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For each biomarker, we quantified the relative contribution of each predictor to the variance explained by the model. We also compared the contribution between apolipoprotein E-ɛ4 carriers and non-carriers. We found that topological proximity to areas of maximal pathology through the functional connectome explained significant parts of variance for all Keywords: Alzheimer’s disease; pathology spreading; structural connectivity; functional connectivity; relative importance analysis Author: Salma Bougacha Creator: Servigistics Arbortext Advanced Print Publisher 11.1.4546/W-x64 Producer: PDFlib+PDI 9.0.7p3 (C++/Win64) CreationDate: Mon Jan 6 12:29:20 2025 CET ModDate: Mon Jan 6 14:28:22 2025 CET Custom Metadata: yes Metadata Stream: yes Tagged: yes UserProperties: no Suspects: no Form: AcroForm JavaScript: no Pages: 16 Encrypted: no Page size: 612.283 x 790.866 pts Page rot: 0 File size: 1481269 bytes Optimized: yes PDF version: 1.6 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- FSWZBG+TimesNewRomanPSMT CID TrueType Identity-H yes yes yes 1451 0 XAMNUX+GillSansMTStd-Medium Type 1C Custom yes yes yes 1454 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secfcae459-s2.1.1 Item: Title: Middle-aged healthy adults Destination: secfcae459-s2.1.2 Children: Item: Title: Cam-CAN dataset Destination: secfcae459-s2.1.2.1 Item: Title: IMAP dataset Destination: secfcae459-s2.1.2.2 Item: Title: Data preprocessing Destination: secfcae459-s2.2 Children: Item: Title: ADNI structural MRI and PET imaging preprocessing Destination: secfcae459-s2.2.1 Item: Title: Cam-CAN diffusion MRI preprocessing Destination: secfcae459-s2.2.2 Item: Title: IMAP functional MRI preprocessing Destination: secfcae459-s2.2.3 Item: Title: IMAP structural MRI preprocessing Destination: secfcae459-s2.2.4 Item: Title: Quantification of pathologies Destination: secfcae459-s2.3 Children: Item: Title: Determination of individual patients’ biomarkers patterns Destination: secfcae459-s2.3.1 Item: Title: Identification of brain maximal pathology sites Destination: secfcae459-s2.3.2 Item: Title: Determination of group-level regional biomarkers Destination: secfcae459-s2.3.3 Item: Title: Healthy middle-aged brain characteristics Destination: secfcae459-s2.4 Children: Item: Title: Structural connectome Destination: secfcae459-s2.4.1 Item: Title: Functional connectome Destination: secfcae459-s2.4.2 Item: Title: Inter-regional cortical distance network Destination: secfcae459-s2.4.3 Item: Title: Computation of pathologies predictors and confounding variables Destination: secfcae459-s2.5 Item: Title: Statistical analyses Destination: secfcae459-s2.6 Children: Item: Title: Cross-validated regression and relative importance analyses Destination: secfcae459-s2.6.1 Item: Title: Bootstrap confidence intervals Destination: secfcae459-s2.6.2 Item: Title: Comparison of relative contributions between APOE-ɛ4-positive and negative patients Destination: secfcae459-s2.6.3 Item: Title: Visualizations Destination: secfcae459-s2.7 Item: Title: Results Destination: secfcae459-s3 Children: Item: Title: Structural and functional topological descriptors showed partly distinct patterns Destination: secfcae459-s3.1 Item: Title: Structural and functional topological proximity to maximal pathology sites were weakly correlated Destination: secfcae459-s3.2 Item: Title: Connectivity patterns shaped Alzheimer’s disease through concurrent mechanisms Destination: secfcae459-s3.3 Item: Title: APOE-ɛ4 carriage affected contributions consistently across all biomarkers Destination: secfcae459-s3.4 Item: Title: Discussion Destination: secfcae459-s4 Item: Title: Supplementary material Destination: secfcae459-s5 Item: Title: Acknowledgements Destination: acknow Item: Title: Funding Destination: secfcae459-s6 Item: Title: Competing interests Destination: secfcae459-s7 Item: Title: Data availability Destination: secfcae459-s8 Item: Title: References Destination: reflist Filters: FilterPipeline: FlateDecode FilterPipeline: DCTDecode Images: Image: NisoImageMetadata: FormatName: image/jpg CompressionScheme: JPEG ImageWidth: 1000 ImageHeight: 1000 BitsPerSample: 8 BitsPerSampleUnit: 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pathologies Salma Bougacha Daniel Roquet Brigitte Landeau Elise Saul Mikaël Naveau Siya Sherif Alexandre Bejanin Marc Dhenain Ashish Raj Denis Vivien Gaël Chetelat for the Alzheimer’s Disease Neuroimaging Initiative DOI: 10.1093/braincomms/fcae459; Brain Communications, 7, 1, 2025-01-06.; Abstract: Four important imaging biomarkers of Alzheimer’s disease, namely grey matter atrophy, glucose hypometabolism and amyloid-β and tau deposition, follow stereotypical spatial distributions shaped by the brain network of structural and functional connections. In this case-control study, we combined several predictors reflecting various possible mechanisms of spreading through structural and functional pathways to predict the topography of the four biomarkers in amyloid-positive patients while controlling for the effect of spatial distance along the cortex. For each biomarker, we quantified the relative contribution of each predictor to the variance explained by the model. We also compared the contribution between apolipoprotein E-ɛ4 carriers and non-carriers. We found that topological proximity to areas of maximal pathology through the functional connectome explained significant parts of variance for all © The Author(s) 2025. Published by Oxford University Press on behalf of the Guarantors of Brain. Alzheimer’s disease pathology spreading structural connectivity functional connectivity relative importance analysis Journal Brain Communications © The Author(s) 2025. 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