LncRNA ANRIL acts as a modular scaffold of WDR5 and HDAC3 complexes and promotes alteration of the vascular smooth muscle cell phenotype

Zhang, Chengxin; Ge, Shangqing; Gong, Wei; Xu, Jinguo; Guo, Zhixin; Liu, Zhuang; Gao, Xiaotian; Wei, Xiaoyong; Ge, Shuping

doi:10.1038/s41419-020-2645-3

Cited by 67 publications

(56 citation statements)

References 39 publications

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“…It is the case of lnc-ANRIL which functions as a scaffold to induce the binding of the WDR5 and HDAC3 proteins to form a complex. This association drives the regulation of NOX1 expression by histone modification and upregulated ROS level, among others [61].…”

Section: Lnc-rnas Functionsmentioning

confidence: 97%

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

et al. 2021

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Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

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Section: Lnc-rnas Functionsmentioning

confidence: 97%

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

et al. 2021

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“…In the following, recently identified lncRNAs will be discussed. Interestingly, the most significant cardiovascular disease related genomic locus Chr9p21.3 includes ANRIL lncRNA, which promotes VSMC phenotype switching when overexpressed through possibly acting as a molecular scaffold to promote WDR5 and HDAC3 complex forming (Zhang et al, 2020). LncRNA nuclear paraspeckle assembly transcript 1 (NEAT1), on the other hand, seems to promote VSMC phenotype switch from a contractile to a synthetic cell type by inhibiting the chromatin modifier WDR5, normally stimulating the expression of contractile VSMC specific genes (Ahmed et al, 2018).…”

Section: The Role Of Long Non-coding Rnas In Vsmc Phenotype Switchingmentioning

confidence: 99%

Epigenetic Regulation of Vascular Smooth Muscle Cell Phenotype Switching in Atherosclerotic Artery Remodeling: A Mini-Review

et al. 2021

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Atherosclerosis is a chronic inflammatory disease characterized by extensive remodeling of medium and large-sized arteries. Inward remodeling (=lumen shrinkage) of the vascular walls is the underlying cause for ischemia in target organs. Therefore, inward remodeling can be considered the predominant feature of atherosclerotic pathology. Outward remodeling (=lumen enlargement) is a physiological response compensating for lumen shrinkage caused by neointimal hyperplasia, but as a pathological response to changes in blood flow, outward remodeling leads to substantial arterial wall thinning. Thinned vascular walls are prone to rupture, and subsequent thrombus formation accounts for the majority of acute cardiovascular events. Pathological remodeling is driven by inflammatory cells which induce vascular smooth muscle cells to switch from quiescent to a proliferative and migratory phenotype. After decades of intensive research, the molecular mechanisms of arterial remodeling are starting to unfold. In this mini-review, we summarize the current knowledge of the epigenetic and transcriptional regulation of vascular smooth muscle cell phenotype switching from the contractile to the synthetic phenotype involved in arterial remodeling and discuss potential therapeutic options.

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“…LncRNA ANRIL is the prime candidate gene at Chr9p21 and widely recognized as a critical part of endothelial inflammation and cell proliferation (91,(94)(95)(96)(97). Single nucleotide polymorphisms (SNPs) and splice variants of ANRIL were reported to regulate endothelial cell activities involved in coronary artery heart disease (CAD) and MI (98)(99)(100)(101)(102)(103). Abnormal expression of ANRIL is associated with vascular endothelium injury and proliferation, migration, and apoptosis of VSMCs; which also contribute to mononuclear cell adhesion and proliferation (104,105).…”

Section: Anrilmentioning

confidence: 99%

The Role of Long Non-coding RNAs in Sepsis-Induced Cardiac Dysfunction

Zhang

et al. 2021

Front. Cardiovasc. Med.

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Sepsis is a syndrome with life-threatening organ dysfunction induced by a dysregulated host response to infection. The heart is one of the most commonly involved organs during sepsis, and cardiac dysfunction, which is usually indicative of an extremely poor clinical outcome, is a leading cause of death in septic cases. Despite substantial improvements in the understanding of the mechanisms that contribute to the origin and responses to sepsis, the prognosis of sepsis-induced cardiac dysfunction (SICD) remains poor and its molecular pathophysiological changes are not well-characterized. The recently discovered group of mediators known as long non-coding RNAs (lncRNAs) have presented novel insights and opportunities to explore the mechanisms and development of SICD and may provide new targets for diagnosis and therapeutic strategies. LncRNAs are RNA transcripts of more than 200 nucleotides with limited or no protein-coding potential. Evidence has rapidly accumulated from numerous studies on how lncRNAs function in associated regulatory circuits during SICD. This review outlines the direct evidence of the effect of lncRNAs on SICD based on clinical trials and animal studies. Furthermore, potential functional lncRNAs in SICD that have been identified in sepsis studies are summarized with a proven biological function in research on other cardiovascular diseases.

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LncRNA ANRIL acts as a modular scaffold of WDR5 and HDAC3 complexes and promotes alteration of the vascular smooth muscle cell phenotype

Cited by 67 publications

References 39 publications

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

Epigenetic Regulation of Vascular Smooth Muscle Cell Phenotype Switching in Atherosclerotic Artery Remodeling: A Mini-Review

The Role of Long Non-coding RNAs in Sepsis-Induced Cardiac Dysfunction

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