Altered DNA methylation in liver and adipose tissues derived from individuals with obesity and type 2 diabetes.

BACKGROUND: Obesity is a well-recognized risk factor for insulin resistance and type 2 diabetes (T2D), although the precise mechanisms underlying the relationship remain unknown. In this study we identified alterations of DNA methylation influencing T2D pathogenesis, in subcutaneous and visceral adipose tissues, liver, and blood from individuals with obesity. METHODS: The study included individuals with obesity, with and without T2D. From these patients, we obtained samples of liver tissue (n = 16), visceral and subcutaneous adipose tissues (n = 30), and peripheral blood (n = 38). We analyzed DNA methylation using Illumina Infinium Human Methylation arrays, and gene expression profiles using HumanHT-12 Expression BeadChip Arrays. RESULTS: Analysis of DNA methylation profiles revealed several loci with differential methylation between individuals with and without T2D, in all tissues. Aberrant DNA methylation was mainly found in the liver and visceral adipose tissue. Gene ontology analysis of genes with altered DNA methylation revealed enriched terms related to glucose metabolism, lipid metabolism, cell cycle regulation, and response to wounding. An inverse correlation between altered methylation and gene expression in the four tissues was found in a subset of genes, which were related to insulin resistance, adipogenesis, fat storage, and inflammation. CONCLUSIONS: Our present findings provide additional evidence that aberrant DNA methylation may be a relevant mechanism involved in T2D pathogenesis among individuals with obesity

A computational toxicogenomics approach identifies a list of highly hepatotoxic compounds from a large microarray database.

The liver and the kidney are the most common targets of chemical toxicity, due to their major metabolic and excretory functions. However, since the liver is directly involved in biotransformation, compounds in many currently and normally used drugs could affect it adversely. Most chemical compounds are already labeled according to FDA-approved labels using DILI-concern scale. Drug Induced Liver Injury (DILI) scale refers to an adverse drug reaction. Many compounds do not exhibit hepatotoxicity at early stages of development, so it is important to detect anomalies at gene expression level that could predict adverse reactions in later stages. In this study, a large collection of microarray data is used to investigate gene expression changes associated with hepatotoxicity. Using TG-GATEs a large-scale toxicogenomics database, we present a computational strategy to classify compounds by toxicity levels in human and animal models through patterns of gene expression. We combined machine learning algorithms with time series analysis to identify genes capable of classifying compounds by FDA-approved labeling as DILI-concern toxic. The goal is to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. The study illustrates that expression profiling can be used to classify compounds according to different hepatotoxic levels; to label those that are currently labeled as undertemined; and to determine if at the molecular level, animal models are a good proxy to predict hepatotoxicity in humans

Down-Regulation of TLR and JAK/STAT Pathway Genes Is Associated with Diffuse Cutaneous Leishmaniasis: A Gene Expression Analysis in NK Cells from Patients Infected with Leishmania mexicana.

An important NK-cell inhibition with reduced TNF-α, IFN-γ and TLR2 expression had previously been identified in patients with diffuse cutaneous leishmaniasis (DCL) infected with Leishmania mexicana. In an attempt to pinpoint alterations in the signaling pathways responsible for the NK-cell dysfunction in patients with DCL, this study aimed at identifying differences in the NK-cell response towards Leishmania mexicana lipophosphoglycan (LPG) between patients with localized and diffuse cutaneous leishmaniasis through gene expression profiling. Our results indicate that important genes involved in the innate immune response to Leishmania are down-regulated in NK cells from DCL patients, particularly TLR and JAK/STAT signaling pathways. This down-regulation showed to be independent of LPG stimulation. The study sheds new light for understanding the mechanisms that undermine the correct effector functions of NK cells in patients with diffuse cutaneous leishmaniasis contributing to a better understanding of the pathobiology of leishmaniasis

Hierarchical clustering of top ranked genes in both of the Rat models in vivo, in vitro.

<p>In red values with high MB statistic and in blue negative MB values. Rat in vitro (left) and Rat in vivo (right). Colored bar on the top shows DILI concern, black means unassigned or model compound, yellow indicates No DILI, orange Less DILI and red Most DILI.</p

List of 48 compounds found in common for Human in vitro, Rat in vitro and Rat in vivo.

<p>All previously reported as highly toxic.</p

All previously reported as highly toxic compounds found in common for Human in vitro, Rat in vitro and Rat in vivo models.

<p>All previously reported as highly toxic compounds found in common for Human in vitro, Rat in vitro and Rat in vivo models.</p

Hierarchical clustering of top ranked genes in Human in vitro model.

<p>In the x-axis the compounds are shown and in the y-axis the selected genes by MB and MAD. In red, values with high MB statistic and in blue negative MB values. Colored bar on the top shows DILI concern, black means unassigned or model compound, yellow indicates No DILI, orange Less DILI and red Most DILI. Gene set enrichment analysis (top-right) was done with pre-ranked GSEA. Marked with a green vertical bar are genes that remain significant across the majority of compounds and the list on the far right shows the list of compounds with the highest statistical significance.</p

Dynamic range of MB statistics.

<p>Dynamic range of MB statistics.</p

Time course approach on different compounds.

<p>(a) Carbon Tetrachloride on Human in vitro samples (b) Aspirin on Human in vitro samples and (c) Phenytoin on Rat in vitro samples. Colors are assigned by dose: Control(red), Low (green), Middle (blue), High (cyan). On the x-axis the time measurements 2hr, 8hr, 24hr; on the y-axis the gene expression values at each time point.</p