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MicroRNA Mediated Changes in Drug Metabolism and Target Gene Expression by Efavirenz and Rifampicin In Vitro: Clinical Implications
Author(s) -
Marelize Swart,
Collet Dandara
Publication year - 2019
Publication title -
omics a journal of integrative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.811
H-Index - 58
eISSN - 1557-8100
pISSN - 1536-2310
DOI - 10.1089/omi.2019.0122
Subject(s) - cyp3a4 , microrna , efavirenz , cyp2b6 , fold change , gene expression , drug , biology , pharmacology , drug metabolism , messenger rna , gene , human immunodeficiency virus (hiv) , enzyme , immunology , cytochrome p450 , genetics , biochemistry , viral load , antiretroviral therapy
Efavirenz (EFV) and rifampicin (RMP) are widely prescribed in Africa for treatment of HIV/AIDS and tuberculosis epidemics. Exposure to medicines can alter drug metabolism, for example, through changes in expression of microRNAs. We report, in this study, novel observations on the ways in which EFV and RMP change microRNA expression signatures in vitro in HepaRG cells. Additionally, we discuss the clinical implications of changes in expression of drug-metabolizing enzyme genes, such as CYP3A4 , CYP3A5 , UGT1A1 , CYP2B6 , and NR1I3 . Differentiated HepaRG cells were treated with EFV (6.4 μM) or RMP (24.4 μM) for 24 h. Treatment of HepaRG cells with EFV resulted in a significant increase in messenger RNA (mRNA) expression for CYP3A4 (12.51-fold, p  = 0.002), CYP3A5 (2.10-fold, p  = 0.019), and UGT1A1 (2.52-fold, p  = 0.005), whereas NR1I3 expression decreased (0.41-fold, p  = 0.02). On the other hand, treatment of HepaRG cells with RMP resulted in a significant increase in mRNA expression for CYP2B6 (6.68-fold, p  = 0.007) and CYP3A4 (111.96-fold, p  = 0.001), whereas NR1I3 expression decreased (0.46-fold, p  = 0.033). These data point to several important clinical implications through changes in drug/drug interaction risks and achieving optimal therapeutics. All in all, this study shows that differential expression of microRNAs after treatment with EFV and RMP adds another layer of complexity that should be incorporated in pharmacogenomic algorithms to render drug response more predictable.

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