METHODOLOGY/PRINCIPAL FINDINGS: Genome-wide microarray-based transcription analysis was carried out to detect the genes associated with metabolic resistance in these populations. Comparisons of the susceptible New Orleans strain to three non-exposed multiple insecticide resistant field strains; Penang, Kuala Lumpur and Kota Bharu detected 2605, 1480 and 425 differentially expressed transcripts respectively (fold-change>2 and p-value ≤ 0.05). 204 genes were commonly over-expressed with monooxygenase P450 genes (CYP9J27, CYP6CB1, CYP9J26 and CYP9M4) consistently the most up-regulated detoxification genes in all populations, indicating that they possibly play an important role in the resistance. In addition, glutathione S-transferases, carboxylesterases and other gene families commonly associated with insecticide resistance were also over-expressed. Gene Ontology (GO) enrichment analysis indicated an over-representation of GO terms linked to resistance such as monooxygenases, carboxylesterases, glutathione S-transferases and heme-binding. Polymorphism analysis of CYP9J27 sequences revealed a high level of polymorphism (except in Joho Bharu), suggesting a limited directional selection on this gene. In silico analysis of CYP9J27 activity through modelling and docking simulations suggested that this gene is involved in the multiple resistance in Malaysian populations as it is predicted to metabolise pyrethroids, DDT and bendiocarb.
CONCLUSION/SIGNIFICANCE: The predominant over-expression of cytochrome P450s suggests that synergist-based (PBO) control tools could be utilised to improve control of this major dengue vector across Malaysia.
PURPOSE: The concomitant use of therapeutic drugs may cause potential drug-drug interactions by decreasing or increasing plasma levels of the administered drugs, leading to a suboptimal clinical efficacy or a higher risk of toxicity. Thus, evaluating the inhibitory potential of a new chemical entity, and to clarify the mechanism of inhibition and kinetics in the various CYP enzymes is an important step to predict drug-drug interactions.
STUDY DESIGN: This study was designed to assess the potential inhibitory effects of Alpinia conchigera Griff. rhizomes extract and its active constituent, ACA, on nine c-DNA expressed human cytochrome P450s (CYPs) enzymes using fluorescent CYP inhibition assay.
METHODS/RESULTS: The half maximal inhibitory concentration (IC50) of Alpinia conchigera Griff. rhizomes extract and ACA was determined for CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C19, CYP2D6, CYP2E1, CYP3A4 and CYP3A5. A. conchigera extract only moderately inhibits on CYP3A4 (IC50 = 6.76 ± 1.88µg/ml) whereas ACA moderately inhibits the activities of CYP1A2 (IC50 = 4.50 ± 0.10µM), CYP2D6 (IC50 = 7.50 ± 0.17µM) and CYP3A4 (IC50 = 9.50 ± 0.57µM) while other isoenzymes are weakly inhibited. In addition, mechanism-based inhibition studies reveal that CYP1A2 and CYP3A4 exhibited non-mechanism based inhibition whereas CYP2D6 showed mechanism-based inhibition. Lineweaver-Burk plots depict that ACA competitively inhibited both CYP1A2 and CYP3A4, with a Ki values of 2.36 ± 0.03 µM and 5.55 ± 0.06µM, respectively, and mixed inhibition towards CYP2D6 with a Ki value of 4.50 ± 0.08µM. Further, molecular docking studies show that ACA is bound to a few key amino acid residues in the active sites of CYP1A2 and CYP3A4, while one amino residue of CYP2D6 through predominantly Pi-Pi interactions.
CONCLUSION: Overall, ACA may demonstrate drug-drug interactions when co-administered with other therapeutic drugs that are metabolized by CYP1A2, CYP2D6 or CYP3A4 enzymes. Further in vivo studies, however, are needed to evaluate the clinical significance of these interactions.
METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.
RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.
CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.