In mouse models of atherosclerosis, normalization of hyperlipidemia promotes macrophage emigration and regression of atherosclerotic plaques in part by liver X receptor (LXR)-mediated induction of the chemokine receptor CCR7. Here we report that LXRα serine 198 (S198) phosphorylation modulates CCR7 expression. Low levels of S198 phosphorylation are observed in plaque macrophages in the regression environment where high levels of CCR7 expression are observed. Consistent with these findings, CCR7 gene expression in human and mouse macrophages cell lines is induced when LXRα at S198 is nonphosphorylated. In bone marrow-derived macrophages (BMDMs), we also observed induction of CCR7 by ligands that promote nonphosphorylated LXRα S198, and this was lost in LXR-deficient BMDMs. LXRα occupancy at the CCR7 promoter is enhanced and histone modifications associated with gene repression are reduced in RAW264.7 cells expressing nonphosphorylated LXRα (RAW-LXRα S198A) compared to RAW264.7 cells expressing wild-type (WT) phosphorylated LXRα (RAW-LXRα WT). Expression profiling of ligand-treated RAW-LXRα S198A cells compared to RAW-LXRα WT cells revealed induction of cell migratory and anti-inflammatory genes and repression of proinflammatory genes. Modeling of LXRα S198 in the nonphosphorylated and phosphorylated states identified phosphorylation-dependent conformational changes in the hinge region commensurate with the presence of sites for protein interaction. Therefore, gene transcription is regulated by LXRα S198 phosphorylation, including that of antiatherogenic genes such as CCR7.

We have developed a mouse model of atherosclerotic plaque regression in which an atherosclerotic aortic arch from a hyperlipidemic donor is transplanted into a normolipidemic recipient, resulting in rapid elimination of cholesterol and monocyte-derived macrophage cells (CD68+) from transplanted vessel walls. To gain a comprehensive view of the differences in gene expression patterns in macrophages associated with regressing compared with progressing atherosclerotic plaque, we compared mRNA expression patterns in CD68+ macrophages extracted from plaque in aortic aches transplanted into normolipidemic or into hyperlipidemic recipients. In CD68+ cells from regressing plaque we observed that genes associated with the contractile apparatus responsible for cellular movement (e.g. actin and myosin) were up-regulated whereas genes related to cell adhesion (e.g. cadherins, vinculin) were down-regulated. In addition, CD68+ cells from regressing plaque were characterized by enhanced expression of genes associated with an anti-inflammatory M2 macrophage phenotype, including arginase I, CD163 and the C-lectin receptor. Our analysis suggests that in regressing plaque CD68+ cells preferentially express genes that reduce cellular adhesion, enhance cellular motility, and overall act to suppress inflammation.

HMG-CoA reductase inhibitors (statins) decrease atherosclerosis by lowering low-density-lipoprotein cholesterol. Statins are also thought to have additional anti-atherogenic properties, yet defining these non-conventional modes of statin action remains incomplete. We have previously developed a novel mouse transplant model of atherosclerosis regression in which aortic segments from diseased donors are placed into normolipidemic recipients. With this model, we demonstrated the rapid loss of CD68+ cells (mainly macrophages) in plaques through the induction of a chemokine receptor CCR7-dependent emigration process. Because the human and mouse CCR7 promoter contain Sterol Response Elements (SREs), we hypothesized that Sterol Regulatory Element Binding Proteins (SREBPs) are involved in increasing CCR7 expression and through this mechanism, statins would promote CD68+ cell emigration from plaques. We examined whether statin activation of the SREBP pathway in vivo would induce CCR7 expression and promote macrophage emigration from plaques. We found that western diet-fed apoE(-/-) mice treated with either atorvastatin or rosuvastatin led to a substantial reduction in the CD68+ cell content in the plaques despite continued hyperlipidemia. We also observed a significant increase in CCR7 mRNA in CD68+ cells from both the atorvastatin and rosuvastatin treated mice associated with emigration of CD68+ cells from plaques. Importantly, CCR7(-/-)/apoE(-/-) double knockout mice failed to display a reduction in CD68+ cell content upon statin treatment. Statins also affected the recruitment of transcriptional regulatory proteins and the organization of the chromatin at the CCR7 promoter to increase the transcriptional activity. Statins promote the beneficial remodeling of plaques in diseased mouse arteries through the stimulation of the CCR7 emigration pathway in macrophages. Therefore, statins may exhibit some of their clinical benefits by not only retarding the progression of atherosclerosis, but also accelerating its regression.

The accurate diagnosis in the early stage of schizophrenia (SZ) is of great importance yet remains challenging. The classification between SZ and control groups based on magnetic resonance imaging (MRI) data using machine learning method could be helpful for SZ diagnosis. Increasing evidence showed that the combination of multimodal MRI data might further improve the classification performance However, medication effect has a profound influence on patients' anatomical and functional features and may reduce the classification efficiency. In this paper, we proposed a multimodal classification method to discriminate drug-naïve first-episode schizophrenia patients from healthy controls (HCs) by a combined structural MRI, diffusion tensor imaging (DTI) and resting state-functional MRI data. To reduce the feature dimension of multimodal data, we applied sparse coding (SC) for feature selection and multi-kernel support vector machine (SVM) for feature combination and classification. The best classification performance with the classification accuracy of 84.29% and area under the receiver operating characteristic (ROC) curve (AUC) of 81.64% was achieved when all modality data were combined. Interestingly, the identified functional markers were mainly found in default mode network (DMN) and cerebellar connections, while the structural markers were within limbic system and prefrontal-thalamo-hippocampal circuit.