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Ageing is associated with molecular signatures of inflammation and type 2 diabetes in rat pancreatic islets.

ABSTRACT: AIMS/HYPOTHESIS:Ageing is a major risk factor for development of metabolic diseases such as type 2 diabetes. Identification of the mechanisms underlying this association could help to elucidate the relationship between age-associated progressive loss of metabolic health and development of type 2 diabetes. We aimed to determine molecular signatures during ageing in the endocrine pancreas. METHODS:Global gene transcription was measured in pancreatic islets isolated from young and old rats by Ilumina BeadChip arrays. Promoter DNA methylation was measured by Sequenom MassArray in 46 genes that showed differential expression with age, and correlations with expression were established. Alterations in morphological and cellular processes with age were determined by immunohistochemical methods. RESULTS:Age-related changes in gene expression were found at 623 loci (>1.5-fold, false discovery rate [FDR] <5%), with a significant (FDR?

SUBMITTER: Sandovici I

PROVIDER: S-EPMC4742511 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Ageing is associated with molecular signatures of inflammation and type 2 diabetes in rat pancreatic islets.

Sandovici Ionel I Hammerle Constanze M CM Cooper Wendy N WN Smith Noel H NH Tarry-Adkins Jane L JL Dunmore Benjamin J BJ Bauer Julien J Andrews Simon R SR Yeo Giles S H GS Ozanne Susan E SE Constância Miguel M

Diabetologia 20151223 3

<h4>Aims/hypothesis</h4>Ageing is a major risk factor for development of metabolic diseases such as type 2 diabetes. Identification of the mechanisms underlying this association could help to elucidate the relationship between age-associated progressive loss of metabolic health and development of type 2 diabetes. We aimed to determine molecular signatures during ageing in the endocrine pancreas.<h4>Methods</h4>Global gene transcription was measured in pancreatic islets isolated from young and ol ...[more]

PMID: 26699651

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Project description:BackgroundThe Goto-Kakizaki (GK) rat is a well-studied non-obese spontaneous type 2 diabetes (T2D) animal model characterized by impaired glucose-stimulated insulin secretion (GSIS) in the pancreatic beta cells. MicroRNAs (miRNAs) are short regulatory RNAs involved in many fundamental biological processes. We aim to identify miRNAs that are differentially-expressed in the pancreatic islets of the GK rats and investigate both their short- and long term glucose-dependence during glucose-stimulatory conditions.Methodology/principal findingsGlobal profiling of 348 miRNAs in the islets of GK rats and Wistar controls (females, 60 days, N = 6 for both sets) using locked nucleic acid (LNA)-based microarrays allowed for the clear separation of the two groups. Significant analysis of microarrays (SAM) identified 30 differentially-expressed miRNAs, 24 of which are predominantly upregulated in the GK rat islets. Monitoring of qPCR-validated miRNAs during GSIS experiments on isolated islets showed disparate expression trajectories between GK and controls indicating distinct short- and long-term glucose dependence. We specifically found expression of rno-miR-130a, rno-miR-132, rno-miR-212 and rno-miR-335 to be regulated by hyperglycaemia. The putative targets of upregulated miRNAs in the GK, filtered with glucose-regulated mRNAs, were found to be enriched for insulin-secretion genes known to be downregulated in T2D patients. Finally, the binding of rno-miR-335 to a fragment of the 3'UTR of one of known down-regulated exocytotic genes in GK islets, Stxbp1 was shown by luciferase assay.Conclusions/significanceThe perturbed miRNA network found in the GK rat islets is indicative of a system-wide impairment in the regulation of genes important for the normal functions of pancreatic islets, particularly in processes involving insulin secretion during glucose stimulatory conditions. Our findings suggest that the reduced insulin secretion observed in the GK rat may be partly due to upregulated miRNA expression leading to decreased production of key proteins of the insulin exocytotic machinery.

Project description:AimsThe transcriptome of different dissociated pancreatic islet cells has been described in enzymatically isolated islets in both health and disease. However, the isolation, culturing, and dissociation procedures likely affect the transcriptome profiles, distorting the biological conclusions. The aim of the current study was to characterize the cells of the islets of Langerhans from subjects with and without type 1 diabetes in a way that reflects the in vivo situation to the highest possible extent.MethodsIslets were excised using laser capture microdissection directly from frozen pancreatic tissue sections obtained from organ donors with (n = 7) and without (n = 8) type 1 diabetes. Transcriptome analysis of excised samples was performed using AmpliSeq. Consecutive pancreatic sections were used to estimate the proportion of beta-, alpha-, and delta cells using immunofluorescence and to examine the presence of CD31 positive endothelial regions using immunohistochemistry.ResultsThe proportion of beta cells in islets from subjects with type 1 diabetes was reduced to 0% according to both the histological and transcriptome data, and several alterations in the transcriptome were derived from the loss of beta cells. In total, 473 differentially expressed genes were found in the islets from subjects with type 1 diabetes. Functional enrichment analysis showed that several of the most upregulated gene sets were related to vasculature and angiogenesis, and histologically, vascular density was increased in subjects with type 1 diabetes. Downregulated in type 1 diabetes islets was the gene set epithelial mesenchymal transition.ConclusionA number of transcriptional alterations are present in islets from subjects with type 1 diabetes. In particular, several gene sets related to vasculature and angiogenesis are upregulated and there is an increased vascular density, suggesting an altered microvasculature in islets from subjects with type 1 diabetes. By studying pancreatic islets extracted directly from snap-frozen pancreatic tissue, this study reflects the in vivo situation to a high degree and gives important insights into islet pathophysiology in type 1 diabetes.

Project description:ObjectiveType 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that encode genetic predisposition. More than 90% of associated single-nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity.MethodsWe present genome-wide single-cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell combinatorial indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on U-Net architecture to accurately predict open chromatin peak calls in rare cell populations.ResultsWe show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, T2D GWAS SNPs are significantly enriched in beta cell-specific and across cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals.ConclusionsCollectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways.

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Ageing is associated with molecular signatures of inflammation and type 2 diabetes in rat pancreatic islets.

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Ageing is associated with molecular signatures of inflammation and type 2 diabetes in rat pancreatic islets.

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