Background

The choline-derived metabolite trimethylamine N-oxide (TMAO) has been demonstrated to contribute to atherosclerosis and is associated with coronary artery disease risk.

Methods and results

We explored the impact of TMAO on endothelial and smooth muscle cell function in vivo, focusing on disease-relevant outcomes for atherogenesis. Initially, we observed that aortas of LDLR(-/-) mice fed a choline diet showed elevated inflammatory gene expression compared with controls. Acute TMAO injection at physiological levels was sufficient to induce the same inflammatory markers and activate the well-known mitogen-activated protein kinase, extracellular signal-related kinase, and nuclear factor-κB signaling cascade. These observations were recapitulated in primary human aortic endothelial cells and vascular smooth muscle cells. We also found that TMAO promotes recruitment of activated leukocytes to endothelial cells. Through pharmacological inhibition, we further showed that activation of nuclear factor-κB signaling was necessary for TMAO to induce inflammatory gene expression in both of these relevant cell types as well as endothelial cell adhesion of leukocytes.

Conclusions

Our results suggest a likely contributory mechanism for TMAO-dependent enhancement in atherosclerosis and cardiovascular risks.

Objective- The objective of this study was to determine the basis of resistance to atherosclerosis of inbred mouse strain BALB/cJ. Approach and Results- BALB/cJ mice carry a naturally occurring null mutation of the gene encoding the transcription factor Zhx2, and genetic analyses suggested that this may confer resistance to atherosclerosis. On a hyperlipidemic low-density lipoprotein receptor null background, BALB/cJ mice carrying the mutant allele for Zhx2 exhibited up to a 10-fold reduction in lesion size as compared with an isogenic strain carrying the wild-type allele. Several lines of evidence, including bone marrow transplantation studies, indicate that this effect of Zhx2 is mediated, in part, by monocytes/macrophages although nonbone marrow-derived pathways are clearly involved as well. Both in culture and in atherosclerotic lesions, macrophages from Zhx2 null mice exhibited substantially increased apoptosis. Zhx2 null macrophages were also enriched for M2 markers. Effects of Zhx2 on proliferation and other bone marrow-derived cells, such as lymphocytes, were at most modest. Expression microarray analyses identified >1000 differentially expressed transcripts between Zhx2 wild-type and null macrophages. To identify the global targets of Zhx2, we performed ChIP-seq (chromatin immunoprecipitation sequencing) studies with the macrophage cell line RAW264.7. The ChIP-seq peaks overlapped significantly with gene expression and together suggested roles for transcriptional repression and apoptosis. Conclusions- A mutation of Zhx2 carried in BALB/cJ mice is responsible in large part for its relative resistance to atherosclerosis. Our results indicate that Zhx2 promotes macrophage survival and proinflammatory functions in atherosclerotic lesions, thereby contributing to lesion growth.

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.