A Systems Biology Approach for Personalized Medicine in Refractory Epilepsy

Naimo, Giuseppina Daniela; Guarnaccia, Maria; Sprovieri, T.; Ungaro, C; Conforti, Francesca Luisa; Andò, Sebastiano; Cavallaro, Sebastiano

doi:10.3390/ijms20153717

Cited by 32 publications

(21 citation statements)

References 107 publications

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“…It was observed that patients became resistant to most or to all broad range AEDs with different mechanisms of action [70]. The reported frequency of nonresponders is approximately 30% [4, 10, 71, 72].…”

Section: Discussionmentioning

confidence: 99%

“…P-gp overexpression reduces the AEDs bioavailability in the epileptic cells, which contributes to refractory epilepsy. Some studies suggested that its altered function could be a result of genetic variants especially SNPs located in the ABCB1 gene [4, 17–25]. The most studied SNPs in this gene are C1236T (rs1128503) in exon 12, G2677T (rs2032582) in exon 21, and C3435T (rs1045642) in exon 26 [26–32].…”

Section: Introductionmentioning

confidence: 99%

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ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

et al. 2019

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Background Epilepsy is one of the most common neurological disorders with about 30% treatment failure rate. An interindividual variations in efficacy of antiepileptic drugs (AEDs) make the treatment of epilepsy challenging, which can be attributed to genetic factors such as ATP-Binding Cassette sub-family B, member1 (ABCB1) gene polymorphisms. Objective The main objective of the present study is to evaluate the association of ABCB1 C1236T, G2677T, and C3435T polymorphisms with treatment response among Tunisian epileptic patients. Materials and Methods One hundred epileptic patients, originated from north of Tunisia, were recruited and categorized into 50 drug-resistant and 50 drug-responsive patients treated with antiepileptic drugs (AEDs) as per the International League Against Epilepsy. DNA of patients was extracted and ABCB1 gene polymorphisms studied using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Results The C1236T, G2677T, and C3435T polymorphisms were involved into AED resistance. Significant genotypic (C1236T TT (p ≤ 0.001); G2677T TT (p = 0.001); C3435T TT (p ≤ 0.001)) and allelic associations (C1236T T (3.650, p ≤ 0.001); G2677TT (1.801, p = 0.044); C3435T T (4.730, p ≤ 0.001)) with drug resistance epilepsy (DRE) were observed. A significant level of linkage disequilibrium (LD) was also noted between ABCB1 polymorphisms. Patients with the haplotypes CT and TT (C1236T-G2677T); GT, TC, and TT (G2677T-C3435T); CT and TT (C1236T-C3435T); CTT, TTC, TGT, and TTT (C1236T-G2677T-C3435T) were also significantly associated to AED resistance. Conclusions The response to antiepileptics seems to be modulated by TT genotypes, T alleles, and the predicted haplotypes for the tested SNPs in our population. Genetic analysis is a valuable tool for predicting treatment response and thus will contribute to personalized medicine for Tunisian epileptic patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

et al. 2019

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“…This is particularly important for potential future application of c-tDCS, known to historically induce inhibition, on excitotoxic populations such as Epilepsy and those prone to seizures. Drug-resistance is considered common in Epileptic populations (Abou El Ella et al, 2018;Assenza et al, 2017;Hung et al, 2013;Naimo et al, 2019;Tecchio et al, 2018). Links between drug-resistance and particular gene variants (Baghel et al, 2016;Hung et al, 2013) offer insight into the role gene variants play in the activity of inhibitory cortical pathways.…”

Section: Genetic Analysismentioning

confidence: 99%

Genetic polymorphisms do not predict inter-individual variability to cathodal transcranial direct current stimulation of the primary motor cortex

Pellegrini

Zoghi

Jaberzadeh

2020

Preprint

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High variability between individuals (i.e. inter-individual variability) in response to transcranial direct current stimulation (tDCS) has become a commonly reported issue in the tDCS literature in recent years. Inherent genetic differences between individuals has been proposed as a contributing factor to observed response variability. This study investigated whether tDCS inter-individual variability was genetically mediated. A large sample-size of sixty-one healthy males received cathodal-tDCS (c-tDCS) and sham-tDCS, of the primary motor cortex at 1mA and 10-minutes via 6x4cm active and 7x5cm return electrodes. Corticospinal excitability (CSE) was assessed via twenty-five single-pulse transcranial magnetic stimulation motor evoked potentials (MEP).Intracortical inhibition (ICI) was assessed via twenty-five 3ms inter-stimulus interval (ISI) pairedpulse MEPs, known as short-interval intracortical inhibition (SICI). Intracortical facilitation (ICF) was assessed via twenty-five 10ms ISI paired-pulse MEPs. Gene variants encoding for excitatory and inhibitory neuroreceptors were determined via saliva samples. Pre-determined thresholds and statistical cluster analyses were used to subgroup individuals. Two distinct subgroups were identified, 'responders' reducing CSE following c-tDCS and 'non-responders' showing no reduction or even increase in CSE. Differences in CSE between responders and non-responders following c-tDCS were not explained by changes in SICI or ICF. No significant relationships were reported between gene variants and inter-individual variability to c-tDCS suggesting the chosen gene variants did not influence the activity of the neuroreceptors involved in eliciting changes in CSE in responders following c-tDCS. In this largest c-tDCS study of its kind, novel insights were reported into the contribution genetic factors may play in observed inter-individual variability to c-tDCS. Key WordsCorticospinal excitability, Gamma-aminobutyric acid, Inter-individual variability, N-methyl-daspartic acid, Single nucleotide polymorphism This study therefore aimed to be the first of its kind to investigate the relationship between NMDA and GABA receptor gene variants and inter-individual variability to c-tDCS. In a large sample-size, this study also aimed to investigate the predictive value of the selected gene variants for response to c-tDCS. The significance of this study will be its novelty in investigating c-tDCS, and its largescale nature which will facilitate meaningful subgroup statistical analysis, thus increasing the power and impact of the research findings. This may provide insight into future studies investigating the application of c-tDCS whereby reductions in cortical excitability and CSE is desired such as in excitotoxic neurological populations such as Epilepsy and those prone to seizures.We hypothesised there would be an association and predictive capacity between the selected gene variants and c-tDCS response. We hypothesised normal expression of genes encoding for GABA receptors would be associated...

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“…According to the International League Against Epilepsy, DRE is defined as the failure to achieve sustained seizure freedom after adequate trials of two tolerated and appropriately chosen AEDs treatments (monotherapies or combination therapies) [3]. The mechanism of DRE is not fully clear and may be related to the sensitivity of drug targets, activity of drug transporters, cytochrome P450, structural neural network, and other potential causes of epilepsy [4]. Abrupt and repetitive seizures may lead to neurobiochemical changes in the brain, cognitive decline, and serious psychological problems in PWEs, which can seriously affect patients' quality of life and cause an increased burden on their families.…”

Section: Introductionmentioning

confidence: 99%

Models for predicting treatment efficacy of antiepileptic drugs and prognosis of treatment withdrawal in epilepsy patients

Yang

Wang

Han

2021

Acta Epileptologica

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Although antiepileptic drugs (AEDs) are the most effective treatment for epilepsy, 30–40% of patients with epilepsy would develop drug-refractory epilepsy. An accurate, preliminary prediction of the efficacy of AEDs has great clinical significance for patient treatment and prognosis. Some studies have developed statistical models and machine-learning algorithms (MLAs) to predict the efficacy of AEDs treatment and the progression of disease after treatment withdrawal, in order to provide assistance for making clinical decisions in the aim of precise, personalized treatment. The field of prediction models with statistical models and MLAs is attracting growing interest and is developing rapidly. What’s more, more and more studies focus on the external validation of the existing model. In this review, we will give a brief overview of recent developments in this discipline.

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A Systems Biology Approach for Personalized Medicine in Refractory Epilepsy

Cited by 32 publications

References 107 publications

ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

Genetic polymorphisms do not predict inter-individual variability to cathodal transcranial direct current stimulation of the primary motor cortex

Models for predicting treatment efficacy of antiepileptic drugs and prognosis of treatment withdrawal in epilepsy patients

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