[Incidence of sudden death in epilepsy (SUDEP): update and limitations]. / Inzidenz des plötzlichen Epilepsietodes (SUDEP): Update und Limitationen.

BACKGROUND: Sudden unexpected death in epilepsy (SUDEP) is in most cases probably due to a fatal complication of tonic-clonic seizures and plays a significant role in the premature mortality of individuals with epilepsy. The reported risks of SUDEP vary considerably depending on the study population, so that an up-dated systematic review of SUDEP incidence including most recent studies is required to improve the estimated SUDEP risk and the counseling of individuals with epilepsy. OBJECTIVE: To provide an overview of the current research landscape concerning SUDEP incidence across different patient populations and discuss potential conclusions and existing limitations. MATERIAL AND METHODS: A systematic literature review on SUDEP incidence was conducted in MEDLINE and EMBASE, supplemented by a manual search in June 2023. Out of a total of 3324 publications, 50 were reviewed for this study. RESULTS: The analyzed studies showed significant heterogeneity concerning cohorts, study design and data sources. Studies conducted without specific criteria and relying on comprehensive registers indicated an incidence of 0.78-1.2 per 1000 patient-years. Research providing incidences across various age groups predominantly show an increase with age, peaking in middle age. DISCUSSION: Due to varying methods of data collection and incidence calculation, comparing between studies is challenging. The association with age might be due to an underrepresentation of children, adolescents and patients over 60 years. CONCLUSION: Considering all age groups and types of epilepsy it is estimated that about 1 in 1000 individuals with epilepsy dies of SUDEP annually. With an assumed epilepsy prevalence of 0.6% in Germany, this could lead to more than one SUDEP case daily. Standardization of research methods is essential to gain more profound insights.

Proteomic analysis of the human hippocampus identifies neuronal pentraxin 1 (NPTX1) as synapto-axonal target in late-stage Parkinson's disease.

Parkinson's disease (PD) affects a significant proportion of the population over the age of 60 years, and its prevalence is increasing. While symptomatic treatment is available for motor symptoms of PD, non-motor complications such as dementia result in diminished life quality for patients and are far more difficult to treat. In this study, we analyzed PD-associated alterations in the hippocampus of PD patients, since this brain region is strongly affected by PD dementia. We focused on synapses, analyzing the proteome of post-mortal hippocampal tissue from 16 PD cases and 14 control subjects by mass spectrometry. Whole tissue lysates and synaptosomal fractions were analyzed in parallel. Differential analysis combined with bioinformatic network analyses identified neuronal pentraxin 1 (NPTX1) to be significantly dysregulated in PD and interacting with proteins of the synaptic compartment. Modulation of NPTX1 protein levels in primary hippocampal neuron cultures validated its role in synapse morphology. Our analysis suggests that NPTX1 contributes to synaptic pathology in late-stage PD and represents a putative target for novel therapeutic strategies.

Incidence, Prevalence, Hospitalization Rates, and Treatment Patterns in Myasthenia Gravis: A 10-Year Real-World Data Analysis of German Claims Data.

BACKGROUND: Myasthenia gravis (MG) is a rare chronic autoimmune disease caused by autoantibodies directed against postsynaptic antigens of the neuromuscular junction. Over the last decades, increasing incidence and prevalence rates have been reported. Epidemiological data on prevalence and incidence in Germany are lacking. Furthermore, the MG treatment landscape is rapidly changing due to the continued approval of novel monoclonal antibodies. METHOD: This is a retrospective study assessing incidence, prevalence, and hospitalization rates of MG as well as treatment patterns in Germany over 10 years based on medical claims data covering 6.1 million insured persons. RESULTS: Between 2011 and 2020, the prevalence rate of MG increased from 15.7 to 28.2 per 100,000 person-years. The age-adjusted incidence rate was 2.8 per 100,000 person-years within the study period (95% confidence interval, 2.43-3.22) and decreased dramatically in 2020, the year of the COVID-19 pandemic. Similarly, the hospitalization rate fluctuated within the study period but reached an overall low of 8.3% in 2020 (mean hospitalization rate 11.5%). Treatment patterns showed that most MG patients are treated with base therapy. However, crisis intervention is necessary for 2-5% of MG patients, and therapeutic monoclonal antibodies, including rituximab and eculizumab, are increasingly used. CONCLUSION: This is the first study on MG prevalence and incidence rates in Germany. Data show an increase in prevalence by 1.8-fold over 10 years. Decreasing incidence and hospitalization rates in 2020 hint at the impact of the COVID-19 pandemic. Treatment patterns in MG are changing with the advent of therapeutic monoclonal antibodies in this indication.

A decade of chronic lymphocytic leukaemia therapy in Germany: Real-world treatment patterns and outcomes (2010-2022).

Pharmacotherapy options for chronic lymphocytic leukaemia (CLL) have expanded significantly in recent years. These options include chemotherapy, chemoimmunotherapy and signalling pathway inhibitors. A notable shift in the treatment landscape began with the widespread adoption of ibrutinib in 2016. This analysis of claims data focuses on understanding how the use of novel therapies has evolved in clinical practice over the past decade in Germany. Anonymized claims data (2010-2022) from German statutory health insurance was used, covering patient demographics, treatments, and prescriptions. The study population included patients with two confirmed CLL diagnoses. Treatment patterns were analysed, and survival outcomes were compared using time-to-event analyses. In the analysed cohort of 2983 incident CLL patients, 1041 started first-line therapy between 2011 and 2022, with a median duration of 18 months from diagnosis to the first prescription. Chemoimmunotherapy, the predominant 1L therapy until 2019, decreased significantly, while targeted therapy usage increased from 3% in 2015 to 77% in 2022. Targeted therapies became dominant in patients receiving treatment for relapsed or refractory disease after 2016. Median treatment durations were: 122 days for chemo, 176 days for chemo-immuno, and 373 days for targeted therapy. The overall survival for patients diagnosed in or after 2016 was significantly better (hazard ratio 0.56, 95% confidence interval, 0.44-0.69)). The adoption of targeted therapies like ibrutinib and venetoclax has transformed CLL treatment in Germany, leading to improved patient outcomes. Additionally, we demonstrate successful adherence to evolving clinical guidelines.

Bias-invariant RNA-sequencing metadata annotation.

BACKGROUND: Recent technological advances have resulted in an unprecedented increase in publicly available biomedical data, yet the reuse of the data is often precluded by experimental bias and a lack of annotation depth and consistency. Missing annotations makes it impossible for researchers to find datasets specific to their needs. FINDINGS: Here, we investigate RNA-sequencing metadata prediction based on gene expression values. We present a deep-learning-based domain adaptation algorithm for the automatic annotation of RNA-sequencing metadata. We show, in multiple experiments, that our model is better at integrating heterogeneous training data compared with existing linear regression-based approaches, resulting in improved tissue type classification. By using a model architecture similar to Siamese networks, the algorithm can learn biases from datasets with few samples. CONCLUSION: Using our novel domain adaptation approach, we achieved metadata annotation accuracies up to 15.7% better than a previously published method. Using the best model, we provide a list of >10,000 novel tissue and sex label annotations for 8,495 unique SRA samples. Our approach has the potential to revive idle datasets by automated annotation making them more searchable.