Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

Daskalopoulou, Aphrodite; Giotaki, Sotiria G.; Toli, Konstantina; Minia, Angeliki; Pliaka, Vaia; Alexopoulos, Leonidas G.; Deftereos, Gerasimos; Iliodromitis, Konstantinos; Dimitroulis, Dimitrios; Siasos, Gerasimos; Verikokos, Christos; Iliopoulos, Dimitrios

doi:10.3390/biomedicines11051273

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…Recent studies demonstrated the accumulation of CD4 + T cells, monocytes, macrophages, and B cells in the dilated arterial wall ( 3 , 4 ). In parallel, several cytokines including CCL5, HBD1, and ICAM1 were confirmed in association with AA ( 5 ). However, such endpoint-driven conclusions could only identify the potential of these targets as biomarkers, as it is challenging to characterize whether the appearance of these immune cells/inflammatory cytokines is a cause or a consequence of AA, which is one of the reasons why there is a lack of effective pharmacological interventions.…”

Section: Introductionmentioning

confidence: 92%

Deciphering the role of CX3CL1-CX3CR1 in aortic aneurysm pathogenesis: insights from Mendelian randomization and transcriptomic analyses

Qian,

Zheng,

et al. 2024

Front. Immunol.

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BackgroundThe crucial role of inflammation in aortic aneurysm (AA) is gaining prominence, while there is still a lack of key cytokines or targets for effective clinical translation.MethodsMendelian randomization (MR) analysis was performed to identify the causal relationship between 91 circulating inflammatory proteins and AA and between 731 immune traits and AA. Bulk RNA sequencing data was utilized to demonstrate the expression profile of the paired ligand-receptor. Gene enrichment analysis, Immune infiltration, and correlation analysis were employed to deduce the potential role of CX3CR1. We used single-cell RNA sequencing data to pinpoint the localization of CX3CL1 and CX3CR1, which was further validated by multiplex immunofluorescence staining. Cellchat analysis was utilized to infer the CX3C signaling pathway. Trajectory analysis and the Cytosig database were exploited to determine the downstream effect of CX3CL1-CX3CR1.ResultsWe identified 4 candidates (FGF5, CX3CL1, IL20RA, and SCF) in multiple two-sample MR analyses. Subsequent analysis of the expression profile of the paired receptor revealed the significant upregulation of CX3CR1 in AA and its positive correlation with pro-inflammatory macrophages. Two sample MR between immune cell traits and AA demonstrated the potential causality between intermediate monocytes and AA. We finally deciphered in single-cell sequencing data that CX3CL1 sent by endothelial cells (ECs) acted on CX3CR1 of intermediated monocytes, leading to its recruitment and pro-inflammatory responses.ConclusionOur study presented a genetic insight into the pathogenetic role of CX3CL1-CX3CR1 in AA, and further deciphered the CX3C signaling pathway between ECs and intermediate monocytes.

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Section: Introductionmentioning

confidence: 92%

Deciphering the role of CX3CL1-CX3CR1 in aortic aneurysm pathogenesis: insights from Mendelian randomization and transcriptomic analyses

Qian,

Zheng,

et al. 2024

Front. Immunol.

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“…Yang et al, demonstrated an increase in C18-ceramide in ATAAD, suggesting its role in aortic inflammation via association with NLRP3 in the NLR family [ 228 ]. Moreover, a novel comparison of a targeted proteomic approach has shown that patients with ATAA have increased serum levels of several inflammatory markers, such as IL-8, intracellular adhesion molecule-1 (ICAM1), C–C motif chemokine ligand 5 (CCL5), and human beta-defensin 1 (HBD1) (Table 3 ) [ 41 ].…”

Section: Sporadic and Genetic Biomarkers In Ataa(d)mentioning

confidence: 99%

Unveiling cellular and molecular aspects of ascending thoracic aortic aneurysms and dissections

Ganizada,

Veltrop,

Akbulut

et al. 2024

Basic Res Cardiol

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Ascending thoracic aortic aneurysm (ATAA) remains a significant medical concern, with its asymptomatic nature posing diagnostic and monitoring challenges, thereby increasing the risk of aortic wall dissection and rupture. Current management of aortic repair relies on an aortic diameter threshold. However, this approach underestimates the complexity of aortic wall disease due to important knowledge gaps in understanding its underlying pathologic mechanisms.Since traditional risk factors cannot explain the initiation and progression of ATAA leading to dissection, local vascular factors such as extracellular matrix (ECM) and vascular smooth muscle cells (VSMCs) might harbor targets for early diagnosis and intervention. Derived from diverse embryonic lineages, VSMCs exhibit varied responses to genetic abnormalities that regulate their contractility. The transition of VSMCs into different phenotypes is an adaptive response to stress stimuli such as hemodynamic changes resulting from cardiovascular disease, aging, lifestyle, and genetic predisposition. Upon longer exposure to stress stimuli, VSMC phenotypic switching can instigate pathologic remodeling that contributes to the pathogenesis of ATAA.This review aims to illuminate the current understanding of cellular and molecular characteristics associated with ATAA and dissection, emphasizing the need for a more nuanced comprehension of the impaired ECM–VSMC network.

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Machine Learning and Omics Analysis in Aortic Aneurysm

Lareyre,

Chaudhuri,

Nasr

et al. 2023

Angiology

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Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellular and molecular pathways involved. Omics generate a large amount of data and several studies have highlighted that artificial intelligence (AI) and techniques such as machine learning (ML)/deep learning (DL) can be of use in analyzing such complex datasets. However, only a few studies have so far reported the use of ML/DL for omics analysis in aortic aneurysms. The aim of this study is to summarize recent advances on the use of ML/DL for omics analysis to decipher aortic aneurysm pathophysiology and develop patient-tailored risk prediction models. In the light of current knowledge, we discuss current limits and highlight future directions in the field.

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Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

Cited by 3 publications

References 42 publications

Deciphering the role of CX3CL1-CX3CR1 in aortic aneurysm pathogenesis: insights from Mendelian randomization and transcriptomic analyses

Deciphering the role of CX3CL1-CX3CR1 in aortic aneurysm pathogenesis: insights from Mendelian randomization and transcriptomic analyses

Unveiling cellular and molecular aspects of ascending thoracic aortic aneurysms and dissections

Machine Learning and Omics Analysis in Aortic Aneurysm

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