Dataset Information

Data mining of atherosclerotic plaque transcriptomes predicts STAT1-dependent inflammatory signal integration in vascular disease.

ABSTRACT: Atherosclerotic plaque development involves multiple extra- and intra-cellular signals engaging cells from the immune system and from the vasculature. Pro-inflammatory pathways activated by interferon gamma (IFN?) and toll-like receptor 4 (TLR4) ligands are profoundly involved in plaque formation and have been shown to involve cross-talk in all atheroma-interacting cell types leading to increased activation of signal transducer and activator of transcription-1 (STAT1) and elevated expression of pro-inflammatory mediators. Here we demonstrate that in Gene Expression Omnibus repository (GEO) deposited microarray datasets, obtained from human coronary and carotid atherosclerotic plaques, a significant increase in expression of pro-inflammatory and immunomodulatory genes can be detected. Moreover, increased expression of multiple chemokines, adhesion molecules and matrix-remodeling molecules was commonly detected in both plaque types and correlated with the presence of putative STAT1 binding sites in their promoters, suggesting strong involvement of STAT1 in plaque development. We also provide evidence to suggest that STAT1-nuclear factor kappa-light-chain-enhancer of activated B cells (NF?B) or STAT1-interferon-regulated factor (IRF) regulatory modules are over-represented in the promoters of these inflammatory genes, which points to a possible contribution of IFN? and TLR4 cross-talk in the process of atherogenesis. Finally, a subset of these genes encodes for secreted proteins that could serve as a basis of a non-invasive diagnostic assay. The results of our in silico analysis in vitro provide potential evidence that STAT1-dependent IFN?-TLR4 cross-talk plays a crucial role in coronary and carotid artery plaque development and identifies a STAT1-dependent gene signature that could represent a novel diagnostic tool to monitor and diagnose plaque progression in human atherosclerosis.

SUBMITTER: Sikorski K

PROVIDER: S-EPMC4159852 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Data mining of atherosclerotic plaque transcriptomes predicts STAT1-dependent inflammatory signal integration in vascular disease.

Sikorski Krzysztof K Wesoly Joanna J Bluyssen Hans A R HA

International journal of molecular sciences 20140818 8

Atherosclerotic plaque development involves multiple extra- and intra-cellular signals engaging cells from the immune system and from the vasculature. Pro-inflammatory pathways activated by interferon gamma (IFNγ) and toll-like receptor 4 (TLR4) ligands are profoundly involved in plaque formation and have been shown to involve cross-talk in all atheroma-interacting cell types leading to increased activation of signal transducer and activator of transcription-1 (STAT1) and elevated expression of ...[more]

PMID: 25196434

Similar Datasets

Project description:Atherosclerosis is a chronic inflammatory disease of the blood vessels, characterized by atherosclerotic lesions. Early vascular injury initiates excessive inflammatory and immune responses, communicated by blood leukocytes and cells from the vasculature. Key factors contributing to early stages of atherosclerosis and plaque development include the pro-inflammatory cytokine IFNγ, which is vital for both innate and adaptive immunity and is also expressed at high levels in atherosclerotic lesions. Recent discoveries provide novel evidence to suggest that IFNγ-activated STAT1 orchestrates a platform of cell-type common and specific inflammatory responses in Vascular Smooth Muscle Cells (VSMC) and macrophages (MΦ) that are instrumental in the onset and progression of atherosclerotic plaque formation. Therefore, we compared genome-wide transcriptional responses of mouse VSMCs and bone marrow-derived macrophages (BMDMs) in time-dependent IFNγ response using RNA-seq. We identified genes upregulated both in a common and cell-type-specific manner. Next, comparative analysis with RNAseq data from aortic plaques from HFD-treated ApoEKO mice identified 225 differentially expressed genes with a BMDM-specific character. These included many known IFNγ target genes containing putative GAS and ISRE sites in their promoters. Likewise, using a scRNAseq data set obtained from human coronary atherosclerotic plaques, identified 98 pro-inflammatory and pro-atherogenic genes that were characterized as BMDM-specific and exclusively expressed in foamy, inflammatory, monocytes and tissue-resident BMDM subtypes. Finally, we identified a 25 BMDM-specific gene subset commonly expressed in mouse and human plaques, over-representing STAT1-binding sites and predominantly associated with Leukocyte Chemotaxis and Migration. These results provide strong evidence for a BMDM-specific role of STAT1 in coronary artery plaque development and identify a BMDM-specific STAT1-dependent pro-inflammatory gene signature that could serve to monitor and diagnose plaque progression in human atherosclerosis.

Project description:Background and purposeGadolinium enhancement on high-resolution vessel wall imaging (HR-VWI) is an imaging marker of intracranial atherosclerotic stenosis (ICAS) plaque instability. This study aimed to evaluate the relationships between hematological inflammatory indicators and the enhancement of ICAS plaques and to search for hematological indicators that can predict ICAS plaque instability.MethodsConsecutive adult patients diagnosed with ICAS from April 2018 to December 2021 were recruited retrospectively, and every patient underwent HR-VWI. Plaque enhancement was measured qualitatively and quantitatively. The plaque-to-pituitary stalk contrast ratio (CR) indicated the degree of plaque enhancement. Clinical and laboratory data, including the lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII), were recorded. The hematological inflammatory indicators were compared between ICAS patients with and without plaque enhancement and between patients with and without symptomatic plaque. The hematological inflammatory indicators and the CR were compared using linear regression. Furthermore, receiver operating characteristic curve analysis was performed to assess the discriminative abilities of the inflammatory indicators to predict plaque instability.ResultsFifty-nine patients were included. The NLR, SII and LMR were significantly correlated with plaque enhancement. The LMR was independently associated with plaque enhancement, and a linear negative correlation was observed between the LMR and CR (R = 0.716, P < 0.001). The NLR, LMR, plaque enhancement and CR were significantly associated with symptomatic ICAS, and the LMR and plaque enhancement were independent risk factors for symptomatic ICAS. The optimal cutoff value of the admission LMR to distinguish symptomatic plaque from asymptomatic plaque was 4.0 (80.0% sensitivity and 70.6% specificity).ConclusionThe LMR was independently associated with ICAS plaque enhancement and showed a linear negative correlation with CR. The LMR and plaque enhancement were independent risk factors for symptomatic ICAS. An LMR ≤ 4.0 may predict ICAS plaque instability.

Dataset Information

Data mining of atherosclerotic plaque transcriptomes predicts STAT1-dependent inflammatory signal integration in vascular disease.

Publications

Data mining of atherosclerotic plaque transcriptomes predicts STAT1-dependent inflammatory signal integration in vascular disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets