Risk-conferring HLA variants in an epilepsy cohort: benefits of multifaceted use of whole genome sequencing in clinical practice.

BACKGROUND: Whole genome sequencing is increasingly used in healthcare, particularly for diagnostics. However, its clinically multifaceted potential for individually customised diagnostic and therapeutic care remains largely unexploited. We used existing whole genome sequencing data to screen for pharmacogenomic risk factors related to antiseizure medication-induced cutaneous adverse drug reactions (cADRs), such as human leucocyte antigen HLA-B*15:02, HLA-A*31:01 variants. METHODS: Genotyping results, generated from the Genomics England UK 100 000 Genomes Project primarily for identification of disease-causing variants, were used to additionally screen for relevant HLA variants and other pharmacogenomic variants. Medical records were retrospectively reviewed for clinical and cADR phenotypes for HLA variant carriers. Descriptive statistics and the χ2 test were used to analyse phenotype/genotype data for HLA carriers and compare frequencies of additional pharmacogenomic variants between HLA carriers with and without cADRs, respectively. RESULTS: 1043 people with epilepsy were included. Four HLA-B*15:02 and 86 HLA-A*31:01 carriers were identified. One out of the four identified HLA-B*15:02 carriers had suffered antiseizure medication-induced cADRs; the point prevalence of cADRs was 16.9% for HLA-A*31:01 carriers of European origin (n=46) and 14.4% for HLA-A*31:01 carriers irrespective of ancestry (n=83). CONCLUSIONS: Comprehensive utilisation of genetic data spreads beyond the search for causal variants alone and can be extended to additional clinical benefits such as identifying pharmacogenomic biomarkers, which can guide pharmacotherapy for genetically-susceptible individuals.

Risk factors and outcome of hyperammonaemia in people with epilepsy.

BACKGROUND: Hyperammonaemia is a recognised complication of antiseizure treatment but risk factors leading to individual patient susceptibility and outcome remain unclear. OBJECTIVE: To identify risk factors for hyperammonaemia and investigate the impact of its management on clinical outcomes. METHODS: We carried out a retrospective observational study of adults with epilepsy who had ammonia tested over a 3-year period. Hyperammonaemia was defined as ammonia level > 35 µmol/L. Patients were classified into two groups: hyperammonaemic and non-hyperammonaemic. Association analyses and linear regression analysis were used to identify risk factors for hyperammonaemia. RESULTS: We reviewed 1002 ammonia requests in total and identified 76 people with epilepsy who had ammonia concentration measured, including 26 with repeated measurements. 59/76 (78%) were found to have hyperammonaemia. There was borderline statistical significance of hyperammonaemia being less common in patients with an established monogenic/metabolic condition than in those with structural or cryptogenic epilepsy (P = 0.05). Drug resistance, exposure to stiripentol and oxcarbazepine were identified as risk factors for hyperammonaemia. We found a dose-dependent association between valproate and hyperammonaemia (P = 0.033). Clinical symptoms were reported in 22/59 (37%) of the hyperammonaemic group. Improved clinical outcomes with concurrent decrease in ammonia concentration were seen in 60% of patients following treatment adjustment. CONCLUSIONS: Drug resistance and exposure to stiripentol, oxcarbazepine or high-dose valproate are associated with an increased risk of hyperammonaemia. Clinicians should consider symptoms related to hyperammonaemia in patients on high-dose valproate or multiple antiseizure treatments. Prompt identification of hyperammonaemia and subsequent treatment adjustments can lead to improved clinical outcomes.

Neurocraft: software for microscale brain network dynamics.

The brain operates at millisecond timescales but despite of that, the study of its functional networks is approached with time invariant methods. Equally, for a variety of brain conditions treatment is delivered with fixed temporal protocols unable to monitor and follow the rapid progression and therefore the cycles of a disease. To facilitate the understanding of brain network dynamics we developed Neurocraft, a user friendly software suite. Neurocraft features a highly novel signal processing engine fit for tracking evolving network states with superior time and frequency resolution. A variety of analytics like dynamic connectivity maps, force-directed representations and propagation models, allow for the highly selective investigation of transient pathophysiological dynamics. In addition, machine-learning tools enable the unsupervised investigation and selection of key network features at individual and group-levels. For proof of concept, we compared six seizure-free and non seizure-free focal epilepsy patients after resective surgery using Neurocraft. The network features were calculated using 50 intracranial electrodes on average during at least 120 epileptiform discharges lasting less than one second, per patient. Powerful network differences were detected in the pre-operative data of the two patient groups (effect size = 1.27), suggesting the predictive value of dynamic network features. More than one million patients are treated with cardiac and neuro modulation devices that are unable to track the hourly or daily changes in a subject's disease. Decoding the dynamics of transition from normal to abnormal states may be crucial in the understanding, tracking and treatment of neurological conditions. Neurocraft provides a user-friendly platform for the research of microscale brain dynamics and a stepping stone for the personalised device-based adaptive neuromodulation in real-time.

The Epidemiology of Neurological Complications in Adults With Sickle Cell Disease: A Retrospective Cohort Study.

Introduction: Risk factors for neurological complications in sickle cell disease differ in the adult and pediatric populations. Here, we focused on neurological complications in adults with sickle cell disease. Methods: Patients were selected using the audit data from the St George's Hospital Red Cell Database. The genotyping, demographics, clinical data, and investigation findings were collected. Results: A total of 303 patients were enrolled in the study: hemoglobin S homozygosity (HbSS) genotype 56%, hemoglobin S and C coinheritance (HbSC) genotype 35%, and hemoglobin S and ß-thalassemia coinheritance (HbSß) thalassemia genotype 9%; the mean age was 38.8 years (±13.5 SD) with 46% males. The most common neurological complication was cerebrovascular disease (n = 37, 12%) including those with ischemic stroke (10%), cerebral vasculopathy (3%), and intracranial hemorrhage (1%). Ischemic stroke was common among the HbSS genotype compared with other genotypes (8 vs. 1.6%, p = 0.001). Comparing the patients with sickle cell disease who had suffered a stroke to those who had not, there was a higher proportion of intracranial vasculopathy (p = 0.001, in particular, Moyamoya) and cognitive dysfunction (p < 0.0001). Conclusion: Our cohort supports previous reports that the most common neurological complication in adult sickle cell patients is cerebrovascular disease. Strategies to prevent cerebral vasculopathy and cognitive impairment should be explored.