Prediction of Psoriatic Arthritis in Patients With Psoriasis Using DNA Methylation Profiles.

OBJECTIVE: Psoriatic 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 patients with psoriasis 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 patients with psoriasis will develop PsA prior to the onset of musculoskeletal symptoms. METHODS: Genome-wide DNA methylation was assessed in blood samples from patients with psoriasis who went on to develop arthritis (converters) and patients with psoriasis who did not (biologic naive, matched for age, sex, psoriasis duration, and duration of follow-up). Methylation differences between converters and nonconverters were identified by a multivariate linear regression model including clinical covariates (age, sex, body mass index, smoking). Predictive performance of methylation markers was assessed by developing support vector machine classification models with and without the addition of clinical variables. RESULTS: We identified a set of 36 highly relevant methylation markers (false discovery rate: adjusted P < 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 nonconverters with an area under the receiver operating characteristic curve of 0.9644. CONCLUSION: This study shows that DNA methylation patterns at an early stage of psoriatic disease can distinguish between patients who will develop PsA from those who will not during the same follow-up.

Variation in Actionable Pharmacogenetic Markers in Natives and Mestizos From Mexico.

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.