Project description:Genome wide DNA methylation profiling of normal and ascending aorta tissue samples from normal and aortic dissection patients. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 485,512 CpGs in ascending aorta tissue samples. Samples included 4 normal donors and 4 patients with aortic dissection.
Project description:Genome wide DNA methylation profiling of ascending aorta tissue samples from normal, aortic dissection and bicuspid aortic valve patients with aortic dilation. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across more than 450,000 CpGs in ascending aorta samples. Samples included 6 normal donors, 12 patients with aortic dissection and 6 patients with bicuspid aortic valve and dilated aorta.
Project description:Differentially expressed genes were identified by comparing the gene expression profiling of dissected ascending aorta with that of control. Results provide important information to indicate pathogenesis of aortic dissection.
Project description:Purpose: The aim of this study is to have a fullscape of molecular pathology of Stanford type A aortic dissection Methods: All TAAD patients under consideration underwent an ascending aortic replacement surgery during a cardiopulmonary bypass. The normal ascending aortic tissue samples were obtained from patients undergoing coronary artery bypass grafting surgery (CABG) without any aortic diseases. We selected 20 samples (10 TAAD and 10 normal) for the whole transcriptome sequencing. Total RNA was extracted from each sample using TRIzol Reagent (ThermoFisher) and was stored in 1 mL of 75% ethanol at -80 ℃ until further usage. Conclusions: We identified exaggerated autophagy as a molecular biomarker for aortic dissection. We also predicted 10 hub genes and an HIF1A-ATG3 axis which could provide new insights in understanding aortic dissection.
Project description:To identify the m6A methylome in the aorta of patients with acute aortic dissection. MeRIP-seq and RNA-seq experiments of aortic media tissue samples obtained from AD patients and controls were conducted. Compared with control group, the upmethylated coding genes of AD were primarily enriched in the processes associated with extracellular fibril organization, while the genes with downmethylation were enriched in the processes associated with cell death regulation. Furthermore, many differentially methylated m6A sites (DMMSs) coding proteins were mainly annotated during the extracellular matrix and inflammatory responses.
Project description:To identify the m6A methylome in the aorta of patients with acute aortic dissection. MeRIP-seq and RNA-seq experiments of aortic media tissue samples obtained from AD patients and controls were conducted. Compared with control group, the upmethylated coding genes of AD were primarily enriched in the processes associated with extracellular fibril organization, while the genes with downmethylation were enriched in the processes associated with cell death regulation. Furthermore, many differentially methylated m6A sites (DMMSs) coding proteins were mainly annotated during the extracellular matrix and inflammatory responses.
Project description:Stanford type A aortic dissection (STAAD) is an aortic degenerative remodeling disease carrying an exceedingly high mortality worldwide. The irreversible weakening, dilatation and dissection of the ascending aorta contributes to circulatory failure and premature death. Dissections manifest distinct patterns in both clinical presentations and histophathological features during disease temporal transition. Therefore, we delineate a full repertoire of cellular landscape and dynamic interplay in distinct temporal patterns of STAAD using single-cell transcriptomics for comprehensively understanding of disease features and temporal evolution. We performed single-cell RNA sequencing with ascending aortic tissues from 14 participants, including 9 patients with STAAD (4 acute, 3 subacute, and 2 chronic) and 5 control subjects. Unsupervised clustering was performed based on transcriptional profiles of highly variable genes. Single T cell analysis by RNA sequencing and TCR tracking (STARTRACT) was performed to quantitatively delineate the developmental trajectory of aortic T lymphocytes. On the basis of molecular signatures and distinct disease patterns, we draw a spatiotemporal map of disease subtype-specific alterations and complex interplay among cell types. The transcriptional profiles of 93,397 individual cells enable us to identify 12 major cell types and 37 subtypes in human ascending aorta. Comparisons of transcriptomes of disease subtypes reveal striking stage-specific cellular diversity and transcriptional dynamics in phenotypic switch, vascular inflammation, cell death and survival, extracellular matrix remodeling, and cell-cell interactions during disease temporal transition. Modeling of developmental trajectory revealed that the defects in mitochondrial OXPHOS drives phenotypic switch of contractile smooth muscle cells to synthetic myofibroblasts through AP-1 transcriptional complex. STARTRACT analysis revealed that CD8+ HSP are preferentially enriched and potentially clonally expanded in acute AD. Intersection of disease risk genes with our dataset reveals distinct gene panel in discriminating temporal-specifc AD. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the cellular diversity and heterogeneity in human aorta. The distinct alterations of cell type- and disease subtype-specific spatiotemporal features will ultimately facilitate the design of more precisely tailored anti-AD therapies.
Project description:Adverse aortic remodeling increases the risk of aorta-related adverse events (AAEs) after thoracic endovascular aortic repair (TEVAR) and affects the overall prognosis of aortic dissection (AD). It is imperative to delve into the exploration of prognostic indicators to We performed single-cell transcriptomic and proteomic profiling of aortic lesions and peripheral blood samples, respectively, from patients with AD and healthy subjects. We then integrated single-cell RNA to identify phenotype-relevant subpopulations.