Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA102635 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To determine how gene expression is altered in aorta tissue in response to aortic aneurysm disease. Thoracic or abdominal aorta tissue was isolated from patients requiring surgery due to aortic aneurysm or other (control) reason.
2024-10-09 | GSE202267 | GEO
Project description:To discover novel biomarkers for aortic aneurysm, serum samples of patients with thoracic aortic aneurysm were fractionated, tryptic digested, and subjected to proteome analysis.
2023-11-15 | PXD033774 | JPOST Repository
Project description:In current models of ascending aortic disease, mural cells undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore the intersection of this biology with quantitative trait GWAS loci we analyzed the genetic features of thoracic aortic aneurysm tissue. Single nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data. In total, we sequenced 71,689 nuclei from human thoracic aortas without aneurysm, and with sporadic aneurysm. We identified 14 clusters, aligning with 11 cell types, predominantly VSMCs, consistent with existing histologic data, but contrary to the majority of human aortic single cell studies to-date. With unbiased methodology, we found 7 VSMC and 6 fibroblast subclusters. Differentially expressed genes (DEGs) analysis revealed a VSMC group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. DEGs were used to prioritize genes at aortic diameter and distensibility GWAS loci highlighting the genes JUN, LTBP4, and IL34 in fibroblasts, ENTPD1, PDLIM5, ACTN4, and GLRX in VSMCs, as well as LRP1 in macrophage populations. In conclusion, using nuclear RNA sequencing we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.
2022-10-03 | GSE207784 | GEO
Project description:Aneurysmatic and dissection cells show a specific alteration of gene expression, which allow a disease specific distinction. We used microarrays to analyse the cellular gene expression of controls, thoracic aortic aneurysm, and aortic dissection.
2022-12-02 | GSE219204 | GEO
Project description:Comparison of whole genome expression profiles to characterize gene expression during development of thoracic aortic aneurysm in fibrillin-1 hypomorphic mice (Fbn1mgR/mgR).
2018-01-27 | GSE109722 | GEO
Project description:Patients with bicuspid aortic valve (BAV) have increased risk of thoracic ascending aortic aneurysm (AscAA) and dissection compared to those with a normal tricuspid aortic valve (TAV). The present study was undertaken to evaluate whether differences in gene expression exist in aortas from BAV and TAV patients with AscAA. Keywords: disease state analysis
2007-06-28 | GSE5180 | GEO
Project description:Bicuspid aortic valve (BAV) is the most common congenital heart anomaly and is prone to cause complications, such as valvular stenosis and thoracic aortic dilation. There is currently no reliable way to predict the progression rate to thoracic aortic aneurysm. Here, we aimed to characterize the proteomic landscape in the plasma of stenotic BAV patients and provide potential biomarkers to predict progressive aortic dilation. Plasma samples were obtained from 45 subjects (30 stenotic BAV patients and 15 healthy controls). All samples were properly prepared and analyzed using mass spectrometry (MS)-based label-free quantitative proteomics.
2021-08-19 | PXD027125 | Pride
Project description:Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, revealing 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests, and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (HR = 1.43 per SD; CI 1.32-1.54; P = 3.3·10-20). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.
2021-01-30 | GSE165824 | GEO
Project description:Although abnormal TGFbeta signaling is observed in several heritable forms of thoracic aortic aneurysms and dissections including Marfan syndrome, the precise role of TGFbeta signaling in aortic disease progression is still disputed. Using a mouse genetic approach and quantitative isobaric labeling proteomics, we sought to investigate the role of TGFbeta signaling in molecular pathways of pathogenesis associated with development of aortic aneurysm and aortic rupture. This study reports an isoform-specific effect of TGFbeta in MFS aortic disease and the effects of deleting the first hybrid domain of fibrillin-1 on TGFbeta signaling. Distinct molecular differences in mouse models of aneurysm (Fbn_GT-8_plus), of aneurysm and rupture (Fbn1_GT-8_H1delta), and of microdissection (Fbn1_H1delta_plus) were identified, which associated with TGFbeta signaling and extracellular matrix composition, possibly contributing to the development of dissection and rupture. These findings offer new insights into the pathophysiological mechanisms that potentially drive initiation of aortic dissection and could pave the way for development of new treatment targets of aortic disease.
2023-10-09 | PXD036222 | Pride
Project description:In the present study, we evaluated miRNA expression profiles of 32 patient aortic aneurysm tissue and plasma samples using Illumina next-generation sequencing platform. A total of 20 miRNA were differentially expressed in tissues, 17 miRNAs - in plasma samples. Differentially expressed miRNAs determined in the present study could be applied for thoracic ascending aneurysm diagnosis.
2020-04-14 | GSE122266 | GEO