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The current state‐of‐the‐art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed‐computing‐based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t‐distributed neighborhood embedding (t‐SNE) model for dimensionality reduction and visualization of tumor classification results in two‐dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user‐friendly local data management and federated methylome‐based tumor classification calculations for multiple collaborators in a DataSHIELD environment. The freely accessible web interface supports convenient data upload, result review, and summary report generation. Importantly, increasing sample size as achieved through distributed access to additional datasets allows DistSNE to improve cluster analysis and enhance predictive power. Collectively, DistSNE enables a simple and fast classification of CNS tumors using large‐scale methylation data from distributed sources, while maintaining the privacy and allowing easy and flexible network expansion to other institutes. This approach holds great potential for advancing human brain tumor classification and fostering collaborative precision medicine in neuro‐oncology. [ABSTRACT FROM AUTHOR]

This article explores the distribution and composition of the ferritin complex in the adult brain and its connection to neuroferritinopathy (NF), a type of neurodegeneration with brain iron accumulation (NBIA). NF is characterized by symptoms like movement disturbances and tremors. The study identifies a novel variant in the ferritin heavy chain gene (FTH1) that is associated with NF and provides insights into the role of ferritin in both healthy and diseased brains. [Extracted from the article]