Role of tumor necrosis factor-α in the human systemic endotoxin-induced transcriptome

Abstract

TNFα has been implicated in the pathogenesis of various inflammatory diseases. Different strategies to inhibit TNFα in patients with sepsis and chronic inflammatory conditions have shown contrasting outcomes. Although TNFα inhibitors are widely used in clinical practice, the impact of TNFα antagonism on white blood cell gene expression profiles during acute inflammation in humans in vivo has not been assessed. We here leveraged the established model of human endotoxemia to examine the effect of the TNFα antagonist, etanercept, on the genome-wide transcriptional responses in circulating leukocytes induced by intravenous LPS administration in male subjects. Etanercept pre-treatment resulted in a markedly dampened transcriptional response to LPS. Gene co-expression network analysis revealed this LPS-induced transcriptome can be categorized as TNFα responsive and non-responsive modules. Highly significant TNFα responsive modules include NF-kB signaling, antiviral responses and T-cell mediated responses. Within these TNFα responsive modules we delineate fundamental genes involved in epigenetic modifications, transcriptional initiation and elongation. Thus, we provide comprehensive information about molecular pathways that might be targeted by therapeutic interventions that seek to inhibit TNFα activity during human inflammatory diseases.

Figure 1. Genomic analysis of the systemic LPS-induced transcriptional response and impact of TNFα inhibition.

A. Volcano plot analysis (integrating p-values and log2 foldchanges) for the LPS-induced response in subjects treated with placebo. B. Volcano plot analysis of the LPS-induced response in subjects treated with the TNFα antagonist etanercept. Red dots in panels A and B indicate probes that showed a fold-change ≥1.5 or ≤1.5. C. Unsupervised hierarchical clustering heatmap of the 4077 LPS-induced transcripts that were influenced by etanercept treatment as identified by ANOVA (q-value <0.05). Columns represent subject samples and rows represent transcripts. Red indicates increased gene expression, and blue indicates decreased gene expression.

Figure 2. LPS-induced TNFα responsive and non-responsive transcriptional module delineation by weighted correlation analysis.

Each transcriptional module, encompassing highly intercorrelating transcripts, was represented by its first principal component across all samples (module eigengene). A. Bar plot of module significance for the effect of etanercept on the LPS-response based on unpaired student t statistics of the module eigengene between post-LPS samples from placebo and etanercept-treated subjects. The red line denotes the multiple-test corrected significance threshold (−log₁₀ p = 2.88). B. Bar plot denoting the upregulated and downregulated gene counts per IPA (ww.ingenuity.com) interactome pathway for both the LPS-challenged placebo-treated and LPS-challenged etanercept-treated samples.

Figure 3. TNFα responsive module hub (driver) genes and co-expression network visualization.

Genes within transcriptional modules can be categorized as peripheral or hubs on the basis of how correlated a gene is with all other genes in the network, defined as the genes' connectivity measure, k. High intramodulr connectivities denote highly important module genes oftentimes possessing transcriptional factor activity. A. Unsupervised hierarchical clustering heatmap plot of the TNFα responsive module hub genes. Red denotes high expression; blue denotes low expression. The relative importance of each module within the co-expression network can be highlighted by unsupervised visualizations of each genes' weighted correlation coefficient. This was implemented in the Cytoscape® platform B. TNFα responsive co-expression modules were visualized by an organic layout considering weighted correlation coefficients >0.1 (equivalent to correlation coefficient >0.9).

Figure 4. Interactome relationships of the core TNFα responsive co-expression modules.

Integrating IPA (www.ingenuity.com) derived experimentally observed gene functional and co-expression network relationships allowed for the construction of a LPS-induced and TNFα-responsive gene activity model anchored at important hub genes. Panel a. illustrates the interactome relationships among transcripts in the NF-kB signaling and role of PKR in interferon induction and antiviral response modules with HIVEP1 and CBX7 as hub genes, respectively. Panel b. illustrates the interactome relationships among the regulation of IL-2 expression in activated and anergic T lymphocytes module with CD6 as hub gene. Foldchanges (Red denotes high expression, green denotes low expression) derived from the differential gene expression analysis of the unpaired LPS+placebo and LPS+etanercept comparison where genes present significant ANOVA q-values (q<0.05). IPA interactome inference denoted by gray edges; gene coexpression network relationships denoted by turquoise (NF-kB signaling), purple (IL10 signaling), red (Regulation of IL-2 Expression in Activated and Anergic T Lymphocytes), yellow (Ephrin Receptor Signaling) and blue (Role of PKR in Interferon Induction and Antiviral Response) edges.