Transcriptomic and Multi-Scale Network Analyses Reveal Key Drivers of Cardiovascular Disease

被引:0
|
作者
Tumenbayar, Bat-Ider [1 ,2 ]
Pham, Khanh [3 ]
Biber, John C. [3 ]
Drewes, Rhonda [3 ]
Bae, Yongho [3 ,4 ]
机构
[1] SUNY Buffalo, Dept Pharmacol & Toxicol, Buffalo, NY 14203 USA
[2] Univ Penn, Dept Med, Philadelphia, PA 19104 USA
[3] SUNY Buffalo, Dept Pathol & Anat Sci, Buffalo 14203, NY USA
[4] SUNY Buffalo, Dept Biomed Engn, Buffalo, NY 14203 USA
来源
IEEE TRANSACTIONS ON MOLECULAR BIOLOGICAL AND MULTI-SCALE COMMUNICATIONS | 2025年 / 11卷 / 01期
基金
美国国家卫生研究院;
关键词
Injuries; Diseases; Transcriptomics; Proteins; Gene expression; Bioinformatics; Arteries; Pathology; Biological processes; Atherosclerosis; Genome-wide analysis; molecular communication; mechanobiology; arterial stiffness; actin cytoskeleton; ECM; EXTRACELLULAR-MATRIX; MOUSE MODEL; INFLAMMATION; EXPRESSION; ANGIOTENSINOGEN; PATHOGENESIS; SUPPRESSION; RISK;
D O I
10.1109/TMBMC.2024.3501576
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cardiovascular diseases (CVDs) and pathologies are often driven by changes in molecular signaling and communication, as well as in cellular and tissue components, particularly those involving the extracellular matrix (ECM), cytoskeleton, and immune response. The fine-wire vascular injury model is commonly used to study neointimal hyperplasia and vessel stiffening, but it is not typically considered a model for CVDs. However, applying this model to study CVDs in conjunction with established processes could offer valuable insights. In this paper, we hypothesize that vascular injury induces changes in gene expression, molecular communication, and biological processes similar to those observed in CVDs at both the transcriptome and protein levels. To investigate this, we analyzed gene expression in microarray datasets from injured and uninjured femoral arteries in mice two weeks post-injury, identifying 1,467 significantly and differentially expressed genes involved in several CVDs such as including vaso-occlusion, arrhythmia, and atherosclerosis. We further constructed a protein-protein interaction network with seven functionally distinct clusters, with notable enrichment in ECM, metabolic processes, actin-based process, and immune response. Significant molecular communications were observed between the clusters, most prominently among those involved in ECM and cytoskeleton organizations, inflammation, and cell cycle. Machine Learning Disease pathway analysis revealed that vascular injury-induced crosstalk between ECM remodeling and immune response clusters contributed to aortic aneurysm, neovascularization of choroid, and kidney failure. Additionally, we found that interactions between ECM and actin cytoskeletal reorganization clusters were linked to cardiac damage, carotid artery occlusion, and cardiac lesions. Overall, through multi-scale bioinformatic analyses, we demonstrated the robustness of the vascular injury model in eliciting transcriptomic and molecular network changes associated with CVDs, highlighting its potential for use in cardiovascular research.
引用
收藏
页码:78 / 90
页数:13
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