Transcription Factor MAFF (MAF Basic Leucine Zipper Transcription Factor F) Regulates an Atherosclerosis Relevant Network Connecting Inflammation and Cholesterol Metabolism.

BACKGROUND: Coronary artery disease (CAD) is a multifactorial condition with both genetic and exogenous causes. The contribution of tissue-specific functional networks to the development of atherosclerosis remains largely unclear. The aim of this study was to identify and characterize central regulators and networks leading to atherosclerosis. METHODS: Based on several hundred genes known to affect atherosclerosis risk in mouse (as demonstrated in knockout models) and human (as shown by genome-wide association studies), liver gene regulatory networks were modeled. The hierarchical order and regulatory directions of genes within the network were based on Bayesian prediction models, as well as experimental studies including chromatin immunoprecipitation DNA-sequencing, chromatin immunoprecipitation mass spectrometry, overexpression, small interfering RNA knockdown in mouse and human liver cells, and knockout mouse experiments. Bioinformatics and correlation analyses were used to clarify associations between central genes and CAD phenotypes in both human and mouse. RESULTS: The transcription factor MAFF (MAF basic leucine zipper transcription factor F) interacted as a key driver of a liver network with 3 human genes at CAD genome-wide association studies loci and 11 atherosclerotic murine genes. Most importantly, expression levels of the low-density lipoprotein receptor (LDLR) gene correlated with MAFF in 600 CAD patients undergoing bypass surgery (STARNET [Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task]) and a hybrid mouse diversity panel involving 105 different inbred mouse strains. Molecular mechanisms of MAFF were tested in noninflammatory conditions and showed positive correlation between MAFF and LDLR in vitro and in vivo. Interestingly, after lipopolysaccharide stimulation (inflammatory conditions), an inverse correlation between MAFF and LDLR in vitro and in vivo was observed. Chromatin immunoprecipitation mass spectrometry revealed that the human CAD genome-wide association studies candidate BACH1 (BTB domain and CNC homolog 1) assists MAFF in the presence of lipopolysaccharide stimulation with respective heterodimers binding at the MAF recognition element of the LDLR promoter to transcriptionally downregulate LDLR expression. CONCLUSIONS: The transcription factor MAFF was identified as a novel central regulator of an atherosclerosis/CAD-relevant liver network. MAFF triggered context-specific expression of LDLR and other genes known to affect CAD risk. Our results suggest that MAFF is a missing link between inflammation, lipid and lipoprotein metabolism, and a possible treatment target.

Flavin containing monooxygenase 3 exerts broad effects on glucose and lipid metabolism and atherosclerosis.

We performed silencing and overexpression studies of flavin containing monooxygenase (FMO) 3 in hyperlipidemic mouse models to examine its effects on trimethylamine N-oxide (TMAO) levels and atherosclerosis. Knockdown of hepatic FMO3 in LDL receptor knockout mice using an antisense oligonucleotide resulted in decreased circulating TMAO levels and atherosclerosis. Surprisingly, we also observed significant decreases in hepatic lipids and in levels of plasma lipids, ketone bodies, glucose, and insulin. FMO3 overexpression in transgenic mice, on the other hand, increased hepatic and plasma lipids. Global gene expression analyses suggested that these effects of FMO3 on lipogenesis and gluconeogenesis may be mediated through the PPARα and Kruppel-like factor 15 pathways. In vivo and in vitro results were consistent with the concept that the effects were mediated directly by FMO3 rather than trimethylamine/TMAO; in particular, overexpression of FMO3 in the human hepatoma cell line, Hep3B, resulted in significantly increased glucose secretion and lipogenesis. Our results indicate a major role for FMO3 in modulating glucose and lipid homeostasis in vivo, and they suggest that pharmacologic inhibition of FMO3 to reduce TMAO levels would be confounded by metabolic interactions.

Regulation of NF-κB signaling by oxidized glycerophospholipid and IL-1ß induced miRs-21-3p and -27a-5p in human aortic endothelial cells.

Exposure of endothelial cells (ECs) to agents such as oxidized glycerophospholipids (oxGPs) and cytokines, known to accumulate in atherosclerotic lesions, perturbs the expression of hundreds of genes in ECs involved in inflammatory and other biological processes. We hypothesized that microRNAs (miRNAs) are involved in regulating the inflammatory response in human aortic endothelial cells (HAECs) in response to oxGPs and interleukin 1ß (IL-1ß). Using next-generation sequencing and RT-quantitative PCR, we characterized the profile of expressed miRNAs in HAECs pre- and postexposure to oxGPs. Using this data, we identified miR-21-3p and miR-27a-5p to be induced 3- to 4-fold in response to oxGP and IL-1ß treatment compared with control treatment. Transient overexpression of miR-21-3p and miR-27a-5p resulted in the downregulation of 1,253 genes with 922 genes overlapping between the two miRNAs. Gene Ontology functional enrichment analysis predicted that the two miRNAs were involved in the regulation of nuclear factor κB (NF-κB) signaling. Overexpression of these two miRNAs leads to changes in p65 nuclear translocation. Using 3' untranslated region luciferase assay, we identified 20 genes within the NF-κB signaling cascade as putative targets of miRs-21-3p and -27a-5p, implicating these two miRNAs as modulators of NF-κB signaling in ECs.

Genetic regulation of mouse liver metabolite levels.

We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome-wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co-variation across various biological scales.

Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages.

Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.

Identification of Abcc6 as the major causal gene for dystrophic cardiac calcification in mice through integrative genomics.

The genetic factors contributing to the complex disorder of myocardial calcification are largely unknown. Using a mouse model, we fine-mapped the major locus (Dyscalc1) contributing to the dystrophic cardiac calcification (DCC) to an 840-kb interval containing 38 genes. We then identified the causal gene by using an approach integrating genetic segregation and expression array analyses to identify, on a global scale, cis-acting DNA variations that perturb gene expression. By studying two intercrosses, in which the DCC trait segregates, a single candidate gene (encoding the ATP-binding cassette transporter ABCC6) was identified. Transgenic complementation confirmed Abcc6 as the underlying causal gene for Dyscalc1. We demonstrate that in the cross, the expression of Abcc6 is highly correlated with the local mineralization regulatory system and the BMP2-Wnt signaling pathway known to be involved in the systemic regulation of calcification, suggesting potential pathways for the action of Abcc6 in DCC. Our results demonstrate the power of the integrative genomics in discovering causal genes and pathways underlying complex traits.

Genetics of gene expression surveyed in maize, mouse and man.

Treating messenger RNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been pursued in gene-specific ways. Transcript abundances often serve as a surrogate for classical quantitative traits in that the levels of expression are significantly correlated with the classical traits across members of a segregating population. The correlation structure between transcript abundances and classical traits has been used to identify susceptibility loci for complex diseases such as diabetes and allergic asthma. One study recently completed the first comprehensive dissection of transcriptional regulation in budding yeast, giving a detailed glimpse of a genome-wide survey of the genetics of gene expression. Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at cellular biochemical processes. Here we describe comprehensive genetic screens of mouse, plant and human transcriptomes by considering gene expression values as quantitative traits. We identify a gene expression pattern strongly associated with obesity in a murine cross, and observe two distinct obesity subtypes. Furthermore, we find that these obesity subtypes are under the control of different loci.