Identifying functional modules for coronary artery disease by a prior knowledge-based approach

Li, Haoli; Zuo, Xiaoyu; Ouyang, Ping; Lin, Mei-Hua; Zhao, Zhigang; Liang, Yan; Zhong, Shouqiang; Rao, Shaoqi

doi:10.1016/j.gene.2013.12.049

Cited by 11 publications

(5 citation statements)

References 57 publications

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“…Third, we used two large independent CAD GWAS meta-analyses, merged and trimmed overlapping CAD-associated gene sets, and imposed a strict Bonferroni threshold for final statistical evaluation of the CAD signals to avoid false positives and focus on the most reliable core processes for CAD. Fourth, we utilized scores of empirically-derived gene networks from diverse CAD-related tissues to extract the CAD network architecture and the key driver genes, whereas previous studies have relied on literature-based topologies, protein-protein interaction networks, or single-tissue networks [3], [38]–[40]. Lastly, we performed targeted siRNA studies in HAEC to provide experimental support for our in silico findings.…”

Section: Discussionmentioning

confidence: 93%

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Mäkinen¹,

et al. 2014

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The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.

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Section: Discussionmentioning

confidence: 93%

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Mäkinen¹,

et al. 2014

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“…Therefore, the genetic basis of CAD has remained largely unknown due to the limited understanding of just a small proportion of individual genetic variations. There is a developing consensus that genetic variations of CAD often function by sophisticated interactions through a modular fashion rather than individually [10]. With the improvement of computational methods, gene set-based association analysis (GSA) aimed at evaluating the joint effects of a defined gene set by quantifying the susceptibility or statistical significance of individual functional units, e.g.…”

Section: Introductionmentioning

confidence: 99%

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-Wide SNP Data

Zhao

Luan

Zuo

et al. 2016

Genomics, Proteomics &Amp; Bioinformatics

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Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer’s disease, non-alcoholic fatty liver disease, and Huntington’s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer’s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer’s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

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“…Therefore, it may be inferred that LCK and ZAP70 serve a role in CAD, which may partly be by regulating natural killer cell mediated cytotoxicity and primary immunodeficiency pathways. Additionally, a previous study with a novel knowledge-based approach revealed that the Fc gamma R-mediated phagocytosis pathway is a pathogenic mechanism for CAD ( 38 ). Likewise, the present study suggests that ‘Fc gamma R-mediated phagocytosis’ may have a function in CAD.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of promising molecular biomarkers and pathways for coronary artery disease using WGCNA and MetaDE methods

Yan

2018

Mol Med Report

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The present study aimed to examine the molecular mechanisms of coronary artery disease (CAD). A total of four microarray datasets (training dataset no. GSE12288; validation dataset nos. GSE20680, GSE20681 and GSE42148) were downloaded from the Gene Expression Omnibus database, which included CAD and healthy samples. Weighted gene co-expression network analysis was applied to identify highly preserved modules across the four datasets. Differentially expressed genes (DEGs) with significant consistency in the four datasets were selected using the MetaDE method. The overlapping genes amongst the DEGs with significant consistency and in the preserved modules were used to construct a protein-protein interaction (PPI) network, followed by functional enrichment analysis. A total of 11 modules were established in the training dataset, and five of them were highly preserved across all four datasets, including 873 genes. There was a total of 836 DEGs with significant consistency in the four datasets. A total of 177 overlapping genes were selected, with which a PPI network was constructed. The top five genes of the PPI network were identified based on their degrees: LCK proto-oncogene, Src family tyrosine kinase (LCK), euchromatic histone lysine methyltransferase 2 (EHMT2), inosine monophosphate dehydrogenase 2 (IMPDH2), protein phosphatase 4 catalytic subunit (PPP4C) and ζ-chain of T-cell receptor associated protein kinase 70 (ZAP70). Genes in the PPI network were significantly involved in a number of Kyoto Encyclopedia Genes and Genomes pathways, including the ‘natural killer cell mediated cytotoxicity’, ‘primary immunodeficiency’ and ‘Fc gamma R-mediated phagocytosis’ pathways. LCK, EHMT2, IMPDH2, PPP4C and ZAP70 are suggested as promising molecular biomarkers for CAD. The ‘natural killer cell mediated cytotoxicity’, ‘primary immunodeficiency’ and ‘Fc gamma R-mediated phagocytosis’ pathways may serve important roles in CAD.

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Identifying functional modules for coronary artery disease by a prior knowledge-based approach

Cited by 11 publications

References 57 publications

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-Wide SNP Data

Integrative analysis of promising molecular biomarkers and pathways for coronary artery disease using WGCNA and MetaDE methods

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