Fibrosis: A nexus between atrial fibrillation and left atrial appendage thrombosis

Chahine, Yaacoub; Akoum, Nazem

doi:10.1111/jce.15382

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Histologically quantified LAA fibrosis burden is higher in patients with AF than in those in sinus rhythm, and in patients with LAA thrombus than in those without. 24,25 The mechanism by which atrial fibrosis contributes to thrombogenesis is not completely understood. A decrease in left atrial strain was shown in the presence of extensive late gadolinium enhancement MRI (LGE-MRI) fibrosis.…”

Section: Cardioembolic Strokementioning

confidence: 99%

Machine Learning and the Conundrum of Stroke Risk Prediction

Chahine

Magoon

Maidu

et al. 2023

Arrhythm Electrophysiol Rev

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Stroke is a leading cause of death worldwide. With escalating healthcare costs, early non-invasive stroke risk stratification is vital. The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. This review summarises recent efforts to deploy machine learning (ML) to predict stroke risk and enrich the understanding of the mechanisms underlying stroke. The surveyed body of literature includes studies comparing ML algorithms with conventional statistical models for predicting cardiovascular disease and, in particular, different stroke subtypes. Another avenue of research explored is ML as a means of enriching multiscale computational modelling, which holds great promise for revealing thrombogenesis mechanisms. Overall, ML offers a new approach to stroke risk stratification that accounts for subtle physiologic variants between patients, potentially leading to more reliable and personalised predictions than standard regression-based statistical associations.

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Section: Cardioembolic Strokementioning

confidence: 99%

Machine Learning and the Conundrum of Stroke Risk Prediction

Chahine

Magoon

Maidu

et al. 2023

Arrhythm Electrophysiol Rev

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“… 4 Factors like ion channel abnormalities, cardiomyocyte remodeling, and cardiac neuromodulation disorders 5 , 6 contribute to reduced atrial contractile function and blood pooling, increasing the risk of thrombosis and stroke. 7 The function of immune cells in atrial tissue is closely related to the progression of AF. 8 To better comprehend the development of AF, further clarification of the remodeling mechanisms in AF is necessary at the cellular and molecular levels.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation

Yang,

Xu,

Zhao

et al. 2024

IJGM

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Background Macrophages play a crucial role in the progression of AF, closely linked to atrial inflammation and myocardial fibrosis. However, the functions and molecular mechanisms of different phenotypic macrophages in AF are not well understood. This study aims to analyze the infiltration characteristics of atrial immune cells in AF patients and further explore the role and molecular expression patterns of M2 macrophage-related genes in AF. Methods This study integrates single-cell and large-scale sequencing data to analyze immune cell infiltration and molecular characterization of the LAA in patients with AF, using SR as a control group. CIBERSORT assesses immune cell types in LAA tissues; WGCNA identifies signature genes; cell clustering analyzes cell types and subpopulations; cell communication explores macrophage interactions; hdWGCNA identifies M2 macrophage gene modules in AF. AF biomarkers are identified using LASSO and Random Forest, validated with ROC curves and RT-qPCR. Potential molecular mechanisms are inferred through TF-miRNA-mRNA networks and single-gene enrichment analyses. Results Myeloid cell subsets varied considerably between the AF and SR groups, with a significant increase in M2 macrophages in the AF group. Signals of inflammation and matrix remodeling were observed in AF. M2 macrophage-related genes IGF1, PDK4, RAB13 , and TMEM176B were identified as AF biomarkers, with RAB13 and TMEM176B being novel markers. A TF-miRNA-mRNA network was constructed using target genes, which are enriched in the PPAR signaling pathway and fatty acid metabolism. Conclusion Over infiltration of M2 macrophages may be an important factor in the progression of AF. The M2 macrophage-related genes IGF1, RAB13, TMEM176B and PDK4 may regulate the progression of AF through the PPAR signaling pathway and fatty acid metabolism.

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The correlation between ultrasonographic morphology and structure of the left atrial appendage, blood flow velocity, and plasma galectin-3 levels with thrombus formation in the left atrial appendage of patients with atrial fibrillation

Zhao,

Li,

Zhang

et al. 2024

J Med Biochemistry

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Background: To explore the correlation between left atrial appendage morphology, blood flow velocity and plasma galectin-3 and thrombosis in patients with atrial fibrillation. Methods: Patients with atrial fibrillation who received treatment and completed ultrasound examination in hospital from 2022 to December 2023 were enrolled. According to whether there was left atrial appendage thrombosis, the patients were divided into a control group (no left atrial appendage thrombosis was found) and a study group (left atrial appendage thrombosis was found). The morphology and structure of the left atrial appendage, blood flow velocity and plasma galectin-3 level were recorded，exploring its correlation with left atrium thrombosis. Results: A total of 330 patients with atrial fibrillation were enrolled, including 278 in the control group and 52 in the study group. Left group and the control group of morphological structure differences (P < 0.05). The main lobe length, ostial area, longest diameter, shortest diameter, left atrial appendage volume and left atrial volume in the study group were higher than those in the control group (P < 0.05). The left atrial appendage emptying velocity, filling velocity and left ventricular ejection fraction of the study group were lower than those of the control group, and the left ventricular end-diastolic diameter was higher than that of the control group (P < 0.05). Group of white blood cell count, neutrophils/lymphocyte ratio, plasma galactose lectin - 3 levels were higher than control group (P < 0.05). ROC curve analysis of left atrial appendage emptying velocity, left atrial appendage filling velocity, left atrial end-diastolic diameter and left atrial ejection fraction had higher diagnostic value (P < 0.05). Conclusion: Left atrial appendage morphology, blood flow velocity and plasma galectin-3 level are important factors to evaluate the risk of left atrial appendage thrombosis in patients with atrial fibrillation, which can be used for clinical diagnosis and decision-making.

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Fibrosis: A nexus between atrial fibrillation and left atrial appendage thrombosis

Cited by 3 publications

References 13 publications

Machine Learning and the Conundrum of Stroke Risk Prediction

Machine Learning and the Conundrum of Stroke Risk Prediction

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation

The correlation between ultrasonographic morphology and structure of the left atrial appendage, blood flow velocity, and plasma galectin-3 levels with thrombus formation in the left atrial appendage of patients with atrial fibrillation

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