Gene expression profiles displayed by peripheral blood mononuclear cells from patients with type 2 diabetes mellitus focusing on biological processes implicated on the pathogenesis of the disease

Patients with type 2 diabetes mellitus (T2DM) exhibit insulin resistance associated with obesity and inflammatory response, besides an increased level of oxidative DNA damage as a consequence of the hyperglycemic condition and the generation of reactive oxygen species (ROS). In order to provide information on the mechanisms involved in the pathophysiology of T2DM, we analyzed the transcriptional expression patterns exhibited by peripheral blood mononuclear cells (PBMCs) from patients with T2DM compared to non-diabetic subjects, by investigating several biological processes: inflammatory and immune responses, responses to oxidative stress and hypoxia, fatty acid processing, and DNA repair. PBMCs were obtained from 20 T2DM patients and eight non-diabetic subjects. Total RNA was hybridized to Agilent whole human genome 4x44K one-color oligo-microarray. Microarray data were analyzed using the GeneSpring GX 11.0 software (Agilent). We used BRB-ArrayTools software (gene set analysis - GSA) to investigate significant gene sets and the Genomica tool to study a possible influence of clinical features on gene expression profiles. We showed that PBMCs from T2DM patients presented significant changes in gene expression, exhibiting 1320 differentially expressed genes compared to the control group. A great number of genes were involved in biological processes implicated in the pathogenesis of T2DM. Among the genes with high fold-change values, the up-regulated ones were associated with fatty acid metabolism and protection against lipid-induced oxidative stress, while the down-regulated ones were implicated in the suppression of pro-inflammatory cytokines production and DNA repair. Moreover, we identified two significant signaling pathways: adipocytokine, related to insulin resistance; and ceramide, related to oxidative stress and induction of apoptosis. In addition, expression profiles were not influenced by patient features, such as age, gender, obesity, pre/post-menopause age, neuropathy, glycemia, and HbA(1c) percentage. Hence, by studying expression profiles of PBMCs, we provided quantitative and qualitative differences and similarities between T2DM patients and non-diabetic individuals, contributing with new perspectives for a better understanding of the disease. (C) 2012 Elsevier B.V. All rights reserved.

Genome mapping and expression analyses of human intronic noncoding RNAs reveal tissue-specific patterns and enrichment in genes related to regulation of transcription

Abstract Background RNAs transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression. However, the complement of human genes in which introns are transcribed, and the number of intronic transcriptional units and their tissue expression patterns are not known. Results A survey of mRNA and EST public databases revealed more than 55,000 totally intronic noncoding (TIN) RNAs transcribed from the introns of 74% of all unique RefSeq genes. Guided by this information, we designed an oligoarray platform containing sense and antisense probes for each of 7,135 randomly selected TIN transcripts plus the corresponding protein-coding genes. We identified exonic and intronic tissue-specific expression signatures for human liver, prostate and kidney. The most highly expressed antisense TIN RNAs were transcribed from introns of protein-coding genes significantly enriched (p = 0.002 to 0.022) in the 'Regulation of transcription' Gene Ontology category. RNA polymerase II inhibition resulted in increased expression of a fraction of intronic RNAs in cell cultures, suggesting that other RNA polymerases may be involved in their biosynthesis. Members of a subset of intronic and protein-coding signatures transcribed from the same genomic loci have correlated expression patterns, suggesting that intronic RNAs regulate the abundance or the pattern of exon usage in protein-coding messages. Conclusion We have identified diverse intronic RNA expression patterns, pointing to distinct regulatory roles. This gene-oriented approach, using a combined intron-exon oligoarray, should permit further comparative analysis of intronic transcription under various physiological and pathological conditions, thus advancing current knowledge about the biological functions of these noncoding RNAs.

Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients

Abstract Background Regardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics. Results The use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis. Conclusions These results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.