Current classification of neurodegenerative diseases (ND) based on clinical phenotypes does not take into
account underlying disease heterogeneity, or overlapping disease mechanisms, thus hindering therapy development. Segregation and re-classification of ND phenotypes is urgently needed. From a therapeutic perspective, this should be based on causal and druggable factors that best target therapeutic approaches for complex NDs. BRAIN-MEND will reclassify existing phenotypic classifications using pathway and network analyses within and across complex NDs including Alzheimer Disease (AD), Parkinson Disease (PD),Amyotrophic Lateral Sclerosis (ALS), Frontotemporal Dementia (FTD), Corticobasal Degeneration (CBD), Multiple System Atrophy (MSA), and Progressive Supranuclear Palsy (PSP). We will use three innovative methods pioneered or adopted by the consortium: WP1 will use genetic data from many ND data sets
and apply the latest methodologies to identify causal genetic factors acting on molecular pathways, specifically distinguishing ; WP2 will analyse epigenetic data sets and apply cutting edge methods to identify epigenetic factors associated with molecular pathways of ND; and WP3 will identify drug targets from network analyses using
results from WP1 and WP2 without requiring prior knowledge of mechanism. WP4 will use analysis of medical literature and patient records to identify novel or under-recognized clusters of related clinical features. These complementary
approaches allow for iterative cross-validation of elucidated factors by WP1-4, followed by confirmation in new patient samples and cell models. BRAIN-MEND will reclassify ND phenotypes based on biologically meaningful categories corresponding to subgroups (heterogeneity)and common pathways (pleiotropy) to enhance disease understanding and
facilitate drug development across the entire complex ND landscape. WP5 will manage the project and disseminate results. Patients and caregivers will be intimately involved throughout the project for example by WP5 establishing an online platform that supports patients in tracing and contacting like-minded patients independent of their specific ND diagnosis, to also unlock the artificial barriers between NDs from a patient perspective. Our consortium is highly qualified to perform the work proposed, as evidenced by a mean PI h-index of 61, major impact in phenotypic and mechanistic research in
neurodegeneration and neuropsychiatry, direct expertise with and access to an unprecedented large and rich dataset spanning all complex NDs, track record in cross disorder analyses, and the related tools, biobanks and cell models needed