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Background  MicroRNAs (miRNAs) are post-transcriptional regulators involved in numerous biological processes including the pathogenesis of Alzheimer’s disease (AD). A key gene of AD,  ADAM10 , controls the proteolytic processing of  APP  and the formation of the amyloid plaques and is known to be regulated by miRNA in hepatic cancer cell lines. To predict miRNAs regulating  ADAM10  expression concerning AD, we developed a computational approach.    Methods  MiRNA binding sites in the human  ADAM10  3' untranslated region were predicted using the RNA22, RNAhybrid and miRanda programs and ranked by specific selection criteria with respect to AD such as differential regulation in AD patients and tissue-specific expression. Furthermore, target genes of  miR-103 ,  miR-107  and  miR-1306  were derived from six publicly available miRNA target site prediction databases. Only target genes predicted in at least four out of six databases in the case of  miR-103  and  miR-107  were compared to genes listed in the AlzGene database including genes possibly involved in AD. In addition, the target genes were used for Gene Ontology analysis and literature mining. Finally, we used a luciferase assay to verify the potential effect of these three miRNAs on  ADAM10  3'UTR in SH-SY5Y cells.    Results  Eleven miRNAs were selected, which have evolutionary conserved binding sites. Three of them ( miR-103 ,  miR-107 ,  miR-1306 ) were further analysed as they are linked to AD and most strictly conserved between different species. Predicted target genes of  miR-103  ( p -value = 0.0065) and  miR-107  ( p -value = 0.0009) showed significant overlap with the AlzGene database except for  miR-1306 . Interactions between  miR-103  and  miR-107  to genes were revealed playing a role in processes leading to AD.  ADAM10  expression in the reporter assay was reduced by  miR-1306  (28%),  miR-103  (45%) and  miR-107  (52%).    Conclusions  Our approach shows the requirement of incorporating specific, disease-associated selection criteria into the prediction process to reduce the amount of false positive predictions. In summary, our method identified three miRNAs strongly suggested to be involved in AD, which possibly regulate  ADAM10  expression and hence offer possibilities for the development of therapeutic treatments of AD.

Computational identification and experimental validation of microRNAs binding to the Alzheimer-related gene ADAM10