4.7 Article

Sensory Neuropathy Affects Cardiac miRNA Expression Network Targeting IGF-1, SLC2a-12, EIF-4e, and ULK-2 mRNAs

Journal

Publisher

MDPI
DOI: 10.3390/ijms20040991

Keywords

capsaicin; heart; network analysis; microRNA; sensory neuropathy

Funding

  1. National Research, Development and Innovation Office of Hungary [GINOP-2.3.2-15-2016-00040, OTKA KH_17 125570, NVKP_16-1-2016-0017]
  2. Higher Education Institutional Excellence Program of the Ministry of Human Capacities in Hungary
  3. European Cooperation in Science and Technology (COST action, EU-Cardioprotection) [CA16225]
  4. CardioRNA COST action [CA17129]
  5. Hungarian Academy of Sciences

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Background: Here we examined myocardial microRNA (miRNA) expression profile in a sensory neuropathy model with cardiac diastolic dysfunction and aimed to identify key mRNA molecular targets of the differentially expressed miRNAs that may contribute to cardiac dysfunction. Methods: Male Wistar rats were treated with vehicle or capsaicin for 3 days to induce systemic sensory neuropathy. Seven days later, diastolic dysfunction was detected by echocardiography, and miRNAs were isolated from the whole ventricles. Results: Out of 711 known miRNAs measured by miRNA microarray, the expression of 257 miRNAs was detected in the heart. As compared to vehicle-treated hearts, miR-344b, miR-466b, miR-98, let-7a, miR-1, miR-206, and miR-34b were downregulated, while miR-181a was upregulated as validated also by quantitative real time polymerase chain reaction (qRT-PCR). By an in silico network analysis, we identified common mRNA targets (insulin-like growth factor 1 (IGF-1), solute carrier family 2 facilitated glucose transporter member 12 (SLC2a-12), eukaryotic translation initiation factor 4e (EIF-4e), and Unc-51 like autophagy activating kinase 2 (ULK-2)) targeted by at least three altered miRNAs. Predicted upregulation of these mRNA targets were validated by qRT-PCR. Conclusion: This is the first demonstration that sensory neuropathy affects cardiac miRNA expression network targeting IGF-1, SLC2a-12, EIF-4e, and ULK-2, which may contribute to cardiac diastolic dysfunction. These results further support the need for unbiased omics approach followed by in silico prediction and validation of molecular targets to reveal novel pathomechanisms.

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