METHOD: The main polymorphisms on the cytochrome P450 (CYP) genes, CYP2A6, CYP2B6, CYP2C19, CYP2D6, CYP3A4 and CYP3A5, and the multi-drug resistance 1 gene (MDR1) were genotyped in 78 healthy Vietnamese subjects. Pharmacokinetic metrics were available for CYP2A6 (coumarin), CYP2C19 (mephenytoin), CYP2D6 (metoprolol) and CYP3As (midazolam), allowing correlations with the determined genotype.
RESULTS: In the CYP2 family, we detected alleles CYP2A6*4 (12%) and *5 (15%); CYP2B6*4 (8%), *6 (27%); CYP2C19*2 (31%) and *3 (6%); CYP2D6*4, *5, *10 (1, 8 and 44%, respectively). In the CYP3A family, CYP3A4*1B was detected at a low frequency (2%), whereas CYP3A5 *3 was detected at a frequency of 67%. The MDR1 3435T allele was present with a prevalence of 40%. Allele proportions in our cohort were compared with those reported for other Asian populations. CYP2C19 genotypes were associated to the S-4'-OH-mephenytoin/S-mephenytoin ratio quantified in plasma 4 h after intake of 100 mg mephenytoin. While CYP2D6 genotypes were partially reflected by the alpha-OH-metroprolol/metoprolol ratio in plasma 4 h after dosing, no correlation existed between midazolam plasma concentrations 4 h post-dose and CYP3A genotypes.
CONCLUSIONS: The Vietnamese subjects of our study cohort presented allele prevalences in drug-metabolising enzymes that were generally comparable with those reported in other Asian populations. Deviations were found for CYP2A6*4 compared to a Chinese population (12 vs. 5%, respectively; P = 0.023), CYP2A6*5 compared with a Korean population (15 vs. <1%, respectively; P < 0.0001), a Malaysian population (1%; P < 0.0001) and a Chinese population (1%; P < 0.0001); CYP2B6*6 compared with a Korean population (27 vs. 12%; P = 0.002) and a Japanese population (16%; P = 0.021). Pharmacokinetic metrics versus genotype analysis reinforces the view that the predictive value of certain globally common variants (e.g. CYP2D6 single nucleotide polymorphisms) should be evaluated in a population-specific manner.
METHODOLOGY/PRINCIPAL FINDINGS: The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007-2013. These data were split between the years 2007-2011 (historic period) and 2012-2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1-12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1-12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4-16 weeks.
CONCLUSIONS/SIGNIFICANCE: An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.