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Experimental Biology for the Identification of Causal Pathways in Atherosclerosis.

ABSTRACT: More than 60 genomic loci have been implicated by genome-wide association studies (GWAS) and exome-wide association studies as conferring an increased risk of myocardial infarction and coronary artery disease (CAD). However, the causal gene and variant is often unclear. Using the functional analysis of genetic variants in experimental animal models, we anticipate understanding which candidate gene at a specific locus is associated with atherosclerosis and revealing the underlying molecular and cellular mechanisms, ultimately leading to the identification of causal pathways in atherosclerosis and may provide novel therapeutic targets for the treatment of atherosclerotic cardiovascular disease.

SUBMITTER: Guo Y

PROVIDER: S-EPMC7088260 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Experimental Biology for the Identification of Causal Pathways in Atherosclerosis.

Guo Yanhong Y Garcia-Barrio Minerva T MT Wang Laiyuan L Chen Y Eugene YE

Cardiovascular drugs and therapy 20160201 1

More than 60 genomic loci have been implicated by genome-wide association studies (GWAS) and exome-wide association studies as conferring an increased risk of myocardial infarction and coronary artery disease (CAD). However, the causal gene and variant is often unclear. Using the functional analysis of genetic variants in experimental animal models, we anticipate understanding which candidate gene at a specific locus is associated with atherosclerosis and revealing the underlying molecular and c ...[more]

PMID: 26847647

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Project description:BackgroundAtherosclerosis (AS) is a chronic inflammatory disease that might induce severe cardiovascular events, such as myocardial infarction and cerebral infarction. These risk factors in the pathogenesis of AS remain uncertain and further research is needed. This study aims to explore the potential molecular mechanisms of AS by bioinformatics analyses.MethodsGSE100927 gene expression profiles, including 69 AS samples and 35 healthy controls, were downloaded from Gene Expression Omnibus database and indenfied for key genes and pathways in AS.ResultsA total of 443 differentially expressed genes (DEGs) between control and AS were identified, including 323 down-regulated genes and 120 up-regulated genes. The Gene ontology terms enriched by the up-regulated DEGs were associated with the regulation of leukocyte activation, endocytic vesicle, and cytokine binding, while the down-regulated DEGs were associated with negative regulation of cell growth, extracellular matrix, and G protein-coupled receptor binding. KEGG pathway analysis showed that the up-regulated DEGs were enriched in Osteoclast differentiation and Phagosome, while the down-regulated DEGs were enriched in vascular smooth muscle contraction and cGMP-PKG signaling pathway. Using the modular analysis of Cytoscape, we identified 3 modules mainly involved in Leishmaniasis and Osteoclast differentiation. The GSEA analysis showed the up-regulated gene sets were enriched in the ribosome, ascorbated metabolism, and propanoate metabolism. The LASSO Cox regression analysis showed the top 3 genes were TNF, CX3CR1, and COL1R1. Finally, we found these immune cells were conferred significantly higher infiltrating density in the AS group.ConclusionsOur data showed the pathway of Osteoclast differentiation and Leishmaniasis was involved in the AS process and we developed a three-gene model base on the prognosis of AS. These findings clarified the gene regulatory network of AS and may provide a novel target for AS therapy.

Project description:Gastric cancer is the fourth cause of cancer death globally, and gastric adenocarcinoma is its most common type. Efforts for the treatment of gastric cancer have increased its median survival rate by only seven months. Due to the relatively low response of gastric cancer to surgery and adjuvant therapy, as well as the complex role of risk factors in its incidences, such as protein-pomp inhibitors (PPIs) and viral and bacterial infections, we aimed to study the pathological pathways involved in gastric cancer development and investigate possible medications by systems biology and bioinformatics tools. In this study, the protein-protein interaction network was analyzed based on microarray data, and possible effective compounds were discovered. Non-coding RNA versus coding RNA interaction network and gene-disease network were also reconstructed to better understand the underlying mechanisms. It was found that compounds such as amiloride, imatinib, omeprazole, troglitazone, pantoprazole, and fostamatinib might be effective in gastric cancer treatment. In a gene-disease network, it was indicated that diseases such as liver carcinoma, breast carcinoma, liver fibrosis, prostate cancer, ovarian carcinoma, and lung cancer were correlated with gastric adenocarcinoma through specific genes, including hgf, mt2a, mmp2, fbn1, col1a1, and col1a2. It was shown that signaling pathways such as cell cycle, cell division, and extracellular matrix organization were overexpressed, while digestion and ion transport pathways were underexpressed. Based on a multilevel systems biology analysis, hub genes in gastric adenocarcinoma showed participation in the pathways such as focal adhesion, platelet activation, gastric acid secretion, HPV infection, and cell cycle. PPIs are hypothesized to have a therapeutic effect on patients with gastric cancer. Fostamatinib seems a potential therapeutic drug in gastric cancer due to its inhibitory effect on two survival genes. However, these findings should be confirmed through experimental investigations.

Dataset Information

Experimental Biology for the Identification of Causal Pathways in Atherosclerosis.

Publications

Experimental Biology for the Identification of Causal Pathways in Atherosclerosis.

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