Arif Shukralla

Seizure recurrence after antiepileptic drug withdrawal and the implications for driving: further results from the MRC Antiepileptic Drug Withdrawal Study and a systematic review

Background In the UK, patients with epilepsy in remission, who withdraw antiepileptic drug (AED) treatment, are advised not to drive during withdrawal and for 6 months thereafter, assuming the risk of recurrence in the next 12 months is below 20%. Those with a seizure recurrence currently have to be seizure-free for 12 months before returning to drive, whether treatment is restarted or not. New EU regulations recommend returning to driving 3 months after restarting treatment. Methods Regression modelling of data from the Medical Research Council AED withdrawal study was undertaken to estimate the risk of seizure recurrence in the next 12 months at various time points following: completion of drug withdrawal; AED reinstatement for those with a recurrence. A systematic review of prospective studies was also undertaken. Results Immediately following treatment withdrawal, the recurrence risk in the next 12 months was 30% (95% CI 25% to 35%) and at 3 months after withdrawal was 15% (95% CI 10% to 19%). At 3 months following the recommencement of treatment following a seizure recurrence, the risk of a seizure in the next 12 months was 26% (95% CI 17% to 35%), at 6 months 18% (95% CI 10% to 27%) and at 12 months 17% (95% CI 3% to 27%). Systematic review results were similar. Conclusion Current UK legislation concerning time off driving after withdrawing AED treatment may be too conservative. For those restarting treatment after a recurrence, current UK guidance may be too conservative but the new EU guidance too liberal.

Reporting of adverse events in randomised controlled trials of antiepileptic drugs using the CONSORT criteria for reporting harms

PURPOSE To assess the reporting of adverse events (AEs) in randomised controlled trials (RCTs) of antiepileptic drugs (AEDs) using the CONSORT statement for harms 2004, and to determine if reporting has changed since introduction of this standard. PRINCIPAL RESULTS One hundred and fifty two RCTs were included from a search of papers published between 1999 and 2008 inclusive. We identified 23 criteria in the CONSORT statements. The mean number of criteria met per trial was 11.3 (95%CI 10.6-12.0). Commercially funded studies met 12.6 and non-commercially funded met 9.4 (p<0.001). Trials recruiting adults met 12.5 and trials recruiting children met 9.3 (p<0.001). Trials published before 2004 met 11.6 and trials published after 2004 met 11.1 (p=0.53). Commercially funded trials met the majority of criteria more than non-commercially sponsored trials, particularly for definition of AEs (RR 3.15, CI 1.67-5.95) and the use of a validated dictionary of terms (RR 3.46, CI 1.41-8.44). Definitions for AEs (RR 2.32, CI 1.07-5.02) and details of analyses (RR 2.05, CI 1.01-4.15) were reported in adult trials more often than trials in children. MAJOR CONCLUSIONS Reporting of AEs in RCTs of AEDs is poor and has not improved since the publication of the CONSORT guidelines on the reporting of harms. Commercially funded trials were better reported than non-commercially funded trials and trials recruiting adults were better reported than trials recruiting children. These findings have serious implications as poor reporting precludes bias being detected and hinders adequate risk benefit analyses. Journal editors, authors and reviewers should be encouraged to follow current guidance.

Identifying the Biological Pathways Underlying Human Focal Epilepsy: From Complexity to Coherence to Centrality

Numerous diverse biological pathways are dysregulated in the epileptic focus. Which of these pathways are most critical in producing the biological abnormalities that lead to epilepsy? Answering this question is key to identifying the primary causes of epilepsy and for discovering new therapeutic strategies with greater efficacy than currently available antiepileptics (AEDs). We have performed the largest genome-wide transcriptomic analysis to date comparing epileptic with normal human hippocampi. We have identified 118 differentially expressed and, for the first time, differentially connected pathways in the epileptic focus. Using network mapping techniques, we have shown that these dysregulated pathways, though seemingly disparate, form a coherent interconnected central network. Using closeness centrality analysis, we have identified that the most influential hub pathways in this network are signalling through G protein-coupled receptors, in particular opioid receptors, and their downstream effectors PKA/CREB and DAG/IP3. Next, we have objectively demonstrated that genetic association of gene sets in independent genome-wide association studies (GWASs) can be used to identify causally relevant gene sets: we show that proven causal epilepsy genes, which cause familial Mendelian epilepsy syndromes, are associated in published sporadic epilepsy GWAS results. Using the same technique, we have shown that central pathways identified (opioid receptor and PKA/CREB and DAG/IP3 signalling pathways) are genetically associated with focal epilepsy and, hence, likely causal. Published functional studies in animal models provide evidence of a role for these pathways in epilepsy. Our work shows that these pathways play a central role in human focal epilepsy and that they are important currently unexploited antiepileptic drug targets.

Genetic regulation of gene expression in the epileptic human hippocampus

&NA; Epilepsy is a serious and common neurological disorder. Expression quantitative loci (eQTL) analysis is a vital aid for the identification and interpretation of disease‐risk loci. Many eQTLs operate in a tissue‐ and condition‐specific manner. We have performed the first genome‐wide cis‐eQTL analysis of human hippocampal tissue to include not only normal (n = 22) but also epileptic (n = 22) samples. We demonstrate that disease‐associated variants from an epilepsy GWAS meta‐analysis and a febrile seizures (FS) GWAS are significantly more enriched with epilepsy‐eQTLs than with normal hippocampal eQTLs from two larger independent published studies. In contrast, GWAS meta‐analyses of two other brain diseases associated with hippocampal pathology (Alzheimers disease and schizophrenia) are more enriched with normal hippocampal eQTLs than with epilepsy‐eQTLs. These observations suggest that an eQTL analysis that includes disease‐affected brain tissue is advantageous for detecting additional risk SNPs for the afflicting and closely related disorders, but not for distinct diseases affecting the same brain regions. We also show that epilepsy eQTLs are enriched within epilepsy‐causing genes: an epilepsy cis‐gene is significantly more likely to be a causal gene for a Mendelian epilepsy syndrome than to be a causal gene for another Mendelian disorder. Epilepsy cis‐genes, compared to normal hippocampal cis‐genes, are more enriched within epilepsy‐causing genes. Hence, we utilize the epilepsy eQTL data for the functional interpretation of epilepsy disease‐risk variants and, thereby, highlight novel potential causal genes for sporadic epilepsy. In conclusion, an epilepsy‐eQTL analysis is superior to normal hippocampal tissue eQTL analyses for identifying the variants and genes underlying epilepsy.

Comparing Drug Treatments in Epilepsy

The great majority of randomised controlled trials (RCTs) that compare antiepileptic drugs are industry sponsored and have the objective of obtaining a monotherapy license for a drug. Such trials do not inform everyday clinical practice as they tend to be too short and to depart from clinical practice by restricting clinicians in their choice of actions. The data that exists provides evidence that drugs with actions on voltage-gated sodium channels provide best seizure control for localised onset seizures and epilepsy syndromes, while valproate provides best seizure control for generalised epilepsy and unclassified syndromes. Drugs do, however, vary in their tolerability over the short term and in their risk for rare serious idiosyncratic adverse events, chronic toxicity and teratogenicity; issues that cannot be examined within the scope of RCTs.

Anti-epileptic drug harms: issues for meta-analysis

Objectives Decisions regarding choice and dose of anti-epileptic drug (AED) are driven by considering the potential benefits of reducing seizure frequency against the potential harms of alternative AEDs. Such decisions should be made using the best available evidence, which often requires a quantitative synthesis of data from multiple randomised controlled trials (RCT). However, the systematic review and meta-analysis of harms data is hindered by problems such as inadequate reporting, heterogeneity of harms definitions, and selective reporting bias. Here we will evaluate the quality of reporting of harms data in epilepsy trials, and assess the potential added value of incorporating harms data beyond the clinical indication of epilepsy.

An integrative in silico system for predicting dysregulated genes in the human epileptic focus: Application to SLC transporters.

Many different gene families are currently being investigated for their potential role in epilepsy and in the response to antiepileptic drugs. A common research challenge is identifying the members of a gene family that are most significantly dysregulated within the human epileptic focus, before taking them forward for resource‐intensive functional studies. Published data about transcriptomic changes within the human epileptic focus remains incomplete. A need exists for an accurate in silico system for the prediction of dysregulated genes within the epileptic focus. We present such a bioinformatic system. We demonstrate the validity of our approach by applying it to the solute carrier (SLC) gene family. There are >400 known SLCs. SLCs have never been systematically studied in epilepsy.

054 Can randomised controlled trial data from non-epilepsy indications be included in meta-analysis for AEDs used in epilepsy? An analysis of adverse event data

Aim To determine if adverse event (AE) outcomes from RCTs of AEDs across non-epilepsy indications (neuropathy & migraine) can be meta-analysed with data from epilepsy trials Method We searched for RCTs meeting inclusion criteria. AEDs included were topiramate, gabapentin, valproate, oxcarbazepine, lacosamide and others. Extracted data were analysed using RevMan 5.0. AEs analysed were; dizziness, ataxia, headache, fatigue, nausea, somnolence, AE withdrawals and any AE. Effect size summary statistics were calculated using the Mantel-Haenszel method. Statistical heterogeneity was assessed using a random effects model generating an I2 statistic. Results Hundred and six RCTs met inclusion criteria. When dizziness was analysed, test between indications showed no heterogeneity (I2=0%) for gabapentin, topiramate, lacosamide and lamotrigine. However, heterogeneity was significant (I2=59%) for oxcarbazepine. When fatigue was the AE outcome, there was no heterogeneity (I2=0%) when we analysed data for gabapentin, lamotrigine, lacosamide, oxcarbazepine and topiramate. When somnolence was the AE outcome, heterogeneity was insignificant for oxcarbazepine (I2=8%), lacosamide (I2=0%) and topiramate (I2=0%), but significant for gabapentin (I2=56%) and lamotrigine (I2=60%). In instances where there was significant heterogeneity, the size of relative risk was greater in the non-epilepsy indications Conclusion AEs of AEDs from non-epilepsy trials could be used in meta-analysis due to low statistical heterogeneity for some interventions and outcomes. Nevertheless this was not the case in all AEDs or outcomes. Effect sizes were larger in the non-epilepsy indications overall.