Dataset Information

A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus.

ABSTRACT: MicroRNAs (miRNAs) are small noncoding RNAs that modulate the cellular transcriptome at the post-transcriptional level. miRNA plays important roles in different disease manifestation, including type 2 diabetes mellitus (T2DM). Many studies have characterized the changes of miRNAs in T2DM, a complex systematic disease; however, few studies have integrated these findings and explored the functional effects of the dysregulated miRNAs identified. To investigate the involvement of miRNAs in T2DM, we obtained and analyzed all relevant studies published prior to 18 October 2016 from various literature databases. From 59 independent studies that met the inclusion criteria, we identified 158 dysregulated miRNAs in seven different major sample types. To understand the functional impact of these deregulated miRNAs, we performed targets prediction and pathway enrichment analysis. Results from our analysis suggested that the altered miRNAs are involved in the core processes associated with T2DM, such as carbohydrate and lipid metabolisms, insulin signaling pathway and the adipocytokine signaling pathway. This systematic survey of dysregulated miRNAs provides molecular insights on the effect of deregulated miRNAs in different tissues during the development of diabetes. Some of these miRNAs and their mRNA targets may have diagnostic and/or therapeutic utilities in T2DM.

SUBMITTER: He Y

PROVIDER: S-EPMC5372489 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus.

He Yuqing Y Ding Yuanlin Y Liang Biyu B Lin Juanjuan J Kim Taek-Kyun TK Yu Haibing H Hang Hanwei H Wang Kai K

International journal of molecular sciences 20170228 3

MicroRNAs (miRNAs) are small noncoding RNAs that modulate the cellular transcriptome at the post-transcriptional level. miRNA plays important roles in different disease manifestation, including type 2 diabetes mellitus (T2DM). Many studies have characterized the changes of miRNAs in T2DM, a complex systematic disease; however, few studies have integrated these findings and explored the functional effects of the dysregulated miRNAs identified. To investigate the involvement of miRNAs in T2DM, we ...[more]

PMID: 28264477

Similar Datasets

Project description:Growing evidence indicates that microRNAs (miRNAs) have a key role in processes involved in type 1 diabetes mellitus (T1DM) pathogenesis, including immune system functions and beta-cell metabolism and death. Although dysregulated miRNA profiles have been identified in T1DM patients, results are inconclusive; with only few miRNAs being consistently dysregulated among studies. Thus, we performed a systematic review of the literature on the subject, followed by bioinformatic analysis, to point out which miRNAs are dysregulated in T1DM-related tissues and in which pathways they act. PubMed and EMBASE were searched to identify all studies that compared miRNA expressions between T1DM patients and non-diabetic controls. Search was completed in August, 2017. Those miRNAs consistently dysregulated in T1DM-related tissues were submitted to bioinformatic analysis, using six databases of miRNA-target gene interactions to retrieve their putative targets and identify potentially affected pathways under their regulation. Thirty-three studies were included in the systematic review: 19 of them reported miRNA expressions in human samples, 13 in murine models and one in both human and murine samples. Among 278 dysregulated miRNAs reported in these studies, 25.9% were reported in at least 2 studies; however, only 48 of them were analyzed in tissues directly related to T1DM pathogenesis (serum/plasma, pancreas and peripheral blood mononuclear cells (PBMCs)). Regarding circulating miRNAs, 11 were consistently dysregulated in T1DM patients compared to controls: miR-21-5p, miR-24-3p, miR-100-5p, miR-146a-5p, miR-148a-3p, miR-150-5p, miR-181a-5p, miR-210-5p, miR-342-3p, miR-375 and miR-1275. The bioinformatic analysis retrieved a total of 5867 validated and 2979 predicted miRNA-target interactions for human miRNAs. In functional enrichment analysis of miRNA target genes, 77 KEGG terms were enriched for more than one miRNA. These miRNAs are involved in pathways related to immune system function, cell survival, cell proliferation and insulin biosynthesis and secretion. In conclusion, eleven circulating miRNAs seem to be dysregulated in T1DM patients in different studies, being potential circulating biomarkers of this disease.

Project description:Background:Type 2 diabetes mellitus (T2DM) is a metabolic disorder with growing prevalence and increasing economic burden. Based on the role of genetics and epigenetic factors on T2DM, we aimed to carry a systematic review and meta-analysis for all miRNA gene polymorphisms and risk of T2DM. Materials and Methods:A computerized literature search was carried out on PubMed, Web of Science, Scopus, Embase, as well as references of relevant review/meta-analysis. Key search terms were "Diabetes Mellitus, Type 2," "MicroRNAs," and "Polymorphism, Single Nucleotide." All types of observational studies from January 1, 1992, to November 30, 2019, were included, without language restriction. Data analysis was performed using R programming language (3.5.2). Level of heterogeneity was obtained by Cochran's Q test (P < 0.05), and subgroup analysis was performed based on ethnicity. Results:Thirty-two polymorphisms from fifteen articles were included. Meta-analysis was carried out based on minor allele frequencies. Seven studies with 2193 cases and 3963 controls were included for rs2910164 polymorphism. In subgroup analysis, there were significant results in Caucasian population in dominant model (odds ratio [OR] =1.12; 95% confidence interval [CI]: 0.83-1.51), homozygote model (OR = 1.78; 95% CI: 1.06-3.00), heterozygote model (OR = 1.77; 95% CI: 1.03-3.05), and recessive model (OR = 1.78; 95% CI: 1.07-2.96). Four studies with 2085 cases and 1933 controls were included for rs895819 polymorphism. Overall, there was no significant result for association with rs895819, but subgroup analysis revealed that minor allele significantly decreased the risk of T2DM in Caucasians by recessive model (OR = 0.34; 95% CI: 0.18-0.66), dominant model (OR = 0.70; 95% CI: 0.52-0.94), homozygote model (OR = 0.32; 95% CI: 0.16-0.62), heterozygote model (OR = 0.37; 95% CI: 0.19-0.74), allelic model (OR = 0.67; 95% CI: 0.52-0.85). Conclusion:The minor allele of rs2910164 may increase the risk of T2DM by leading to lower level of miR-146a. In contrast, minor allele of rs895819 may decrease the risk of T2DM by leading to higher level of miR-27a.

Project description:The prevalence of type 2 diabetes mellitus (T2DM) is increasing dramatically worldwide. Dysregulation of microRNA (miRNA) as key regulators of gene expression, has been reported in numerous diseases including diabetes. The aim of this study was to investigate the expression levels of miRNA-122, miRNA-126-3p and miRNA-146a in diabetic and pre-diabetic patients and in healthy individuals, and to determine whether the changes in the level of these miRNAs are reliable biomarkers in diagnosis, prognosis, and pathogenesis of T2DM. Additionally, we examined the relationship between miRNA levels and plasma concentrations of inflammatory factors including tumor necrosis factor alpha (TNF-α) and interleukin 6 (Il-6) as well as insulin resistance. In this case-control study, participants (n = 90) were allocated to three groups (n = 30/group): T2DM, pre-diabetes and healthy individuals as control (males and females, age: 25-65, body mass index: 25-35). Expression of miRNA was determined by real-time polymerase chain reaction (RT-PCR). Furthermore, plasma concentrations of TNF-α, IL-6 and fasting insulin were measured by enzyme-linked immunosorbent assay. Homeostatic model assessment for insulin resistance (HOMA-IR) was calculated as an indicator of insulin resistance. MiRNA-122 levels were higher while miRNA-126-3p and miRNA-146a levels were lower in T2DM and pre-diabetic patients compared to control (p<0.05). Furthermore, a positive correlation was found between miRNA-122 expression and TNF-α (r = 0.82), IL-6 (r = 0.83) and insulin resistance (r = 0.8). Conversely, negative correlations were observed between miRNA-126-3p and miRNA-146a levels and TNF-α (r = -0.7 and r = -0.82 respectively), IL-6 (r = -0.65 and r = -0.78 respectively) as well as insulin resistance (r = -0.67 and r = -0.78 respectively) (all p<0.05). Findings of this study suggest the miRNAs can potentially contribute to the pathogenesis of T2DM. Further studies are required to examine the reproducibility of these findings.

Project description:AimsTo reduce the burden of type 2 diabetes (T2DM), the disease decision model plays a vital role in supporting decision-making. Currently, there is no comprehensive summary and assessment of the existing decision models for T2DM. The objective of this review is to provide an overview of the characteristics and capabilities of published decision models for T2DM. We also discuss which models are suitable for different study demands.Materials and methodsFour databases (PubMed, Web of Science, Embase, and the Cochrane Library) were electronically searched for papers published from inception to August 2020. Search terms were: "Diabetes-Mellitus, Type 2", "cost-utility", "quality-of-life", and "decision model". Reference lists of the included studies were manually searched. Two reviewers independently screened the titles and abstracts following the inclusion and exclusion criteria. If there was insufficient information to include or exclude a study, then a full-text version was sought. The extracted information included basic information, study details, population characteristics, basic modeling methodologies, model structure, and data inputs for the included applications, model outcomes, model validation, and uncertainty.ResultsFourteen unique decision models for T2DM were identified. Markov chains and risk equations were utilized by four and three models, respectively. Three models utilized both. Except for the Archimedes model, all other models (n = 13) implemented an annual cycle length. The time horizon of most models was flexible. Fourteen models had differences in the division of health states. Ten models emphasized macrovascular and microvascular complications. Six models included adverse events. Majority of the models (n = 11) were patient-level simulation models. Eleven models simulated annual changes in risk factors (body mass index, glycemia, HbA1c, blood pressure (systolic and/or diastolic), and lipids (total cholesterol and/or high-density lipoprotein)). All models reported the main data sources used to develop health states of complications. Most models (n = 11) could deal with the uncertainty of models, which were described in varying levels of detail in the primary studies. Eleven studies reported that one or more validation checks were performed.ConclusionsThe existing decision models for T2DM are heterogeneous in terms of the level of detail in the classification of health states. Thus, more attention should be focused on balancing the desired level of complexity against the required level of transparency in the development of T2DM decision models.

Dataset Information

A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus.

Publications

A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets