Characterizing bedside oculomotor deficits is a critical factor in defining the clinical presentation of hereditary ataxias. Quantitative assessments are increasingly available and have significant advantages, including comparability over time, reduced examiner dependency, and sensitivity to subtle changes. To delineate the potential of quantitative oculomotor assessments as digital-motor outcome measures for clinical trials in ataxia, we searched MEDLINE for articles reporting on quantitative eye movement recordings in genetically confirmed or suspected hereditary ataxias, asking which paradigms are most promising for capturing disease progression and treatment response. Eighty-nine manuscripts identified reported on 1541 patients, including spinocerebellar ataxias (SCA2, n = 421), SCA3 (n = 268), SCA6 (n = 117), other SCAs (n = 97), Friedreich ataxia (FRDA, n = 178), Niemann-Pick disease type C (NPC, n = 57), and ataxia-telangiectasia (n = 85) as largest cohorts. Whereas most studies reported discriminatory power of oculomotor assessments in diagnostics, few explored their value for monitoring genotype-specific disease progression (n = 2; SCA2) or treatment response (n = 8; SCA2, FRDA, NPC, ataxia-telangiectasia, episodic-ataxia 4). Oculomotor parameters correlated with disease severity measures including clinical scores (n = 18 studies (SARA: n = 9)), chronological measures (e.g., age, disease duration, time-to-symptom onset; n = 17), genetic stratification (n = 9), and imaging measures of atrophy (n = 5). Recurrent correlations across many ataxias (SCA2/3/17, FRDA, NPC) suggest saccadic eye movements as potentially generic quantitative oculomotor outcome. Recommendation of other paradigms was limited by the scarcity of cross-validating correlations, except saccadic intrusions (FRDA), pursuit eye movements (SCA17), and quantitative head-impulse testing (SCA3/6). This work aids in understanding the current knowledge of quantitative oculomotor parameters in hereditary ataxias, and identifies gaps for validation as potential trial outcome measures in specific ataxia genotypes.
- MeSH
- ataxie MeSH
- Friedreichova ataxie * MeSH
- genotyp MeSH
- lidé MeSH
- pohyby očí MeSH
- progrese nemoci MeSH
- spinocerebelární degenerace * MeSH
- teleangiektatická ataxie * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
INTRODUCTION: Wilson's disease (WD) is a potentially treatable, inherited disorder resulting from impaired copper metabolism. Pathological copper accumulation causes a range of symptoms, most commonly hepatic and a wide spectrum of neurological symptoms including tremor, dystonia, chorea, parkinsonism, dysphagia, dysarthria, gait and posture disturbances. To reduce copper overload, anti-copper drugs are used that improve liver function and neurological symptoms in up to 85% of patients. However, in some WD patients, treatment introduction leads to neurological deterioration, and in others, neurological symptoms persist with no improvement or improvement only after several years of treatment, severely affecting the patient's quality of life. AREAS COVERED: This review appraises the evidence on various pharmacological and non-pharmacological therapies, neurosurgical procedures and liver transplantation for the management of neurological WD symptoms. The authors also discuss the neurological symptoms of WD, causes of deterioration and present symptomatic treatment options. EXPERT OPINION: Based on case and series reports, current recommendations and expert opinion, WD treatment is focused mainly on drugs leading to negative copper body metabolism (chelators or zinc salts) and copper-restricted diet. Treatment of WD neurological symptoms should follow general recommendations of symptomatic treatment. Patients should be always considered individually, especially in the case of severe, disabling neurological symptoms.
Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.
- MeSH
- autoimunita genetika MeSH
- autoimunitní nemoci * epidemiologie genetika MeSH
- chřipka lidská * epidemiologie genetika MeSH
- lidé MeSH
- narkolepsie * chemicky indukované genetika MeSH
- vakcíny proti chřipce * škodlivé účinky MeSH
- virus chřipky A, podtyp H1N1 * genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
Purpose: Narcolepsy type-1 (NT1) is a rare chronic neurological sleep disorder with excessive daytime sleepiness (EDS) as usual first and cataplexy as pathognomonic symptom. Shortening the NT1 diagnostic delay is the key to reduce disease burden and related low quality of life. Here we investigated the changes of diagnostic delay over the diagnostic years (1990-2018) and the factors associated with the delay in Europe. Patients and Methods: We analyzed 580 NT1 patients (male: 325, female: 255) from 12 European countries using the European Narcolepsy Network database. We combined machine learning and linear mixed-effect regression to identify factors associated with the delay. Results: The mean age at EDS onset and diagnosis of our patients was 20.9±11.8 (mean ± standard deviation) and 30.5±14.9 years old, respectively. Their mean and median diagnostic delay was 9.7±11.5 and 5.3 (interquartile range: 1.7-13.2 years) years, respectively. We did not find significant differences in the diagnostic delay over years in either the whole dataset or in individual countries, although the delay showed significant differences in various countries. The number of patients with short (≤2-year) and long (≥13-year) diagnostic delay equally increased over decades, suggesting that subgroups of NT1 patients with variable disease progression may co-exist. Younger age at cataplexy onset, longer interval between EDS and cataplexy onsets, lower cataplexy frequency, shorter duration of irresistible daytime sleep, lower daytime REM sleep propensity, and being female are associated with longer diagnostic delay. Conclusion: Our findings contrast the results of previous studies reporting shorter delay over time which is confounded by calendar year, because they characterized the changes in diagnostic delay over the symptom onset year. Our study indicates that new strategies such as increasing media attention/awareness and developing new biomarkers are needed to better detect EDS, cataplexy, and changes of nocturnal sleep in narcolepsy, in order to shorten the diagnostic interval.
- Publikační typ
- časopisecké články MeSH
BACKGROUND AND OBJECTIVES: Recent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers. METHODS: We used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups. RESULTS: We included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters. DISCUSSION: Using a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features.
- MeSH
- idiopatická hypersomnie * diagnóza MeSH
- kataplexie * diagnóza MeSH
- lidé MeSH
- mladiství MeSH
- narkolepsie * diagnóza farmakoterapie MeSH
- poruchy nadměrné spavosti * diagnóza epidemiologie MeSH
- shluková analýza MeSH
- Check Tag
- lidé MeSH
- mladiství MeSH
- Publikační typ
- časopisecké články MeSH
- pozorovací studie MeSH
Increased incidence rates of narcolepsy type-1 (NT1) have been reported worldwide after the 2009-2010 H1N1 influenza pandemic (pH1N1). While some European countries found an association between the NT1 incidence increase and the H1N1 vaccination Pandemrix, reports from Asian countries suggested the H1N1 virus itself to be linked to the increased NT1 incidence. Using robust data-driven modeling approaches, that is, locally estimated scatterplot smoothing methods, we analyzed the number of de novo NT1 cases (n = 508) in the last two decades using the European Narcolepsy Network database. We confirmed the peak of NT1 incidence in 2010, that is, 2.54-fold (95% confidence interval [CI]: [2.11, 3.19]) increase in NT1 onset following 2009-2010 pH1N1. This peak in 2010 was found in both childhood NT1 (2.75-fold increase, 95% CI: [1.95, 4.69]) and adulthood NT1 (2.43-fold increase, 95% CI: [2.05, 2.97]). In addition, we identified a new peak in 2013 that is age-specific for children/adolescents (i.e. 2.09-fold increase, 95% CI: [1.52, 3.32]). Most of these children/adolescents were HLA DQB1*06:02 positive and showed a subacute disease onset consistent with an immune-mediated type of narcolepsy. The new 2013 incidence peak is likely not related to Pandemrix as it was not used after 2010. Our results suggest that the increased NT1 incidence after 2009-2010 pH1N1 is not unique and our study provides an opportunity to develop new hypotheses, for example, considering other (influenza) viruses or epidemiological events to further investigate the pathophysiology of immune-mediated narcolepsy.
- MeSH
- chřipka lidská * epidemiologie prevence a kontrola MeSH
- dítě MeSH
- dospělí MeSH
- incidence MeSH
- lidé MeSH
- mladiství MeSH
- narkolepsie * epidemiologie etiologie MeSH
- vakcinace MeSH
- vakcíny proti chřipce * MeSH
- virus chřipky A, podtyp H1N1 * MeSH
- Check Tag
- dítě MeSH
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Asie MeSH
- Evropa MeSH
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of poorly defined diseases with excessive daytime sleepiness as a core feature. Due to the considerable overlap of symptoms and the rarity of the diseases, it is difficult to identify distinct phenotypes of CH. Machine learning (ML) can help to identify phenotypes as it learns to recognize clinical features invisible for humans. Here we apply ML to data from the huge European Narcolepsy Network (EU-NN) that contains hundreds of mixed features of narcolepsy making it difficult to analyze with classical statistics. Stochastic gradient boosting, a supervised learning model with built-in feature selection, results in high performances in testing set. While cataplexy features are recognized as the most influential predictors, machine find additional features, e.g. mean rapid-eye-movement sleep latency of multiple sleep latency test contributes to classify NT1 and NT2 as confirmed by classical statistical analysis. Our results suggest ML can identify features of CH on machine scale from complex databases, thus providing 'ideas' and promising candidates for future diagnostic classifications.
- MeSH
- biologické modely * MeSH
- databáze faktografické statistika a číselné údaje MeSH
- datové soubory jako téma MeSH
- dospělí MeSH
- interpretace statistických dat MeSH
- lidé MeSH
- mladý dospělý MeSH
- narkolepsie klasifikace diagnóza patofyziologie MeSH
- polysomnografie statistika a číselné údaje MeSH
- řízené strojové učení * MeSH
- ROC křivka MeSH
- spánek REM fyziologie MeSH
- spánková latence fyziologie MeSH
- stochastické procesy MeSH
- vzácné nemoci klasifikace diagnóza patofyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Cíl: Zmapování závislosti na tabáku u osob s narkolepsií s kataplexií (NC), s narkolepsií bez kataplexie (N) a s idiopatickou hypersomnií (IH). Ověření hypotézy, že ve střední Evropě je prevalence kouření u NC proti N a IH vyšší. Soubor a metodika: Podle vlastního strukturovaného dotazníku jsme se ptali na kouření 172 dospělých pacientů, z toho 111 s NC, 37 N a 24 IH v průběhu ambulantního vyšetření nebo telefonického pohovoru. Výsledky: Pravidelnými kuřáky ve skupině NC je 46,8 % pacientů, ve skupině N 18,9 % pacientů a ve skupině IH 12,5 % pacientů. Zastoupení kuřáků ve skupině NC je významně vyšší oproti hodnotě 16,4 % kuřáků ve skupině N a IH dohromady (p = 0,0006; two-sided Fischer test). Závěr: Zastoupení kuřáků je u NC oproti běžné populaci více než dvojnásobné (prevalence aktivních denních kuřáků v České republice je 18 %) a je vyšší než u nemocných s N a IH dohromady.
Aim: To map the prevalence of smoking among patients with narcolepsy-cataplexy (NC), narcolepsy without cataplexy (N) and idiopathic hypersomnia (IH) and verify whether smoking prevalence in NC patients is higher than in N and IH patients in Central Europe. Methods: We asked 172 adult patients about smoking (111 of them with NC, 37 with N and 24 with IH) using our own structured questionnaire during their outpatient examination or during phone interview. Results: Daily smokers represented 46.8% in the NC group, 18.9% in N and 12.5% in the IH group. The prevalence of smoking in the N and IH group together is 16.4%, i.e. significantly lower than the prevalence in the NC group (p = 0.0006, two-sided Fisher test). Conclusion: The prevalence of daily smoking among patients with NC is more than twice as high as in the Czech general adult population (18%), and higher than smoking prevalence among N and IH patients together.
- MeSH
- dospělí MeSH
- idiopatická hypersomnie MeSH
- klinická studie jako téma MeSH
- kouření * MeSH
- lidé středního věku MeSH
- lidé MeSH
- narkolepsie * MeSH
- poruchy vyvolané užíváním tabáku MeSH
- prevalence MeSH
- průzkumy a dotazníky MeSH
- senioři nad 80 let MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- ženské pohlaví MeSH
Narcolepsy with cataplexy is a rare disease with an estimated prevalence of 0.02% in European populations. Narcolepsy shares many features of rare disorders, in particular the lack of awareness of the disease with serious consequences for healthcare supply. Similar to other rare diseases, only a few European countries have registered narcolepsy cases in databases of the International Classification of Diseases or in registries of the European health authorities. A promising approach to identify disease-specific adverse health effects and needs in healthcare delivery in the field of rare diseases is to establish a distributed expert network. A first and important step is to create a database that allows collection, storage and dissemination of data on narcolepsy in a comprehensive and systematic way. Here, the first prospective web-based European narcolepsy database hosted by the European Narcolepsy Network is introduced. The database structure, standardization of data acquisition and quality control procedures are described, and an overview provided of the first 1079 patients from 18 European specialized centres. Due to its standardization this continuously increasing data pool is most promising to provide a better insight into many unsolved aspects of narcolepsy and related disorders, including clear phenotype characterization of subtypes of narcolepsy, more precise epidemiological data and knowledge on the natural history of narcolepsy, expectations about treatment effects, identification of post-marketing medication side-effects, and will contribute to improve clinical trial designs and provide facilities to further develop phase III trials.
- MeSH
- databáze faktografické * normy MeSH
- dospělí MeSH
- fenotyp MeSH
- internet MeSH
- kataplexie farmakoterapie epidemiologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- narkolepsie * farmakoterapie epidemiologie MeSH
- postmarketingový dozor MeSH
- prospektivní studie MeSH
- registrace * normy MeSH
- řízení kvality MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- šíření informací MeSH
- vzácné nemoci farmakoterapie epidemiologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa epidemiologie MeSH
- Publikační typ
- abstrakt z konference MeSH
