Dataset Information

Microarray and proteome array in an atherosclerosis mouse model for identification of biomarkers in whole blood.

ABSTRACT: Cardiovascular disease (CVD) is highly fatal, and 80 percent of the mortality is attributed to heart attack and stroke. Atherosclerosis is a disease that increases a patient's risk to CVD and is characterized by atheroma formed by immune cells, lipids, and smooth muscle cells. When an atherosclerotic lesion grows and blocks blood vessels or when an atheroma ruptures and blocks blood vessels by embolism, sudden angina, or stroke can occur. It is therefore important to diagnose atherosclerosis early and prevent its progression to more severe disease. Although myeloperoxidase, plasma fibrinogen, cardiac troponin-I, and C-reactive protein have been considered as diagnostic markers for multiple cardiac risks, specific biomarkers for atherosclerosis have not been clearly determined yet. Particularly, reliable biomarkers for the diagnosis of atherosclerosis using whole blood are not yet available. In this study, we screened potential biomarker genes and proteins from whole blood of apolipoprotein E knockout (ApoE-/- ) mice maintained on a Western diet, by comparing them to ApoE+/+ mice. We used whole blood for microarray and proteome array. Candidate genes and proteins identified from each method were confirmed with quantitative real-time PCR and ELISA. Based on our data, we speculate that Lilrb4a, n-R5s136, and IL-5 are potential targets that can be developed into novel biomarkers of atherosclerosis. Our study contributes to the diagnosis of atherosclerosis using whole blood in clinical settings.

SUBMITTER: Gwon SY

PROVIDER: S-EPMC6643112 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Microarray and proteome array in an atherosclerosis mouse model for identification of biomarkers in whole blood.

Gwon Sun-Yeong SY Lee Hae Min HM Rhee Ki-Jong KJ Sung Ho Joong HJ

International journal of medical sciences 20190602 6

Cardiovascular disease (CVD) is highly fatal, and 80 percent of the mortality is attributed to heart attack and stroke. Atherosclerosis is a disease that increases a patient's risk to CVD and is characterized by atheroma formed by immune cells, lipids, and smooth muscle cells. When an atherosclerotic lesion grows and blocks blood vessels or when an atheroma ruptures and blocks blood vessels by embolism, sudden angina, or stroke can occur. It is therefore important to diagnose atherosclerosis ear ...[more]

PMID: 31337962

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Project description:Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE(-/-) mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE(-/-) mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE(-/-) mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of ?(1)-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, ?(1)-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE(-/-) mice on HFD. Urinary excretion levels of collagen and ?(1)-antitrypsin fragments also significantly correlated with intraplaque collagen and ?(1)-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, ?(1)-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in murine and human atherosclerosis and thus also defines potential novel therapeutic targets.

Project description:Background:Lipid infiltration and inflammatory response run through the occurrence of atherosclerosis. Differentiation into macrophages and foam cell formation are the key steps of AS. Aim of this study was that the differential gene expression between foam cells and macrophages was analyzed to search the key links of foam cell generation, so as to explore the pathogenesis of atherosclerosis and provide targets for the early screening and prevention of coronary artery disease (CAD).Methods:The gene expression profiles of GSE9874 were downloaded from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9874) on GPL96 [HG-U133A] Affymetrix Human Genome U133. A total of 22,383 genes were analyzed for differentially expression genes (DEGs) by Bayes package. GO enrichment analysis and KEGG pathway analysis for DEGs were performed using KOBAS 3.0 software (Peking University, Beijing, China). STRING software (STRING 10.0; European Molecular Biology Laboratory, Heidelberg, Germany) was used to analyze the protein-protein interaction (PPI) of DEGs.Results:A total of 167 DEGs between macrophages and foam cells were identified. Compared with macrophages, 102 genes were significantly upregulated and 65 genes were significantly downregulated (P?<?0.01, fold-change >?1) in foam cells. DEGs were mainly enrich in 'sterol biosynthetic and metabolic process', 'cholesterol metabolic and biosynthetic process' by GO enrichment analysis. The results of KEGG pathway analysis showed all differential genes are involved in biological processes through 143 KEGG pathways. A PPI network of the DEGs was constructed and 10 outstanding genes of the PPI network was identified by using Cytoscape, which include HMGCR, SREBF2, LDLR, HMGCS1, FDFT1, LPL, DHCR24, SQLE, ABCA1 and FDPS.Conclusion:Lipid metabolism related genes and molecular pathways were the key to the transformation of macrophages into foam cells. Therefore, lipid metabolism disorder is the key to turn macrophages into foam cells, which plays a major role in CAD.

Dataset Information

Microarray and proteome array in an atherosclerosis mouse model for identification of biomarkers in whole blood.

Publications

Microarray and proteome array in an atherosclerosis mouse model for identification of biomarkers in whole blood.

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