Dataset Information

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker.

ABSTRACT: Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as coronary atherosclerosis. Based on the l-DNB methodology, by using the metabolomics data of plasma of patients with coronary atherosclerosis at different stages, we accurately detected the early-warning signals of each patient. Moreover, we also discovered a group of dynamic network biomarkers (DNBs) which play key roles in driving the progression of the disease. Our study provides a new insight into the individualized early diagnosis of coronary atherosclerosis and may contribute to the development of personalized medicine.

SUBMITTER: Ge J

PROVIDER: S-EPMC7350211 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker.

Ge Jing J Song Chenxi C Zhang Chengming C Liu Xiaoping X Chen Jingzhou J Dou Kefei K Chen Luonan L

Genes 20200620 6

Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as cor ...[more]

PMID: 32575789

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Project description:PurposeThe specific mechanisms and biomarkersunderlying the progression of stable coronary artery disease (CAD) to acute myocardial infarction (AMI) remain unclear. The current study aims to explore novel gene biomarkers associated with CAD progression by analyzing the transcriptomic sequencing data of peripheral blood monocytes in different stages of CAD.Material and methodsA total of 24 age- and sex- matched patients at different CAD stages who received coronary angiography were enrolled, which included 8 patients with normal coronary angiography, 8 patients with angiographic intermediate lesion, and 8 patients with AMI. The RNA from peripheral blood monocytes was extracted and transcriptome sequenced to analyze the gene expression and the differentially expressed genes (DEG). A Gene Oncology (GO) enrichment analysis was performed to analyze the biological function of genes. Weighted gene correlation network analysis (WGCNA) was performed to classify genes into several gene modules with similar expression profiles, and correlation analysis was carried out to explore the association of each gene module with a clinical trait. The dynamic network biomarker (DNB) algorithm was used to calculate the key genes that promote disease progression. Finally, the overlapping genes between different analytic methods were explored.ResultsWGCNA analysis identified a total of nine gene modules, of which two modules have the highest positive association with CAD stages. GO enrichment analysis indicated that the biological function of genes in these two gene modules was closely related to inflammatory response, which included T-cell activation, cell response to inflammatory stimuli, lymphocyte activation, cytokine production, and the apoptotic signaling pathway. DNB analysis identified a total of 103 genes that may play key roles in the progression of atherosclerosis plaque. The overlapping genes between DEG/WGCAN and DNB analysis identified the following 13 genes that may play key roles in the progression of atherosclerosis disease: SGPP2, DAZAP2, INSIG1, CD82, OLR1, ARL6IP1, LIMS1, CCL5, CDK7, HBP1, PLAU, SELENOS, and DNAJB6.ConclusionsThe current study identified a total of 13 genes that may play key roles in the progression of atherosclerotic plaque and provides new insights for early warning biomarkers and underlying mechanisms underlying the progression of CAD.

Project description:BackgroundAn increasing number of authors employing intravascular ultrasound (IVUS) and virtual histology (VH-IVUS) have investigated the effect of statin use on plaque volume (PV) and plaque composition. However, inconsistent results have been reported. Therefore, we conducted a meta-analysis to determine the appropriate regimen of statins to effectively stabilize vulnerable coronary plaques.MethodsOnline electronic databases were carefully searched for all relevant studies. We compared mean values of PV and plaque composition between baseline and follow-up in patients receiving statin therapy. We pooled treatment effects and calculated mean differences (MD) with the 95% confidence interval (CI) using a random-effects model. By stratified analyses, we explored the influence of clinical presentation, dose and duration of statin treatment, and low-density lipoprotein-cholesterol (LDL-C) levels on the effects of statins.ResultsSeventeen studies involving 2,171 patients were analyzed. Statin therapy significantly decreased PV (-5.3 mm(3); 95% CI: -3.3 mm(3) to -7.2 mm(3) P < 0.001), without heterogeneity. When considering the dose and duration of statins used, only subgroups employing a high dose and long duration demonstrated a significant reduction in PV (p < 0.001). A significant decrease in PV was noted if achieved LDL-C levels were <100 mg/dL (p < 0.001). Statin treatment could induce a twofold decrease in PV in patients with acute coronary syndrome (ACS) compared with that observed in patients with stable angina pectoris (SAP). A regressive trend was seen for necrotic core volume (MD: -2.1 mm(3); 95% CI: -4.7 mm(3) to 0.5 mm(3), P = 0.11). However, statin use did not induce a significant change for fibrotic, fibro-fatty, or dense calcium compositions.ConclusionsOur meta-analysis demonstrated that statin therapy (especially that involving a high dose and long duration and achieving <100 mg/dL LDL-C levels) can significantly decrease PV in patients with SAP or ACS. These data suggested that statins can be used to reduce the atheroma burden for secondary prevention by appropriately selecting the statin regimen. No significant change in plaque composition was seen after statin therapy.

Dataset Information

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker.

Publications

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker.

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