BackgroundThere is a wide variation in susceptibility to health effects of arsenic, which, in part, may be due to differences in arsenic metabolism. Arsenic is metabolized by reduction and methylation reactions, catalyzed by reductases and methyltransferases.ObjectivesOur goal in this study was to elucidate the influence of various demographic and genetic factors on the metabolism of arsenic.MethodsWe studied 415 individuals from Hungary, Romania, and Slovakia by measuring arsenic metabolites in urine using liquid chromatography with hydride generation and inductively coupled plasma mass spectrometry (HPLC-HG-ICPMS). We performed genotyping of arsenic (+III) methyltransferase (AS3MT), glutathione S-transferase omega 1 (GSTO1), and methylene-tetrahydrofolate reductase (MTHFR).ResultsThe results show that the M287T (T→C) polymorphism in the AS3MT gene, the A222V (C→T) polymorphism in the MTHFR gene, body mass index, and sex are major factors that influence arsenic metabolism in this population, with a median of 8.0 μg/L arsenic in urine. Females < 60 years of age had, in general, higher methylation efficiency than males, indicating an influence of sex steroids. That might also explain the observed better methylation in overweight or obese women, compared with normal weight men. The influence of the M287T (T→C) polymorphism in the AS3MT gene on the methylation capacity was much more pronounced in men than in women.ConclusionsThe factors investigated explained almost 20% of the variation seen in the metabolism of arsenic among men and only around 4% of the variation among women. The rest of the variation is probably explained by other methyltransferases backing up the methylation of arsenic.

BackgroundIn polypharmacy patients under home health management, pharmacogenetic testing coupled with guidance from a clinical decision support tool (CDST) on reducing drug, gene, and cumulative interaction risk may provide valuable insights in prescription drug treatment, reducing re-hospitalization and emergency department (ED) visits. We assessed the clinical impact of pharmacogenetic profiling integrating binary and cumulative drug and gene interaction warnings on home health polypharmacy patients.Methods and findingsThis prospective, open-label, randomized controlled trial was conducted at one hospital-based home health agency between February 2015 and February 2016. Recruitment came from patient referrals to home health at hospital discharge. Eligible patients were aged 50 years and older and taking or initiating treatment with medications with potential or significant drug-gene-based interactions. Subjects (n = 110) were randomized to pharmacogenetic profiling (n = 57). The study pharmacist reviewed drug-drug, drug-gene, and cumulative drug and/or gene interactions using the YouScript® CDST to provide drug therapy recommendations to clinicians. The control group (n = 53) received treatment as usual including pharmacist guided medication management using a standard drug information resource. The primary outcome measure was the number of re-hospitalizations and ED visits at 30 and 60 days after discharge from the hospital.The mean number of re-hospitalizations per patient in the tested vs. untested group was 0.25 vs. 0.38 at 30 days (relative risk (RR), 0.65; 95% confidence interval (CI), 0.32–1.28; P = 0.21) and 0.33 vs. 0.70 at 60 days following enrollment (RR, 0.48; 95% CI, 0.27–0.82; P = 0.007). The mean number of ED visits per patient in the tested vs. untested group was 0.25 vs. 0.40 at 30 days (RR, 0.62; 95% CI, 0.31–1.21; P = 0.16) and 0.39 vs. 0.66 at 60 days (RR, 0.58; 95% CI, 0.34–0.99; P = 0.045). Differences in composite outcomes at 60 days (exploratory endpoints) were also found. Of the total 124 drug therapy recommendations passed on to clinicians, 96 (77%) were followed. These findings should be verified with additional prospective confirmatory studies involving real-world applications in larger populations to broaden acceptance in routine clinical practice.ConclusionsPharmacogenetic testing of polypharmacy patients aged 50 and older, supported by an appropriate CDST, considerably reduced re-hospitalizations and ED visits at 60 days following enrollment resulting in potential health resource utilization savings and improved healthcare.Trial registrationClinicalTrials.gov NCT02378220

The subarachnoid space, where cerebrospinal fluid (CSF) flows over the brain and spinal cord, is lined on one side by arachnoid barrier (AB) cells that form part of the blood-CSF barrier. However, despite the fact that drugs are administered into the CSF and CSF drug concentrations are used as a surrogate for brain drug concentration following systemic drug administration, the tightjunctioned AB cells have never been examined for whether they express drug transporters that would influence CSF and central nervous system drug disposition. Hence, we characterized drug transporter expression and function in AB cells. Immunohistochemical analysis showed P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) in mouse AB cells but not other meningeal tissue. The Gene Expression Nervous System Atlas (GENSAT) database and the Allen Mouse Brain Atlas confirmed these observations. Microarray analysis of mouse and human arachnoidal tissue revealed expression of many drug transporters and some drug-metabolizing enzymes. Immortalized mouse AB cells express functional P-gp on the apical (dura-facing) membrane and BCRP on both apical and basal (CSF-facing) membranes. Thus, like blood-brain barrier cells and choroid plexus cells, AB cells highly express drug transport proteins and likely contribute to the blood-CSF drug permeation barrier.