There are several important relapsing demyelinating syndromes (RDS) that may present in childhood, of which paediatric-onset multiple sclerosis is the most common. These are rare conditions, so recognising presentations and referring early to specialist services is important to enable prompt diagnosis and effective treatment. Understanding of RDS is rapidly evolving, with many new and effective treatments that aim to reduce relapses and disability accumulation. A holistic and child-focused approach to management is key to supporting patients and families, with thought given to early detection of cognitive and psychological issues to provide appropriate support.
Abstract 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.
Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalized epilepsy in both ictal and interictal states. Here, we characterize differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. Ninety-five control EEGs were acquired from two independent studies [Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project]. We extracted frequency and functional network-based features from 10 to 20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. In addition, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2-5 Hz) (P = 0.0007, hedges' g = 0.55) and low-alpha (6-9 Hz) (P = 2.9 × 10-8, g = 0.80) frequency bands, peak alpha frequency (P = 0.000007, g = 0.66), functional network mean degree (P = 0.0006, g = 0.48) and brain network ictogenicity (P = 0.00006, g = 0.56) between epilepsy and controls. Since age (P = 0.009) and epoch length (P = 1.7 × 10-8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared with controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalized epilepsy particularly for their use as biomarkers.
Abstract Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.
Episodic ataxia type 2 (EA2) is an autosomal dominant calcium channelopathy caused by a mutation in the CACNA1A gene. Other variants in this gene can cause familial hemiplegic migraine and spinocerebellar ataxia type 6. EA2 is characterized by paroxysmal ataxia. Between attacks, more than 90% of patients exhibit nystagmus and oculomotor disturbances, whilst 50% of patients experience migraines. Episodes may respond to Acetazolamide or 4-aminopyridine. A persistent nystagmus in infancy or episodic vomiting in childhood usually does not trigger investigation for channelopathies. We present the case of a girl who presented with persistent nystagmus in late infancy and episodic vomiting in early childhood secondary to a new pathogenic variant in CACNA1A gene.
Case report
Patient presented with episodes of eye-rolling at 10 months of age. She had variable nystagmus and an abnormal head posture to compensate for the nystagmus. The rest of neurology examination, developmental history, EEG and MRI scan were normal. She was diagnosed with congenital idiopathic nystagmus and underwent a left inferior oblique recession, which showed some success. At the age of 4 years, she presented with episodic vomiting and lethargy every 4–6 weeks. Blood and urine tests excluded a metabolic disorder as a cause. Clinical diagnosis of migraine was made but episodes continued despite propranolol prophylaxis. Subsequently her mother disclosed family history of episodic events associated with migraine, ataxia and sickness in the girl's great-grandfather, grandfather and maternal uncle. The uncle had a genetic diagnosis of EA2. The girl had no ataxia during her vomiting episodes. Genetic testing identified a new variant in CACNA1A gene called CACNA1A: c.3565_3568delinsCTp.(Asn1189Leufs*27. She was diagnosed with EA2 and commenced on Acetazolamide, to which she responded well.
Discussion
Episodic events with autonomic or neurological features may be due to channelopathies. CACNA1A can produce features of migraine and ataxia. Ocular features like nystagmus have been reported to manifest before other clinical features. Attention to family history and gene testing helps in identifying such conditions with specific treatment options.
Medically unexplained or functional illnesses in children are associated with significant morbidity and healthcare costs due to delay in diagnosis and lack of bespoke services. Brighton and Hove CCG commissioned a 2 year pilot service for functional disorders in children based at the Royal Alexandra Children's Hospital, Brighton. Our one year experience highlights the challenges in service development and some key learning points.
Observations
Although initially commissioned as a chronic pain service, during the yearlong consultation process it was agreed that a wider service covering all forms of functional illnesses was necessary. The team consists of paediatrician, physiotherapist, psychologist, occupational therapist and administrator. Key challenges during service development included scarcity of published evidence around physical and psychological therapies in children and outcome measures for service evaluation. Deciding on thresholds for escalation of safeguarding and self harm concern was also challenging. These were overcome through evidence search and consultation with existing services. Weekly work involves triaging team meeting, clinics and therapy sessions. Therapy involves one to one and group physiotherapy and psychology as well as Yoga and mindfulness. The service is also launching a group session for psychoeducation on mind –body interaction. School liaison and home visits are also part of rehabilitative work. A total of 35 patients were seen. Medically unexplained chronic pain (25) was the commonest reason for referral. Non epileptic attacks (3), and other (7) functional illnesses were also seen. Other functional illnesses included medically unexplained visual loss, swallowing difficulties and functional paralysis. 42% of children had school attendance of 75% or lesser and 20% were unable to attend school because of their symptoms. In chronic pain patients there was a high incidence of diagnosed or undiagnosed learning difficulties (55%) like dyslexia (36%), sensory processing issues (27%) and social communication difficulties (18%). PedsQL™, RCADS, school attendance, patient/referrer feedback, primary and secondary care services utilisation will be the key outcome measures.
Conclusions
Our learning points in overcoming challenges in service set up will hopefully help aspiring services. Undiagnosed learning difficulties may well be a factor in the origin and perpetuation of functional illnesses along with other bio-psychosocial factors.
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