The combined effects of multiple polymorphisms in several drug-metabolizing enzyme and transporter genes can contribute to considerable interindividual variation in drug disposition and response. Therefore, it has been of increasing interest to generate scalable, flexible and cost-effective technologies for large-scale genotyping of the drug-metabolizing enzyme and transporter genes. However, the number of drug-metabolizing enzyme and transporter gene variants exceeds the capacity of current technologies to comprehensively assess multiple polymorphisms in a single, multiplexed assay. The Targeted Genotyping System (Affymetrix, CA, USA) provides a solution to this challenge, by combining molecular inversion probe technology with universal microarrays to provide a method that is capable of analyzing thousands of variants in a single reaction, while remaining relatively insensitive to cross-reactivity between reaction components. This review will focus on the Targeted Genotyping System and how this technology was adapted to enable comprehensive analysis of drug-metabolizing enzyme and transporter gene polymorphisms.
Background: Drug metabolism is a multistep process by which the body disposes of xenobiotic agents such as therapeutic drugs. Genetic variation in the enzymes involved in this process can lead to variability in a patient's response to medication. Methods: We used molecular-inversion probe technology to develop a multiplex genotyping assay that can simultaneously test for 1227 genetic variants in 169 genes involved in drug metabolism, excretion, and transport. Within this larger set of variants, we performed analytical validation of a clinically defined core set of 165 variants in 27 genes to assess accuracy, imprecision, and dynamic range. Results: In a test set of 91 samples, genotyping accuracy for the core set probes was 99.8% for called genotypes, with a 1.2% no-call (NC) rate. The majority of the core set probes (133 of 165) had <1 genotyping failure in the test set; a subset of 12 probes was responsible for the majority of failures (mainly NC). Genotyping results were reproducible upon repeat testing with overall within-and between-run variation of 1.1% and 1.4%, respectively-again, primarily NCs in a subset of probes. The assay showed stable genotyping results over a 6-fold range of input DNA. Conclusions: This assay generates a comprehensive assessment of a patient's metabolic genotype and is a tool that can provide a more thorough understanding of
Objective:Inflammation plays an essential role in epilepsy. Studies indicate that cytokines and neurotrophic factors can act in neuroexcitability and epileptogenesis. We aimed to investigate the association between plasma inflammatory and neurotrophic markers, seizure frequency, and chronic epilepsy subtypes.Methods:We studied 446 patients with epilepsy and 166 healthy controls. We classified patients according to etiology and seizure frequency. We measured plasma levels of interleukin-1 (IL-1), IL-2, IL-4, IL-6, IL-10, IL-17, interferon-γ (IFNγ), tumor necrosis factor α (TNFα), soluble TNF receptor 1 (sTNFr1), sTNFr2, brain-derived neurotrophic factor (BDNF), neurotrophic factor 3 (NT3), NT4/5, ciliary neurotrophic factor (CNTF), nerve growth factor (NGF), and glial cell line-derived neurotrophic factor (GDNF) by enzyme-linked immunosorbent assay or cytometric bead array. Results:The plasma levels of BDNF, NT3, NGF, and sTNFr2 were higher, whereas IL-2, IL-4, IL-6, IL-10, IL-17, IFNγ, TNFα, CNTF, and sTNFr1 were lower in patients than controls. IL1, GDNF, and NT4/5 were similar between groups. These markers did not correlate with age, sex, and epilepsy duration.The molecule sTNFr2 was the best marker to discriminate patients from controls (area under the curve = .857), also differing between patients with frequent and infrequent seizures.Significance:This large cohort confirmed that patients with epilepsy have abnormal levels of plasma inflammatory and neurotrophic markers independent of the underlying etiology. Plasma level of sTNFr2 was related to seizure frequency and discriminated people with or without epilepsy with good accuracy, making it a potential biomarker for epilepsy and seizure burden.
This study aimed to assess subjective and objective sleep parameters in a homogeneous group of drug-resistant mesial temporal lobe epilepsy (MTLE)1 patients through internationally validated clinical questionnaires, video-electroencephalographic (VEEG)2 and polysomnographic (PSG)3 studies. Fifty-six patients with definite diagnosis of MTLE who were candidates for epilepsy surgery underwent a detailed clinical history, the Pittsburgh Sleep Quality Index (PSQI),4 Epworth Sleepiness Scale (ESS),5 Stanford Sleepiness Scale (SSS),6 neurological examination, 1.5 T brain magnetic resonance imaging, VEEG and PSG. Sixteen percent of patients reported significant daytime sleepiness as measured by ESS and 27% reported low levels of sleep quality as measured by PSQI. Patients with medically resistant epilepsy by MTLE showed increased wakefulness after sleep onset (WASO) with mean ± standard deviation of 17.4 ± 15.6, longer non-rapid eye movement (NREM)7 1 (7.5 ± 4.6%) and NREM3 sleep (26.6 ± 11.8%), abnormal rapid eye movement (REM)8 latency in 30/56 patients, shorter REM sleep (16.7 ± 6.6%), and abnormal alpha delta patterns were observed in 41/56 patients. The analysis of interictal epileptic discharges (IEDs)9 evidenced highest spiking rate during NREM3 sleep and higher concordance with imaging data when IEDs were recorded in sleep, mainly during REM sleep. We concluded that patients with MTLE showed disrupted sleep architecture that may result in daytime dysfunction and sleep complaints. Furthermore, NREM sleep activated focal IEDs and them - when recorded during sleep - had higher localizing value.
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