T1DBase: update 2011, organization and presentation of large-scale data sets for type 1 diabetes research

Segregation Analysis of Genotyped and Family-Phased, Long Range MHC Classical Class I and Class II Haplotypes in 5 Families With Type 1 Diabetes Proband in the United Arab Emirates

The classical Human Leucocyte Antigen (HLA) class II haplotypes of the Major Histocompatibility Complex (MHC) that are associated with type 1 diabetes (T1D) were identified in five families from the United Arab Emirates (UAE). Segregation analyses were performed on these 5 families with the disease, 3 with one child and 2 with 2 children diagnosed with T1D. Three HLA-DR4 haplotypes were identified: HLA- DRB1^∗04:01:01-DQB1^∗03:02:01:01; HLA- DRB1^∗04:02:01- DQB1^∗03:02:01; and HLA -DRB1^∗04:05:01-DQB1^∗02:02:01:02. All have previously been identified to be associated with T1D in studies of the Arabian population. In the 10 parents from the 5 families, 9 had at least one HLA-DR4 and HLA-DR3 haplotype which potentially increases the risk of T1D. Of these 9 parents, 3 were heterozygous for HLA-DR4/HLA-DR3 and one was homozygous for HLA-DR3. Two haplotypes that were identified here extend to the HLA class I region were previously designated AH8.2 (HLA -A^∗26-B^∗08-DRB1^∗03) and AH50.2 (HLA -C^∗06-B^∗50-DRB1^∗03:01-DQ^∗02) and associated with diabetes in neighboring North Indian populations. This study provides examples of MHC haplotype analysis in pedigrees to improve our understanding of the genetics of T1D in the understudied population of the UAE.

Lead Optimization Resources in Drug Discovery for Diabetes

BACKGROUND

Diabetes, defined as a chronic metabolic syndrome, exhibits global prevalence and phenomenal rise worldwide. The rising incidence accounts for a global health crisis, demonstrating a profound effect on low and middle-income countries, particularly people with limited healthcare facilities.

METHODS

Highlighting the prevalence of diabetes and its socio-economic implications on the population across the globe, the article aimed to address the emerging significance of computational biology in drug designing and development, pertaining to identification and validation of lead molecules for diabetes treatment.

RESULTS

The drug discovery programs have shifted the focus on in silico prediction strategies minimizing prolonged clinical trials and expenses. Despite technological advances and effective drug therapies, the fight against life-threatening, disabling disease has witnessed multiple challenges. The lead optimization resources in computational biology have transformed the research on the identification and optimization of anti-diabetic lead molecules in drug discovery studies. The QSAR approaches and ADMET/Toxicity parameters provide significant evaluation of prospective "drug-like" molecules from natural sources.

CONCLUSION

The science of computational biology has facilitated the drug discovery and development studies and the available data may be utilized in a rational construction of a drug 'blueprint' for a particular individual based on the genetic organization. The identification of natural products possessing bioactive properties as well as their scientific validation is an emerging prospective approach in antidiabetic drug discovery.

Utility and First Clinical Application of Screening Embryos for Polygenic Disease Risk Reduction

For over 2 decades preimplantation genetic testing (PGT) has been in clinical use to reduce the risk of miscarriage and genetic disease in patients with advanced maternal age and risk of transmitting disease. Recently developed methods of genome-wide genotyping and machine learning algorithms now offer the ability to genotype embryos for polygenic disease risk with accuracy equivalent to adults. In addition, contemporary studies on adults indicate the ability to predict polygenic disorders with risk equivalent to monogenic disorders. Existing biobanks provide opportunities to model the clinical utility of polygenic disease risk reduction among sibling adults. Here, we provide a mathematical model for the use of embryo screening to reduce the risk of type 1 diabetes. Results indicate a 45-72% reduced risk with blinded genetic selection of one sibling. The first clinical case of polygenic risk scoring in human preimplantation embryos from patients with a family history of complex disease is reported. In addition to these data, several common and accepted practices place PGT for polygenic disease risk in the applicable context of contemporary reproductive medicine. In addition, prediction of risk for PCOS, endometriosis, and aneuploidy are of particular interest and relevance to patients with infertility and represent an important focus of future research on polygenic risk scoring in embryos.

Risk variants disrupting enhancers of TH1 and TREG cells in type 1 diabetes

Functional interpretation of noncoding genetic variants identified by genome-wide association studies is a major challenge in human genetics and gene regulation. We generated epigenomics data using primary cells from type 1 diabetes patients. Using these data, we identified and validated multiple novel risk variants for this disease. In addition, our ranked list of candidate risk SNPs represents the most comprehensive annotation based on T1D-specific T-cell data. Because many autoimmune diseases share some genetic underpinnings, our dataset may be used to understand causal noncoding mutations in related autoimmune diseases.

Genome-wide association studies (GWASs) have revealed 59 genomic loci associated with type 1 diabetes (T1D). Functional interpretation of the SNPs located in the noncoding region of these loci remains challenging. We perform epigenomic profiling of two enhancer marks, H3K4me1 and H3K27ac, using primary T_H1 and T_REG cells isolated from healthy and T1D subjects. We uncover a large number of deregulated enhancers and altered transcriptional circuitries in both cell types of T1D patients. We identify four SNPs (rs10772119, rs10772120, rs3176792, rs883868) in linkage disequilibrium (LD) with T1D-associated GWAS lead SNPs that alter enhancer activity and expression of immune genes. Among them, rs10772119 and rs883868 disrupt the binding of retinoic acid receptor α (RARA) and Yin and Yang 1 (YY1), respectively. Loss of binding by YY1 also results in the loss of long-range enhancer–promoter interaction. These findings provide insights into how noncoding variants affect the transcriptomes of two T-cell subtypes that play critical roles in T1D pathogenesis.

UVEOGENE: An SNP database for investigations on genetic factors associated with uveitis and their relationship with other systemic autoimmune diseases

Uveitis is an intraocular inflammatory disease which can lead to serious visual impairment. Genetic factors have been shown to be involved in its development. However, few databases have focused on the information of associations between single nucleotide polymorphisms (SNPs) and uveitis. To discover the exact genetic background of uveitis, we developed an SNP database specific for uveitis, “UVEOGENE,” which includes 370 genes and 918 SNPs covering 14 uveitis entities and 40 populations from 286 PubMed English‐language papers. Stratification analyses by gender, HLA status, and different clinical features were also extracted from the publications. As a result, 371 associations were judged as “statistically significant.” These associations were also shared with Global Variome shared Leiden Open Variation Database (LOVD) (https://databases.lovd.nl/shared/genes). Based on these associations, we investigated the genetic relationship among three widely studied uveitis entities including Behcet's disease (BD), Vogt–Koyanagi–Harada (VKH) disease, and acute anterior uveitis (AAU). Furthermore, “UVEOGENE” can be used as a reliable and informative resource to identify similarities as well as differences in the genetic susceptibility among uveitis and other autoimmune diseases. UVEOGENE is freely accessible at http://www.uvogene.com.

Association of serum bilirubin level with lung function decline: a Korean community-based cohort study

BACKGROUND

Bilirubin has been reported to be associated with respiratory diseases due to its antioxidant action. We aimed to evaluate the relationship between serum bilirubin concentration and annual lung function decline in the Korean general population.

METHODS

The study included 7986 subjects aged 40-69 years from the Ansung-Ansan cohort database I (2001-2002)-III (2005-2006). We analyzed the relationships between serum bilirubin level and forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC), FEV₁/FVC, and mean forced expiratory flow between 25 and 75% of FVC (FEF_25-75%) at baseline, as well as the annual average changes in these lung parameters.

RESULTS

The FEV₁, FVC, and FEF_25-75% were significantly associated with serum bilirubin levels after adjustment for age, sex, body mass index (BMI), and smoking status (all P < 0.001). When stratified according to smoking status, these relationships were significant in never-smokers. Additionally, serum bilirubin level was negatively associated with the annual decline in FEV₁ and FVC, and positively associated with the annual decline in FEV₁/FVC after adjustment for age, sex, BMI, baseline lung function, and smoking status (all P < 0.001).

CONCLUSIONS

We found significant associations of serum bilirubin levels with FEV₁, FVC, and FEF_25-75% in the general population, especially in never-smokers. Moreover, serum bilirubin levels were related with the annual decline in FEV₁, FVC, and FEV₁/FVC ratio.

Two Novel MicroRNA Biomarkers Related to β-Cell Damage and Their Potential Values for Early Diagnosis of Type 1 Diabetes

CONTEXT

New strategies and biomarkers are needed in the early detection of β-cell damage in the progress of type 1 diabetes mellitus (T1DM).

OBJECTIVE

To explore whether serum microRNAs (miRNA) should be served as biomarkers for T1DM.

DESIGN, SETTINGS, AND PATIENTS

The miRNA profile was established with miRNA microarray in discovery phase (six T1DM, six controls). A miRNA-based model for T1DM diagnosis was developed using logistic regression analysis in the training dataset (40 T1DM, 56 controls) and then validated with leave-one-out cross validation and another independent validation dataset (33 T1DM, 29 controls).

MAIN OUTCOME MEASURES

Quantitative reverse transcription polymerase chain reaction was applied to confirm the differences of candidate miRNAs between T1DM and controls. Area under the receiver-operating characteristic (ROC) curve (AUC) was used to evaluate diagnostic accuracy. INS-1 cells, streptozotocin-treated mice (n = 4), and nonobese diabetic (NOD) mice (n = 12) were used to evaluate the association of miRNAs with β-cell damage.

RESULTS

A miRNA -based model was established in the training dataset with high diagnostic accuracy for T1DM (AUC = 0.817) based on six candidate differential expressed miRNAs identified in discovery phase. The validation dataset showed the model's satisfactory diagnostic performance (AUC = 0.804). Secretions of miR-1225-5p and miR-320c were significantly increased in streptozotocin-treated mice and INS-1 cells. Noteworthy, the elevation of these two miRNAs was observed before glucose elevation in the progress of diabetes in NOD mice.

CONCLUSIONS

Two miRNA biomarkers (miR-1225-5p and miR-320c) related to β-cell damage were identified in patients with recent-onset T1DM. The miRNA-based model established in this study exhibited a good performance in diagnosis of T1DM.

Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young

BACKGROUND

Genetic predisposition for type 1 diabetes (T1D) is largely determined by human leukocyte antigen (HLA) genes; however, over 50 other genetic regions confer susceptibility. We evaluated a previously reported 10-factor weighted model derived from the Type 1 Diabetes Genetics Consortium to predict the development of diabetes in the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Performance of the model, derived from individuals with first-degree relatives (FDR) with T1D, was evaluated in DAISY general population (GP) participants as well as FDR subjects.

METHODS

The 10-factor weighted risk model (HLA, PTPN22 , INS , IL2RA , ERBB3 , ORMDL3 , BACH2 , IL27 , GLIS3 , RNLS ), 3-factor model (HLA, PTPN22, INS ), and HLA alone were compared for the prediction of diabetes in children with complete SNP data (n = 1941).

RESULTS

Stratification by risk score significantly predicted progression to diabetes by Kaplan-Meier analysis (GP: P = .00006; FDR: P = .0022). The 10-factor model performed better in discriminating diabetes outcome than HLA alone (GP, P = .03; FDR, P = .01). In GP, the restricted 3-factor model was superior to HLA (P = .03), but not different from the 10-factor model (P = .22). In contrast, for FDR the 3-factor model did not show improvement over HLA (P = .12) and performed worse than the 10-factor model (P = .02) CONCLUSIONS: We have shown a 10-factor risk model predicts development of diabetes in both GP and FDR children. While this model was superior to a minimal model in FDR, it did not confer improvement in GP. Differences in model performance in FDR vs GP children may lead to important insights into screening strategies specific to these groups.

Isl1β Overexpression With Key β Cell Transcription Factors Enhances Glucose-Responsive Hepatic Insulin Production and Secretion

Adenoviral gene transfer of key β cell developmental regulators including Pdx1, Neurod1, and Mafa (PDA) has been reported to generate insulin-producing cells in the liver. However, PDA insulin secretion is transient and glucose unresponsive. Here, we report that an additional β cell developmental regulator, insulin gene enhancer binding protein splicing variant (Isl1β), improved insulin production and glucose-responsive secretion in PDA mice. Microarray gene expression analysis suggested that adenoviral PDA transfer required an additional element for mature β cell generation, such as Isl1 and Elf3 in the liver. In vitro promoter analysis indicated that splicing variant Isl1, or Isl1β, is an important factor for transcriptional activity of the insulin gene. In vivo bioluminescence monitoring using insulin promoter-luciferase transgenic mice verified that adenoviral PDA + Isl1β transfer produced highly intense luminescence from the liver, which peaked at day 7 and persisted for more than 10 days. Using insulin promoter-GFP transgenic mice, we further confirmed that Isl1β supplementation to PDA augmented insulin-producing cells in the liver, insulin production and secretion, and β cell‒related genes. Finally, the PDA + Isl1β combination ameliorated hyperglycemia in diabetic mice for 28 days and enhanced glucose tolerance and responsiveness. Thus, our results suggest that Isl1β is a key additional transcriptional factor for advancing the generation of insulin-producing cells in the liver in combination with PDA.

Persistent coxsackievirus B4 infection induces microRNA dysregulation in human pancreatic cells

Enterovirus infections are implicated in the development of type 1 diabetes (T1D). MicroRNAs as regulators of gene expression are involved in many physiological and pathological processes. Given that viral infections dysregulate cellular microRNAs, we investigated the impact of persistent coxsackievirus B4 infection on microRNA expression of human pancreatic cells. Next-generation sequencing was used to determine microRNA expression in PANC-1 cells persistently infected (for several weeks) with coxsackievirus B4 and uninfected control cells. Target prediction restricted to T1D risk genes was performed with miRWalk2.0. Functional annotation analysis was performed with DAVID6.7. Expression of selected microRNAs and T1D risk genes was measured by quantitative reverse-transcription polymerase chain reaction. Eighty-one microRNAs were dysregulated in persistently infected PANC-1 cells. Forty-nine of the known fifty-five T1D risk genes were predicted as putative targets of at least one of the dysregulated microRNAs. Most functional annotation terms that were enriched in these 49 putative target genes were related to the immune response or autoimmunity. mRNA levels of AFF3, BACH2, and IL7R differed significantly between persistently infected cells and uninfected cells. This is the first characterization of the microRNA expression profile changes induced by persistent coxsackievirus B4 infection in pancreatic cells. The predicted targeting of genes involved in the immune response and autoimmunity by the dysregulated microRNAs as well as the dysregulated expression of diabetes risk genes shows that persistent coxsackievirus B4 infection profoundly impacts the host cell. These data support the hypothesis of a possible link between persistent coxsackievirus B4 infection and the development of T1D.

Can Non-HLA Single Nucleotide Polymorphisms Help Stratify Risk in TrialNet Relatives at Risk for Type 1 Diabetes?

CONTEXT

Genome-wide association studies identified >50 type 1 diabetes (T1D) associated non-human leukocyte antigens (non-HLA) loci.

OBJECTIVE

The purpose of this study was to assess the contribution of non-HLA single nucleotide polymorphisms (SNPs) to risk of disease progression.

DESIGN AND SETTING

The TrialNet Pathway to Prevention Study follows relatives of T1D patients for development of autoantibodies (Abs) and T1D.

PARTICIPANTS

Using the Immunochip, we analyzed 53 diabetes-associated, non-HLA SNPs in 1016 Ab-positive, at-risk non-Hispanic white relatives.

MAIN OUTCOME MEASURE

Effect of SNPs on the development of multiple Abs and T1D.

RESULTS

Cox proportional analyses included all substantial non-HLA SNPs, HLA genotypes, relationship to proband, sex, age at initial screening, initial Ab type, and number. Factors involved in progression from single to multiple Abs included age at screening, relationship to proband, HLA genotypes, and rs3087243 (cytotoxic T lymphocyte antigen-4). Significant factors for diabetes progression included age at screening, Ab number, HLA genotypes, rs6476839 [GLIS family zinc finger 3 (GLIS3)], and rs3184504 [SH2B adaptor protein 3 (SH2B3)]. When glucose area under the curve (AUC) was included, factors involved in disease progression included glucose AUC, age at screening, Ab number, relationship to proband, HLA genotypes, rs6476839 (GLIS3), and rs7221109 (CCR7). In stratified analyses by age, glucose AUC, age at screening, sibling, HLA genotypes, rs6476839 (GLIS3), and rs4900384 (C14orf64) were significantly associated with progression to diabetes in participants <12 years old, whereas glucose AUC, sibling, rs3184504 (SH2B3), and rs4900384 (C14orf64) were significant in those ≥12.

CONCLUSIONS

In conclusion, we identified five non-HLA SNPs associated with increased risk of progression from Ab positivity to disease that may improve risk stratification for prevention trials.

The Inhibitory G Protein α-Subunit, Gαz, Promotes Type 1 Diabetes-Like Pathophysiology in NOD Mice

The α-subunit of the heterotrimeric Gz protein, Gαz, promotes β-cell death and inhibits β-cell replication when pancreatic islets are challenged by stressors. Thus, we hypothesized that loss of Gαz protein would preserve functional β-cell mass in the nonobese diabetic (NOD) model, protecting from overt diabetes. We saw that protection from diabetes was robust and durable up to 35 weeks of age in Gαz knockout mice. By 17 weeks of age, Gαz-null NOD mice had significantly higher diabetes-free survival than wild-type littermates. Islets from these mice had reduced markers of proinflammatory immune cell infiltration on both the histological and transcript levels and secreted more insulin in response to glucose. Further analyses of pancreas sections revealed significantly fewer terminal deoxynucleotidyltransferase-mediated dUTP nick end labeling (TUNEL)-positive β-cells in Gαz-null islets despite similar immune infiltration in control mice. Islets from Gαz-null mice also exhibited a higher percentage of Ki-67-positive β-cells, a measure of proliferation, even in the presence of immune infiltration. Finally, β-cell-specific Gαz-null mice phenocopy whole-body Gαz-null mice in their protection from developing hyperglycemia after streptozotocin administration, supporting a β-cell-centric role for Gαz in diabetes pathophysiology. We propose that Gαz plays a key role in β-cell signaling that becomes dysfunctional in the type 1 diabetes setting, accelerating the death of β-cells, which promotes further accumulation of immune cells in the pancreatic islets, and inhibiting a restorative proliferative response.

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

IMPORTANCE

The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

OBJECTIVE

To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

DATA SOURCES

Genomewide association studies (GWAS) published up to January 15, 2015.

STUDY SELECTION

GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

DATA EXTRACTION AND SYNTHESIS

Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

MAIN OUTCOMES AND MEASURES

Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

RESULTS

Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

CONCLUSIONS AND RELEVANCE

It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis

AIMS/HYPOTHESIS

Type 1 diabetes is an endocrine disease where a long preclinical phase, characterised by immune cell infiltration in the islets of Langerhans, precedes elevated blood glucose levels and disease onset. Although several studies have investigated the role of the immune system in this process of insulitis, the importance of the beta cells themselves in the initiation of type 1 diabetes is less well understood. The aim of this study was to investigate intrinsic differences present in the islets from diabetes-prone NOD mice before the onset of insulitis.

METHODS

The islet transcriptome and proteome of 2-3-week-old mice was investigated by microarray and 2-dimensional difference gel electrophoresis (2D-DIGE), respectively. Subsequent analyses using sophisticated pathway analysis and ranking of differentially expressed genes and proteins based on their relevance in type 1 diabetes were performed.

RESULTS

In the preinsulitic period, alterations in general pathways related to metabolism and cell communication were already present. Additionally, our analyses pointed to an important role for post-translational modifications (PTMs), especially citrullination by PAD2 and protein misfolding due to low expression levels of protein disulphide isomerases (PDIA3, 4 and 6), as causative mechanisms that induce beta cell stress and potential auto-antigen generation.

CONCLUSIONS/INTERPRETATION

We conclude that the pancreatic islets, irrespective of immune differences, may contribute to the initiation of the autoimmune process.

DATA AVAILABILITY

All microarray data are available in the ArrayExpress database ( www.ebi.ac.uk/arrayexpress ) under accession number E-MTAB-5264.

A computational study on role of 6-(hydroxymethyl)-3-[3,4,5-trihydroxy-6-[(3,4,5-trihydroxyoxan-2-yl)oxymethyl]oxan-2-yl]oxyoxane-2,4,5-triol in the regulation of blood glucose level

6-(hydroxymethyl)-3-[3,4,5-trihydroxy-6-[(3,4,5-trihydroxyoxan-2-yl)oxymethyl]oxan-2-yl]oxyoxane-2,4,5-triol (SID 242078875) was isolated from the fruits of Syzygium densiflorum Wall. ex Wight & Arn (Myrtaceae), which has been traditionally used in the treatment of diabetes by the tribes of The Nilgiris, Tamil Nadu, India. In this study, reverse pharmacophore mapping approach and text-based database search identified the dipeptidyl peptidase-IV, protein-tyrosine phosphatase 1B, phosphoenolpyruvate carboxykinase, glycogen synthase kinase-3β and glucokinase as potential targets of SID 242078875 in diabetes management. Further, molecular docking was performed to predict the binding pose of SID 242078875 in the active site region of the target protein. In addition, dynamic behaviour and stability of protein-ligand complexes were observed for a period of 50 ns through molecular dynamics simulation.

ERBB3-rs2292239 as primary type 1 diabetes association locus among non-HLA genes in Chinese

Type 1 diabetes (T1D) is an autoimmune disease that has strong contribution of genetic factors to its etiology. We aimed to assess the genetic association between non-HLA genes and T1D in a Chinese case-control cohort recruited from multiple centers consisting of 364 patients with T1D and 719 unrelated healthy children. We genotyped 55 single nucleotide polymorphisms (SNP) markers located in 16 non-HLA genes (VTCN1, PTPN22, CTLA4, SUMO4, CD274, IL2RA, INS, DHCR7, ERBB3, VDR, CYP27B1, CD69, CD276, PTPN2, UBASH3A, and IL2RB) using SNaPshot multiple single-base extension methods. After multivariate analysis and correction for multiple comparisons, we identified the SNP rs2292239 in ERBB3 gene were significantly associated with T1D. The frequency of the major G allele was significantly decreased in patients with T1D (68.8% in T1D vs 77.3% in controls, OR 0.65, 95% CI 0.53–0.79, P = 0.02), and the minor allele T was associated with an increased risk of T1D (OR 1.55, 95% CI 1.26–1.90, P = 0.02). Our haplotype analysis confirmed that rs2292239 was the primary T1D association locus in our current investigation. These results indicated that the ERBB3-rs2292239 was the primary T1D association locus among the investigated 55 SNPs in 16 non-HLA genes in Chinese Han population.

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A large scale case-control genetic association study on type 1 diabetes in Chinese investigating on-HLA genes.

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rs2292239 in the ERBB3 gene conferred the primary non-HLA association in Chinese type 1 diabetes.

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Markers in the common candidate genes, such as PTPN22, CTLA4, IL2RA, and INS, were not significantly associated with T1D in our Chinese cohort.

Cytokines and Pancreatic β-Cell Apoptosis

The discovery 30 years ago that inflammatory cytokines cause a concentration, activity, and time-dependent bimodal response in pancreatic β-cell function and viability has been a game-changer in the fields of research directed at understanding inflammatory regulation of β-cell function and survival and the causes of β-cell failure and destruction in diabetes. Having until then been confined to the use of pathophysiologically irrelevant β-cell toxic chemicals as a model of β-cell death, researchers could now mimic endocrine and paracrine effects of the cytokine response in vitro by titrating concentrations in the low to the high picomolar-femtomolar range and vary exposure time for up to 14-16h to reproduce the acute regulatory effects of systemic inflammation on β-cell secretory responses, with a shift to inhibition at high picomolar concentrations or more than 16h of exposure to illustrate adverse effects of local, chronic islet inflammation. Since then, numerous studies have clarified how these bimodal responses depend on discrete signaling pathways. Most interest has been devoted to the proapoptotic response dependent upon mainly nuclear factor κ B and mitogen-activated protein kinase activation, leading to gene expressional changes, endoplasmic reticulum stress, and triggering of mitochondrial dysfunction. Preclinical studies have shown preventive effects of cytokine antagonism in animal models of diabetes, and clinical trials demonstrating proof of concept are emerging. The full clinical potential of anticytokine therapies has yet to be shown by testing the incremental effects of appropriate dosing, timing, and combinations of treatments. Due to the considerable translational importance of enhancing the precision, specificity, and safety of antiinflammatory treatments of diabetes, we review here the cellular, preclinical, and clinical evidence of which of the death pathways recently proposed in the Nomenclature Committee on Cell Death 2012 Recommendations are activated by inflammatory cytokines in the pancreatic β-cell to guide the identification of antidiabetic targets. Although there are still scarce human data, the cellular and preclinical studies point to the caspase-dependent intrinsic apoptosis pathway as the prime effector of inflammatory β-cell apoptosis.

Coxsackievirus B5 Infection Induces Dysregulation of microRNAs Predicted to Target Known Type 1 Diabetes Risk Genes in Human Pancreatic Islets

Extensive research has identified enterovirus (EV) infections as key environmental triggers of type 1 diabetes. However, the underlying molecular mechanisms via which EVs contribute to the pathogenesis of type 1 diabetes remain unclear. Given that EVs dysregulate host microRNAs (miRNAs), which function as key regulators of β-cell biology, we investigated the impact of coxsackievirus B5 (CVB5) infection on the cellular expression of miRNAs within human islets. Using high-throughput quantitative PCR nanofluidics arrays, the expression of 754 miRNAs was examined in CVB5-infected human pancreatic islets. In total, 33 miRNAs were significantly dysregulated (≥ threefold difference) in the infected compared with control islets (P < 0.05). Subsequently, these differentially expressed miRNAs were predicted to target mRNAs of 57 known type 1 diabetes risk genes that collectively mediate various biological processes, including the regulation of cell proliferation, cytokine production, the innate immune response, and apoptosis. In conclusion, we report the first global miRNA expression profiling of CVB5-infected human pancreatic islets. We propose that EVs disrupt the miRNA-directed suppression of proinflammatory factors within β-cells, thereby resulting in an exacerbated antiviral immune response that promotes β-cell destruction and eventual type 1 diabetes.

Inflammatory bowel diseases, chronic liver diseases and the lung

This review is devoted to the distinct associations of inflammatory bowel diseases (IBD) and chronic liver disorders with chronic airway diseases, namely chronic obstructive pulmonary disease and bronchial asthma, and other chronic respiratory disorders in the adult population. While there is strong evidence for the association of chronic airway diseases with IBD, the data are much weaker for the interplay between lung and liver multimorbidities. The association of IBD, encompassing Crohn's disease and ulcerative colitis, with pulmonary disorders is underlined by their heterogeneous respiratory manifestations and impact on chronic airway diseases. The potential relationship between the two most prevalent liver-induced pulmonary vascular entities, i.e. portopulmonary hypertension and hepatopulmonary syndrome, and also between liver disease and other chronic respiratory diseases is also approached. Abnormal lung function tests in liver diseases are described and the role of increased serum bilirubin levels on chronic respiratory problems are considered.

Pancreatic Beta Cell Survival and Signaling Pathways: Effects of Type 1 Diabetes-Associated Genetic Variants

Type 1 diabetes (T1D) is a complex autoimmune disease in which pancreatic beta cells are specifically destroyed by the immune system. The disease has an important genetic component and more than 50 loci across the genome have been associated with risk of developing T1D. The molecular mechanisms by which these putative T1D candidate genes modulate disease risk, however, remain poorly characterized and little is known about their effects in pancreatic beta cells. Functional studies in in vitro models of pancreatic beta cells, based on techniques to inhibit or overexpress T1D candidate genes, allow the functional characterization of several T1D candidate genes. This requires a multistage procedure comprising two major steps, namely accurate selection of genes of potential interest and then in vitro and/or in vivo mechanistic approaches to characterize their role in pancreatic beta cell dysfunction and death in T1D. This chapter details the methods and settings used by our groups to characterize the role of T1D candidate genes on pancreatic beta cell survival and signaling pathways, with particular focus on potentially relevant pathways in the pathogenesis of T1D, i.e., inflammation and innate immune responses, apoptosis, beta cell metabolism and function.

A SNP in the Immunoregulatory Molecule CTLA-4 Controls mRNA Splicing In Vivo but Does Not Alter Diabetes Susceptibility in the NOD Mouse

CTLA-4 is a critical "checkpoint" regulator in autoimmunity. Variation in CTLA-4 isoform expression has been linked to type 1 diabetes development in human and NOD mouse studies. In the NOD mouse, a causative link between increased expression of the minor isoform ligand-independent CTLA-4 and a reduction in diabetes has become widely accepted. Altered splicing of CTLA-4 has been attributed to a single nucleotide polymorphism (SNP) in Ctla4 exon2 (e2_77A/G). To investigate this link, we have used NOD embryonic stem (ES) cells to generate a novel NOD transgenic line with the 77A/G SNP. This strain phenocopies the increase in splicing toward the liCTLA4 isoform seen in B10 Idd5.1 mice. Crucially, the SNP does not alter the spontaneous incidence of diabetes, the incidence of cyclophosphamide-induced diabetes, or the activation of diabetogenic T-cell receptor transgenic CD4(+) T cells after adoptive transfer. Our results show that one or more of the many other linked genetic variants between the B10 and NOD genome are required for the diabetes protection conferred by Idd5.1. With the NOD mouse model closely mimicking the human disease, our data demonstrate that knock-in transgenic mice on the NOD background can test causative mutations relevant in human diabetes.

Genetic architecture of early pre-inflammatory stage transcription signatures of autoimmune diabetes in the pancreatic lymph nodes of the NOD mouse reveals significant gene enrichment on chromosomes 6 and 7

Autoimmune diseases are characterized by the stimulation of an excessive immune response to self-tissues by inner and/or outer organism factors. Common characteristics in their etiology include a complex genetic predisposition and environmental triggers as well as the implication of the major histocompatibility (MHC) locus on human chromosome 6p21. A restraint number of non-MHC susceptibility genes, part of the genetic component of type 1 diabetes have been identified in human and in animal models, while the complete spectrum of genes involved remains unknown. We elaborate herein patterns of chromosomal organization of 162 genes differentially expressed in the pancreatic lymph nodes of Non-Obese Diabetic mice, carefully selected by early sub-phenotypic evaluation (presence or absence of insulin autoantibodies). Chromosomal assignment of these genes revealed a non-random distribution on five chromosomes (47%). Significant gene enrichment was observed in particular for two chromosomes, 6 and 7. While a subset of these genes coding for secreted proteins showed significant enrichment on both chromosomes, the overall pool of genes was significantly enriched on chromosome 7. The significance of this unexpected gene distribution on the mouse genome is discussed in the light of novel findings indicating that genes affecting common diseases map to recombination “hotspot” regions of mammalian genomes. The genetic architecture of transcripts differentially expressed in specific stages of autoimmune diabetes offers novel venues towards our understanding of patterns of inheritance potentially affecting the pathological disease mechanisms.

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Chromosomal organization of differentially expressed genes in early autoimmunity

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Non-random distribution of type 1 diabetes-related transcripts on the mouse genome

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High density of genetic polymorphisms on specific loci of chromosomes 6 and 7

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Correlation of mapping positions on chromosomes 6 and 7 with known T1D loci

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Our study offers candidate genes and loci drawn in the genomics of T1D initiation.

Animal models for diabetes: Understanding the pathogenesis and finding new treatments

Diabetes mellitus is a lifelong, metabolic disease that is characterised by an inability to maintain normal glucose homeostasis. There are several different forms of diabetes, however the two most common are Type 1 and Type 2 diabetes. Type 1 diabetes is caused by the autoimmune destruction of pancreatic beta cells and a subsequent lack of insulin production, whilst Type 2 diabetes is due to a combination of both insulin resistance and an inability of the beta cells to compensate adequately with increased insulin release. Animal models are increasingly being used to elucidate the mechanisms underlying both Type 1 and Type 2 diabetes as well as to identify and refine novel treatments. However, a wide range of different animal models are currently in use. The majority of these models are suited to addressing certain specific aspects of diabetes research, but may be of little use in other studies. All have pros and cons, and selecting an appropriate model for addressing a specific question is not always a trivial task and will influence the study results and their interpretation. Thus, as the number of available animal models increases it is important to consider the potential roles of these models in the many different aspects of diabetes research. This review gathers information on the currently used experimental animal models of both Type 1 and Type 2 diabetes and evaluates their advantages and disadvantages for research purposes and details the factors that should be taken into account in their use.

Sleeping Beauty Transposon Mutagenesis as a Tool for Gene Discovery in the NOD Mouse Model of Type 1 Diabetes

A number of different strategies have been used to identify genes for which genetic variation contributes to type 1 diabetes (T1D) pathogenesis. Genetic studies in humans have identified >40 loci that affect the risk for developing T1D, but the underlying causative alleles are often difficult to pinpoint or have subtle biological effects. A complementary strategy to identifying "natural" alleles in the human population is to engineer "artificial" alleles within inbred mouse strains and determine their effect on T1D incidence. We describe the use of the Sleeping Beauty (SB) transposon mutagenesis system in the nonobese diabetic (NOD) mouse strain, which harbors a genetic background predisposed to developing T1D. Mutagenesis in this system is random, but a green fluorescent protein (GFP)-polyA gene trap within the SB transposon enables early detection of mice harboring transposon-disrupted genes. The SB transposon also acts as a molecular tag to, without additional breeding, efficiently identify mutated genes and prioritize mutant mice for further characterization. We show here that the SB transposon is functional in NOD mice and can produce a null allele in a novel candidate gene that increases diabetes incidence. We propose that SB transposon mutagenesis could be used as a complementary strategy to traditional methods to help identify genes that, when disrupted, affect T1D pathogenesis.

Contrasting the Genetic Background of Type 1 Diabetes and Celiac Disease Autoimmunity

Type 1 diabetes (T1D) and celiac disease (CeD) cluster in families and can occur in the same individual. Genetic loci have been associated with susceptibility to both diseases. Our aim was to explore the genetic differences between individuals developing both these diseases (double autoimmunity) versus those with only one. We hypothesized that double autoimmunity individuals carry more of the genetic risk markers that are shared between the two diseases independently. SNPs were genotyped in loci associated with T1D (n=42) and CeD (n=28) in 543 subjects who developed double autoimmunity, 2,472 subjects with T1D only, and 2,223 CeD-only subjects. For identification of loci that were specifically associated with individuals developing double autoimmunity, two association analyses were conducted: double autoimmunity versus T1D and double autoimmunity versus CeD. HLA risk haplotypes were compared between the two groups. The CTLA4 and IL2RA loci were more strongly associated with double autoimmunity than with either T1D or CeD alone. HLA analyses indicated that the T1D high-risk genotype, DQ2.5/DQ8, provided the highest risk for developing double autoimmunity (odds ratio 5.22, P=2.25×10(-29)). We identified a strong HLA risk genotype (DQ2.5/DQ8) predisposing to double autoimmunity, suggesting a dominant role for HLA. Non-HLA loci, CTLA4 and IL2RA, may also confer risk to double autoimmunity. Thus, CeD patients who carry the DQ2.5/DQ8 genotype may benefit from periodic screening of autoantibodies related to T1D.

Serum Bilirubin and Disease Progression in Mild COPD

BACKGROUND

COPD is a chronic inflammatory disorder associated with oxidative stress. Serum bilirubin has potent antioxidant actions, and higher concentrations have been shown to protect against oxidative stress. The relation between serum bilirubin and COPD progression is unknown.

METHODS

Serum bilirubin was measured in 4,680 smokers aged 35 to 60 years old with mild to moderate airflow limitation. The relationship of serum bilirubin to postbronchodilator FEV₁ and rate of FEV1 decline over 3 to 9 years was determined using regression modeling. Total and disease-specific mortality were also ascertained.

RESULTS

Serum bilirubin was positively related to FEV₁ (P < .001). Serum bilirubin was also negatively related to the annual decline in FEV₁ when adjusted for baseline demographics, pack-years smoked, and baseline measures of lung function (P = .01). Additionally, serum bilirubin was negatively associated with risk of death from coronary heart disease (P = .03); however, the relationships between bilirubin and other mortality end points were not statistically significant (P > .05).

CONCLUSIONS

Bilirubin is inversely related to COPD disease severity and progression. Higher serum bilirubin concentration was associated with a higher FEV₁ and less annual decline in FEV₁. Bilirubin was also associated with less coronary heart disease mortality. These data support the hypothesis that bilirubin has a protective effect on COPD disease progression, possibly through its antioxidant actions. Bilirubin may prove useful as an easily accessible and readily available blood-based COPD biomarker.

Phenolyzer: phenotype-based prioritization of candidate genes for human diseases

Prior biological knowledge and phenotype information may help to identify disease genes from human whole-genome and whole-exome sequencing studies. We developed Phenolyzer (http://phenolyzer.usc.edu), a tool that uses prior information to implicate genes involved in diseases. Phenolyzer exhibits superior performance over competing methods for prioritizing Mendelian and complex disease genes, based on disease or phenotype terms entered as free text.

DAPD: A Knowledgebase for Diabetes Associated Proteins

Recent advancements in genomics and proteomics provide a solid foundation for understanding the pathogenesis of diabetes. Proteomics of diabetes associated pathways help to identify the most potent target for the management of diabetes. The relevant datasets are scattered in various prominent sources which takes much time to select the therapeutic target for the clinical management of diabetes. However, additional information about target proteins is needed for validation. This lacuna may be resolved by linking diabetes associated genes, pathways and proteins and it will provide a strong base for the treatment and planning management strategies of diabetes. Thus, a web source "Diabetes Associated Proteins Database (DAPD)" has been developed to link the diabetes associated genes, pathways and proteins using PHP, MySQL. The current version of DAPD has been built with proteins associated with different types of diabetes. In addition, DAPD has been linked to external sources to gain the access to more participatory proteins and their pathway network. DAPD will reduce the time and it is expected to pave the way for the discovery of novel anti-diabetic leads using computational drug designing for diabetes management. DAPD is open accessed via following url www.mkarthikeyan.bioinfoau.org/dapd.

Distinct patterns of heparan sulphate in pancreatic islets suggest novel roles in paracrine islet regulation

Heparan sulphate proteoglycans (HSPGs) exist in pancreatic beta cells, and HS seems to modulate important interactions in the islet microenvironment. However, the intra-islet structures of HS in health or altered glucose homeostasis are currently unknown. Here we show that distinct spatial distribution of HS motifs is present in islets in the adult, that intra-islet HS motifs are mostly conserved between rodents and humans, and that HS is abundant in glucagon producing islet alpha cells. In beta cells HS is characterised by 2-O, 6-O and N-sulphated moieties, whereas HS in alpha cells is N-acetylated, N-, and 2-O sulphated and low in 6-O groups. Differential expression of three HS modifying genes in alpha and beta cells was observed and may account for the different HS patterns. Furthermore, we found that FGF1 and FGF2 were present in alpha cells, whereas functional FGFRs exist in beta cells, but not in the alpha cell line aTC1-6, or in primary alpha cells in islets. FGF1 induced signalling was dependent on 2-O, and 6-O HS sulphation in beta cells, and HS desulphation reduced beta cell proliferation and potentiated oxidant induced apoptosis. In leptin resistant animals and in islets from streptozotocin treated rats there was a reduction in alpha cell HS expression. These data demonstrate the distinct HS expression patterns in alpha and beta islet cells and propose a novel role for alpha cells as a source of paracrine FGF ligands to neighbouring beta cells with specific cell-associated HS domains mediating the activation and diffusion of paracrine ligands.

VSEAMS: a pipeline for variant set enrichment analysis using summary GWAS data identifies IKZF3, BATF and ESRRA as key transcription factors in type 1 diabetes

MOTIVATION

Genome-wide association studies (GWAS) have identified many loci implicated in disease susceptibility. Integration of GWAS summary statistics (P-values) and functional genomic datasets should help to elucidate mechanisms.

RESULTS

We extended a non-parametric SNP set enrichment method to test for enrichment of GWAS signals in functionally defined loci to a situation where only GWAS P-values are available. The approach is implemented in VSEAMS, a freely available software pipeline. We use VSEAMS to identify enrichment of type 1 diabetes (T1D) GWAS associations near genes that are targets for the transcription factors IKZF3, BATF and ESRRA. IKZF3 lies in a known T1D susceptibility region, while BATF and ESRRA overlap other immune disease susceptibility regions, validating our approach and suggesting novel avenues of research for T1D.

AVAILABILITY AND IMPLEMENTATION

VSEAMS is available for download (http://github.com/ollyburren/vseams).

Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets

Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis, corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans, corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5, KCNJ11, HLA-DQA1, INS, PDX1 and GRB10. CpGs of significant cis-mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes (GPX7, GSTT1 and SNX19) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans.

Inter-individual variation in genetics and epigenetics affects biological processes and disease susceptibility. However, most studies have investigated genetic and epigenetic mechanisms independently and to uncover novel mechanisms affecting disease susceptibility there is a highlighted need to study interactions between these factors on a genome-wide scale. To identify novel loci affecting islet function and potentially diabetes, we performed the first genome-wide methylation quantitative trait locus (mQTL) analysis in human pancreatic islets including DNA methylation of 468,787 CpG sites located throughout the genome. Our results showed that DNA methylation of 11,735 CpGs in 4,504 unique genes is regulated by genetic factors located in cis (67,438 SNP-CpG pairs). Furthermore, significant mQTLs cover previously reported diabetes loci including KCNJ11, INS, HLA, PDX1 and GRB10. We also found mQTLs associated with gene expression and insulin secretion in human islets. By performing causality inference tests (CIT), we identified CpGs where DNA methylation potentially mediates the genetic impact on gene expression and insulin secretion. Our functional follow-up experiments further demonstrated that identified mQTLs/genes (GPX7, GSTT1 and SNX19) directly affect pancreatic β-cell function. Together, our study provides a detailed map of genome-wide associations between genetic and epigenetic variation, which affect gene expression and insulin secretion in human pancreatic islets.

A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed () with 12 of the 22 SNPs showing . Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, ), NRP1 (rs722988, ), BAD (rs694739, ), CTSB (rs1296023, ), FYN (rs11964650, ), UBE2G1 (rs9906760, ), MAP3K14 (rs17759555, ), ITGB1 (rs1557150, ), and IL7R (rs1445898, ). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available.

Hope for GWAS: relevant risk genes uncovered from GWAS statistical noise

Hundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.1) with any of these diseases are functionally connected beyond noise expectation. This functional coherence was used to identify disease-relevant subnetworks, which were shown to be enriched in known genes, outperforming the selection of top GWAS genes. As a proof of principle, we applied this approach to breast cancer, supporting well-known breast cancer genes, while pinpointing novel susceptibility genes for experimental validation. This study reinforces the idea that GWAS are under-analyzed and that missing heritability is rather hidden. It extends the use of protein networks to reveal this missing heritability, thus leveraging the large investment in GWAS that produced so far little tangible gain.

Effects of GWAS-associated genetic variants on lncRNAs within IBD and T1D candidate loci

Long non-coding RNAs are a new class of non-coding RNAs that are at the crosshairs in many human diseases such as cancers, cardiovascular disorders, inflammatory and autoimmune disease like Inflammatory Bowel Disease (IBD) and Type 1 Diabetes (T1D). Nearly 90% of the phenotype-associated single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) lie outside of the protein coding regions, and map to the non-coding intervals. However, the relationship between phenotype-associated loci and the non-coding regions including the long non-coding RNAs (lncRNAs) is poorly understood. Here, we systemically identified all annotated IBD and T1D loci-associated lncRNAs, and mapped nominally significant GWAS/ImmunoChip SNPs for IBD and T1D within these lncRNAs. Additionally, we identified tissue-specific cis-eQTLs, and strong linkage disequilibrium (LD) signals associated with these SNPs. We explored sequence and structure based attributes of these lncRNAs, and also predicted the structural effects of mapped SNPs within them. We also identified lncRNAs in IBD and T1D that are under recent positive selection. Our analysis identified putative lncRNA secondary structure-disruptive SNPs within and in close proximity (+/-5 kb flanking regions) of IBD and T1D loci-associated candidate genes, suggesting that these RNA conformation-altering polymorphisms might be associated with diseased-phenotype. Disruption of lncRNA secondary structure due to presence of GWAS SNPs provides valuable information that could be potentially useful for future structure-function studies on lncRNAs.

Improving prediction of type 1 diabetes by testing non-HLA genetic variants in addition to HLA markers

OBJECTIVE

The purpose of this study was to explore whether non-human leukocyte antigen (non-HLA) genetic markers can improve type 1 diabetes(T1D) prediction in a prospective cohort with high-risk HLA-DR,DQ genotypes.

METHODS

The Diabetes Autoimmunity Study in the Young (DAISY) follows prospectively for the development of T1D and islet autoimmunity (IA)children at increased genetic risk. A total of 1709 non-Hispanic White DAISY participants have been genotyped for 27 non-HLA single nucleotide polymorphisms (SNPs) and one microsatellite.

RESULTS

In multivariate analyses adjusting for family history and HLA-DR3/4 genotype, PTPN22 (rs2476601) and two UBASH3A (rs11203203 and rs9976767) SNPs were associated with development of IA [hazard ratio(HR)=1.87, 1.55, and 1.54, respectively, all p ≤ 0.003], while GLIS3 and IL2RA showed borderline association with development of IA. INS,UBASH3A, and IFIH1 were significantly associated with progression from IA to diabetes (HR=1.65, 1.44, and 1.47, respectively, all p ≤ 0.04), while PTPN22 and IL27 showed borderline association with progression from IA to diabetes. In survival analysis, 45% of general population DAISY children with PTPN22 rs2476601 TT or HLA-DR3/4 and UBASH3A rs11203203 AA developed diabetes by age 15, compared with 3% of children with all other genotypes (p<0.0001). Addition of non-HLA markers to HLA-DR3/4,DQ8 did not improve diabetes prediction in first-degree relatives.

CONCLUSION

Addition of PTPN22 and UBASH3A SNPs to HLA-DR,DQ genotyping can improve T1D risk prediction.

Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility

The insult leading to autoantibody development in children who will progress to develop type 1 diabetes (T1D) has remained elusive. To investigate the genes and molecular pathways in the pathogenesis of this disease, we performed genome-wide transcriptomics analysis on a unique series of prospective whole-blood RNA samples from at-risk children collected in the Finnish Type 1 Diabetes Prediction and Prevention study. We studied 28 autoantibody-positive children, out of which 22 progressed to clinical disease. Collectively, the samples covered the time span from before the development of autoantibodies (seroconversion) through the diagnosis of diabetes. Healthy control subjects matched for date and place of birth, sex, and HLA-DQB1 susceptibility were selected for each case. Additionally, we genotyped the study subjects with Immunochip to identify potential genetic variants associated with the observed transcriptional signatures. Genes and pathways related to innate immunity functions, such as the type 1 interferon (IFN) response, were active, and IFN response factors were identified as central mediators of the IFN-related transcriptional changes. Importantly, this signature was detected already before the T1D-associated autoantibodies were detected. Together, these data provide a unique resource for new hypotheses explaining T1D biology.

MicroRNA expression profiling and functional annotation analysis of their targets in patients with type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) results from an autoimmune attack against the insulin-producing pancreatic β-cells, leading to elimination of insulin production. The exact cause of this disorder is still unclear. Although the differential expression of microRNAs (miRNAs), small non-coding RNAs that control gene expression in a post-transcriptional manner, has been identified in many diseases, including T1DM, only scarce information exists concerning miRNA expression profile in T1DM. Thus, we employed the microarray technology to examine the miRNA expression profiles displayed by peripheral blood mononuclear cells (PBMCs) from T1DM patients compared with healthy subjects. Total RNA extracted from PBMCs from 11 T1DM patients and nine healthy subjects was hybridized onto Agilent human miRNA microarray slides (V3), 8x15K, and expression data were analyzed on R statistical environment. After applying the rank products statistical test, the receiver-operating characteristic (ROC) curves were generated and the areas under the ROC curves (AUC) were calculated. To examine the functions of the differentially expressed (p-value<0.01, percentage of false-positives <0.05) miRNAs that passed the AUC cutoff value ≥ 0.90, the database miRWalk was used to predict their potential targets, which were afterwards submitted to the functional annotation tool provided by the Database for Annotation, Visualization, and Integrated Discovery (DAVID), version 6.7, using annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We found 57 probes, corresponding to 44 different miRNAs (35 up-regulated and 9 down-regulated), that were differentially expressed in T1DM and passed the AUC threshold of 0.90. The hierarchical clustering analysis indicated the discriminatory power of those miRNAs, since they were able to clearly distinguish T1DM patients from healthy individuals. Target prediction indicated that 47 candidate genes for T1DM are potentially regulated by the differentially expressed miRNAs. After performing functional annotation analysis of the predicted targets, we observed 22 and 12 annotated KEGG pathways for the induced and repressed miRNAs, respectively. Interestingly, many pathways were enriched for the targets of both up- and down-regulated miRNAs and the majority of those pathways have been previously associated with T1DM, including many cancer-related pathways. In conclusion, our study indicated miRNAs that may be potential biomarkers of T1DM as well as provided new insights into the molecular mechanisms involved in this disorder.

Genetics of diabetes--are we missing the genes or the disease?

Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Several pathogenic processes are involved in the development of diabetes. These range from autoimmune destruction of the beta-cells of the pancreas with consequent insulin deficiency to abnormalities that result in resistance to insulin action (American Diabetes Association, 2011). The vast majority of cases of diabetes fall into two broad categories. In type 1 diabetes (T1D), the cause is an absolute deficiency of insulin secretion, whereas in type 2 diabetes (T2D), the cause is a combination of resistance to insulin action and an inadequate compensatory insulin secretory response. However, the subdivision into two main categories represents a simplification of the real situation, and research during the recent years has shown that the disease is much more heterogeneous than a simple subdivision into two major subtypes assumes. Worldwide prevalence figures estimate that there are 280 million diabetic patients in 2011 and more than 500 million in 2030 (http://www.diabetesatlas.org/). In Europe, about 6-8% of the population suffer from diabetes, of them about 90% has T2D and 10% T1D, thereby making T2D to the fastest increasing disease in Europe and worldwide. This epidemic has been ascribed to a collision between the genes and the environment. While our knowledge about the genes is clearly better for T1D than for T2D given the strong contribution of variation in the HLA region to the risk of T1D, the opposite is the case for T2D, where our knowledge about the environmental triggers (obesity, lack of exercise) is much better than the understanding of the underlying genetic causes. This lack of knowledge about the underlying genetic causes of diabetes is often referred to as missing heritability (Manolio et al., 2009) which exceeds 80% for T2D but less than 25% for T1D. In the following review, we will discuss potential sources of this missing heritability which also includes the possibility that our definition of diabetes and its subgroups is imprecise and thereby making the identification of genetic causes difficult.

Statistical testing of shared genetic control for potentially related traits

Integration of data from genome‐wide single nucleotide polymorphism (SNP) association studies of different traits should allow researchers to disentangle the genetics of potentially related traits within individually associated regions. Formal statistical colocalisation testing of individual regions requires selection of a set of SNPs summarising the association in a region. We show that the SNP selection method greatly affects type 1 error rates, with published studies having used methods expected to result in substantially inflated type 1 error rates. We show that either avoiding variable selection and instead testing the most informative principal components or integrating over variable selection using Bayesian model averaging can help control type 1 error rates. Application to data from Graves' disease and Hashimoto's thyroiditis reveals a common genetic signature across seven regions shared between the diseases, and indicates that in five of six regions associated with Graves' disease and not Hashimoto's thyroiditis, this more likely reflects genuine absence of association with the latter rather than lack of power. Our examination, by simulation, of the performance of colocalisation tests and associated software will foster more widespread adoption of formal colocalisation testing. Given the increasing availability of large expression and genetic association datasets from disease‐relevant tissue and purified cell populations, coupled with identification of regulatory sequences by projects such as ENCODE, colocalisation analysis has the potential to reveal both shared genetic signatures of related traits and causal disease genes and tissues.

Advances in our understanding of the pathophysiology of Type 1 diabetes: lessons from the NOD mouse

T1D (Type 1 diabetes) is an autoimmune disease caused by the immune-mediated destruction of pancreatic β-cells. Studies in T1D patients have been limited by the availability of pancreatic samples, a protracted pre-diabetic phase and limitations in markers that reflect β-cell mass and function. The NOD (non-obese diabetic) mouse is currently the best available animal model of T1D, since it develops disease spontaneously and shares many genetic and immunopathogenic features with human T1D. Consequently, the NOD mouse has been extensively studied and has made a tremendous contribution to our understanding of human T1D. The present review summarizes the key lessons from NOD mouse studies concerning the genetic susceptibility, aetiology and immunopathogenic mechanisms that contribute to autoimmune destruction of β-cells. Finally, we summarize the potential and limitations of immunotherapeutic strategies, successful in NOD mice, now being trialled in T1D patients and individuals at risk of developing T1D.

TGF-β superfamily member Nodal stimulates human β-cell proliferation while maintaining cellular viability

In an effort to expand human islets and enhance allogeneic islet transplant for the treatment of type 1 diabetes, identifying signaling pathways that stimulate human β-cell proliferation is paramount. TGF-β superfamily members, in particular activin-A, are likely involved in islet development and may contribute to β-cell proliferation. Nodal, another TGF-β member, is present in both embryonic and adult rodent islets. Nodal, along with its coreceptor, Cripto, are pro-proliferative factors in certain cell types. Although Nodal stimulates apoptosis of rat insulinoma cells (INS-1), Nodal and Cripto signaling have not been studied in the context of human islets. The current study investigated the effects of Nodal and Cripto on human β-cell proliferation, differentiation, and viability. In the human pancreas and isolated human islets, we observed Nodal mRNA and protein expression, with protein expression observed in β and α-cells. Cripto expression was absent from human islets. Furthermore, in cultured human islets, exogenous Nodal stimulated modest β-cell proliferation and inhibited α-cell proliferation with no effect on cellular viability, apoptosis, or differentiation. Nodal stimulated the phosphorylation of mothers against decapentaplegic (SMAD)-2, with no effect on AKT or MAPK signaling, suggesting phosphorylated SMAD signaling was involved in β-cell proliferation. Cripto had no effect on human islet cell proliferation, differentiation, or viability. In conclusion, Nodal stimulates human β-cell proliferation while maintaining cellular viability. Nodal signaling warrants further exploration to better understand and enhance human β-cell proliferative capacity.

Type 1 diabetes: primary antigen/peptide/register/trimolecular complex

Type 1A diabetes (autoimmune) is now immunologically predictable in man, but preventable only in animal models. What triggers the development of autoimmunity in genetically susceptible individuals remains unknown. Studies of non-obese diabetic (NOD) mice reveal that interactions between T-cell receptors of diabetogenic T cell and an MHC class II loaded with an autoantigen are key determinates of the disease. With insulin as the primary target in the NOD mouse, likely man, and possibly the RT1-U rat models, therapeutic targeting of the components of these anti-insulin trimolecular complexes we believe provide a fulcrum for development of preventive therapy. In particular for the NOD mouse model, there is extensive evidence that the dominant insulin peptide driving disease initiation is insulin B chain amino acids 9-23 (SHLVEALYLVCGERG) recognized predominantly by germ-line sequences of a specific T-cell receptor Valpha (TRAV5D-4), and small molecules or monoclonal antibodies directed at this recognition complex can prevent diabetes.

The non-obese diabetic mouse sequence, annotation and variation resource: an aid for investigating type 1 diabetes

Model organisms are becoming increasingly important for the study of complex diseases such as type 1 diabetes (T1D). The non-obese diabetic (NOD) mouse is an experimental model for T1D having been bred to develop the disease spontaneously in a process that is similar to humans. Genetic analysis of the NOD mouse has identified around 50 disease loci, which have the nomenclature Idd for insulin-dependent diabetes, distributed across at least 11 different chromosomes. In total, 21 Idd regions across 6 chromosomes, that are major contributors to T1D susceptibility or resistance, were selected for finished sequencing and annotation at the Wellcome Trust Sanger Institute. Here we describe the generation of 40.4 mega base-pairs of finished sequence from 289 bacterial artificial chromosomes for the NOD mouse. Manual annotation has identified 738 genes in the diabetes sensitive NOD mouse and 765 genes in homologous regions of the diabetes resistant C57BL/6J reference mouse across 19 candidate Idd regions. This has allowed us to call variation consequences between homologous exonic sequences for all annotated regions in the two mouse strains. We demonstrate the importance of this resource further by illustrating the technical difficulties that regions of inter-strain structural variation between the NOD mouse and the C57BL/6J reference mouse can cause for current next generation sequencing and assembly techniques. Furthermore, we have established that the variation rate in the Idd regions is 2.3 times higher than the mean found for the whole genome assembly for the NOD/ShiLtJ genome, which we suggest reflects the fact that positive selection for functional variation in immune genes is beneficial in regard to host defence. In summary, we provide an important resource, which aids the analysis of potential causative genes involved in T1D susceptibility.

Database URLs:http://www.sanger.ac.uk/resources/mouse/nod/; http://vega-previous.sanger.ac.uk/info/data/mouse_regions.html

Fibroblast growth factor receptor like-1 (FGFRL1) interacts with SHP-1 phosphatase at insulin secretory granules and induces beta-cell ERK1/2 protein activation

FGFRL1 is a newly identified member of the fibroblast growth factor receptor (FGFR) family expressed in adult pancreas. Unlike canonical FGFRs that initiate signaling via tyrosine kinase domains, the short intracellular sequence of FGFRL1 consists of a putative Src homology domain-2 (SH2)-binding motif adjacent to a histidine-rich C terminus. As a consequence of nonexistent kinase domains, FGFRL1 has been postulated to act as a decoy receptor to inhibit canonical FGFR ligand-induced signaling. In pancreatic islet beta-cells, canonical FGFR1 signaling affects metabolism and insulin processing. This study determined beta-cell expression of FGFRL1 as well as consequent effects on FGFR1 signaling and biological responses. We confirmed FGFRL1 expression at the plasma membrane and within distinct intracellular granules of both primary beta-cells and βTC3 cells. Fluorescent protein-tagged FGFRL1 (RL1) induced a significant ligand-independent increase in MAPK signaling. Removal of the histidine-rich domain (RL1-ΔHis) or entire intracellular sequence (RL1-ΔC) resulted in greater retention at the plasma membrane and significantly reduced ligand-independent ERK1/2 responses. The SHP-1 phosphatase was identified as an RL1-binding substrate. Point mutation of the SH2-binding motif reduced the ability of FGFRL1 to bind SHP-1 and activate ERK1/2 but did not affect receptor localization to insulin secretory granules. Finally, overexpression of RL1 increased cellular insulin content and matrix adhesion. Overall, these data suggest that FGFRL1 does not function as a decoy receptor in beta-cells, but rather it enhances ERK1/2 signaling through association of SHP-1 with the receptor's intracellular SH2-binding motif.

Defining the Sequence Elements and Candidate Genes for the Coloboma Mutation

The chicken coloboma mutation exhibits features similar to human congenital developmental malformations such as ocular coloboma, cleft-palate, dwarfism, and polydactyly. The coloboma-associated region and encoded genes were investigated using advanced genomic, genetic, and gene expression technologies. Initially, the mutation was linked to a 990 kb region encoding 11 genes; the application of the genetic and genomic tools led to a reduction of the linked region to 176 kb and the elimination of 7 genes. Furthermore, bioinformatics analyses of capture array-next generation sequence data identified genetic elements including SNPs, insertions, deletions, gaps, chromosomal rearrangements, and miRNA binding sites within the introgressed causative region relative to the reference genome sequence. Coloboma-specific variants within exons, UTRs, and splice sites were studied for their contribution to the mutant phenotype. Our compiled results suggest three genes for future studies. The three candidate genes, SLC30A5 (a zinc transporter), CENPH (a centromere protein), and CDK7 (a cyclin-dependent kinase), are differentially expressed (compared to normal embryos) at stages and in tissues affected by the coloboma mutation. Of these genes, two (SLC30A5 and CENPH) are considered high-priority candidate based upon studies in other vertebrate model systems.

Genetic analysis of type 1 diabetes: embryonic stem cells as new tools to unlock biological mechanisms in type 1 diabetes

The nonobese diabetic (NOD) mouse has provided an important animal model for studying the mechanism and genetics of type 1 diabetes over the past 30 years. Arguably, the bio-breeding (BB) rat model may be an even closer phenotypic mimic of the typical human disease. A large number of distinct genetic traits which influence diabetes development have been defined through an extraordinary effort, most conspicuously in the mouse model. However, in both NOD and BB models the lack of availability of robust means for experimental genetic manipulation has restricted our understanding of the mechanisms underlying this spontaneous autoimmune disease. Recent developments in the derivation of embryonic stem (ES) cells have the potential to transform this picture. We argue here that targeting of NOD strain ES cells can bring much needed certainty to our present understanding of the genetics of type 1 diabetes in the NOD mouse. In addition, ES cells can play important roles in the future, in both the NOD mouse and BB rat models, through the generation of new tools to investigate the mechanisms by which genetic variation acts to promote diabetes.

Genetics of canine diabetes mellitus: are the diabetes susceptibility genes identified in humans involved in breed susceptibility to diabetes mellitus in dogs?

Diabetes mellitus is a common endocrinopathy in companion animals, characterised by hyperglycaemia, glycosuria and weight loss, resulting from an absolute or relative deficiency in the pancreatic hormone insulin. There are breed differences in susceptibility to diabetes mellitus in dogs, with the Samoyed breed being overrepresented, while Boxers are relatively absent in the UK population of diabetic dogs, suggesting that genetic factors play an important role in determining susceptibility to the disease. A number of genes, linked with susceptibility to diabetes mellitus in humans, are associated with an increased risk of diabetes mellitus in dogs, some of which appear to be relatively breed-specific. Diabetes mellitus in dogs has been associated with major histocompatibility complex (MHC) class II genes (dog leucocyte antigen; DLA), with similar haplotypes and genotypes being identified in the most susceptible breeds. A region containing a variable number of tandem repeats (VNTR) and several polymorphisms have been identified in the canine insulin gene, with some alleles associated with susceptibility or resistance to diabetes mellitus in a breed-specific manner. Polymorphisms in the canine CTLA4 promoter and in other immune response genes are associated with susceptibility to diabetes mellitus in a number of pedigree breeds. Genome wide association studies are currently underway that should shed further light on the genetic factors responsible for the breed profile seen in the diabetic dog population.

Autologous regulatory T cells for the treatment of type 1 diabetes

The immune system is tasked with defending the host from a wide array of pathogens and environmental insults. When uncontrolled, this endeavor may lead to off-target reactivity to self-tissues resulting in multiple autoimmune diseases including type 1 diabetes (T1D). This multifactorial disease process involves over 40 susceptibility genes and is influenced by poorly characterized environmental factors. While many questions regarding the pathogenesis of the disease process remain, it has become increasingly clear that the progression to disease results from a breakdown in the processes that maintain peripheral immune tolerance. The end result of this process is localized tissue inflammation, islet dysfunction, and ultimately the destruction of pancreatic β cells due to concomitant defects in innate and adaptive immune responses. A number of immunomodulatory intervention trials have now been conducted in patients at risk for or with recent onset T1D, often with the goal of restoring immune tolerance by inducing regulatory T cells (Tregs). Unfortunately, many of these trials have fallen short of inducing persistent immune regulation. This shortfall has led to additional efforts to more directly shift the balance from destructive effector T cell (Teff) responses to favor Tregs, including the use of autologous Treg cell therapy. In this review we will discuss key concepts related to the use of autologous Treg cell therapy for the treatment of T1D. Among these topics, we will discuss the notions of genetic control of Treg activity, Treg cellular plasticity, and requirements for antigen-specificity.