An integrated analysis of several genes known to intervene in the different steps of metabolism is required to predict atorvastatin's AUC.

The identification and characterization of pharmacogenetic variants in Latin American populations is still an ongoing endeavor. Here, we investigated SNVs on genes listed by the Pharmacogenomics Knowledge Base in 1284 Mestizos and 94 Natives from Mexico. Five institutional cohorts with NGS data were retrieved from different research projects at INMEGEN, sequencing files were filtered for 55 pharmacogenes present in all cohorts to identify novel and known variation. Bioinformatic tools VEP, PROVEAN, and FATHMM were used to assess, in silico, the functional impact of this variation. Next, we focused on 17 genes with actionable variants that have been clinically implemented. Allele frequencies were compared with major continental groups and differences discussed in the scope of a pharmacogenomic impact. We observed a wide genetic variability for known and novel SNVs, the largest variation was on UGT1A > ACE > COMT > ABCB1 and the lowest on APOE and NAT2. Although with allele frequencies around 1%, novel variation was observed in 16 of 17 PGKB genes. In Natives we identified 59 variants and 58 in Mestizos. Several genes did not show novel variation, on CYP2B6, CYP2D6, and CYP3A4 in Natives; and APOE, UGT1A, and VKORC1 in Mestizos. Similarities in allele frequency, comparing major continental groups for VIP pharmacogenes, hint towards a comparable PGx for drugs metabolized by UGT1A1, DPYD, ABCB1, CBR3, COMT, and TPMT; in contrast to variants on CYP3A5 and CYP2B6 for which significant MAF differences were identified. Our observations offer some discernment into the extent of pharmacogenetic variation registered up-to-date in Mexicans and contribute to quantitatively dissect actionable pharmacogenetic variants in Natives and Mestizos.

ObjectivePsoriatic arthritis (PsA) is an immune‐mediated inflammatory arthritis, associated with psoriasis, that significantly increases morbidity and mortality risk. We currently lack the means of predicting which psoriasis patients will develop PsA, and a large number of patients remain undiagnosed. Regulation of gene expression through DNA methylation can potentially trigger and maintain PsA pathophysiological processes. We aimed to identify DNA methylation markers that can predict which psoriasis patients will develop PsA prior to the onset of musculoskeletal symptoms.MethodsGenome‐wide DNA methylation was assessed in blood samples from psoriasis patients that went on to develop arthritis (converters) and psoriasis patients that did not (biologic naive, matched for age, sex, psoriasis duration and duration of follow up). Methylation differences between converters and non‐converters were identified by a multi‐variate linear regression model including clinical covariates (age, sex, BMI, smoking). Predictive performance of methylation markers was assessed by developing support vector machine classification models with and without the addition of clinical variables.ResultsWe identified a set of 36 highly relevant methylation markers (FDR‐adjusted p‐values lower than 0.05 and a minimum change in methylation of 0.05) across 15 genes and several intergenic regions. A classification model relying on these markers identified converters and non‐converters with an area under the ROC curve of 0.9644.ConclusionThis study shows that DNA methylation patterns at an early stage of psoriatic disease can distinguish between patients that will develop PsA from those that will not during the same follow‐up.This article is protected by copyright. All rights reserved.image