BACKGROUND AND PURPOSE: The global burden of neurological diseases exceeds 43.1%, imposing a significant burden on patients, caregivers and society. This paper presents a roadmap to reduce this burden and improve brain health (BH) in Europe. METHODS: The roadmap is based on the European Academy of Neurology's (EAN) five-pillar BH strategy: advancing a global BH approach (P1), supporting policymaking (P2), fostering research (P3), promoting education (P4), and raising awareness of prevention and treatment (P5). It reviews current efforts, collaborations and future directions aligned with the WHO Intersectoral Global Action Plan (iGAP) for Neurological Disorders and suggests future initiatives and call for action. RESULTS: P1: Support WHO-iGAP through defined action points, international collaborations, in particular, the WHO BH Unit, and the EAN Brain Health Mission. P2: Collaborate with 48 national neurological societies to promote National Brain Plans (NBPs), addressing local needs, and improving access to care. P3: Advocate for more research funding; identify determinants of BH; develop preventive measures. P4: Provide educational opportunities for neurologists, public education programs, and advocacy training, including tools to educate the public. P5: Spearhead global awareness campaigns, organize public educational activities, and train BH advocates to contribute toward sustainable and long-term public health campaigns and policy engagement. CONCLUSIONS: The paper highlights the importance of a unified approach, integrating international collaborations and local initiatives, to improve BH outcomes based on the WHO-iGAP, and support sustainable development goals, in particular SDG 3: Good Health and Well-being and SDG 4: Quality Education.
BACKGROUND AND PURPOSE: Neurological disorders constitute a significant portion of the global disease burden, affecting >30% of the world's population. This prevalence poses a substantial threat to global health in the foreseeable future. A lack of awareness regarding this high burden of neurological diseases has led to their underrecognition, underappreciation, and insufficient funding. Establishing a strategic and comprehensive research agenda for brain-related studies is a crucial step towards aligning research objectives among all pertinent stakeholders and fostering greater societal awareness. METHODS: A scoping literature review was undertaken by a working group from the European Academy of Neurology (EAN) to identify any existing research agendas relevant to neurology. Additionally, a specialized survey was conducted among all EAN scientific panels, including neurologists and patients, inquiring about their perspectives on the current research priorities and gaps in neurology. RESULTS: The review revealed the absence of a unified, overarching brain research agenda. Existing research agendas predominantly focus on specialized topics within neurology, resulting in an imbalance in the number of agendas across subspecialties. The survey indicated a prioritization of neurological disorders and research gaps. CONCLUSIONS: Building upon the findings from the review and survey, key components for a strategic and comprehensive neurological research agenda in Europe were delineated. This research agenda serves as a valuable prioritization tool for neuroscientific researchers, as well as for clinicians, donors, and funding agencies in the field of neurology. It offers essential guidance for creating a roadmap for research and clinical advancement, ultimately leading to heightened awareness and reduced burden of neurological disorders.
- Klíčová slova
- Europe, neurological disorders, research agenda, research gaps, research priorities,
- MeSH
- globální zátěž nemocemi MeSH
- lidé MeSH
- nemoci nervového systému * epidemiologie terapie MeSH
- neurologie * MeSH
- výzkum MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa epidemiologie MeSH
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
- Názvy látek
- vakcíny proti chřipce * 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.
- Klíčová slova
- cataplexy, diagnostic delay, machine learning, misdiagnosis, symptom onset,
- Publikační typ
- časopisecké články MeSH
Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.
- Klíčová slova
- brain imaging, general data protection regulation, informed consent,
- MeSH
- informovaný souhlas pacienta * etika MeSH
- lidé MeSH
- mozek diagnostické zobrazování MeSH
- neurozobrazování * etika MeSH
- šíření informací * etika MeSH
- subjekty výzkumu * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- úvodníky 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.
- Klíčová slova
- H1N1 influenza, childhood narcolepsy, 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
- Názvy látek
- vakcíny proti chřipce * 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
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.
- Klíčová slova
- European Narcolepsy Centres, epidemiology, multicentre studies, narcolepsy, prospective data collection, standardized prospective database,
- 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
