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Aims: Heterogeneity in the rate of β‐cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease‐modifying clinical trials. Integrative analyses of baseline multi‐omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis. Methods: We collected samples in a pan‐European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi‐Omics Factor Analysis to identify molecular signatures correlating with post‐diagnosis decline in β‐cell mass measured as fasting C‐peptide. Results: Two molecular signatures were significantly correlated with fasting C‐peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non‐lymphoid cell interactions and G‐protein coupled receptor signalling events that were inversely associated with a rapid decline in β‐cell function. The second signature was related to translation and viral infection was inversely associated with change in β‐cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid β‐cell decline. Conclusions: Features that differ between individuals with slow and rapid decline in β‐cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have identified over 40 type 1 diabetes risk loci. The clinical impact of these loci on β-cell function during disease progression is unknown. We aimed at testing whether a genetic risk score could predict glycemic control and residual β-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-1β + 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. [ABSTRACT FROM AUTHOR]

Background: The incidence of type 1 diabetes mellitus (T1DM) is increasing globally, and as a consequence, more patients are affected by microvascular complications such as diabetic retinopathy (DR). The aim of this study was to elucidate possible associations between diabetes-related single-nucleotide polymorphisms (SNP) and the development of DR. Methods: Three hundred and thirty-nine patients with T1DM from the Danish Cohort of Pediatric Diabetes 1987 (DCPD1987) went through an ophthalmic examination in 1995; 185 of these were reexamined in 2011. The development of DR was assessed by comparison of overall DR level between baseline and follow-up in the worst eye at baseline. Patients were graded on a modified version of the Early Treatment Diabetic Retinopathy Study (ETDRS) scale, and 20 SNPs were genotyped in 130 of the 185 patients. Results: We found the CTSH/rs3825932 variant (C > T) was associated with reduced risk of progression to proliferative diabetic retinopathy (PDR) (OR [95 % CI] = 0.20 [0.07-0.56], p = 2.4 × 10, p = 0.048) and ERBB3/rs2292239 variant (G > T) associated with increased risk of two-step progression (OR [95 % CI] = 2.76 [1.31-5.80], p = 7.5 × 10, p = 0.15). The associations were independent of other known risk factors, such as HbA1c, sex, and diastolic blood pressure. Conclusion: In conclusion, CTSH/rs3825932 and ERBB3/rs2292239 SNPs were associated with reduced risk of progression to PDR and two-step progression of DR on the ETDRS scale accordingly. The variant CTSH remained statistically significant after adjusting for multiple testing. Our results suggest an overlap between genetic variants that confer risk of T1DM and progression of DR. [ABSTRACT FROM AUTHOR]