Sehr geehrte Kolleginnen und Kollegen, zur Neurowoche 2026 begrüßen wir Sie im Namen der Deutschen Gesellschaft für Neuropathologie und Neuroanatomie herzlich. Die Neuropathologie hat ihr diagnostisches und wissenschaftliches Spektrum in den vergangenen Jahren deutlich erweitert. Molekulare Tumorklassifikation, Methylierungsdiagnostik, Hochdurchsatzsequenzierung und digitale, KI-gestützte Analyseverfahren sind heute fester Bestandteil unseres Faches und prägen zunehmend klinische Entscheidungen und wissenschaftliche Entwicklungen. Viele dieser Entwicklungen wurden in enger Zusammenarbeit mit den klinischen Neurofächern aufgebaut und weiterentwickelt. Dies betrifft nicht nur die Neuroonkologie, sondern ebenso neurodegenerative, entzündliche und neuromuskuläre Erkrankungen. Die Neuropathologie bewegt sich dabei an der Schnittstelle zwischen Forschung, Diagnostik und klinischer Anwendung. Der enge Austausch mit Neurologie, Neurochirurgie, Neuroradiologie, Neuropädiatrie und den weiteren neurowissenschaftlichen Disziplinen ist hierfür von zentraler Bedeutung. Gerade deshalb bietet die Neurowoche einen besonderen Rahmen. Sie ermöglicht den fachübergreifenden Austausch und schafft Raum für gemeinsame Diskussionen über neue wissenschaftliche Entwicklungen, diagnostische Konzepte und klinische Herausforderungen. Gerade die interdisziplinäre Zusammenarbeit innerhalb der Neurofächer ist eine wesentliche Voraussetzung, um translationale Entwicklungen in die klinische Anwendung zu überführen. Im neuropathologischen Programm erwarten Sie wissenschaftliche Sitzungen mit aktuellen Entwicklungen aus Diagnostik, translationaler Forschung und experimenteller Neurowissenschaft. Besonders wichtig ist uns dabei auch die Einbindung jüngerer Kolleginnen und Kollegen, die mit neuen wissenschaftlichen und methodischen Impulsen zur Weiterentwicklung unseres Faches beitragen. Wir freuen uns auf die Diskussionen und den persönlichen Austausch während der Neurowoche 2026. Mit besten Grüßen Prof. Dr. Till Acker Prof. Dr. Christian Mawrin DGNN-Kongresspräsidenten
Background: Alzheimer's disease drug development has produced a 99.6 percent failure rate for disease-modifying compounds (244 compounds tested 2002-2012, one regulatory approval; Cummings et al., 2014; Cummings, 2018)-the most sustained and costly therapeutic failure in the history of modern medicine. The field's standard explanation is that the biology is intractable. The present analysis offers a different and more instructive diagnosis: the failure was not primarily scientific. It was institutional. Objective: To characterize the structural and institutional forces that sustained investment in repeatedly ineffective mechanisms of action across 567 Phase 2 and Phase 3 Alzheimer's trials from 2010 to 2026, and to determine whether peer-reviewed alternative pathogenic frameworks were available at the time each major Go/No Go decision was made. Methods: Trials were identified from ClinicalTrials.gov using the following criteria: primary diagnosis of Alzheimer's disease or mild cognitive impairment attributed to Alzheimer's disease; Phase 2 or Phase 3; status of terminated or completed; primary completion date between January 1, 2010 and May 4, 2026. After exclusion of 70 trials not classifiable by mechanism of action, a final analytic dataset of 497 trials was classified by primary mechanism using the Common Alzheimer's Disease Research Ontology (CADRO). A temporal alignment analysis was conducted for the 12 largest trials by enrollment (N ≥ 1,300), mapping each trial's initiation date against the publication dates of peer-reviewed alternative mechanistic frameworks available at the time of trial launch. Results: Amyloid-targeting approaches accounted for approximately 31 percent of the 497 classified trials, nearly all of which failed to demonstrate clinical efficacy. Among the 12 largest trials, 11 targeted amyloid pathology and 10 were terminated for futility or lack of efficacy. All 12 trials were initiated after the publication in high-impact journals of peer-reviewed alternative frameworks, including the TREM2 neuroinflammation pathway, the antimicrobial protection hypothesis, the periodontitis-associated bacterial pathogenesis hypothesis, and the GLP-1 metabolic pathways. The post-2022 period revealed that genuinely novel non-amyloid mechanisms-TREM2 agonism, GLP-1 receptor stimulation, filamin A modulation, and progranulin/sortilin restoration-also failed to produce clinical benefit at scale despite confirmed target engagement. Three establishment forces are identified as operative causes: regulatory path dependency, institutional entrenchment within grant and editorial review panels, and shareholder-driven sunk-cost pressures. Conclusion: The 567-trial record constitutes a structural verdict on a model of drug development that was never designed to solve a problem of this complexity. The uniformity of negative results across all mechanism categories-amyloid, tau, neuroinflammation, metabolic, and synaptic-points toward deeper problems of disease definition, intervention timing, and endpoint validity that institutional and financial pressures have prevented the field from confronting. The Dominantly Inherited Alzheimer Network (DIAN) biomarker data demonstrates that pathology precedes symptoms by 15-25 years; the 2025 DIAN Trials Unit (DIAN-TU) extension provides the first evidence that treatment before symptom onset may delay dementia. Prevention trials in asymptomatic at-risk populations represent the only strategy the accumulated trial record has not yet refuted.
Background: DNA methylation profiling is a tool that provides key support for central nervous system (CNS) tumor classification. However, diagnostically ambiguous pediatric cases may result in discordant outputs across classifiers. We developed MAGIBU, a cross-platform, projection-based framework that embeds individual methylomes into a fixed CNS reference landscape, ranking diagnostic entities by local epigenetic proximity to support clinician-led integrative diagnosis. Methods: As a proof-of-concept, we evaluated MAGIBU in eight morphologically challenging pediatric/juvenile CNS tumors with unresolved diagnoses after institutional and central pathology review. To establish a benchmark in the absence of a definitive histopathological ground truth, a consensus epigenetic reference was defined a priori for cases showing concordant results between the Heidelberg CNS Tumor Methylation Classifier and Methylscape Analysis. Comparisons were also performed with Epigenomic Digital Pathology (EpiDiP). To validate MAGIBU beyond this discovery cohort, performance was assessed at the family level across the CNS methylation spectrum (n = 678, 28 methylation families), on non-array platforms (whole-genome bisulfite sequencing and Oxford Nanopore), and in a focused analysis of the low-grade glioma and diffuse midline glioma compartment across four independent cohorts (n = 670). Results: In the discovery cohort, MAGIBU achieved high concordance with the consensus reference (Cohen's κ = 0.855), outperforming EpiDiP (κ = 0.278), which frequently placed low-grade tumors in proximity to higher-grade reference regions. Conclusions: MAGIBU provides a stable, quantitative differential diagnosis framework that mitigates the limitations of rigid categorical assignments. By leveraging a distance-based proximity metric, it offers a transparent decision-support tool that integrates effectively with clinical, radiological, and molecular data. While performance is inherently dependent on reference atlas composition, MAGIBU represents a robust complementary approach for the diagnostic workup of ambiguous CNS tumors.
