Key gene screening and diagnostic model establishment for acute type a aortic dissection DOI Creative Commons

Yue Pan,

Zhi‐Ming Yu, Xiaoyu Qian

и другие.

Frontiers in Genetics, Год журнала: 2025, Номер 16

Опубликована: Апрель 24, 2025

Aortic dissection, particularly acute type A aortic dissection (ATAAD), is a life-threatening cardiovascular emergency with alarmingly high mortality rates globally. Despite advancements in imaging techniques like computed tomography angiography (CTA), delayed diagnosis and incomplete understanding of molecular mechanisms persist, contributing to poor outcomes. Recent studies highlight the role immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, metabolic-epigenetic interactions AD pathogenesis, underscoring need for novel biomarkers therapeutic targets. This study aims identify critical genes pathways associated ATAAD, develop multi-omics diagnostic model, evaluate potential interventions improve clinical Transcriptome datasets from Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment immunoinfiltration analyses performed explore biological interactions. External dataset validation PCR testing samples (n = 9) conducted confirm differences. nomogram model was constructed evaluated predictive accuracy. Six core identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, Slc24a4, four (Ccl2, Npy1r) showing significant validation. revealed associations migration, development regulation, extracellular matrix pathways, PI3K-Akt signaling pathway. Immunoinfiltration demonstrated increased infiltration B precursors, resting NK cells, M2 macrophages ATAAD tissues, negatively correlating expression. The exhibited precision (AUC=0.935, 95% CI: 0.908-0.963), supported by calibration decision curve analyses. identifies key markers emphasizing dysregulation remodeling. provides tool early screening, potentially reducing through timely intervention. These findings advance offer actionable targets future research applications.

Язык: Английский

Key gene screening and diagnostic model establishment for acute type a aortic dissection DOI Creative Commons

Yue Pan,

Zhi‐Ming Yu, Xiaoyu Qian

и другие.

Frontiers in Genetics, Год журнала: 2025, Номер 16

Опубликована: Апрель 24, 2025

Aortic dissection, particularly acute type A aortic dissection (ATAAD), is a life-threatening cardiovascular emergency with alarmingly high mortality rates globally. Despite advancements in imaging techniques like computed tomography angiography (CTA), delayed diagnosis and incomplete understanding of molecular mechanisms persist, contributing to poor outcomes. Recent studies highlight the role immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, metabolic-epigenetic interactions AD pathogenesis, underscoring need for novel biomarkers therapeutic targets. This study aims identify critical genes pathways associated ATAAD, develop multi-omics diagnostic model, evaluate potential interventions improve clinical Transcriptome datasets from Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment immunoinfiltration analyses performed explore biological interactions. External dataset validation PCR testing samples (n = 9) conducted confirm differences. nomogram model was constructed evaluated predictive accuracy. Six core identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, Slc24a4, four (Ccl2, Npy1r) showing significant validation. revealed associations migration, development regulation, extracellular matrix pathways, PI3K-Akt signaling pathway. Immunoinfiltration demonstrated increased infiltration B precursors, resting NK cells, M2 macrophages ATAAD tissues, negatively correlating expression. The exhibited precision (AUC=0.935, 95% CI: 0.908-0.963), supported by calibration decision curve analyses. identifies key markers emphasizing dysregulation remodeling. provides tool early screening, potentially reducing through timely intervention. These findings advance offer actionable targets future research applications.

Язык: Английский

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