Weighted Gene Co-Expression Network Analysis Reveals Key Genes and Potential Drugs in Abdominal Aortic Aneurysm.
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ABSTRACT:
SUBMITTER: Kan KJ
PROVIDER: S-EPMC8152975 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThere is still an unmet need for therapeutic drugs for patients with an abdominal aortic aneurysm (AAA), especially for candidates unsuitable for surgical or interventional repair. Therefore, the purpose of this in silico study is to identify significant genes and regulatory mechanisms in AAA patients to predicate the potential therapeutic compounds for significant genes.MethodsThe GSE57691 dataset was obtained from Gene Expression Omnibus (GEO) and used to identify the differentially expressed genes (DEGs) and weighted correlation network analysis (WGCNA). The biological function of DEGs was determined using gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). AAA-related genes were obtained from the Comparative Toxicogenomics Database (CTD) using the keywords: aortic aneurysm and abdominal. The hub genes in AAA were obtained by overlapping DEGs, WGCNA-based hub genes, and CTD-based genes. The diagnostic values of hub genes were determined using ROC curve analysis. Hereby, a TF-miRNA-hub gene network was constructed based on the miRnet database. Using these data, potential therapeutic compounds for the therapy of AAA were predicted based on the Drug Gene Interaction Database (DGIdb).ResultsA total of 218 DEGs (17 upregulated and 201 downregulated) and their biological function were explored; 4093 AAA-related genes were derived by text mining. Three hub modules and 144 hub genes were identified by WGCNA. asparagine synthetase (ASNS), axin-related protein 2 (AXIN2), melanoma cell adhesion molecule (MCAM), and the testis-specific Y-encoded-like protein 1 (TSPYL1) were obtained as intersecting hub genes and the diagnostic values were confirmed with ROC curves. As potential compounds targeting the hub genes, asparaginase was identified as the target compound for ASNS. Prednisolone and abiraterone were identified as compounds targeting TSPYL1. For MCAM and TSPYL1, no potential therapeutic compound could be predicted.ConclusionUsing WGCNA analysis and text mining, pre-existing gene expression data were used to provide novel insight into potential AAA-related protein targets. For two of these targets, compounds could be predicted.
| S-EPMC9138830 | biostudies-literature
Project description:BackgroundThoracic aortic aneurysm (TAA) is a potentially life-threatening disease for which few medical therapies are available. Thus, it is critically important to investigate the underlying molecular mechanisms of TAA, and identify potential targets for TAA treatment.MethodsDifferentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were screened, and a weighted correlation network analysis (WGCNA) was employed to construct a weighted miRNA co-expression network using GSE110527. The DEMs were then mapped into the whole co-expression network of all samples, and a DEM coexpression network was created. Molecular Complex Detection (MCODE) was used to identify crucial miRNAs. Target genes were predicted using the miRTarbase database, and further screened by identifying genes that overlapped with the DEGs of GSE26155. The screened target genes were validated using GSE9106, and the successfully validated genes were considered as crucial genes. Finally, a miRNA risk score for diagnosing TAA was calculated by undertaking a least absolute shrinkage and selection operator (LASSO) regression.ResultsThe tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) signaling pathway was found in DEM functional enrichment. Crucial miRNAs were identified and target genes were predicted and associated with the regulation of the TRAIL signaling pathway. Next, 113 important target genes were identified as overlapping with the DEGs of GSE26155. These genes were further validated, and 5 successfully validated genes were considered as crucial genes. Finally, the miRNA risk score calculated by the LASSO regression was shown to have potential diagnostic value.ConclusionsWe performed a WGCNA analysis to construct a weighted miRNA co-expression network, predicted target genes of crucial miRNAs, identified crucial genes, and finally calculated a miRNA risk score. The results showed that pathways and genes associated with apoptosis appear to play an important role in TAA pathogenesis, and that medications targeting apoptosis might slow TAA progression. Future in vitro and in vivo experimental studies need to be undertaken to further validate our findings and investigate the mechanistic details of these crucial miRNAs and crucial genes.
| S-EPMC8182548 | biostudies-literature
Project description:Objectives: Abdominal aortic aneurysms (AAAs) are associated with high mortality rates. The genes and pathways linked with AAA remain poorly understood. This study aimed to identify key differentially expressed genes (DEGs) linked to the progression of AAA using bioinformatics analysis. Methods: Gene expression profiles of the GSE47472 and GSE57691 datasets were acquired from the Gene Expression Omnibus (GEO) database. These datasets were merged and normalized using the "sva" R package, and DEGs were identified using the limma package in R. The functions of these DEGs were assessed using Cytoscape software. We analyzed the DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein-protein interaction networks were assembled using Cytoscape, and crucial genes were identified using the Cytoscape plugin, molecular complex detection. Data from GSE15729 and GSE24342 were also extracted to verify our findings. Results: We found that 120 genes were differentially expressed in AAA. Genes associated with inflammatory responses and nuclear-transcribed mRNA catabolic process were clustered in two gene modules in AAA. The hub genes of the two modules were IL6, RPL21, and RPL7A. The expression levels of IL6 correlated positively with RPL7A and negatively with RPL21. The expression of RPL21 and RPL7A was downregulated, whereas that of IL6 was upregulated in AAA. Conclusions: The expression of RPL21 or RPL7A combined with IL6 has a diagnostic value for AAA. The novel DEGs and pathways identified herein might provide new insights into the underlying molecular mechanisms of AAA.
| S-EPMC8329524 | biostudies-literature
Project description:Inflammation is strongly implicated in the pathogenesis of abdominal aortic aneurysms (AAA). This review examined the potential role of biologic disease-modifying anti-rheumatic drugs (bDMARDs) as repurposed drugs for treating AAA. Published evidence from clinical and preclinical studies was examined. Findings from animal models suggested that a deficiency or inhibition of tumour necrosis factor-α (TNF-α) (standard mean difference (SMD): -8.37, 95% confidence interval (CI): -9.92, -6.82), interleukin (IL)-6 (SMD: -1.44, 95% CI: -2.85, -0.04) and IL-17 (SMD: -3.36, 95% CI: -4.21, -2.50) led to a significantly smaller AAA diameter compared to controls. Human AAA tissue samples had significantly increased TNF-α (SMD: 1.68, 95% CI: 0.87, 2.49), IL-1β (SMD: 1.93, 95% CI: 1.08, 2.79), IL-6 (SMD: 2.56, 95% CI: 1.79, 3.33) and IL-17 (SMD: 6.28, 95% CI: 3.57, 8.99) levels compared to non-AAA controls. In human serum, TNF-α (SMD: 1.11, 95% CI: 0.25, 1.97) and IL-6 (SMD: 1.42, 95% CI: 0.91, 1.92) levels were significantly elevated compared to non-AAA controls. These findings implicate TNF-α, IL-17 and IL-6 in AAA pathogenesis. Randomised controlled trials testing the value of bDMARDs in limiting AAA growth may be warranted.
| S-EPMC9598733 | biostudies-literature
Project description:Background While numerous interventions effectively interfered with abdominal aortic aneurysm (AAA) formation/progression in preclinical models, none of the successes translated into clinical success. Hence, a systematic exploration of parallel and divergent processes in clinical AAA disease and its 2 primary models (the porcine pancreatic elastase and angiotensin-II infusion [AngII] murine model) was performed to identify mechanisms relevant for aneurysm disease. Methods and Results This study combines Movat staining and pathway analysis for histological and genomic comparisons between clinical disease and its models. The impact of a notable genomic signal for metabolic reprogramming was tested in a rescue trial (AngII model) evaluating the impact of 1-(4-pyridinyl)-3-(2-quinolinyl)-2-propen-1-one (PFK15)-mediated interference with main glycolytic switch PFKFB3. Histological evaluation characterized the AngII model as a dissection model that is accompanied by adventitial fibrosis. The porcine pancreatic elastase model showed a transient inflammatory response and aortic dilatation, followed by stabilization and fibrosis. Normalization of the genomic responses at day 14 confirmed the self-limiting nature of the porcine pancreatic elastase model. Clear parallel genomic responses with activated adaptive immune responses, and particularly strong signals for metabolic switching were observed in human AAA and the AngII model. Rescue intervention with the glycolysis inhibitor PFK15 in the AngII model showed that interference with the glycolytic switching quenches aneurysm formation. Conclusions Despite clear morphological contrasts, remarkable genomic parallels exist for clinical AAA disease and the AngII model. The metabolic response appears causatively involved in AAA progression and provides a novel therapeutic target. The clear transient genomic response classifies the porcine pancreatic elastase model as a disease initiation model.
| S-EPMC8649280 | biostudies-literature
Project description:Abdominal artery aneurysm (AAA) refers to abdominal aortic dilatation of 3 cm or greater. AAA is frequently underdiagnosed due to often asymptomatic character of the disease, leading to elevated mortality due to aneurysm rupture. MiRNA constitute a pool of small RNAs controlling gene expression and is involved in many pathologic conditions in human. Targeted panel detecting altered expression of miRNA and genes involved in AAA would improve early diagnosis of this disease. In the presented study, we selected and analyzed miRNA and gene expression signatures in AAA patients. Next, generation sequencing was applied to obtain miRNA and gene-wide expression profiles from peripheral blood mononuclear cells in individuals with AAA and healthy controls. Differential expression analysis was performed using DESeq2 and uninformative variable elimination by partial least squares (UVE-PLS) methods. A total of 31 miRNAs and 51 genes were selected as the most promising biomarkers of AAA. Receiver operating characteristics (ROC) analysis showed good diagnostic ability of proposed biomarkers. Genes regulated by selected miRNAs were determined in silico and associated with functional terms closely related to cardiovascular and neurological diseases. Proposed biomarkers may be used for new diagnostic and therapeutic approaches in management of AAA. The findings will also contribute to the pool of knowledge about miRNA-dependent regulatory mechanisms involved in pathology of that disease.
| S-EPMC7355415 | biostudies-literature
Project description:Abdominal aortic aneurysm (AAA) is a chronic vascular disease caused by localized weakening and broadening of the abdominal aorta. AAA is a clearly underdiagnosed disease and is burdened with a high mortality rate (65-85%) from AAA rupture. Studies indicate that abnormal regulation of angiogenesis and inflammation contributes to progression and onset of this disease; however, dysregulations in the molecular pathways associated with this disease are not yet fully explained. Therefore, in our study, we aimed to identify dysregulations in the key regulators of angiogenesis and inflammation in patients with AAA in peripheral blood mononuclear cells (using qPCR) and plasma samples (using ELISA). Expression levels of ANGPT1, CXCL8, PDGFA, TGFB1, VEGFB, and VEGFC and plasma levels of TGF-alpha, TGF-beta 1, VEGF-A, and VEGF-C were found to be significantly altered in the AAA group compared to the control subjects without AAA. Associations between analyzed factors and risk factors or biochemical parameters were also explored. Any of the analyzed factors was associated with the size of the aneurysm. The presented study identified dysregulations in key angiogenesis- and inflammation-related factors potentially involved in AAA formation, giving new insight into the molecular pathways involved in the development of this disease and providing candidates for biomarkers that could serve as diagnostic or therapeutic targets.
| S-EPMC10418409 | biostudies-literature
Project description:Abdominal aortic aneurysm (AAA) is hallmarked by irreversible dilation of the infrarenal aorta. Lipid deposition in the aortic wall and the potential importance of a lipid disorder in AAA etiology highlight the need to explore lipid variation during AAA development. This study aimed to systematically characterize the lipidomics associated with AAA size and progression. Plasma lipids from 106 subjects (36 non-AAA controls and 70 AAA patients) were comprehensively analyzed using untargeted lipidomics. An AAA animal model was established by embedding angiotensin-II pump in ApoE-/- mice for four weeks and blood was collected at 0, 2 and 4 weeks for lipidomic analysis. Using a false-discovery rate (FDR) < 0.05, a group of lysophosphatidylcholines (lysoPCs) were specifically decreased in AAA patients and mice. LysoPCs were principally lower in the AAA patients with larger diameter (diameter > 50 mm) than those with a smaller size (30 mm < diameter < 50 mm), and levels of lysoPCs were also found to be decreased with modelling time and aneurysm formation in AAA mice. Correlation matrices between lipids and clinical characteristics identified that the positive correlation between lysoPCs and HDL-c was reduced and negative correlations between lysoPCs and CAD rate, lysoPCs and hsCRP were converted to positive correlations in AAA compared to control. Weakened positive correlations between plasma lysoPCs and circulating HDL-c in AAA suggested that HDL-lysoPCs may elicit instinctive physiological effects in AAA. This study provides evidence that reduced lysoPCs essentially underlie the pathogenesis of AAA and that lysoPCs are promising biomarkers for AAA development.
| S-EPMC10299432 | biostudies-literature
Project description:BackgroundCalcific aortic valve disease (CAVD) is the most common subclass of valve heart disease in the elderly population and a primary cause of aortic valve stenosis. However, the underlying mechanisms remain unclear.MethodsThe gene expression profiles of GSE83453, GSE51472, and GSE12644 were analyzed by 'limma' and 'weighted gene co-expression network analysis (WGCNA)' package in R to identify differentially expressed genes (DEGs) and key modules associated with CAVD, respectively. Then, enrichment analysis was performed based on Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, DisGeNET, and TRRUST database. Protein-protein interaction network was constructed using the overlapped genes of DEGs and key modules, and we identified the top 5 hub genes by mixed character calculation.ResultsWe identified the blue and yellow modules as the key modules. Enrichment analysis showed that leukocyte migration, extracellular matrix, and extracellular matrix structural constituent were significantly enriched. SPP1, TNC, SCG2, FAM20A, and CD52 were identified as hub genes, and their expression levels in calcified or normal aortic valve samples were illustrated, respectively.ConclusionsThis study suggested that SPP1, TNC, SCG2, FAM20A, and CD52 might be hub genes associated with CAVD. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.
| S-EPMC8138987 | biostudies-literature
Project description:Abdominal aortic aneurysm (AAA) is a multifactorial disease with a strong genetic component. Since the first candidate gene studies were published 20 years ago, approximately 100 genetic association studies using single nucleotide polymorphisms (SNPs) in biologically relevant genes have been reported on AAA. These studies investigated SNPs in genes of the extracellular matrix, the cardiovascular system, the immune system, and signaling pathways. Very few studies were large enough to draw firm conclusions and very few results could be replicated in another sample set. The more recent unbiased approaches are family-based DNA linkage studies and genome-wide genetic association studies, which have the potential of identifying the genetic basis for AAA, only when appropriately powered and well-characterized large AAA cohorts are used. SNPs associated with AAA have already been identified in these large multicenter studies. One significant association was of a variant in a gene called contactin-3, which is located on chromosome 3p12.3. However, two follow-up studies could not replicate this association. Two other SNPs, which are located on chromosome 9p21 and 9q33, were replicated in other samples. The two genes with the strongest supporting evidence of contribution to the genetic risk for AAA are the CDKN2BAS gene, also known as ANRIL, which encodes an antisense ribonucleic acid that regulates expression of the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B, and DAB2IP, which encodes an inhibitor of cell growth and survival. Functional studies are now needed to establish the mechanisms by which these genes contribute toward AAA pathogenesis.
| S-EPMC3058859 | biostudies-literature