Bioinformatic reanalysis of gene expression microarray data reveals a number of previously unrecognized lncRNAs implicated in the pathogenesis of aortic stenosis

    Authors

    Keywords

    aortic valve stenosis, lncRNA, bioinformatic analysis

    DOI

    https://doi.org/10.15836/ccar2016.636

    Full Text

    Objective: Long noncoding RNAs (lncRNAs), a class of noncoding RNA larger than 200 nucleotides, constitute a heterogenic class of regulatory RNAs that includes, for example, intergenic lncRNAs, antisense transcripts, and enhancer RNAs. Due to their ability to modulate miR/mRNA networks and chromatin structure their therapeutic potential is extremely vast thus opening the opportunity for the development of new treatment strategies to be used in cardiovascular medicine. Recent studies indicate that altered expression and function of lncRNAs have also an important role in the development and progression of aortic valve stenosis (AS) and AS-induced cardiac hypertrophy. However, our knowledge of lncRNAs differentially expressed in stenotic aortic valves or during AS-induced cardiac fibrosis and remodelling is still limited on a few examples and as such, requires further investigation. ( 1 ) Methods: We performed bioinformatic reanalysis of published microarray expressional studies of stenotic and control human aortic valves tissue samples. Data are analyzed using the online Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8. Results: In addition to lncRNA MALAT1 and H19 with known role in the osteogenic transdifferentiation of valvular interstitial cells during the process of aortic valve calcification bioinformatic analysis revealed several previously unrecognized intergenic, intronic and antisense lncRNAs and lncRNA relate miRNA host genes that are differentially expressed in aortic valve tissue of AS patients compared to control valves ( Figure 1 ). LncRNA differentially expressed in aortic stenosis tissue compared to normal aortic valve leaflets. Conclusion: Bioinformatic data mining of gene expression microarray data combined with upgraded annotation of the human genome landscape provides a useful tool for revealing many previously unrecognized lncRNA transcripts implicated in the pathogenesis of AS.

    Cardiologia Croatica
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    Bioinformatic reanalysis of gene expression microarray data reveals a number of previously unrecognized lncRNAs implicated in the pathogenesis of aortic stenosis

    Extended Abstract
    Issue12
    Published
    Pages636-637
    PDF via DOIhttps://doi.org/10.15836/ccar2016.636
    aortic valve stenosis
    lncRNA
    bioinformatic analysis

    Authors

    Martina Zeljko*ORCIDCroatia
    Igor GoševORCIDUnited States of America
    Darko PočanićORCIDCroatia
    Damir KozmarORCIDCroatia
    Darko VujanićORCIDCroatia
    Zoran LegčevićCroatia
    Dino BešićORCIDCroatia
    Frane PaićORCIDCroatia

    Full Text

    Objective: Long noncoding RNAs (lncRNAs), a class of noncoding RNA larger than 200 nucleotides, constitute a heterogenic class of regulatory RNAs that includes, for example, intergenic lncRNAs, antisense transcripts, and enhancer RNAs. Due to their ability to modulate miR/mRNA networks and chromatin structure their therapeutic potential is extremely vast thus opening the opportunity for the development of new treatment strategies to be used in cardiovascular medicine. Recent studies indicate that altered expression and function of lncRNAs have also an important role in the development and progression of aortic valve stenosis (AS) and AS-induced cardiac hypertrophy. However, our knowledge of lncRNAs differentially expressed in stenotic aortic valves or during AS-induced cardiac fibrosis and remodelling is still limited on a few examples and as such, requires further investigation. ( 1 ) Methods: We performed bioinformatic reanalysis of published microarray expressional studies of stenotic and control human aortic valves tissue samples. Data are analyzed using the online Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8. Results: In addition to lncRNA MALAT1 and H19 with known role in the osteogenic transdifferentiation of valvular interstitial cells during the process of aortic valve calcification bioinformatic analysis revealed several previously unrecognized intergenic, intronic and antisense lncRNAs and lncRNA relate miRNA host genes that are differentially expressed in aortic valve tissue of AS patients compared to control valves ( Figure 1 ). LncRNA differentially expressed in aortic stenosis tissue compared to normal aortic valve leaflets. Conclusion: Bioinformatic data mining of gene expression microarray data combined with upgraded annotation of the human genome landscape provides a useful tool for revealing many previously unrecognized lncRNA transcripts implicated in the pathogenesis of AS.