Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes distinguishes markers of disease and C-peptide trajectory.

AIMS/HYPOTHESIS: There is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs). METHODS: Selected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years (n=86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs (n=194). RESULTS: Eleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family. CONCLUSIONS/INTERPRETATION: The association of several targeted proteins with fasting C-peptide/glucose levels in the first year after diagnosis suggests their connection with the underlying changes accompanying alterations in beta cell function in type 1 diabetes. Moreover, the direction of change in GPX3 during the first year was indicative of subsequent fasting C-peptide/glucose levels, and supports further investigation of this and other serum protein measurements in future studies of beta cell function in type 1 diabetes.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium.

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants' clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. CONCLUSIONS/INTERPRETATION: The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes.

Genetic Risk Score Modelling for Disease Progression in New-Onset Type 1 Diabetes Patients: Increased Genetic Load of Islet-Expressed and Cytokine-Regulated Candidate Genes Predicts Poorer Glycemic Control.

Genome-wide association studies (GWAS) have identified over 40 type 1 diabetes risk loci. The clinical impact of these loci on ß-cell function during disease progression is unknown. We aimed at testing whether a genetic risk score could predict glycemic control and residual ß-cell function in type 1 diabetes (T1D). As gene expression may represent an intermediate phenotype between genetic variation and disease, we hypothesized that genes within T1D loci which are expressed in islets and transcriptionally regulated by proinflammatory cytokines would be the best predictors of disease progression. Two-thirds of 46 GWAS candidate genes examined were expressed in human islets, and 11 of these significantly changed expression levels following exposure to proinflammatory cytokines (IL-1ß + IFNγ + TNFα) for 48 h. Using the GWAS single nucleotide polymorphisms (SNPs) from each locus, we constructed a genetic risk score based on the cumulative number of risk alleles carried in children with newly diagnosed T1D. With each additional risk allele carried, HbA1c levels increased significantly within first year after diagnosis. Network and gene ontology (GO) analyses revealed that several of the 11 candidate genes have overlapping biological functions and interact in a common network. Our results may help predict disease progression in newly diagnosed children with T1D which can be exploited for optimizing treatment.

A20 Inhibits ß-Cell Apoptosis by Multiple Mechanisms and Predicts Residual ß-Cell Function in Type 1 Diabetes.

Activation of the transcription factor nuclear factor kappa B (NFkB) contributes to ß-cell death in type 1 diabetes (T1D). Genome-wide association studies have identified the gene TNF-induced protein 3 (TNFAIP3), encoding for the zinc finger protein A20, as a susceptibility locus for T1D. A20 restricts NF-κB signaling and has strong antiapoptotic activities in ß-cells. Although the role of A20 on NF-κB inhibition is well characterized, its other antiapoptotic functions are largely unknown. By studying INS-1E cells and rat dispersed islet cells knocked down or overexpressing A20 and islets isolated from the ß-cell-specific A20 knockout mice, we presently demonstrate that A20 has broader effects in ß-cells that are not restricted to inhibition of NF-κB. These involves, suppression of the proapoptotic mitogen-activated protein kinase c-Jun N-terminal kinase (JNK), activation of survival signaling via v-akt murine thymoma viral oncogene homolog (Akt) and consequently inhibition of the intrinsic apoptotic pathway. Finally, in a cohort of T1D children, we observed that the risk allele of the rs2327832 single nucleotide polymorphism of TNFAIP3 predicted lower C-peptide and higher hemoglobin A1c (HbA1c) levels 12 months after disease onset, indicating reduced residual ß-cell function and impaired glycemic control. In conclusion, our results indicate a critical role for A20 in the regulation of ß-cell survival and unveil novel mechanisms by which A20 controls ß-cell fate. Moreover, we identify the single nucleotide polymorphism rs2327832 of TNFAIP3 as a possible prognostic marker for diabetes outcome in children with T1D.

The genetic and regulatory architecture of ERBB3-type 1 diabetes susceptibility locus.

The study aimed to explore the role of ERBB3 in type 1 diabetes (T1D). We examined whether genetic variation of ERBB3 (rs2292239) affects residual ß-cell function in T1D cases. Furthermore, we examined the expression of ERBB3 in human islets, the effect of ERBB3 knockdown on apoptosis in insulin-producing INS-1E cells and the genetic and regulatory architecture of the ERBB3 locus to provide insights to how rs2292239 may confer disease susceptibility. rs2292239 strongly correlated with residual ß-cell function and metabolic control in children with T1D. ERBB3 locus associated lncRNA (NONHSAG011351) was found to be expressed in human islets. ERBB3 was expressed and down-regulated by pro-inflammatory cytokines in human islets and INS-1E cells; knockdown of ERBB3 in INS-1E cells decreased basal and cytokine-induced apoptosis. Our data suggests an important functional role of ERBB3 and its potential regulators in the ß-cells and may constitute novel targets to prevent ß-cell destruction in T1D.

Genetic Determinants of Enterovirus Infections: Polymorphisms in Type 1 Diabetes and Innate Immune Genes in the MIDIA Study.

Enteroviruses have been suggested as triggers of type 1 diabetes (T1D). We aimed to assess whether established T1D susceptibility single nucleotide polymorphisms (SNPs) and candidate SNPs in innate immune genes were associated with the frequency of enterovirus infection in otherwise healthy children. Fifty-six established T1D SNPs and 97 other candidate immunity SNPs were typed in 419 children carrying the T1D high-risk genotype, HLA-DR4-DQ8/DR3-DQ2 genotype, and 373 children without this genotype. Enteroviral RNA was detected using real-time polymerase chain reaction, with primers detecting essentially all enterovirus serotypes, in 7,393 longitudinal stool samples collected monthly (age range 3-36 months). The most significant association was with two T1D SNPs, rs12150079 (ZPBP2/ORMDL3/GSDMB region) (enterovirus frequency: AA 7.3%, AG 8.7%, GG 9.7%, RR = 0.86, overall p = 1.87E-02) and rs229541 (C1QTNF6/SSTR3/RAC2) (enterovirus frequency: CC 7.8%, CT 9.7%, TT 9.4%, RR = 1.13, overall p = 3.6E-02), followed by TLR8 (rs2407992) (p = 3.8E-02), TLR3 (1914926) (p = 4.9E-02), and two other T1D SNPs (IFIH1 rs3747517, p = 4.9E-02 and PTPN22, rs2476601, p = 5.3E-02). However, the quantile-quantile plot of p-values with confidence intervals for all 153 SNPs did not reveal clear evidence for rejection of the complete null hypothesis. Among a number of SNPs in candidate genes, we found no evidence for strong associations with enterovirus presence in stool samples from Norwegian children.

Shared Genetic Basis for Type 1 Diabetes, Islet Autoantibodies, and Autoantibodies Associated With Other Immune-Mediated Diseases in Families With Type 1 Diabetes.

Type 1 diabetes (T1D) is a polygenic autoimmune disease that is often present with autoantibodies directed against pancreatic islet proteins. Many genetic susceptibility loci are shared with other autoimmune or immune-mediated diseases that also cosegregate in families with T1D. The aim of this study was to investigate whether susceptibility loci identified in genome-wide association studies (GWAS) of T1D were also associated with autoantibody positivity in individuals with diabetes. Fifty single nucleotide polymorphisms (SNPs) were genotyped in 6,556 multiethnic cases collected by the Type 1 Diabetes Genetics Consortium (T1DGC). These were tested for association with three islet autoantibodies-against autoantibodies to GAD (GADA), IA-2 (IA-2A), and zinc transporter 8 (ZnT8A)-and autoantibodies against thyroid peroxidase (TPOA) in autoimmune thyroid disease, gastric parietal cells (PCA) in autoimmune gastritis, transglutaminase (TGA) in celiac disease, and 21-hydroxylase (21-OHA) in autoimmune hypoadrenalism. In addition to the MHC region, we identify SNPs in five susceptibility loci (IFIH1, PTPN22, SH2B3, BACH2, and CTLA4) as significantly associated with more than one autoantibody at a false discovery rate less than 5%. IFIH1/2q24 demonstrated the most unrestricted association, as significant association was demonstrated for PCA, TPOA, GADA, 21-OHA, and IA-2A. In addition, 11 loci were significantly associated with a single autoantibody.

Novel Association Between Immune-Mediated Susceptibility Loci and Persistent Autoantibody Positivity in Type 1 Diabetes.

Islet autoantibodies detected at disease onset in patients with type 1 diabetes are signs of an autoimmune destruction of the insulin-producing ß-cells. To further investigate the genetic determinants of autoantibody positivity, we performed dense immune-focused genotyping on the Immunochip array and tested for association with seven disease-specific autoantibodies in a large cross-sectional cohort of 6,160 type 1 diabetes-affected siblings. The genetic association with positivity for GAD autoantibodies (GADAs), IA2 antigen (IA-2A), zinc transporter 8, thyroid peroxidase, gastric parietal cells (PCAs), tissue transglutaminase, and 21-hydroxylase was tested using a linear mixed-model regression approach to simultaneously control for population structure and family relatedness. Four loci were associated with autoantibody positivity at genome-wide significance. Positivity for GADA was associated with 3q28/LPP, for IA-2A with 1q23/FCRL3 and 11q13/RELA, and for PCAs with 2q24/IFIH1. The 3q28 locus showed association after only 3 years duration and might therefore be a marker of persistent GADA positivity. The 1q23, 11q13, and 2q24 loci were associated with autoantibodies close to diabetes onset and constitute candidates for early screening. Major susceptibility loci for islet autoantibodies are separate from type 1 diabetes risk, which may have consequences for intervention strategies to reduce autoimmunity.

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.