wide association studies have revealed that most human complex diseases (for example, cancer, diabetes and psychiatric disorders) are affected by a large number of variants, each of which explains a small increase in disease risk, suggesting a pattern of polygenic inheritance. At the same time, it has been argued that most complex diseases are genetically heterogeneous because many sporadic cases are observed, as well as cases with a family history. In this study, under the assumption of polygenic inheritance, we derive the expected proportion of sporadic cases using analytical methods and simulation. We show how the proportion of sporadic cases depends on disease prevalence (K) and heritability on the underlying liability scale (h(L)(2)). We predict the underlying heritability and the proportion of sporadic cases for a range of human complex diseases, and show that this proportion is typically large. For a disease with h(L)(2)=63% and K=0.4%, such as schizophrenia, >83% of proband cases are predicted to be sporadic (no affected first-, second- and third-degree relatives) in typical families (on an average, two children per couple). For the majority of these diseases, a large proportion of sporadic cases is expected under the polygenic model, implying that the observed large proportion of sporadic cases is not informative to the causal mechanism of a complex genetic disease.

From disease association to risk assessment: an optimistic view from genome-wide association studies on type 1 diabetes

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of approximately 0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays.

Strategies to prevent type 1 diabetes

Type 1 diabetes is a chronic autoimmune condition resulting from T cell-mediated destruction of the insulin-producing cells in the islets of Langerhans. Its primary cause remains unknown, but it has been established that the clinical presentation is preceded by a long prodrome. This enables individuals at high risk of disease to be identified and offers the possibility of intervention to prevent clinical disease. Many groups are working in this field, concentrating on manipulation of environmental exposures that are potential triggers of autoimmunity and on immunomodulation strategies that aim to prevent destruction of beta-cells. Some interventions have shown promising results in early trials, but effective disease prevention remains elusive. This article reviews current progress in the field.

Familial association between type 1 diabetes and other autoimmune and related diseases

AIMS/HYPOTHESIS

In the era of genome-wide association studies, familial risks are used to estimate disease heritability and success in gene identification. We wanted to estimate associations between type 1 diabetes mellitus and 33 autoimmune and related diseases in parents, offspring, singleton siblings and twins.

METHODS

The availability of a Multigeneration Register in Sweden provides reliable access to families throughout the last century. The diseases in individual family members were obtained through linkage to the Hospital Discharge Register. Standardised incidence ratios (SIRs) were calculated as relative risks of contracting type 1 diabetes in family members of affected patients compared with those lacking affected family members.

RESULTS

Among a total of 450,899 patients, 21,168 were diagnosed with type 1 diabetes. Familial cases amounted to 10.3% of all type 1 diabetes patients. SIR for type 1 diabetes was 8.23 in offspring of affected parents, 11.92 in singleton siblings, 39.22 in multiplex families and 21.88 in twins; the calculated risk for monozygotic twins was 32.33. Type 1 diabetes in offspring was associated with 13 diseases in parents, including Addison's disease (SIR 2.41), asthma (1.38), coeliac disease (2.73), Graves' disease/hyperthyroidism (1.86), Hashimoto disease/hypothyroidism (2.35), pernicious anaemia (3.09), primary biliary cirrhosis (3.63), rheumatoid arthritis (2.12), sarcoidosis (1.62), systemic lupus erythematosus (2.04), ulcerative colitis (1.23) and Wegener's granulomatosis (2.12).

CONCLUSIONS/INTERPRETATION

The concordant familial risks for type 1 diabetes were high and the calculated risk for multiplex families and monozygotic twins may be explained by epistatic gene x gene or gene x environment interactions. Familial associations with several autoimmune and related diseases suggest genetic sharing and challenge to gene identification.

Epigenetics: deciphering how environmental factors may modify autoimmune type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease that has increased two- to threefold over the past half century by as yet unknown means. It is generally accepted that T1D is the result of gene-environment interactions, but such rapid increases in incidence are not explained by Mendelian inheritance. There have been numerous advances in our knowledge of the pathogenesis of T1D. Indeed, there has been a large number of genes identified that contribute to risk for this disease and several environmental factors have been proposed. The complexity of such interactions is yet to be understood for any major chronic disease. Epigenetic regulation is one way to explain the rapid increase in incidence and could be a central mechanism by which environmental factors influence development of diabetes. However, there is remarkably little known about the contribution of epigenetics to T1D pathogenesis. Here we speculate on various candidate processes and molecules of the immune and endocrine systems that could modify risk for T1D through epigenetic regulation.

Twin studies and the heritability of MS: a conclusion

OBJECTIVE

The classical twin study has the potential to evaluate the relative contribution of genes and environment and guide further research strategies, provided the sampling and methods of analysis are correct. We wish to review all the more informative twin studies on multiple sclerosis (MS).

METHODS

We examined six large population-based twin studies in MS and calculated indices of heritability (h(2)), which is the traditional method of assessing genetic contribution to disease and to allow comparison between studies.

RESULTS

This index was found to vary widely from 0.25 to 0.76 with large confidence intervals that reflect small sample size and prevent robust interpretation.

CONCLUSION

Overall the studies support a genetic contribution to disease; however, the imprecision of the heritability estimates and potential biases that they contain mean that very little inference can be drawn its exact size. Given that the magnitude of genetic effect cannot be measured because of the relative infrequency of MS; the consequent difficulty in collecting an informative sample; and in many countries, the lack of a comprehensive twin register, we suggest that further twin prevalence surveys should not be undertaken. Twin studies could be used more effectively in other ways, such as the co-twin case-control approach.

Genetic modifiers play a substantial role in diabetes complicating cystic fibrosis

CONTEXT

Insulin-requiring diabetes affects 7-15% of teens and young adults, and more than 25% of older adults with cystic fibrosis (CF). Pancreatic exocrine disease caused by CF transmembrane conductance regulator (CFTR) dysfunction underlies the high rate of diabetes in CF patients; however, only a subset develops this complication, indicating that other factors are necessary.

OBJECTIVE

Our objective was to estimate the relative contribution of genetic and nongenetic modifiers to the development of diabetes in CF.

DESIGN/PATIENTS

This was a twin and sibling study involving 1366 individuals at 109 centers in the CF Twin and Sibling Study, from which were derived 68 monozygous twin pairs, 23 dizygous twin pairs, and 588 sibling pairs, all with CF.

MAIN OUTCOME MEASURE

Chronic, insulin-requiring diabetes in the setting of CF, as established using longitudinal clinical and biochemical data, was studied.

RESULTS

About 9% of this predominantly pediatric population (mean age = 15.8 yr) had diabetes. Key independent risk factors identified by regression modeling included having a twin or sibling with CF and diabetes, increasing age, pancreatic exocrine insufficiency or two mutations causing severe CFTR dysfunction, decreased lung function or decreased body mass index, and longer duration of glucocorticoid treatment. The concordance rate for diabetes was substantially higher in monozygous twins (0.73) than in dizygous twins and siblings with CF (0.18; P = 0.002). Heritability was estimated as near one (95% confidence interval 0.42-1.0).

CONCLUSIONS

Diabetes is a frequent complication of CF that is associated with worse outcomes. Although a nongenetic factor (steroid treatment) contributes to risk, genetic modifiers (i.e. genes other than CFTR) are the primary cause of diabetes in CF.

Disruptive insights in psychiatry: transforming a clinical discipline

Mental disorders such as schizophrenia, bipolar illness, and depression have become the predominant chronic diseases of young people, accounting for approximately 40% of the medical burden for people aged 15-44 in the United States and Canada. Research is transforming our understanding of these disorders, as exemplified in the articles in this Review Series. Important, "disruptive" insights into pathophysiology are emerging from studies addressing these illnesses as brain disorders, developmental disorders, and complex genetic disorders--rather than only as psychological conflicts or chemical imbalances, as they were considered in the past. Current medications are not sufficient for most patients. A new and deep understanding of the pathophysiology of these disabling disorders is our best hope for a new generation of treatments that will help patients to recover.

Amino acids of Coxsackie B5 virus are critical for infection of the murine insulinoma cell line, MIN-6

It was shown recently that 15 successive passages of a laboratory strain of the Coxsackie B virus 5 in a mouse pancreas (CBV-5-MPP) resulted in apparent changes in the virus phenotype, which led to the capacity to induce a diabetes-like syndrome in mice. For further characterization of islet cell interactions with a passaged virus strain, a murine insulinoma cell line, MIN-6, was selected as an experimental model. The CBV-5-MPP virus strain was not able to replicate in MIN-6 cells in vitro but required adaptation over a few days for progeny production and the generation of cytopathic effects. In order to determine the genetic characteristics required for virus growth in MIN-6 cells, the whole genome of the MIN-6-adapted virus variant was sequenced, and critical amino acids were identified by comparing the sequence with that of a virus strain passaged repeatedly in the mouse pancreas. The results of site-directed mutagenesis demonstrated that only one residue, amino acid 94 of VP1, is a major determinant for virus adaptation to MIN-6 cells.

Epidemiology of type 1 diabetes and what animal models teach us about the role of viruses in disease mechanisms

There is a consensus among epidemiologists that the worldwide incidence rate of type 1 diabetes has been rising in recent decades. The cause of this rise is unknown, but epidemiological studies suggest the involvement of environmental factors, and viral infections in particular. Data demonstrating a cause-and-effect relationship between microbial infections and type 1 diabetes and how viruses may cause disease in humans are currently lacking. However, new evidence from animal models supports the hypothesis that viruses induce disease via mechanisms linked with innate immune upregulation. In the BioBreeding Diabetes Resistant rat, infection with a parvovirus induces islet destruction via upregulation of the toll-like receptor 9 (TLR9) signaling pathway. Data from mouse models of diabetes implicate TLR2, TLR3, and TLR7 in the disease process. Understanding the link between environmental agents and innate immune pathways involved in early stages of diabetes may advance the design of immune interventions to prevent disease in genetically susceptible individuals.

Infection and autoimmunity

The development of some autoimmune diseases is increasing in the developed world faster than can be accounted for by genetic change. The development of these autoimmune diseases, such as Type 1 diabetes, is known to be influenced by both genetic and environmental factors. Environmental factors which have been considered to play a role include infectious agents such as viruses or bacteria. The search for a common initiating infection in the aetiology of Type 1 diabetes as proved thus far inconclusive. An alternative way of considering a role for infection is that infection may have historically prevented the development of autoimmune disease. In the developing world changes have occurred such that many chronic infections have been eliminated and this may have led to the emergence of autoimmune pathology. Evidence in support of this hypothesis is considered here and factors governing the development of autoimmunity compared with those which might have influenced the development of childhood leukaemia.