Multidrug resistance 1 (MDR1) 3435C/T genotyping in childhood drug-resistant epilepsy

2014 ◽  
Vol 36 (2) ◽  
pp. 137-142 ◽  
Author(s):  
Semra Saygi ◽  
Fusun Alehan ◽  
Fatma Belgin Atac ◽  
Ilknur Erol ◽  
Hasibe Verdi ◽  
...  
2017 ◽  
Vol 117 (4) ◽  
pp. 849-855 ◽  
Author(s):  
Beata Smolarz ◽  
Dominik Skalski ◽  
Andrzej Rysz ◽  
Andrzej Marchel ◽  
Hanna Romanowicz ◽  
...  

2010 ◽  
Vol 25 (12) ◽  
pp. 1485-1490 ◽  
Author(s):  
Asude Alpman ◽  
Ferda Ozkinay ◽  
Hasan Tekgul ◽  
Sarenur Gokben ◽  
Sacide Pehlivan ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Ewa Emich-Widera ◽  
Wirginia Likus ◽  
Beata Kazek ◽  
Paweł Niemiec ◽  
Anna Balcerzyk ◽  
...  

Drug-resistant epilepsies still remain one of the most profound problems of contemporary epileptology. Several mechanisms of drug resistance are possible; among them, genetic factors have a prominent place. Much importance is attached to genes, which encode enzymes that metabolize antiepileptic drugs CYP 3A, which belong to the family of cytochromes P450 and the genome of multidrug resistance, such as multidrug resistance 1 (MDR1) that expresses P-glycoprotein (P-gp), a drug transporter protein. The aim of the study was to assess the relation between polymorphism of gene CYP3A5 and polymorphism C3435T of MDR1 gene with the occurrence of focal, drug-resistant epilepsy in children and youths up to 18 years of age. The study comprised 85 patients, and their age range was from 33 months to 18 years of age, suffering from epilepsy, partly responding well to treatment, partly drug resistant. The polymorphism of both genes has been analysed using the PCR-RFLP method. The study failed to corroborate association between polymorphism CYP3A5*3 and C3435T polymorphism in MDR1 gene and pharmacoresistant epilepsy. The results of our research do not confirm the prognostic value of the polymorphisms examined in the prognostication of drug resistance in epilepsies.


2018 ◽  
Vol 26 (2) ◽  
pp. 13-18
Author(s):  
Yu.M. Zabrodskaya ◽  
◽  
D.A. Sitovskaya ◽  
S.M. Malyshev ◽  
T.V. Sokolova ◽  
...  

Epilepsia ◽  
2020 ◽  
Author(s):  
Oumarou Ouédraogo ◽  
Rose‐Marie Rébillard ◽  
Hélène Jamann ◽  
Victoria Hannah Mamane ◽  
Marie‐Laure Clénet ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adriana Leal ◽  
Mauro F. Pinto ◽  
Fábio Lopes ◽  
Anna M. Bianchi ◽  
Jorge Henriques ◽  
...  

AbstractElectrocardiogram (ECG) recordings, lasting hours before epileptic seizures, have been studied in the search for evidence of the existence of a preictal interval that follows a normal ECG trace and precedes the seizure’s clinical manifestation. The preictal interval has not yet been clinically parametrized. Furthermore, the duration of this interval varies for seizures both among patients and from the same patient. In this study, we performed a heart rate variability (HRV) analysis to investigate the discriminative power of the features of HRV in the identification of the preictal interval. HRV information extracted from the linear time and frequency domains as well as from nonlinear dynamics were analysed. We inspected data from 238 temporal lobe seizures recorded from 41 patients with drug-resistant epilepsy from the EPILEPSIAE database. Unsupervised methods were applied to the HRV feature dataset, thus leading to a new perspective in preictal interval characterization. Distinguishable preictal behaviour was exhibited by 41% of the seizures and 90% of the patients. Half of the preictal intervals were identified in the 40 min before seizure onset. The results demonstrate the potential of applying clustering methods to HRV features to deepen the current understanding of the preictal state.


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