MiRNA analysis in Thoracic Aortic aneurysms
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PROVIDER: PRJNA635645 | ENA |
REPOSITORIES: ENA
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Project description:transcriptomic analysis of murine chronic proximal thoracic aortic aneurysms
| PRJNA1149746 | ENA
Project description:Introduction Thoracic aortic aneurysms frequently go undetected until serious complications like acute dissections or ruptures arise. Therefore, this study aims to identify potential blood circulating biomarkers enabling an easy and early diagnosis of thoracic aortic disease. Methods Potential biomarker candidates were identified through two different techniques, untargeted and targeted proteomic as well as exosome analyses. The biomarker levels were compared between two patient groups with thoracic aortic aneurysms and two control groups without thoracic aortic disease. In total, 80 patients (TAA group (n=40) vs. control group (n=40)) were matched for untargeted and targeted proteome analysis, and 85 for exosome analysis (TAA group (n=42) vs. control group (n=43)), based on the availability of blood samples and excised aortic tissue. Levels of biomarker candidates were correlated with aortic diameter, patient age, and histological alterations in aortic tissue using linear and logistic regression models. Results The untargeted proteomic and exosome analysis identified 1,037 and 1,077 proteins, respectively, of which 11 and 28 proteins showed significant differences in concentration between the study groups. Of these, 9 proteins correlated with the aortic diameter: ACTN1 (Regression coefficient B=1.633, p<0.001), CRP (B=0.001, p=0.004), TGM3 (B=-0.293, p=0.010), KRT84 (B=-0.477, p=0.010), IGHG3 (-0.267, p=0.018), DPYSL2 (B=0.644, p=0.020), TSPAN8 (B-0.838, p=0.042), IGKV3D-11 (B=-0.242, p=0.046), and VDAC1 (B=-0.491, p=0.047). Moreover, IGKV3D-11 (B=-3.257, p=0.029), IGHG3 (B=-0.003, p=0.034), and APOC3 (B=-2.104, p=0.037) showed significant correlations with the grade of aortic medial layer degeneration. None of the proteins correlated with patient age. Conclusion The study identified 9 biomarker candidates correlating with the aortic diameter. To enable the clinical use for diagnosis and prognostic assessment, these biomarkers need to be validated in larger external cohorts.
2026-05-13 | PXD061606 | Pride
Project description:Thoracic Aortic Aneurysm (TAA) is characterized by the dilation and degradation of the aorta and is fatal if not diagnosed and treated appropriately. There are no specific clinical symptoms, so better knowledge of the physiopathology of TAAs and their underlying genetic mechanisms is needed to improve diagnosis and therapy. MiRNAs regulate gene expression post-transcriptionally and are known to be involved in cerebrovascular disease. The current study aimed to identify differentially expressed miRNAs in patients with TAAs and determine whether their predicted target genes could be associated with this condition. Nanostring assays identified miRNAs in plasma and tissue samples from four TAA patients. RT-PCR validated the expression levels of these miRNAs in a further 22 plasma samples. Three, hsa-miR140-5p, hsa-miR-191-5p and hsa-miR-214-3p showed significant expression level differences between plasma samples collected pre- and post-surgically from each patient. Analyses of the predicted target gene controlled by these miRNAs revealed nine genes whose expression was investigated in the same 22 plasma samples. The gene expression levels were inversely correlated with the expression of their respective miRNAs. From these, CCND2, CRKL, HEY1, MTMR4, NFIA and PPP1CB, showed fold-change differences >1.5 between the two plasma samples. An in-depth literature search and Cytoscape software three genes; MTMR4, NFIA and PPP1CB, showed a possible association with the TGF-β signalling pathway. It is suggested that the three miRNAs detected together with their target genes could play a role in the TGF-β signalling pathway and thus be involved in TAA pathogenesis.
2020-05-29 | GSE151378 | GEO
Project description:NHLBI GO-ESP: Family Studies (Thoracic aortic aneurysms leading to acute aortic dissections)
| PRJNA75309 | ENA
Project description:This study aimed to establish a chronic proximal thoracic aortic aneurysm(cPTAA) model by combining periaortic elastase application and 90-day oral 3-aminopropionitrile fumarate salt(BAPN) administration.Transcriptome Sequencing was performed using Illumina Novaseq platform in 7 murine cPTAAs or 5 sham-operated proximal thoracic aortas.The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed the differentially expressed genes were most enriched in immune and inflammation related pathways.
2024-12-01 | GSE275166 | GEO
Project description:Aortic aneurysms is increasing as the human population ages. Pathological oxidative stress is implicated in development of aortic aneurysms. We pursued a chemogenetic approach to create an animal model of aortic aneurysm formation using a transgenic mouse line DAAO-TGTie2 that expresses yeast D-amino acid oxidase (DAAO) under control of the endothelial Tie2 promoter. In DAAO-TGTie2 mice, DAAO generates the reactive oxygen species hydrogen peroxide (H2O2) in endothelial cells only when provided with D-amino acids. When DAAO-TGTie2 mice are chronically fed D-alanine, the animals become hypertensive and develop abdominal but not thoracic aortic aneurysms. Generation of H2O2 in the endothelium leads to oxidative stress throughout the vascular wall. Proteomic analyses indicate that the oxidant-modulated protein kinase JNK1 is dephosphorylated by the phophoprotein phosphatase DUSP3 in abdominal but not thoracic aorta, causing activation of KLF4-dependent transcriptional pathways that trigger phenotypic switching and aneurysm formation. Pharmacological DUSP3 inhibition completely blocks aneurysm formation caused by chemogenetic oxidative stress. These studies establish that regional differences in oxidant-modulated signaling pathways lead to differential disease progression in discrete vascular beds, and identify DUSP3 as a potential pharmacological target for the treatment of aortic aneurysms.
2025-02-18 | PXD060700 | Pride
Project description:Descending thoracic aortic aneurysms and dissections can go undetected until severe and catastrophic, and few clinical indices exist to screen for aneurysms or predict their risk of dissection or rupture. This study generated a plasma proteomic dataset from 150 patients with descending thoracic aortic disease and 52 controls to identify proteomic signatures capable of differentiating descending thoracic aortic disease from non-disease controls, as well as between cases with aneurysm versus descending ‘type B’ dissection. Of the 1,468 peptides and 195 proteins quantified across all samples, 853 peptides and 99 proteins were quantitatively different between disease and control patients (BH adjusted p-value < 0.01 from t-tests). Supervised machine learning (ML) methods were used to classify disease from control and aneurysm from descending dissection cases. The highest precision-recall area under the curve (PR AUC) was achieved on the held-out test set using significantly different proteins between disease and control patients (PR AUC 0.99), followed by input of significant peptides (PR AUC 0.96). Despite no statistically significant proteins between aneurysm and dissection cases, use of all proteins was able to modestly classify between the two disease states (PR AUC 0.77). To overcome correlation in the proteins and enable biological pathway analysis, a disease versus control classifier was optimized using only seven unique protein clusters, which achieved comparable performance to models trained on all/significant proteins (accuracy 0.88, F1-score 0.78, PR AUC 0.90). Model interpretation with permutation importance revealed that proteins in the most important clusters for differentiating disease and control function in coagulation, protein-lipid complex remodeling, and acute inflammatory response.
2024-06-16 | PXD041337 | Pride
Project description:National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions (GenTAC-BioLINCC)
| PRJNA1333516 | ENA
Project description:National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions (GenTAC-BioLINCC)
| PRJNA1333517 | ENA
Project description:Expression data in Abdominal Aortic Aneurysms
| PRJNA694659 | ENA