Literature DB >> 28181149

Genome-Wide Sequencing Reveals MicroRNAs Downregulated in Cerebral Cavernous Malformations.

Souvik Kar1, Kiran Kumar Bali2, Arpita Baisantry3, Robert Geffers4, Amir Samii5, Helmut Bertalanffy5.   

Abstract

Cerebral cavernous malformations (CCM) are vascular lesions associated with loss-of-function mutations in one of the three genes encoding KRIT1 (CCM1), CCM2, and PDCD10. Recent understanding of the molecular mechanisms that lead to CCM development is limited. The role of microRNAs (miRNAs) has been demonstrated in vascular pathologies resulting in loss of tight junction proteins, increased vascular permeability and endothelial cell dysfunction. Since the relevance of miRNAs in CCM pathophysiology has not been elucidated, the primary aim of the study was to identify the miRNA-mRNA expression network associated with CCM. Using small RNA sequencing, we identified a total of 764 matured miRNAs expressed in CCM patients compared to the healthy brains. The expression of the selected miRNAs was validated by qRT-PCR, and the results were found to be consistent with the sequencing data. Upon application of additional statistical stringency, five miRNAs (let-7b-5p, miR-361-5p, miR-370-3p, miR-181a-2-3p, and miR-95-3p) were prioritized to be top CCM-relevant miRNAs. Further in silico analyses revealed that the prioritized miRNAs have a direct functional relation with mRNAs, such as MIB1, HIF1A, PDCD10, TJP1, OCLN, HES1, MAPK1, VEGFA, EGFL7, NF1, and ENG, which are previously characterized as key regulators of CCM pathology. To date, this is the first study to investigate the role of miRNAs in CCM pathology. By employing cutting edge molecular and in silico analyses on clinical samples, the current study reports global miRNA expression changes in CCM patients and provides a rich source of data set to understand detailed molecular machinery involved in CCM pathophysiology.

Entities:  

Keywords:  Cerebral cavernous malformations; In silico analyses; MicroRNAs; Pathology; Sequencing; Vascular

Mesh:

Substances:

Year:  2017        PMID: 28181149     DOI: 10.1007/s12031-017-0880-6

Source DB:  PubMed          Journal:  J Mol Neurosci        ISSN: 0895-8696            Impact factor:   3.444


  61 in total

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8.  Biallelic somatic and germline mutations in cerebral cavernous malformations (CCMs): evidence for a two-hit mechanism of CCM pathogenesis.

Authors:  Amy L Akers; Eric Johnson; Gary K Steinberg; Joseph M Zabramski; Douglas A Marchuk
Journal:  Hum Mol Genet       Date:  2008-12-16       Impact factor: 6.150

Review 9.  Role of Delta-Notch signaling in cerebral cavernous malformations.

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10.  Oasis: online analysis of small RNA deep sequencing data.

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3.  Transcriptome Analysis Reveals Altered Expression of Genes Involved in Hypoxia, Inflammation and Immune Regulation in Pdcd10-Depleted Mouse Endothelial Cells.

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5.  Genome-Wide Sequencing Reveals Small Nucleolar RNAs Downregulated in Cerebral Cavernous Malformations.

Authors:  Souvik Kar; Kiran Kumar Bali; Arpita Baisantry; Robert Geffers; Christian Hartmann; Amir Samii; Helmut Bertalanffy
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6.  Transcriptome clarifies mechanisms of lesion genesis versus progression in models of Ccm3 cerebral cavernous malformations.

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7.  Circulating microRNA expression profiling and bioinformatics analysis of patients with coronary artery disease by RNA sequencing.

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8.  Systems-wide analysis unravels the new roles of CCM signal complex (CSC).

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9.  Expression alteration of microRNAs in Nucleus Accumbens is associated with chronic stress and antidepressant treatment in rats.

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Journal:  BMC Med Inform Decis Mak       Date:  2019-12-19       Impact factor: 2.796

10.  Transcriptome-wide Profiling of Cerebral Cavernous Malformations Patients Reveal Important Long noncoding RNA molecular signatures.

Authors:  Santhilal Subhash; Norman Kalmbach; Florian Wegner; Susanne Petri; Torsten Glomb; Oliver Dittrich-Breiholz; Caiquan Huang; Kiran Kumar Bali; Wolfram S Kunz; Amir Samii; Helmut Bertalanffy; Chandrasekhar Kanduri; Souvik Kar
Journal:  Sci Rep       Date:  2019-12-03       Impact factor: 4.379

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