The Effect of Mecp2 on Heart Failure

Wang, Chunli; Wang, Fei; Cao, Qing; Li, Zhen; Huang, Liya; Chen, Shuyan

doi:10.1159/000491610

Cited by 13 publications

(9 citation statements)

References 29 publications

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“…Cardiac arrhythmia is one of the factors contributing to the greater than expected occurrence of sudden death in RTT individuals (Acampa and Guideri, 2006). Although the molecular involvement of MeCP2 is not completely understood, it appears that dysregulation of Rho GTPase cytoskeletal and inflammation mediated chemokine and cytokine signaling pathway genes are involved (Wang et al, 2018).…”

Section: Functional Roles Of Mecp2 Beyond the Brainmentioning

confidence: 99%

MeCP2: The Genetic Driver of Rett Syndrome Epigenetics

2021

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Mutations in methyl CpG binding protein 2 (MeCP2) are the major cause of Rett syndrome (RTT), a rare neurodevelopmental disorder with a notable period of developmental regression following apparently normal initial development. Such MeCP2 alterations often result in changes to DNA binding and chromatin clustering ability, and in the stability of this protein. Among other functions, MeCP2 binds to methylated genomic DNA, which represents an important epigenetic mark with broad physiological implications, including neuronal development. In this review, we will summarize the genetic foundations behind RTT, and the variable degrees of protein stability exhibited by MeCP2 and its mutated versions. Also, past and emerging relationships that MeCP2 has with mRNA splicing, miRNA processing, and other non-coding RNAs (ncRNA) will be explored, and we suggest that these molecules could be missing links in understanding the epigenetic consequences incurred from genetic ablation of this important chromatin modifier. Importantly, although MeCP2 is highly expressed in the brain, where it has been most extensively studied, the role of this protein and its alterations in other tissues cannot be ignored and will also be discussed. Finally, the additional complexity to RTT pathology introduced by structural and functional implications of the two MeCP2 isoforms (MeCP2-E1 and MeCP2-E2) will be described. Epigenetic therapeutics are gaining clinical popularity, yet treatment for Rett syndrome is more complicated than would be anticipated for a purely epigenetic disorder, which should be taken into account in future clinical contexts.

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Section: Functional Roles Of Mecp2 Beyond the Brainmentioning

confidence: 99%

MeCP2: The Genetic Driver of Rett Syndrome Epigenetics

2021

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“…Previous study showed that HF was related to the expression of MECP2 [ 4 ] RBM20 [ 5 ], CaMKII [ 6 ], troponin I [ 7 ] and SERCA2a [ 8 ]. Toll-Like receptor signaling pathway [ 9 ], activin type II receptor signaling pathway [ 10 ], CaMKII signaling pathways [ 11 ], Drp1 signaling pathways [ 12 ] and JAK-STAT signaling pathway [ 13 ] were liable for progression of HF.…”

Section: Introductionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Kolur¹,

Vastrad²,

Vastrad

et al. 2021

BMC Cardiovasc Disord

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Introduction Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. Methods The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein–protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene—miRNA regulatory network and target gene—TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. Results A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene—miRNA regulatory network and target gene—TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. Conclusion The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

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“…GRN (Granulin) was activated in the cerebral artery and heart, and the interaction between GRN and related genes was enhanced in the heart. The interaction between LYZ2 (Lysozyme C-2) and GRN in the heart is associated with the activation of chronic inflammation ( Wang C. et al, 2018 ). Additionally, GRN may influence the remodeling of the cerebral artery by positively regulating N2 (Niemann–Pick type C2) and inhibiting the activation of the ERK 1/2 MAPK signaling pathway ( Csepeggi et al, 2011 ).…”

Section: Resultsmentioning

confidence: 99%

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

et al. 2021

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Heart failure with preserved ejection fraction (HFpEF) is a complex disease characterized by dysfunctions in the heart, adipose tissue, and cerebral arteries. The elucidation of the interactions between these three tissues in HFpEF will improve our understanding of the mechanism of HFpEF. In this study, we propose a multilevel comparative framework based on differentially expressed genes (DEGs) and differentially correlated gene pairs (DCGs) to investigate the shared and unique pathological features among the three tissues in HFpEF. At the network level, functional enrichment analysis revealed that the networks of the heart, adipose tissue, and cerebral arteries were enriched in the cell cycle and immune response. The networks of the heart and adipose tissues were enriched in hemostasis, G-protein coupled receptor (GPCR) ligand, and cancer-related pathway. The heart-specific networks were enriched in the inflammatory response and cardiac hypertrophy, while the adipose-tissue-specific networks were enriched in the response to peptides and regulation of cell adhesion. The cerebral-artery-specific networks were enriched in gene expression (transcription). At the module and gene levels, 5 housekeeping DEGs, 2 housekeeping DCGs, 6 modules of merged protein–protein interaction network, 5 tissue-specific hub genes, and 20 shared hub genes were identified through comparative analysis of tissue pairs. Furthermore, the therapeutic drugs for HFpEF-targeting these genes were examined using molecular docking. The combination of multitissue and multilevel comparative frameworks is a potential strategy for the discovery of effective therapy and personalized medicine for HFpEF.

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The Effect of Mecp2 on Heart Failure

Cited by 13 publications

References 29 publications

MeCP2: The Genetic Driver of Rett Syndrome Epigenetics

MeCP2: The Genetic Driver of Rett Syndrome Epigenetics

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

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