SLCO5A1 and synaptic assembly genes contribute to impulsivity in juvenile myoclonic epilepsy.

Elevated impulsivity is a key component of attention-deficit hyperactivity disorder (ADHD), bipolar disorder and juvenile myoclonic epilepsy (JME). We performed a genome-wide association, colocalization, polygenic risk score, and pathway analysis of impulsivity in JME (n = 381). Results were followed up with functional characterisation using a drosophila model. We identified genome-wide associated SNPs at 8q13.3 (P = 7.5 × 10-9) and 10p11.21 (P = 3.6 × 10-8). The 8q13.3 locus colocalizes with SLCO5A1 expression quantitative trait loci in cerebral cortex (P = 9.5 × 10-3). SLCO5A1 codes for an organic anion transporter and upregulates synapse assembly/organisation genes. Pathway analysis demonstrates 12.7-fold enrichment for presynaptic membrane assembly genes (P = 0.0005) and 14.3-fold enrichment for presynaptic organisation genes (P = 0.0005) including NLGN1 and PTPRD. RNAi knockdown of Oatp30B, the Drosophila polypeptide with the highest homology to SLCO5A1, causes over-reactive startling behaviour (P = 8.7 × 10-3) and increased seizure-like events (P = 6.8 × 10-7). Polygenic risk score for ADHD genetically correlates with impulsivity scores in JME (P = 1.60 × 10-3). SLCO5A1 loss-of-function represents an impulsivity and seizure mechanism. Synaptic assembly genes may inform the aetiology of impulsivity in health and disease.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Lessons from the video-EEG telemetry unit.

Epilepsy is a clinical diagnosis, based primarily on patient and witness histories. Where there is diagnostic uncertainty or when epilepsy surgery is being considered, long-term video-EEG monitoring in a telemetry unit remains the gold standard investigation for diagnostic clarification or presurgical localisation. We present six illustrative cases, highlighting important points that emerged during video-EEG review including potential pitfalls in video-EEG interpretation, and how the investigation helped with diagnosis and subsequent management. The diagnostic process strongly emphasises seizure semiology, more so than EEG.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

An evaluation of the effectiveness of perampanel in people with epilepsy who have previously undergone resective surgery and/or implantation of a vagal nerve stimulator.

About 30% of people with epilepsy (PWE) are drug-resistant. Those with focal seizures may be suitable for epilepsy surgery. Those not amenable to resective surgery can be considered for vagus nerve stimulation (VNS). However, after operative procedures, around 50% of patients continue to experience seizures. A multi-center retrospective study assessing perampanel effectiveness and tolerability for PWE who have undergone surgical resection and/or VNS implantation was performed. The primary outcome was ≥50% reduction in seizure frequency while secondary outcomes included side effects (SEs), dose-related effectiveness, and toxicity. The median perampanel dose was 6 mg. Only one PWE became seizure free. A ≥50% decrease in seizure frequency was observed in 52.8% of the post-resection group and 16.9% of the VNS group (p < 0.001), while SEs were seen in 44.8% and 41.1%, respectively. Perampanel doses greater than 8 mg led to better response in both groups, especially in the post-VNS cohort. SEs were not dose-related and the safety profile was similar to previous observational studies. Perampanel can be beneficial in these two super-refractory epilepsy groups, particularly in PWE with seizures after surgical resection. Doses of more than 8 mg appear to be well tolerated and may be more effective than lower doses in PWE after surgical interventions.

Long-term outcomes after epilepsy surgery, a retrospective cohort study linking patient-reported outcomes and routine healthcare data.

OBJECTIVE: The objective of the study was to assess the long-term outcomes of epilepsy surgery between 1995 and 2015 in South Wales, UK, linking case note review, postal questionnaire, and routinely collected healthcare data. METHOD: We identified patients from a departmental database and collected outcome data from patient case notes, a postal questionnaire, and the QOLIE-31-P and linked with Welsh routinely collected data in the Secure Anonymised Information Linkage (SAIL) databank. RESULTS: Fifty-seven patients were included. Median age at surgery was 34 years (11-70), median: 24 years (2-56) after onset of habitual seizures. Median follow-up was 7 years (2-19). Twenty-eight (49%) patients were free from disabling seizures (Engel Class 1), 9 (16%) experienced rare disabling seizures (Class 2), 13 (23%) had worthwhile improvements (Class 3), and 7 (12%) had no improvement (Class 4). There was a 30% mean reduction in total antiepileptic drug (AED) load at five years postsurgery. Thirty-eight (66.7%) patients experienced tonic-clonic seizures presurgery verses 8 (14%) at last review. Seizure-free patients self-reported a greater overall quality of life (QOL; QOLIE-31-P) when compared with those not achieving seizure freedom. Seizure-free individuals scored a mean of 67.6/100 (100 is best), whereas those with continuing seizures scored 46.0/100 (p < 0.006). There was a significant decrease in the median rate of hospital admissions for any cause after epilepsy surgery (9.8 days per 1000 patient days before surgery compared with 3.9 after p < 0.005). SIGNIFICANCE: Epilepsy surgery was associated with significant improvements in seizures, a reduced AED load, and an improved QOL that closely correlated with seizure outcomes and reduced hospital admission rates following surgery. Despite this, there was a long delay from onset of habitual seizures to surgery. The importance of long-term follow-up is emphasized in terms of evolving medical needs and health and social care outcomes.

Chronic inflammatory demyelinating polyneuropathy: a rare cause of falls.

This case of chronic inflammatory demyelinating polyneuropathy (CIDP) shows that a patient's condition can evolve from the point of admission, gradually manifesting its underlying cause. Our patient's initial presentation of backpain and lower limb weakness prompted investigations which ruled out compressive myelopathy and neuropathy. As upper limb weakness developed later, along with a more proximal and symmetrical pattern of lower limb weakness, the clinical picture suggested polyneuropathy. The diagnosis of CIDP became apparent only after numerous negative tests and nerve conduction studies which identified demyelination. Diagnosing CIDP enabled the commencement of definitive treatment which led to a good recovery.

Current practice and recommendations in UK epilepsy monitoring units. Report of a national survey and workshop.

PURPOSE: Inpatient video-EEG monitoring (VEM) is an important investigation in patients with seizures or blackouts, and in the pre-surgical workup of patients with epilepsy. There has been an expansion in the number of Epilepsy Monitoring Units (EMU) in the UK offering VEM with a necessary increase in attention on quality and safety. Previous surveys have shown variation across centres on issues including consent and patient monitoring. METHOD: In an effort to bring together healthcare professionals in the UK managing patients on EMU, we conducted an online survey of current VEM practice and held a one-day workshop convened under the auspices of the British Chapter of the ILAE. The survey and workshop aimed to cover all aspects of VEM, including pre-admission, consent procedures, patient safety, drug reduction and reinstatement, seizure management, staffing levels, ictal testing and good data recording practice. RESULTS: This paper reports on the findings of the survey, the workshop presentations and workshop discussions. 32 centres took part in the survey and there were representatives from 22 centres at the workshop. There was variation in protocols, procedures and consent processes between units, and levels of observation of monitored patients. Nevertheless, the workshop discussion found broad areas of agreement on points. CONCLUSION: A survey and workshop of UK epilepsy monitoring units found that some variability in practice is inevitable due to different local arrangements and patient groups under investigation. However, there were areas of clear consensus particularly in relation to consent and patient safety that can be applied to most units and form a basis for setting minimum standards.

Non-invasive brain mapping in epilepsy: Applications from magnetoencephalography.

BACKGROUND: Non-invasive in vivo neurophysiological recordings with EEG/MEG are key to the diagnosis, classification, and further understanding of epilepsy. Historically the emphasis of these recordings has been the localisation of the putative sources of epileptic discharges. More recent developments see new techniques studying oscillatory dynamics, connectivity and network properties. NEW METHOD: New analysis strategies for whole head MEG include the development of spatial filters or beamformers for source localisation, time-frequency analysis for cortical dynamics and graph theory applications for connectivity. RESULTS: The idea of epilepsy as a network disorder is not new, and new applications of structural and functional brain imaging show differences in cortical and subcortical networks in patients with epilepsy compared to controls. Concepts of 'focal' and 'generalised' are challenged by evidence of focal onsets in generalised epileptic discharges, and widespread network changes in focal epilepsy. Spectral analyses can show differences in induced cortical response profiles, particularly in photosensitive epilepsy. COMPARISON WITH EXISTING METHOD: This review focuses on the application of MEG in the study of epilepsy, starting with a brief historical perspective, followed by novel applications of source localisation, time-frequency and connectivity analyses. CONCLUSION: Novel MEG analyses approaches show altered cortical dynamics and widespread network alterations in focal and generalised epilepsies, and identification of regional network abnormalities may have a role in epilepsy surgery evaluation.

Rarities in neurology: blue rubber bleb naevus syndrome.

A 62-year-old woman presented with stabbing pain over her left temple radiating to her left cheek when bending forwards or coughing. Neurological examination was normal. There were many cutaneous venous prominences over her body. CT and MR brain scans showed multiple venous anomalies and venous occlusive disease of the left sylvian fissure and superior sagittal sinus. We excluded arteriovenous malformation and dural fistulae with cerebral angiography. Following a clinical genetics assessment, we diagnosed blue rubber bleb naevus syndrome (BRBNS) and gave amitriptyline for her pain. There are only 200 cases of BRBNS in the literature, and central nervous system involvement is rarer still. The syndrome involves multiple cutaneous and visceral venous malformations. Most appear to be sporadic though a few have autosomal dominant inheritance. Although rare, BRBNS represents an important differential diagnosis for patients presenting with multiple and/or multisystem vascular malformations.

Translation of genetic findings to clinical practice in juvenile myoclonic epilepsy.

It has been estimated that JME (juvenile myoclonic epilepsy), when compared to other adult epilepsy syndromes, is most likely to have a genetic cause. However, decades of research have not brought us closer to finding a single 'JME gene' that is important on a population basis. Is this due in part to the genetic complexity of the syndrome, the cryptic nature of the genes of effect, or perhaps because JME is not one condition at all but many? Before we can begin to harness the power of next-generation sequencing techniques, we must first reduce JME down to lacunae of homogeneity--using increasingly more sophisticated phenotyping tools. The current technological advances in gene sequencing have been used to dramatic effect to identify single gene causes in rare syndromes and identify risk variants in malignancies. Filtering the variety of the human exome or genome down into a handful of biologically plausible candidates now relies on a pipeline of biostatistics, software, and functional analyses. It is simply unacceptable to return uncertain findings to the clinical domain and, therefore, it is crucial that pathogenicity is fully determined before families receive genetic counseling and test results.