MicroRNAs in cardiac arrhythmia: DNA sequence variation of MiR-1 and MiR-133A in long QT syndrome.

Long QT syndrome (LQTS) is a genetic cardiac condition associated with prolonged ventricular repolarization, primarily a result of perturbations in cardiac ion channels, which predisposes individuals to life-threatening arrhythmias. Using DNA screening and sequencing methods, over 700 different LQTS-causing mutations have been identified in 13 genes worldwide. Despite this, the genetic cause of 30-50% of LQTS is presently unknown. MicroRNAs (miRNAs) are small (∼ 22 nucleotides) noncoding RNAs which post-transcriptionally regulate gene expression by binding complementary sequences within messenger RNAs (mRNAs). The human genome encodes over 1800 miRNAs, which target about 60% of human genes. Consequently, miRNAs are likely to regulate many complex processes in the body, indeed aberrant expression of various miRNA species has been implicated in numerous disease states, including cardiovascular diseases. MiR-1 and MiR-133A are the most abundant miRNAs in the heart and have both been reported to regulate cardiac ion channels. We hypothesized that, as a consequence of their role in regulating cardiac ion channels, genetic variation in the genes which encode MiR-1 and MiR-133A might explain some cases of LQTS. Four miRNA genes (miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2), which encode MiR-1 and MiR-133A, were sequenced in 125 LQTS probands. No genetic variants were identified in miR-1-1 or miR-133a-1; but in miR-1-2 we identified a single substitution (n.100A> G) and in miR-133a-2 we identified two substitutions (n.-19G> A and n.98C> T). None of the variants affect the mature miRNA products. Our findings indicate that sequence variants of miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2 are not a cause of LQTS in this cohort

Differential Glucose-Regulation of MicroRNAs in Pancreatic Islets of Non-Obese Type 2 Diabetes Model Goto-Kakizaki Rat

The 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

Global microRNA expression profiles in insulin target tissues in a spontaneous rat model of type 2 diabetes

AIMS/HYPOTHESIS: MicroRNAs regulate a broad range of biological mechanisms. To investigate the relationship between microRNA expression and type 2 diabetes, we compared global microRNA expression in insulin target tissues from three inbred rat strains that differ in diabetes susceptibility. METHODS: Using microarrays, we measured the expression of 283 microRNAs in adipose, liver and muscle tissue from hyperglycaemic (Goto-Kakizaki), intermediate glycaemic (Wistar Kyoto) and normoglycaemic (Brown Norway) rats (n = 5 for each strain). Expression was compared across strains and validated using quantitative RT-PCR. Furthermore, microRNA expression variation in adipose tissue was investigated in 3T3-L1 adipocytes exposed to hyperglycaemic conditions. RESULTS: We found 29 significantly differentiated microRNAs (p(adjusted) < 0.05): nine in adipose tissue, 18 in liver and two in muscle. Of these, five microRNAs had expression patterns that correlated with the strain-specific glycaemic phenotype. MiR-222 (p(adjusted) = 0.0005) and miR-27a (p(adjusted) = 0.006) were upregulated in adipose tissue; miR-195 (p(adjusted) = 0.006) and miR-103 (p(adjusted) = 0.04) were upregulated in liver; and miR-10b (p(adjusted) = 0.004) was downregulated in muscle. Exposure of 3T3-L1 adipocytes to increased glucose concentration upregulated the expression of miR-222 (p = 0.008), miR-27a (p = 0.02) and the previously reported miR-29a (p = 0.02). Predicted target genes of these differentially expressed microRNAs are involved in pathways relevant to type 2 diabetes. CONCLUSION: The expression patterns of miR-222, miR-27a, miR-195, miR-103 and miR-10b varied with hyperglycaemia, suggesting a role for these microRNAs in the pathophysiology of type 2 diabetes, as modelled by the Gyoto-Kakizaki rat. We observed similar patterns of expression of miR-222, miR-27a and miR-29a in adipocytes as a response to increased glucose levels, which supports our hypothesis that altered expression of microRNAs accompanies primary events related to the pathogenesis of type 2 diabetes

The Promise and Challenge of Therapeutic MicroRNA Silencing in Diabetes and Metabolic Diseases

MicroRNAs (miRNAs) are small, non-coding, RNA molecules that regulate gene expression. They have a long evolutionary history and are found in plants, viruses, and animals. Although initially discovered in 1993 in Caenorhabditis elegans, they were not appreciated as widespread and abundant gene regulators until the early 2000s. Studies in the last decade have found that miRNAs confer phenotypic robustness in the face of environmental perturbation, may serve as diagnostic and prognostic indicators of disease, underlie the pathobiology of a wide array of complex disorders, and represent compelling therapeutic targets. Pre-clinical studies in animal models have demonstrated that pharmacologic manipulation of miRNAs, mostly in the liver, can modulate metabolic phenotypes and even reverse the course of insulin resistance and diabetes. There is cautious optimism in the field about miRNA-based therapies for diabetes, several of which are already in various stages of clinical trials. This review will highlight both the promise and the most pressing challenges of therapeutic miRNA silencing in diabetes and related conditions

The CEACAM1 expression is decreased in the liver of severely obese patients with or without diabetes

<p>Abstract</p> <p>Background</p> <p>Type 2 diabetes is mainly caused by insulin resistance. The carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is an important candidate for causing insulin resistance.</p> <p>Methods</p> <p>The CEACAM1 expression was evaluated immunohistochemically in the liver tissues of 99 severely obese or non-obese subjects with or without diabetes. The CEACAM1 expression was classified into two categories: a normal expression or a decreased expression.</p> <p>Results</p> <p>The CEACAM1 expression was markedly decreased in the hepatocytes with macrovesicular steatosis. A decreased CEACAM1 expression was noted in 29 (29%) of 99 cases. The incidence of a decreased CEACAM1 expression was significantly higher in high grade fatty liver as well as severe obesity with or without diabetes (p < 0.05). The incidence of a decreased CEACAM1 expression was not different between the diabetic and non-diabetic groups.</p> <p>Conclusions</p> <p>This data supports that a decreased CEACAM1 expression is related to obesity and a fatty liver.</p

Towards the understanding of microRNA and environmental factor interactions and their relationships to human diseases

Increasing studies have shown that the interactions between microRNAs (miRNAs) and environmental factors (EFs) play critical roles in determining phenotypes and diseases. In this study, we revealed a number of important biological insights by analyzing and modeling of miRNA-EF interactions and their relationships with human diseases. We demonstrated that the miRNA signatures of EFs could provide new information on EFs. More importantly, we quantitatively showed that the miRNA signatures of drug/radiation could be used as indicators for evaluating the results of cancer treatments. Finally, we developed a computational model that could efficiently identify the possible relationship between EF and human diseases. Meanwhile, we provided a website (http://cmbi.hsc.pku.edu.cn/miren) for the main results of this study. This study elucidates the mechanisms of EFs, presents a framework for predicting the results of cancer treatments, and develops a model that illustrates the relationships between EFs and human diseases

A rare SNP in pre-miR-34a is associated with increased levels of miR-34a in pancreatic beta cells.

Open Access Article.Changes in the levels of specific microRNAs (miRNAs) can reduce glucose-stimulated insulin secretion and increase beta-cell apoptosis, two causes of islet dysfunction and progression to type 2 diabetes. Studies have shown that single nucleotide polymorphisms (SNPs) within miRNA genes can affect their expression. We sought to determine whether miRNAs, with a known role in beta-cell function, possess SNPs within the pre-miRNA structure which can affect their expression. Using published literature and dbSNP, we aimed to identify miRNAs with a role in beta-cell function that also possess SNPs within the region encoding its pre-miRNA. Following transfection of plasmids, encoding the pre-miRNA and each allele of the SNP, miRNA expression was measured. Two rare SNPs located within the pre-miRNA structure of two miRNA genes important to beta-cell function (miR-34a and miR-96) were identified. Transfection of INS-1 and MIN6 cells with plasmids encoding pre-miR-34a and the minor allele of rs72631823 resulted in significantly (p < 0.05) higher miR-34a expression, compared to cells transfected with plasmids encoding the corresponding major allele. Similarly, higher levels were also observed upon transfection of HeLa cells. Transfection of MIN6 cells with plasmids encoding pre-miR-96 and each allele of rs41274239 resulted in no significant differences in miR-96 expression. A rare SNP in pre-miR-34a is associated with increased levels of mature miR-34a. Given that small changes in miR-34a levels have been shown to cause increased levels of beta-cell apoptosis this finding may be of interest to studies looking at determining the effect of rare variants on type 2 diabetes susceptibility

Downregulation of miR-205 and miR-31 confers resistance to chemotherapy-induced apoptosis in prostate cancer cells

Advanced prostate cancers are known to acquire not only invasive capabilities but also significant resistance to chemotherapy-induced apoptosis. To understand how microRNAs (miRNAs) may contribute to prostate cancer resistance to apoptosis, we compared microRNA expression profiles of a benign prostate cancer cell line WPE1-NA22 and a highly malignant WPE1-NB26 cell line (derived from a common lineage). We found that miR-205 and miR-31 are significantly downregulated in WPE1-NB26 cells, as well as in other cell lines representing advanced-stage prostate cancers. Antiapoptotic genes BCL2L2 (encoding Bcl-w) and E2F6 are identified as the targets of miR-205 and miR-31, respectively. By downregulating Bcl-w and E2F6, miR-205 and miR-31 promote chemotherapeutic agents-induced apoptosis in prostate cancer cells. The promoter region of the miR-205 gene was cloned and was found to be hypermethylated in cell lines derived from advanced prostate cancers, contributing to the downregulation of the gene. Treatment with DNA methylation inhibitor 5-aza-2′-deoxycytidine induced miR-205 expression, downregulated Bcl-w, and sensitized prostate cancer cells to chemotherapy-induced apoptosis. Thus, downregulation of miR-205 and miR-31 has an important role in apoptosis resistance in advanced prostate cancer

MicroRNA-Integrated and Network-Embedded Gene Selection with Diffusion Distance

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways

Circulating microRNAs as novel biomarkers for diabetes mellitus.

Diabetes mellitus is characterized by insulin secretion from pancreatic β cells that is insufficient to maintain blood glucose homeostasis. Autoimmune destruction of β cells results in type 1 diabetes mellitus, whereas conditions that reduce insulin sensitivity and negatively affect β-cell activities result in type 2 diabetes mellitus. Without proper management, patients with diabetes mellitus develop serious complications that reduce their quality of life and life expectancy. Biomarkers for early detection of the disease and identification of individuals at risk of developing complications would greatly improve the care of these patients. Small non-coding RNAs called microRNAs (miRNAs) control gene expression and participate in many physiopathological processes. Hundreds of miRNAs are actively or passively released in the circulation and can be used to evaluate health status and disease progression. Both type 1 diabetes mellitus and type 2 diabetes mellitus are associated with distinct modifications in the profile of miRNAs in the blood, which are sometimes detectable several years before the disease manifests. Moreover, circulating levels of certain miRNAs seem to be predictive of long-term complications. Technical and scientific obstacles still exist that need to be overcome, but circulating miRNAs might soon become part of the diagnostic arsenal to identify individuals at risk of developing diabetes mellitus and its devastating complications