Identification and validation of causal genes for atherosclerosis in mice
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE18479 | GEO | 2010/06/23
SECONDARY ACCESSION(S): PRJNA120217
REPOSITORIES: GEO
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Project description:Identification of causal genes for atherosclerosis in a segregating mouse population and validation via single-gene knockout and plaque progression mouse models. This SuperSeries is composed of the following subset Series: GSE18442: Aortic arch profiling of Ldlr knockout mice with human CETP transgene GSE18443: Aortic arch profiling of Apoe knockout mice Refer to individual Series
2010-06-23 | E-GEOD-18479 | biostudies-arrayexpress
Project description:The goal of this study is to determine whether PRMT2 plays a causal role in the impairment of atherosclerosis regression in diabetes. We examined the consequence of deleting PRMT2 in myeloid cells during the regression of atherosclerosis in normal and diabetic mice. We found significant impairment of atherosclerosis regression under normoglycemic conditions in mice lacking PRMT2 (Prmt2-/-) in myeloid cells that mimic the decrease in regression of atherosclerosis in WT mice under diabetic conditions. This was associated with increased plaque macrophage retention. PRMT2-deficient plaque CD68+ cells under normoglycemic conditions showed increased expression of genes involved in cytokine signaling and inflammation compared to WT cells by RNA seq. Thus, the loss of PRMT2 is causally linked to impaired atherosclerosis regression.
2022-07-20 | GSE203523 | GEO
Project description:Neutrophil extracellular traps (NETs) promote inflammation and atherosclerosis progression. In diabetes they are increased and impair wound healing, during which inflammation normally resolves. Atherosclerosis regression, a process resembling wound healing, is also impaired in diabetes. Thus, we hypothesized that NETs impede atherosclerosis regression in diabetes through unresolved inflammation. Objective: To investigate in diabetes the effect of NETs on plaque macrophage inflammation and whether NETs reduction improves atherosclerosis regression. Findings: Transcriptomic profiling of plaque macrophages from NET positive and negative areas in Ldlr-/- mice revealed inflammasome and glycolysis pathway upregulation, indicating a pro-inflammatory phenotype. During atherosclerosis regression in non-diabetic mice, plaque NET content decreased. In contrast, in diabetic mouse plaques NETs were enriched and persisted after lipid-lowering. DNase1 treatment (to degrade NETs) of diabetic mice reduced plaque NETs and macrophage inflammation and improved atherosclerosis regression after lipid-lowering. Conclusions: NETs decline during atherosclerosis regression in non-diabetic mice, but persist in diabetes and impair regression by exacerbating macrophage inflammation. DNase1 reduced diabetic plaque NETs and macrophage inflammation, and restored atherosclerosis resolution after lipid-lowering, despite ongoing hyperglycemia. Given that humans with diabetes also exhibit impaired atherosclerosis resolution with lipid-lowering, these data suggest that NETs contribute to the increased CVD risk in this population.
2020-05-12 | GSE145200 | GEO
Project description:Regression of atherosclerosis is an important clinical goal, however the pathways that mediate the resolution of atherosclerotic inflammation and reversal of plaques are poorly understood. Regulatory T cells (Tregs) have been shown to be atheroprotective, however numbers of these immunosuppressive cells decrease with disease progression. Using multiple independent mouse models of atherosclerosis regression, we demonstrate that an increase in plaque Tregs is a common signature of regressing plaques. To test if Tregs are required for the resolution of atherosclerotic inflammation and plaque regression during lipid-lowering therapy, we combined CD25 monoclonal antibody (PC61 mAb)-mediated Treg depletion with single-cell RNA-sequencing of immune cells in the plaque and conventional analyses of atherosclerosis. Single cell RNA-sequencing revealed that Tregs from aortic plaques shared some similarity with splenic Tregs, but were distinct from skin and colon Tregs supporting recent findings of tissue-dependent Treg heterogeneity. Furthermore, Tregs from progressing plaques expressed markers of natural Tregs derived from the thymus, whereas Tregs in regressing plaques lacked Nrp1 and Helios expression, suggesting that they are induced in the periphery during lipid lowering. Treatment of atherosclerotic mice with PC61 mAb effectively depleted Tregs in the blood and peripheral tissues, including plaques, and blocked the regression of atherosclerosis induced by apoB anti-sense oligonucleotides. Morphometric analyses revealed that control antibody-treated mice showed a 40% decrease in plaque burden and macrophage content under regression conditions, whereas PC61 mAb-treated mice showed no change in plaque size or inflammatory cell content compared to baseline. Moreover, Treg depletion enhanced inflammatory signaling and blocked tissue reparative functions of macrophages in the regressing plaque, including M2-polarization, efferocytosis and sensing of specialized pro-resolving lipid mediators. Together, these data establish essential roles for Tregs in the resolution of atherosclerotic inflammation and plaque remodeling during regression.
2020-07-22 | GSE141038 | GEO
Project description:Background: Using proteomics, we strove to reveal novel molecular subtypes of human atherosclerotic lesions, study their associations with histology and imaging and relate them to long-term cardiovascular outcomes. Methods: 219 samples were obtained from 120 patients undergoing carotid endarterectomy. Sequential protein extraction was combined with multiplexed, discovery proteomics. Parallel reaction monitoring for 135 proteins was deployed for targeted validation. A combination of statistical, bioinformatics and machine learning methods was used to perform differential expression, network, pathway enrichment analysis and train and evaluate prognostic models. Results: Our extensive proteomics analysis from the core and periphery of plaques doubled the coverage of the plaque proteome compared to the largest proteomics study on atherosclerosis thus far. Plaque inflammation and calcification signatures were inversely correlated and validated with targeted proteomics. The inflammation signature was enriched with neutrophil-derived proteins, including calprotectin (S100A8/9) and myeloperoxidase. The calcification signature contained fetuin-A, osteopontin, and gamma-carboxylated proteins. Sex differences in the proteome of atherosclerosis were explained by a higher proportion of calcified plaques in women. Single-cell RNA sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages and the calcification signature to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in the plaque, i.e., fetuin-A. Echogenic lesions reflect the collagen content and calcification of plaque but carotid Duplex ultrasound fails to capture the extent of inflammatory protein changes in symptomatic plaques. Applying dimensionality reduction and machine learning on the proteomics data defined 4 distinct plaque phenotypes and revealed key protein signatures linked to smooth muscle cell content, plaque calcification and structural extracellular matrix, which improved the 9-year prognostic AUC by 25% compared to ultrasound and histology. A biosignature of four proteins (CNN1, PROC, SERPH, and CSPG2) independently predicted the progression of atherosclerosis and cardiovascular mortality with an AUC of 75% Conclusion: We combined discovery and targeted proteomics with network reconstruction and clustering techniques to provide molecular insights into protein changes in atherosclerotic plaques. The application of proteomics and machine learning techniques revealed distinct clusters of plaques that inform on disease progression and future adverse cardiovascular events.
2023-09-07 | PXD030975 | Pride
Project description:Background: Using proteomics, we strove to reveal novel molecular subtypes of human atherosclerotic lesions, study their associations with histology and imaging and relate them to long-term cardiovascular outcomes. Methods: 219 samples were obtained from 120 patients undergoing carotid endarterectomy. Sequential protein extraction was combined with multiplexed, discovery proteomics. Parallel reaction monitoring for 135 proteins was deployed for targeted validation. A combination of statistical, bioinformatics and machine learning methods was used to perform differential expression, network, pathway enrichment analysis and train and evaluate prognostic models. Results: Our extensive proteomics analysis from the core and periphery of plaques doubled the coverage of the plaque proteome compared to the largest proteomics study on atherosclerosis thus far. Plaque inflammation and calcification signatures were inversely correlated and validated with targeted proteomics. The inflammation signature was enriched with neutrophil-derived proteins, including calprotectin (S100A8/9) and myeloperoxidase. The calcification signature contained fetuin-A, osteopontin, and gamma-carboxylated proteins. Sex differences in the proteome of atherosclerosis were explained by a higher proportion of calcified plaques in women. Single-cell RNA sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages and the calcification signature to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in the plaque, i.e., fetuin-A. Echogenic lesions reflect the collagen content and calcification of plaque but carotid Duplex ultrasound fails to capture the extent of inflammatory protein changes in symptomatic plaques. Applying dimensionality reduction and machine learning on the proteomics data defined 4 distinct plaque phenotypes and revealed key protein signatures linked to smooth muscle cell content, plaque calcification and structural extracellular matrix, which improved the 9-year prognostic AUC by 25% compared to ultrasound and histology. A biosignature of four proteins (CNN1, PROC, SERPH, and CSPG2) independently predicted the progression of atherosclerosis and cardiovascular mortality with an AUC of 75% Conclusion: We combined discovery and targeted proteomics with network reconstruction and clustering techniques to provide molecular insights into protein changes in atherosclerotic plaques. The application of proteomics and machine learning techniques revealed distinct clusters of plaques that inform on disease progression and future adverse cardiovascular events.
2023-11-15 | PXD031052 | Pride
Project description:Low frequency Jak2VF mutations promote atherosclerosis via IL-1 mediated cross-talk. Therapeutic approaches that increase MERTK or TREM2 could promote plaque stabilization in inflammasome-driven atherosclerosis.
2024-11-26 | GSE280703 | GEO
Project description:Smooth muscle cells (SMC) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC transdifferentiation into macrophage-like SMCs. Furthermore, during transdifferentiation, the SMCs' expression of PADI4 upregulating and SMC generated extracellular trap, a web-like structure, which plays key role in the development of atherosclerosis plaque. To reveal the function of SMC's generating ETs during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of mouse atherosclerotic plaques.
2022-11-04 | GSE197073 | GEO
Project description:Atherosclerosis is a transmural chronic inflammatory condition of small and large arteries that is associated with adaptive immune responses at all disease stages. However, impacts of adaptive immune reactions on clinically apparent atherosclerosis such as intima lesion (plaque) rupture, thrombosis, myocardial infarction, and aneurysm largely remain to be identified. It is increasingly recognized that leukocyte infiltrates in plaque, media, and adventitia are distinct but their specific roles have not been defined. To map these infiltrates, we employed laser capture microdissection (LCM) to isolate the three arterial wall laminae using apoE-/- mouse aorta as a model. RNA from LCM-separated tissues was extracted and large scale whole genome expression microarrays were prepared. We observed that the quality of the resulting gene expression maps was compromised by tissue RNA carried over from adjacent laminae during LCM. To account for these flaws, we established quality controls and algorithms to improve the predictive power of LCM-derived microarray data. Our approach creates robust transcriptome atlases of normal and atherosclerotic aorta. Assessing LCM transcriptomes for immunity-related mRNAs indicated markedly distinctive gene expression patterns in the three laminae of the atherosclerotic aorta. These mouse mRNA expression data banks can now be mined to address a wide range of questions in cardiovascular biology. Wild-type and apoE-deficient mice on the C57BL/6J genetic background were maintained on a standard mouse chow. Total aortae were removed at the age of 78 weeks, abdominal aorta was separated from the remainder of the tissue and arterial wall laminae were separated by laser capture microdissection as described (Beer et al. 2011). Following RNA quality controls, microarrays were prepared following MIAME guidelines as described previously (Uzonyi et al. 2006; Graebner et al. 2009; Lotzer et al. 2010).
2011-11-03 | E-GEOD-21419 | biostudies-arrayexpress
Project description:Inflammatory activation of endothelial cells is considered to be the first step in the development of atherosclerosis. Here, we determined the consequences of chronic endothelial NF-κB activation on the development and progression of atherosclerosis as well as plaque regression.
2020-06-28 | GSE150698 | GEO