Genetic polymorphisms in sex hormone metabolizing genes and drug response in women with epilepsy

Thai pharmacogenomics database -2 (TPGxD-2) sequel to TPGxD-1, analyzing genetic variants in 26 non-VIPGx genes within the Thai population

Next-generation sequencing (NGS) has transformed pharmacogenomics (PGx), enabling thorough profiling of pharmacogenes using computational methods and advancing personalized medicine. The Thai Pharmacogenomic Database-2 (TPGxD-2) analyzed 948 whole genome sequences, primarily from the Electricity Generating Authority of Thailand (EGAT) cohort. This study is an extension of the previous Thai Pharmacogenomic Database (TPGxD-1) and specifically focused on 26 non-very important pharmacogenes (VIPGx) genes. Variant calling was conducted using Sentieon (version 201808.08) following GATK's best workflow practices. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0. Star allele analysis was performed with Stargazer v2.0.2, which called star alleles for 22 of 26 non-VIPGx genes. The variant analysis revealed a total of 14,529 variants in 26 non-VIPGx genes, with TBXAS1 had the highest number of variants (27%). Among the 14,529 variants, 2328 were novel (without rsID), with 87 identified as clinically relevant. We also found 56 known PGx variants among the known variants (n = 12,201), with UGT2B7 (19.64%), CYP1B1 (8.9%), SLCO2B1 (8.9%), and POR (8.9%) being the most common. We reported a high frequency of intermediate metabolizers (IMs) in CYP2F1 (34.6%) and CYP4A11 (8.6%), and a high frequency of decreased functional alleles in POR (53.9%) and SLCO1B3 (34.9%) genes. This study enhances our understanding of pharmacogenomic profiling of 26 non-VIPGx genes of notable clinical importance in the Thai population. However, further validation with additional computational and reference genotyping methods is necessary, and novel alleles identified in this study should undergo further orthogonal validation.

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population

PURPOSE

This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in people with epilepsy (PWE).

METHODS

Data was collected from 786 PWE at the Outpatient Department of Neurology, Institute of Human Behavior and Allied Sciences (IHBAS), New Delhi, India from 2005 to 2015. Patients were followed up at the 2nd, 4th, 8th, and 12th month over the span of 1 year for the drugs being administered and their dosage, the serum drug levels, the frequency of seizure control, drug efficacy, the adverse drug reactions (ADRs), and their compliance to ASMs. Several features, including demographic details, medical history, and auxiliary examinations electroencephalogram (EEG) or Computed Tomography (CT) were chosen to discern between patients with distinct remission outcomes. Remission outcomes were categorized into 'good responder (GR)' and 'poor responder (PR)' based on the number of seizures experienced by the patients over the study duration. Our dataset was utilized to train seven classical machine learning algorithms i.e Extreme Gradient Boost (XGB), K-Nearest Neighbor (KNN), Support Vector Classifier (SVC), Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB) and Logistic Regression (LR) to construct classification models.

RESULTS

Our research findings indicate that 1) among the seven algorithms examined, XGB and SVC demonstrated superior predictive performances of ASM treatment outcomes with an accuracy of 0.66 each and ROC-AUC scores of 0.67 (XGB) and 0.66 (SVC) in distinguishing between PR and GR patients. 2) The most influential factor in discerning PR to GR patients is a family history of seizures (no), education (literate) and multitherapy with Chi-square (χ2) values of 12.1539, 8.7232 and 13.620 respectively and odds ratio (OR) of 2.2671, 0.4467, and 1.9453 each. 3). Furthermore, our surrogate analysis revealed that the null hypothesis for both XGB and SVC was rejected at a 100 % confidence level, underscoring the significance of their predictive performance. These findings underscore the robustness and reliability of XGB and SVC in our predictive modelling framework.

SIGNIFICANCE

Utilizing XG Boost and SVC-based machine learning classifier, we successfully forecasted the likelihood of a patient's response to ASM treatment, categorizing them as either PR or GR, post-completion of standard epilepsy examinations. The classifier's predictions were found to be statistically significant, suggesting their potential utility in improving treatment strategies, particularly in the personalized selection of ASM regimens for individual epilepsy patients.

Molecular Insights of Drug Resistance in Epilepsy: Multi-omics Unveil

Epilepsy is a devastating neurological disorder mainly associated with impaired synchronic discharge that leads to sensory, motor, and psychomotor impairments. Till now, about 30 anti-seizure medications (ASMs) have been approved for the management of epilepsy, yet one-third of individuals still have uncontrollable epilepsy and develop resistance. Drug resistance epilepsy (DRE) is defined as the condition where two ASMs fail to control the seizure in epileptic patients. The leading cause of the resistance was the extended use of ASMs. According to various studies, alterations in some genes and their expressions, along with specific metabolic impairments, are suggested to be associated with ASMs resistance and DRE pathophysiology. Several factors aid in the pathophysiology of DRE, such as alterations in protein-encoding genes such as neurotransmitter receptors, drug transporters, ion channels, and drug targets. Furthermore, the altered metabolite levels of metabolites implicated in neurotransmitter signaling, energetic pathways, oxidative stress, and neuroinflammatory signaling differentiate the epileptic patient from the DRE patient. Various DRE biomarkers can be identified using the "integrated omics approach," which includes the study of genomics, transcriptomics, and metabolomics. The current review has been compiled to understand the pathophysiological mechanisms of DRE by focusing on genomics, transcriptomics, and metabolomics. An effort has also been made to identify the therapeutic targets based on identifying significant markers by a multi-omics approach. This has the potential to develop novel therapeutic interventions in the future.

Exploratory focused pharmacogenetic testing reveals novel markers associated with risperidone pharmacokinetics in Saudi children with autism

Background: Autism spectrum disorders (ASDs) encompass a broad range of phenotypes characterized by diverse neurological alterations. Genomic studies have revealed considerable overlap between the molecular mechanisms implicated in the etiology of ASD and genes involved in the pharmacokinetic (PK) and pharmacodynamic (PD) pathways of antipsychotic drugs employed in ASD management. Given the conflicting data originating from candidate PK or PD gene association studies in diverse ethnogeographic ASD populations, dosage individualization based on "actionable" pharmacogenetic (PGx) markers has limited application in clinical practice. Additionally, off-label use of different antipsychotics is an ongoing practice, which is justified given the shortage of approved cures, despite the lack of satisfactory evidence for its safety according to precision medicine. This exploratory study aimed to identify PGx markers predictive of risperidone (RIS) exposure in autistic Saudi children. Methods: This prospective cohort study enrolled 89 Saudi children with ASD treated with RIS-based antipsychotic therapy. Plasma levels of RIS and 9-OH-RIS were measured using a liquid chromatography-tandem mass spectrometry system. To enable focused exploratory testing, genotyping was performed with the Axiom PharmacoFocus Array, which included a collection of probe sets targeting PK/PD genes. A total of 720 PGx markers were included in the association analysis. Results: A total of 27 PGx variants were found to have a prominent impact on various RIS PK parameters; most were not located within the genes involved in the classical RIS PK pathway. Specifically, 8 markers in 7 genes were identified as the PGx markers with the strongest impact on RIS levels (p < 0.01). Four PGx variants in 3 genes were strongly associated with 9-OH-RIS levels, while 5 markers in 5 different genes explained the interindividual variability in the total active moiety. Notably, 6 CYP2D6 variants exhibited strong linkage disequilibrium; however, they significantly influenced only the metabolic ratio and had no considerable effects on the individual estimates of RIS, 9-OH-RIS, or the total active moiety. After correction for multiple testing, rs78998153 in UGT2B17 (which is highly expressed in the brain) remained the most significant PGx marker positively adjusting the metabolic ratio. For the first time, certain human leukocyte antigen (HLA) markers were found to enhance various RIS exposure parameters, which reinforces the gut-brain axis theory of ASD etiology and its suggested inflammatory impacts on drug bioavailability through modulation of the brain, gastrointestinal tract and/or hepatic expression of metabolizing enzymes and transporters. Conclusion: Our hypothesis-generating approach identified a broad spectrum of PGx markers that interactively influence RIS exposure in ASD children, which indicated the need for further validation in population PK modeling studies to define polygenic scores for antipsychotic efficacy and safety, which could facilitate personalized therapeutic decision-making in this complex neurodevelopmental condition.

Genic-intergenic polymorphisms of CYP1A genes and their clinical impact

The humancytochrome P450 1A (CYP1A) subfamily genes, CYP1A1 and CYP1A2, encoding monooxygenases are critically involved in biotransformation of key endogenous substrates (estradiol, arachidonic acid, cholesterol) and exogenous compounds (smoke constituents, carcinogens, caffeine, therapeutic drugs). This suggests their significant involvement in multiple biological pathways with a primary role of maintaining endogenous homeostasis and xenobiotic detoxification. Large interindividual variability exist in CYP1A gene expression and/or catalytic activity of the enzyme, which is primarily due to the existence of polymorphic alleles which encode them. These polymorphisms (mainly single nucleotide polymorphisms, SNPs) have been extensively studied as susceptibility factors in a spectrum of clinical phenotypes. An in-depth understanding of the effects of polymorphic CYP1A genes on the differential metabolic activity and the resulting biological pathways is needed to explain the clinical implications of CYP1A polymorphisms. The present review is intended to provide an integrated understanding of CYP1A metabolic activity with unique substrate specificity and their involvement in physiological and pathophysiological roles. The article further emphasizes on the impact of widely studied CYP1A1 and CYP1A2 SNPs and their complex interaction with non-genetic factors like smoking and caffeine intake on multiple clinical phenotypes. Finally, we attempted to discuss the alterations in metabolism/physiology concerning the polymorphic CYP1A genes, which may underlie the reported clinical associations. This knowledge may provide insights into the disease pathogenesis, risk stratification, response to therapy and potential drug targets for individuals with certain CYP1A genotypes.

Effect of ANKK1 Polymorphisms on Serum Valproic Acid Concentration in Chinese Han Adult Patients in the Early Postoperative Period

INTRODUCTION

This study aimed to investigate the relationship between gene polymorphisms and clinical factors with the concentrations of valproic acid (VPA) in adult patients who underwent neurosurgery in China.

METHODS

A total of 531 serum concentration samples at steady state were collected from 313 patients to develop a population pharmacokinetic (PPK) model. Data analysis was performed using nonlinear mixed effects modeling. Covariates included demographic parameters, biological characteristics, and genetic polymorphism. Bootstrap evaluation showed that the final model was stable. Sensitive analysis was performed to verify the relationship between gene polymorphisms and concentrations of VPA. Linear regression was used to analyze the relationship between VPA concentration, ANKK1, and daily dosage.

RESULTS

In the recruited patients, 17 of 25 single-nucleotide polymorphism distributions were consistent with the Hardy-Weinberg equilibrium. A one-compartment model with first-order absorption and elimination was developed for VPA injections. VPA clearance was significantly influenced by three variables: sex (17.41% higher in male than female patients), body weight, and the ANKK1 gene. Typical values for the elimination clearance and the volume of central compartment were 0.614 L/min and 23.5 L, respectively. The model evaluation indicated the stable and precise performance of the final model. After sensitive analysis using Kruskal-Wallis and Mann-Whitney U tests, we found that patients with AA alleles had higher VPA concentrations than those with GG and AG alleles. Linear regression models showed that gene polymorphisms of ANKK1 had little effects on VPA concentration.

CONCLUSION

A PPK model of VPA in Chinese Han patients was successfully established; this can be helpful for model-informed precision-dosing approaches in clinical patient care, and for exploring the mechanism of VPA-induced weight gain.

Association between ABCB1 polymorphisms and response to antiepileptic drugs among Jordanian epileptic patients

BACKGROUND

Genetic polymorphisms of drug efflux transporters as ATP-binding cassette subfamily B, member 1 (ABCB1) have been suggested to modulate antiepileptic drugs (AEDs) response. We aimed to explore the association of ABCB1 polymorphisms and AEDs resistance among epileptic patients.

METHODS

A total of 86 Jordanian epileptic patients treated with AEDs was included in the study. DNA was extracted from blood samples and genotyping and haplotypes analyses were conducted for Nine single nucleotide polymorphisms (SNPs) on the ABCB1 gene.

RESULTS

Data revealed that none of the examined SNPs were associated with resistance to AEDs neither on the level of alleles nor genotypes. However, strong association was found between rs2235048 (OR = 10.6; 95%CI = [1.89-59.8], p= 0.01), rs1045642 (OR = 14; 95%CI = [1.3-156.7], p= 0.02), rs2032582 (OR = 9.1; 95%CI = [1.4-57.3], p= 0.04) and rs1128503 (OR = 18.7; 95%CI = [1.6-222.9], p= 0.02), ABCB1 polymorphisms and resistance to AEDs among females but not males. Haplotype analysis revealed statistically significant associations. The strongest significant associations were for haplotypes containing 2677G_1236 T in two-SNPshaplotypes (OR = 4.2; 95%CI = [1.2-14.9], p = 0.024); three-SNPs-haplotypes (OR = 4.2; 95% CI = [1.2-14.9], p = 0.02); four-SNPs-haplotypes (OR = 4.1; 95%CI = [1.2-14.3], p = 0.026).

CONCLUSION

Data suggests that there is a gender dependent association between ABCB1 genetic polymorphisms and response to AEDs. Additionally, ABCB1 haplotypes influence the response to AEDs. Further investigation is needed to confirm the results of this study.

Precision medicine in women with epilepsy: The challenge, systematic review, and future direction

Epilepsy is one of the most prevalent neurologic conditions, affecting almost 70 million people worldwide. In the United States, 1.3 million women with epilepsy (WWE) are in their active reproductive years. Women with epilepsy (WWE) face gender-specific challenges such as pregnancy, seizure exacerbation with hormonal pattern fluctuations, contraception, fertility, and menopause. Precision medicine, which applies state-of-the art molecular profiling to diagnostic, prognostic, and therapeutic problems, has the potential to advance the care of WWE by precisely tailoring individualized management to each patient's needs. For example, antiseizure medications (ASMs) are among the most common teratogens prescribed to women of childbearing potential. Teratogens act in a dose-dependent manner on a susceptible genotype. However, the genotypes at risk for ASM-induced teratogenic deficits are unknown. Here we summarize current challenging issues for WWE, review the state-of-art tools for clinical precision medicine approaches, perform a systematic review of pharmacogenomic approaches in management for WWE, and discuss potential future directions in this field. We envision a future in which precision medicine enables a new practice style that puts focus on early detection, prediction, and targeted therapies for WWE.

Possible interplay between the theories of pharmacoresistant epilepsy

Epilepsy is one of the oldest known neurological disorders and is characterized by recurrent seizure activity. It has a high incidence rate, affecting a broad demographic in both developed and developing countries. Comorbid conditions are frequent in patients with epilepsy and have detrimental effects on their quality of life. Current management options for epilepsy include the use of anti-epileptic drugs, surgery, or a ketogenic diet. However, more than 30% of patients diagnosed with epilepsy exhibit drug resistance to anti-epileptic drugs. Further, surgery and ketogenic diets do little to alleviate the symptoms of patients with pharmacoresistant epilepsy. Thus, there is an urgent need to understand the underlying mechanisms of pharmacoresistant epilepsy to design newer and more effective anti-epileptic drugs. Several theories of pharmacoresistant epilepsy have been suggested over the years, the most common being the gene variant hypothesis, network hypothesis, multidrug transporter hypothesis, and target hypothesis. In our review, we discuss the main theories of pharmacoresistant epilepsy and highlight a possible interconnection between their mechanisms that could lead to the development of novel therapies for pharmacoresistant epilepsy.

Development and validation of a predictive model of drug-resistant genetic generalized epilepsy

OBJECTIVE

To develop and validate a clinical prediction model for antiepileptic drug (AED)-resistant genetic generalized epilepsy (GGE).

METHOD

We performed a case-control study of patients with and without drug-resistant GGE, nested within ongoing longitudinal observational studies of AED response at 2 tertiary epilepsy centers. Using a validation dataset, we tested the predictive performance of 3 candidate models, developed from a training dataset. We then tested the candidate models' predictive ability on an external testing dataset.

RESULTS

Of 5,189 patients in the ongoing longitudinal study, 121 met criteria for AED-resistant GGE and 468 met criteria for AED-responsive GGE. There were 66 patients with GGE in the external dataset, of whom 17 were cases. Catamenial epilepsy, history of a psychiatric condition, and seizure types were strongly related with drug-resistant GGE case status. Compared to women without catamenial epilepsy, women with catamenial epilepsy had about a fourfold increased risk for AED resistance. The calibration of 3 models, assessing the agreement between observed outcomes and predictions, was adequate. Discriminative ability, as measured with area under the receiver operating characteristic curve (AUC), ranged from 0.58 to 0.65.

CONCLUSION

Catamenial epilepsy, history of a psychiatric condition, and the seizure type combination of generalized tonic clonic, myoclonic, and absence seizures are negative prognostic factors of drug-resistant GGE. The AUC of 0.6 is not consistent with truly effective separation of the groups, suggesting other unmeasured variables may need to be considered in future studies to improve predictability.

Progesterone receptor ligands for the treatment of endometriosis: the mechanisms behind therapeutic success and failure

BACKGROUND

Despite intense research, it remains intriguing why hormonal therapies in general and progestins in particular sometimes fail in endometriosis.

OBJECTIVE AND RATIONALE

We review here the action mechanisms of progesterone receptor ligands in endometriosis, identify critical differences between the effects of progestins on normal endometrium and endometriosis and envisage pathways to escape drug resistance and improve the therapeutic response of endometriotic lesions to such treatments.

SEARCH METHODS

We performed a systematic Pubmed search covering articles published since 1958 about the use of progestins, estro-progestins and selective progesterone receptor modulators, to treat endometriosis and its related symptoms. Two reviewers screened the titles and abstracts to select articles for full-text assessment.

OUTCOMES

Progesterone receptor signalling leads to down-regulation of estrogen receptors and restrains local estradiol production through interference with aromatase and 17 beta-hydroxysteroid dehydrogenase type 1. Progestins inhibit cell proliferation, inflammation, neovascularisation and neurogenesis in endometriosis. However, progesterone receptor expression is reduced and disrupted in endometriotic lesions, with predominance of the less active isoform (PRA) over the full-length, active isoform (PRB), due to epigenetic abnormalities affecting the PGR gene transcription. Oxidative stress is another mechanism involved in progesterone resistance in endometriosis. Among the molecular targets of progesterone in the normal endometrium that resist progestin action in endometriotic cells are the nuclear transcription factor FOXO1, matrix metalloproteinases, the transmembrane gap junction protein connexin 43 and paracrine regulators of estradiol metabolism. Compared to other phenotypes, deep endometriosis appears to be more resistant to size regression upon medical treatments. Individual genetic characteristics can affect the bioavailability and pharmacodynamics of hormonal drugs used to treat endometriosis and, hence, explain part of the variability in the therapeutic response.

WIDER IMPLICATIONS

Medical treatment of endometriosis needs urgent innovation, which should start by deeper understanding of the disease core features and diverse phenotypes and idiosyncrasies, while moving from pure hormonal treatments to drug combinations or novel molecules capable of restoring the various homeostatic mechanisms disrupted by endometriotic lesions.

Pharmacogenomic Characterization in Bipolar Spectrum Disorders

The holistic approach of personalized medicine, merging clinical and molecular characteristics to tailor the diagnostic and therapeutic path to each individual, is steadily spreading in clinical practice. Psychiatric disorders represent one of the most difficult diagnostic challenges, given their frequent mixed nature and intrinsic variability, as in bipolar disorders and depression. Patients misdiagnosed as depressed are often initially prescribed serotonergic antidepressants, a treatment that can exacerbate a previously unrecognized bipolar condition. Thanks to the use of the patient's genomic profile, it is possible to recognize such risk and at the same time characterize specific genetic assets specifically associated with bipolar spectrum disorder, as well as with the individual response to the various therapeutic options. This provides the basis for molecular diagnosis and the definition of pharmacogenomic profiles, thus guiding therapeutic choices and allowing a safer and more effective use of psychotropic drugs. Here, we report the pharmacogenomics state of the art in bipolar disorders and suggest an algorithm for therapeutic regimen choice.

ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

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.

Implications of genetic variation of common Drug Metabolizing Enzymes and ABC Transporters among the Pakistani Population

Genetic polymorphism of drug metabolizing enzymes and transporters may influence drug response. The frequency varies substantially between ethnicities thus having implications on appropriate selection and dosage of various drugs in different populations. The distribution of genetic polymorphisms in healthy Pakistanis has so far not been described. In this study, 155 healthy adults (98 females) were included from all districts of Karachi. DNA was extracted from saliva and genotyped for relevant SNVs in CYP1A1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4 and CYP3A5 as well as ALDH3A1, GSTA1, ABCB1 and ABCC2. About 64% of the participants were born to parents who were unrelated to each other. There was generally a higher prevalence (p < 0.05) of variant alleles of CYP450 1A2, 2B6, 2C19, 3A5, ALDH3A1, GSTM1 as well as ABCB1 and ABCC2 in this study cohort than in other ethnicities reported in the HapMap database. In contrast, the prevalence of variant alleles was lower in GSTA1. Therefore, in the Pakistani population sample from Karachi a significantly different prevalence of variant drug metabolizing enzymes and ABC transporters was observed as compared to other ethnicities, which could have putative clinical consequences on drug efficacy and safety.

Pharmacogenomics in Asia: a systematic review on current trends and novel discoveries

While early pharmacogenomic studies have primarily been carried out in Western populations, there has been a notable increase in the number of Asian studies over the past decade. We systematically reviewed all pharmacogenomic studies conducted in Asia published before 2016 to highlight trends and identify research gaps in Asia. We observed that pharmacogenomic research in Asia was dominated by larger developed countries, notably Japan and Korea, and mainly driven by local researchers. Studies were focused on drugs acting on the CNS, chemotherapeutics and anticoagulants. Significantly, several novel pharmacogenomic associations have emerged from Asian studies. These developments are highly encouraging for the strength of regional scientific and clinical community and propound the importance of discovery studies in different populations.

Relationship between ABCB1 3435TT genotype and antiepileptic drugs resistance in Epilepsy: updated systematic review and meta-analysis

Background

Antiepileptic drugs (AEDs) are effective medications available for epilepsy. However, many patients do not respond to this treatment and become resistant. Genetic polymorphisms may be involved in the variation of AEDs response. Therefore, we conducted an updated systematic review and a meta-analysis to investigate the contribution of the genetic profile on epilepsy drug resistance.

Methods

We proceeded to the selection of eligible studies related to the associations of polymorphisms with resistance to AEDs therapy in epilepsy, published from January 1980 until November 2016, using Pubmed and Cochrane Library databases. The association analysis was based on pooled odds ratios (ORs) and 95% confidence intervals (CIs).

Results

From 640 articles, we retained 13 articles to evaluate the relationship between ATP-binding cassette sub-family C member 1 (ABCB1) C3435T polymorphism and AEDs responsiveness in a total of 454 epileptic AEDs-resistant cases and 282 AEDs-responsive cases. We found a significant association with an OR of 1.877, 95% CI 1.213–2.905. Subanalysis by genotype model showed a more significant association between the recessive model of ABCB1 C3435T polymorphism (TT vs. CC) and the risk of AEDs resistance with an OR of 2.375, 95% CI 1.775–3.178 than in the dominant one (CC vs. TT) with an OR of 1.686, 95% CI 0.877–3.242.

Conclusion

Our results indicate that ABCB1 C3435T polymorphism, especially TT genotype, plays an important role in refractory epilepsy. As genetic screening of this genotype may be useful to predict AEDs response before starting the treatment, further investigations should validate the association.

Pharmacogenomics in epilepsy

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Genetic variation can influence response to antiepileptic drug (AED) treatment through various effector processes.

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Metabolism of many AEDs is mediated by the cytochrome P450 (CYP) family; some of the CYPs have allelic variants that may affect serum AED concentrations.

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‘Precision medicine’ focuses on the identification of an underlying genetic aetiology allowing personalised therapeutic choices.

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Certain human leukocyte antigen, HLA, alleles are associated with an increased risk of idiosyncratic adverse drug reactions.

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New results are emerging from large-scale multinational efforts, likely imminently to add knowledge of value from a pharmacogenetic perspective.

There is high variability in the response to antiepileptic treatment across people with epilepsy. Genetic factors significantly contribute to such variability. Recent advances in the genetics and neurobiology of the epilepsies are establishing the basis for a new era in the treatment of epilepsy, focused on each individual and their specific epilepsy. Variation in response to antiepileptic drug treatment may arise from genetic variation in a range of gene categories, including genes affecting drug pharmacokinetics, and drug pharmacodynamics, but also genes held to actually cause the epilepsy itself.

From a purely pharmacogenetic perspective, there are few robust genetic findings with established evidence in epilepsy. Many findings are still controversial with anecdotal or less secure evidence and need further validation, e.g. variation in genes for transporter systems and antiepileptic drug targets. The increasing use of genetic sequencing and the results of large-scale collaborative projects may soon expand the established evidence.

Precision medicine treatments represent a growing area of interest, focussing on reversing or circumventing the pathophysiological effects of specific gene mutations. This could lead to a dramatic improvement of the effectiveness and safety of epilepsy treatments, by targeting the biological mechanisms responsible for epilepsy in each specific individual.

Whilst much has been written about epilepsy pharmacogenetics, there does now seem to be building momentum that promises to deliver results of use in clinic.

Genetic contribution of CYP1A1 variant on treatment outcome in epilepsy patients: a functional and interethnic perspective

CYP1A1 gene is involved in estrogen metabolism, and previously, we have reported association of variant rs2606345 with altered anti-epileptic drugs (AED) response in North Indian women with epilepsy (WWE). The present study aims to replicate the pharmacogenetic association, perform functional characterization and study its distribution within ethnically diverse Indian population. The variant was genotyped in 351 patients to assess the pharmacogenetic association and 552 healthy individuals belonging to 24 different ethnic groups to examine the distribution in Indian population. We observed significant overrepresentation of 'A' allele and 'AA' genotype in poor responders in WWE at Bonferroni-corrected significance levels. The recessive allele was found to lower the promoter activity by ~70-80% which was further substantiated by thermally less stable hairpin formed by it (ΔT_m=7 °C). Among all ethnic groups, west Indo-European (IE-W-LP2) subpopulation showed highest genotypic frequency of the variant making women from this community more prone to poor AED response. Our results indicate that rs2606345 influences drug response in WWE by lowering CYP1A1 expression.

Influence of single-nucleotide polymorphisms on deferasirox C trough levels and effectiveness

Deferasirox (DFX) is the only once-daily oral chelator for iron overload and its pharmacokinetic has been related with response to therapy. Our aim was to evaluate DFX plasma concentrations according to single-nucleotide polymorphisms in genes involved in its metabolism (UGT1A1, UGT1A3, CYP1A1, CYP1A2 and CYP2D6) and elimination (MRP2 and BCRP1). Further aim was to define a plasma concentration cutoff value predicting an adequate response to therapy. Plasma concentrations were determined at the end of dosing interval (C trough) using an high-performance liquid chromatography-ultraviolet method. Allelic discrimination was performed by real-time PCR. C trough levels were influenced by UGT1A1C>T rs887829, CYP1A1C>A rs2606345, CYP1A2A>C rs762551, CYP1A2C>T rs2470890 and MRP2G>A rs2273697 polymorphisms. A DFX plasma efficacy cutoff value of 20,000 ng ml(-1) was identified; CYP1A1C>A rs2606345 AA and CYP1A2C>T rs2470890 TT genotypes may predict this value, suggesting a negative predictive role in therapy efficacy. Our data suggest the feasibility of a pharmacogenetic-based DFX dose personalization.

Implications of pharmacogenetics for the therapeutic use of antiepileptic drugs

INTRODUCTION

Epilepsy is a chronic neurological disease manifesting as recurrent seizures. Despite the availability of numerous antiepileptic drugs (AEDs), one-third of the patients are not responsive to treatment. Such inter-individual variability in the response to AEDs may be partly explained by genetic differences. This review summarizes the pharmacogenetics (PGx) of AEDs. In addition, a model-based approach is presented that enables the integration of PGx data with other relevant sources of variability, such as demographic characteristics and co-medications.

AREAS COVERED

A comprehensive overview is provided of the data available in the literature on the evidence for correlations between genetic mutations and pharmacokinetic (PK) and/or pharmacodynamics (PD) of AEDs. This information is then used in an integrated manner in the second part, where PGx differences are parameterized as covariates in PK and PKPD models.

EXPERT OPINION

Polymorphisms are profuse in the PK and PD of AEDs. However, understanding of their clinical implication remains limited due to the lack of methodologies that discriminate the contribution of other sources of variability in CNS exposure to drugs. A model-based approach, in which other intrinsic (e.g., demographic covariates) and extrinsic (e.g., drug-drug interactions) factors are evaluated concurrently is needed to ensure optimization and individualization of treatment in epileptic patients.

Genetic association analysis of transporters identifies ABCC2 loci for seizure control in women with epilepsy on first-line antiepileptic drugs

OBJECTIVE

The ATP-binding cassette (ABC) superfamily of transporters is known to efflux antiepileptic drugs (AEDs) primarily in the brain, gastrointestinal tract, liver, and kidneys. In addition, they are also known to be involved in estrogen disposition and may modulate seizure susceptibility and drug response. The objective of the present study was to investigate the role of genetic variants from ABC transporters in seizure control in epilepsy patients treated with monotherapy of first-line AEDs for 12 months.

METHODS

On the basis of gene coverage and functional significance, a total of 98 single nucleotide polymorphisms from ABCB1, ABCC1, and ABCC2 were genotyped in 400 patients from North India. Of these, 216 patients were eligible for therapeutic assessment. Genetic variants were compared between the 'no-seizures' and the 'recurrent-seizures' groups. Bonferroni corrections for multiple comparisons and adjustment for covariates were performed before assessment of associations.

RESULTS

Functionally relevant promoter polymorphisms from ABCC2: c.-1549G>A and c.-1019A>G either considered alone or in haplotype and diplotype combinations were observed for a significant association with seizure control in women (odds ratio>3.5, P<10, power>95%). Further, low protein-expressing CGT and TGT (c.-24C>T, c.1249G>A, c.3972C>T) haplotypes were always observed to be present in combination with the AG (c.-1549G>A, c.-1019A>G) haplotype that was over-represented in women with 'no seizures'.

CONCLUSION

The distribution of the associated variants supports the involvement of ABCC2 in controlling seizures in women possibly by lowering of its expression. The biological basis of this finding could be an altered interaction of ABCC2 with AEDs and estrogens. These results necessitate replication in a larger pool of patients.

Pharmacogenomics and epilepsy: the road ahead

Epilepsy is one of the most common, serious neurological disorders, affecting an estimated 50 million people worldwide. The condition is typically treated using antiepileptic drugs of which there are 16 in widespread use. However, there are many different syndrome and seizure types within epilepsy and information guiding clinicians on the most effective drug and dose for individual patients is lacking. Further, all of the antiepileptic drugs have associated adverse reactions, some of which are severe and life-threatening. Here, we review the pharmacogenomic work to date in the context of these issues and comment on key aspects of study design that are required to speed up the identification of clinically relevant genetic factors.

Premenstrual dysphoric disorder in women with epilepsy: relationships to potential epileptic, antiepileptic drug, and reproductive endocrine factors

The purpose of this prospective observational investigation was to determine whether the frequency of premenstrual dysphoric disorder (PMDD) and the severity of PMDD symptoms differ between women with epilepsy and controls without epilepsy and whether there exists a relationship between the severity of PMDD symptoms and some epileptic, antiepileptic drug, and reproductive endocrine features. The results suggest that epilepsy, antiepileptic drug levels, ovulatory status, and hormone levels and ratios may all influence PMDD in women with epilepsy. PMDD severity scores may be greater in people with right-sided than in those with left-sided epilepsy, and in people with temporal than in those with nontemporal epileptic foci. PMDD severity scores may be greater with anovulatory cycles, and scores may correlate negatively with midluteal serum progesterone levels and positively with midluteal estradiol/progesterone ratios. Mood score may vary with particular antiepileptic drugs, favoring carbamazepine and lamotrigine over levetiracetam. PMDD severity scores may correlate directly with carbamazepine levels, whereas they correlate inversely with lamotrigine levels.

Genetic variability in estrogen disposition: Potential clinical implications for neuropsychiatric disorders

Variability in the physiological levels of neuroactive estrogens is widely believed to play a role in predisposition to several disorders of the central nervous system. Local biosynthesis of estrogens in the brain as well as their circulating serum levels are known to contribute to this pool of neuroactive steroids. It has been well accepted that estrogens modulate neuronal functions by affecting genesis, differentiation, excitability, and degeneration of nerve cells. These actions of estrogens appear to be more prominent in females with higher concentrations and marked variability of circulating serum levels occurring over a woman's lifetime. However, our knowledge regarding the variability of neuroactive steroid levels is very limited. Furthermore, several studies have recently reported differences in the synchronization of circulating and neuronal levels of estradiol. In the absence of reliable circulating steroid levels, knowledge of genetic variability in estrogen disposition may play a determining factor in predicting altered susceptibility or severity of neuropsychiatric disorders in women. Over the past decade, several genetic variants have been linked to both differential serum estrogen levels and predisposition to diverse types of neuropsychiatric disorders in women. Polymorphisms in genes encoding estrogen-metabolizing enzymes as well as estrogen receptors may account for this phenotypic variability. In this review, we attempt to show the contribution of genetics in determining estrogenicity in females with a particular emphasis on the central nervous system. This knowledge will further provide a driving force for unearthing the novel field of "Estrogen Pharmacogenomics." © 2010 Wiley-Liss, Inc.