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

BackgroundAortic 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 unde...

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Main Authors: Yue Pan, Zhiming Yu, Xiaoyu Qian, Xuesong Zhang, Qun Xue, Weizhang Xiao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Genetics
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Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2025.1586880/full
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author Yue Pan
Zhiming Yu
Xiaoyu Qian
Xuesong Zhang
Qun Xue
Weizhang Xiao
author_facet Yue Pan
Zhiming Yu
Xiaoyu Qian
Xuesong Zhang
Qun Xue
Weizhang Xiao
author_sort Yue Pan
collection DOAJ
description BackgroundAortic 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 of immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, and metabolic-epigenetic interactions in AD pathogenesis, underscoring the need for novel biomarkers and therapeutic targets.ObjectiveThis study aims to identify critical genes and molecular pathways associated with ATAAD, develop a multi-omics diagnostic model, and evaluate potential therapeutic interventions to improve clinical outcomes.MethodsTranscriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. External dataset validation and PCR testing of clinical samples (n = 9) were conducted to confirm gene expression differences. A nomogram diagnostic model was constructed and evaluated for predictive accuracy.ResultsSix core genes were identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, and Slc24a4, with four (Ccl2, Hk2, Tph1, and Npy1r) showing significant differential expression in clinical validation. Functional enrichment revealed associations with immune cell migration, vascular development regulation, extracellular matrix pathways, and the PI3K-Akt signaling pathway. Immunoinfiltration analysis demonstrated increased infiltration of B cell precursors, resting NK cells, and M2 macrophages in ATAAD tissues, negatively correlating with core gene expression. The nomogram model exhibited high diagnostic precision (AUC=0.935, 95% CI: 0.908–0.963), supported by calibration and decision curve analyses.ConclusionThis study identifies key molecular markers and pathways in ATAAD pathogenesis, emphasizing the role of immune dysregulation and extracellular matrix remodeling. The multi-omics diagnostic model provides a novel tool for early screening, potentially reducing mortality through timely intervention. These findings advance the understanding of aortic dissection mechanisms and offer actionable targets for future research and clinical applications.
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spelling doaj-art-caf28bed9e694e578f01bbdd5c978e0e2025-08-20T03:13:29ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-04-011610.3389/fgene.2025.15868801586880Key gene screening and diagnostic model establishment for acute type a aortic dissectionYue PanZhiming YuXiaoyu QianXuesong ZhangQun XueWeizhang XiaoBackgroundAortic 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 of immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, and metabolic-epigenetic interactions in AD pathogenesis, underscoring the need for novel biomarkers and therapeutic targets.ObjectiveThis study aims to identify critical genes and molecular pathways associated with ATAAD, develop a multi-omics diagnostic model, and evaluate potential therapeutic interventions to improve clinical outcomes.MethodsTranscriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. External dataset validation and PCR testing of clinical samples (n = 9) were conducted to confirm gene expression differences. A nomogram diagnostic model was constructed and evaluated for predictive accuracy.ResultsSix core genes were identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, and Slc24a4, with four (Ccl2, Hk2, Tph1, and Npy1r) showing significant differential expression in clinical validation. Functional enrichment revealed associations with immune cell migration, vascular development regulation, extracellular matrix pathways, and the PI3K-Akt signaling pathway. Immunoinfiltration analysis demonstrated increased infiltration of B cell precursors, resting NK cells, and M2 macrophages in ATAAD tissues, negatively correlating with core gene expression. The nomogram model exhibited high diagnostic precision (AUC=0.935, 95% CI: 0.908–0.963), supported by calibration and decision curve analyses.ConclusionThis study identifies key molecular markers and pathways in ATAAD pathogenesis, emphasizing the role of immune dysregulation and extracellular matrix remodeling. The multi-omics diagnostic model provides a novel tool for early screening, potentially reducing mortality through timely intervention. These findings advance the understanding of aortic dissection mechanisms and offer actionable targets for future research and clinical applications.https://www.frontiersin.org/articles/10.3389/fgene.2025.1586880/fullbioinformaticsdiagnostic modeldrug predictionmachine learningtype a aortic dissection
spellingShingle Yue Pan
Zhiming Yu
Xiaoyu Qian
Xuesong Zhang
Qun Xue
Weizhang Xiao
Key gene screening and diagnostic model establishment for acute type a aortic dissection
Frontiers in Genetics
bioinformatics
diagnostic model
drug prediction
machine learning
type a aortic dissection
title Key gene screening and diagnostic model establishment for acute type a aortic dissection
title_full Key gene screening and diagnostic model establishment for acute type a aortic dissection
title_fullStr Key gene screening and diagnostic model establishment for acute type a aortic dissection
title_full_unstemmed Key gene screening and diagnostic model establishment for acute type a aortic dissection
title_short Key gene screening and diagnostic model establishment for acute type a aortic dissection
title_sort key gene screening and diagnostic model establishment for acute type a aortic dissection
topic bioinformatics
diagnostic model
drug prediction
machine learning
type a aortic dissection
url https://www.frontiersin.org/articles/10.3389/fgene.2025.1586880/full
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AT xuesongzhang keygenescreeninganddiagnosticmodelestablishmentforacutetypeaaorticdissection
AT qunxue keygenescreeninganddiagnosticmodelestablishmentforacutetypeaaorticdissection
AT weizhangxiao keygenescreeninganddiagnosticmodelestablishmentforacutetypeaaorticdissection