Distinct molecular trajectories precede amyloid-β and tau pathology in Alzheimer’s disease

Distinct molecular trajectories precede amyloid-β and tau pathology in Alzheimer’s disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Brief Communication Distinct molecular trajectories precede amyloid-β and tau pathology in Alzheimer’s disease Marcel Woo, Seyyed Hosseini, Lukas Raich, Nesrine Rahmouni, Etienne Aumont, and 39 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8960775/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Alzheimer’s disease (AD) progresses over a prolonged preclinical phase marked by early amyloid-β pathology (Aβ), followed by tau spread and neurodegeneration. However, limited understanding of longitudinal, stage-specific molecular processes constrains therapeutic timing and patient stratification. Here, we reconstructed molecular trajectories across the AD continuum by integrating longitudinal cerebrospinal fluid (CSF) proteomics with Aβ and tau biomarkers from two independent cohorts. We identified distinct trajectories emerging prior to Aβ and tau conversion. Preclinical Aβ-dominated transitions were characterized by immune- and lipid-associated programs, whereas tau-dominated transitions at the mild cognitive impairment stage were linked to synaptic, proteostatic, and autophagy-related signatures. These stage-specific trajectories predicted biomarker conversion, including from the preclinical, pre-Aβ stage. Longitudinal voxelwise analyses further revealed spatially distinct cortical Aβ and tau patterns corresponding to inflammatory and proteostatic-synaptic signatures. Together, these findings define temporally ordered molecular pathways underlying AD progression and inform stage-specific therapeutic strategies. Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease Health sciences/Biomarkers/Predictive markers Biological sciences/Neuroscience/Neuroimmunology Figures Figure 1 Main text Alzheimer’s disease (AD) develops over decades, with pathological processes emerging before the onset of clinical symptoms 1 . Therapeutic strategies increasingly target early and preclinical stages 2 , yet treatment development remains constrained by an incomplete understanding of the longitudinal molecular dynamics that drive progression during these phases. Cross-sectional biomarker studies provide valuable snapshots of pathology 3 but are limited in their ability to resolve temporal ordering and transition dynamics of key biological processes, including inflammatory responses 4,5 , synaptic dysfunction 6 , and disturbances in proteasomal function 7,8 . These processes are thought to evolve sequentially over time, potentially defining stage-specific windows of vulnerability 9–13 and therapeutic opportunity. Longitudinal molecular profiling across the early AD continuum is therefore essential to delineate the natural progression of amyloid-β (Aβ) and tau-associated biology and to inform mechanism-guided intervention strategies. To characterize the molecular progression across the AD continuum, we anchored disease time to six clinically and biomarker-defined stages spanning (1) preclinical Aβ-negative (A−) cognitively unimpaired (CU) individuals who did not convert to Aβ-positivity (A+), (2) preclinical CU A− individuals who converted to A+, (3) CU A+ individuals, (4) A+ individuals with mild cognitive impairment (MCI), (5) A+ tau-positive (T+) individuals with MCI, and (6) A+T+ individuals with dementia. This framework was applied to cerebrospinal fluid (CSF) SomaScan proteomic data spanning 6094 proteins from two independent cohorts, comprising 526 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 316 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Longitudinal CSF proteomics were available for 114 TRIAD participants over a follow-up of 2-4 years, enabling within-person modelling of proteomic change (Demographics in Extended Data Tables 1-3 ). Disease stages were associated with the expected progression of established clinical, imaging, and fluid biomarkers, including cognitive decline, hippocampal atrophy, increasing Aβ and tau pathology measured by PET and CSF biomarkers ( Fig. 1a , Extended Data Fig. 1-2 ). This anchoring strategy enabled integration of cross-sectional and longitudinal proteomic data within a unified concatenated disease-time (CDT) framework ( Fig. 1b , Extended Data Fig. 3a ), allowing reconstruction of molecular transition trajectories across early and late AD stages. To identify temporal patterns of proteomic change, we performed unbiased clustering of protein trajectories across the CDT. This analysis identified four clusters with distinct temporal profiles ( Fig. 1c , Extended Data Fig. 3b-c ). While we detected inflammatory proteins like CD74, IL1B, and CLEC2D preceded Aβ-conversion, the largest proteomic changes were concentrated during the transition of A+T– into A+T+, whereas a pronounced reversal of change was observed during later stages with established dementia in A+T+ ( Extended Data Fig. 3d-e ). Functional enrichment analysis revealed that cluster 1, exhibiting steady decline, was associated with RNA processing and transcriptional regulation while the clusters that start to increase in CU A+ were associated with synaptic and stress-response pathways (cluster 2) or inflammation-related processes (cluster 3). Cluster 4 followed a bi-phasic trajectory without significant pathway enrichment, consistent with heterogeneous, mixed-direction biology limiting pathway-level coherence ( Extended Data Fig. 3f-i ). To disentangle Aβ and tau preceding molecular dynamics, we first identified proteins exhibiting significant longitudinal change across the full AD trajectory. For these proteins, we quantified stage-specific differences by comparing rates of change during the pre-Aβ stage (−5 to 0 years), the tau-conversion stage (0 to 10 years), and the period of clinical impairment (0 to 15 years). This framework enabled isolation of proteins showing preferential increases during Aβ-associated or tau-associated progression while remaining stable during the respective other stage, thereby capturing specific molecular changes that precede conversion to Aβ or tau positivity ( Fig. 1d , Extended Data Fig. 3j-k ). We observed a clear separation of molecular trajectories into Aβ-dominated and tau-dominated transition signatures ( Fig. 1e ). Proteins mostly increasing during the tau-conversion stage were associated with synaptic, proteasomal, redox and autophagic pathways, consistent with molecular programs causing tau spread and cognitive decline ( Fig. 1f-g ). Strikingly, proteins increasing during the Aβ conversion stage were enriched for immune- and lipid-associated processes and rose prior to the transition to Aβ positivity, revealing early inflammatory engagement during the preclinical phase of AD ( Fig. 1h ). Finally, we examined whether the stage-specific transition signatures captured biological processes that are already operative before biomarker-defined conversion. The elevated Aβ-transition signature was associated with a higher risk of conversion from A– to A+ ( Fig. 1i ), indicating that immune- and lipid-associated molecular programs precede Aβ conversion. Similarly, the increased tau-transition signature predicted progression from A+T– to A+T+ ( Fig. 1j ), demonstrating that synaptic, proteasomal, and autophagic pathways anticipate tau conversion rather than only emerge as a downstream consequence. Next, we assessed voxelwise associations of the Aβ and tau transition signatures with longitudinal Aβ and tau PET changes in ADNI and TRIAD. The Aβ-associated signature showed spatially distributed longitudinal associations with Aβ PET uptake, involving different cortical regions, consistent with widespread Aβ accumulation during preclinical disease stages ( Fig. 1k ). The tau-associated signature exhibited longitudinal associations with tau PET uptake in mesiotemporal, temporal pole and limbic regions implicated in early tau propagation ( Fig. 1l ). These findings demonstrate that distinct biological pathways are engaged prior to Aβ and tau conversion and that their molecular signatures predict biomarker conversion. Here, we combined longitudinal CSF proteomics with repeated clinical, imaging, and biomarker assessments across two independent cohorts to reconstruct molecular trajectories spanning the AD continuum. We identified a pronounced Aβ-associated tissue response that exhausted in later disease stages with established dementia. Immune- and lipid metabolism-associated pathways were engaged during the preclinical Aβ stage and even preceded Aβ conversion, in line with genetic and preclinical evidence implicating microglial lipid handling and innate immune signaling as central risk mechanisms in AD 14–17 . Synaptic, proteostatic, autophagic, and redox-related pathways rose during the A+T– stage and anticipated tau positivity and clinical impairment, supporting that proteasomal and autophagic dysfunction facilitate tau aggregation, propagation, and neuronal vulnerability 7,18,19 . These pathways can synergize with inflammatory signaling to promote synaptic failure, oxidative stress and neuronal loss 20,21 , providing a mechanistic framework linking proteostasis failure to neurodegeneration. By demonstrating that stage-specific molecular pathways are engaged before overt Aβ or tau positivity and predict subsequent disease transitions, this longitudinal framework supports a stage-informed approach to therapeutic targeting and patient stratification in AD. Declarations Acknowledgements We thank the study participants and the McGill Center for Studies in Aging staff. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. We thank the ADNI participants and their families who made this study possible. Funding This study was supported by the Canadian Institutes of Health Research (CIHR) [MOP-11-51-31; RFN 152985, 159815, 162303], Canadian Consortium of Neurodegeneration and Aging (CCNA; MOP-11-51-31 -team 1), Weston Brain Institute, the Alzheimer’s Association [NIRG-12-92090, NIRP-12-259245], Brain Canada Foundation (CFI Project 34874; 33397), and the Fonds de Recherche du Québec – Santé (FRQS; Chercheur Boursier, 2020-VICO-279314). A.C.M. is supported by the Mitacs Graduate Fellowship (IT27627), the Max E Binz Fellowship-Medicine (F225864C02) and the Grad Excellence Award in Neurology & Neurosurgery (M159875C51). M.S.W. is funded by the Corona Foundation (S0199/10110/2025), and German Research Foundation (WO 2835/1-1). H.Z. is a Wallenberg Scholar and a Distinguished Professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018 and #2019-02397), the European Union’s Horizon Europe research and innovation programme under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer's Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C), the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States (NEuroBioStand, #22HLT07), the Bluefield Project, Cure Alzheimer’s Fund, the Olav Thon Foundation, the Erling-Persson Family Foundation, Familjen Rönströms Stiftelse, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme – Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, the UK Dementia Research Institute at UCL (UKDRI-1003), and an anonymous donor. K.B. is supported by the Swedish Research Council (#2017-00915 and #2022-00732), the Swedish Alzheimer Foundation (#AF-930351, #AF-939721, #AF-968270, and #AF-994551), Hjärnfonden, Sweden (#ALZ2022-0006, #FO2024-0048-TK-130 and FO2024-0048-HK-24), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-965240 and #ALFGBG-1006418), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), the Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495), the Alzheimer’s Association 2022-2025 Grant (SG-23-1038904 QC), La Fondation Recherche Alzheimer (FRA), Paris, France, the Kirsten and Freddy Johansen Foundation, Copenhagen, Denmark, Familjen Rönströms Stiftelse, Stockholm, Sweden, and an anonymous philanthropist and donor. The funding sources had no participation in the design of the study, in the collection, analysis, and interpretation of data or in the manuscript writing. Competing interests M.S.W. received honoraria from Lilly for educational lectures outside the scope of this work. J.T. has served as a consultant for Neurotorium education, Alzheon Inc and Imagination AI, all outside of the scope of the present work. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZpath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Enigma, LabCorp, Merck Sharp & Dohme, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Quanterix, Red Abbey Labs, reMYND, Roche, Samumed, ScandiBio Therapeutics AB, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures sponsored by Alzecure, BioArctic, Biogen, Cellectricon, Fujirebio, LabCorp, Lilly, Novo Nordisk, Oy Medix Biochemica AB, Roche, and WebMD, is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, and is a shareholder of CERimmune Therapeutics (outside submitted work). K.B. has served as a consultant and at advisory boards for Abbvie, AC Immune, ALZPath, AriBio, Beckman-Coulter, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Neurimmune, Novartis, Ono Pharma, Prothena, Quanterix, Roche Diagnostics, Sanofi and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper. References Jack, C. R. et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup. Alzheimer’s Dement. 20 , 5143–5169 (2024). Courade, J.-P., Zetterberg, H., Höglinger, G. U. & Dewachter, I. The evolving landscape of Alzheimer’s disease therapy: From Aβ to tau. Cell 188 , 7337–7354 (2025). Zetterberg, H. & Bendlin, B. B. Biofluid biomarkers in Alzheimer’s disease and other neurodegenerative dementias. Nature 650 , 49–59 (2026). Pascoal, T. A. et al. Microglial activation and tau propagate jointly across Braak stages. Nat. Med. 27 , 1592–1599 (2021). Heneka, M. T. et al. Neuroinflammation in Alzheimer disease. Nat. Rev. Immunol. 25 , 321–352 (2025). Oh, H. S.-H. et al. A cerebrospinal fluid synaptic protein biomarker for prediction of cognitive resilience versus decline in Alzheimer’s disease. Nat. Med. (2025) doi:10.1038/s41591-025-03565-2. Myeku, N. et al. Tau-driven 26S proteasome impairment and cognitive dysfunction can be prevented early in disease by activating cAMP-PKA signaling. Nat. Med. 22 , 46–53 (2016). Maniv, I. et al. Altered ubiquitin signaling induces Alzheimer’s disease-like hallmarks in a three-dimensional human neural cell culture model. Nat. Commun. 14 , 5922 (2023). Ali, M. et al. Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum. Neuron 113 , 1363-1379.e9 (2025). Tijms, B. M. et al. Cerebrospinal fluid proteomics in patients with Alzheimer’s disease reveals five molecular subtypes with distinct genetic risk profiles. Nat. Aging 4 , 33–47 (2024). Afshar, S. et al. Plasma proteomic associations with Alzheimer’s disease endophenotypes. Nat. Aging 5 , 2104–2124 (2025). Woo, M. S. et al. Glia inflammation and cell death pathways drive disease progression in preclinical and early AD. EMBO Mol. Med. 17 , 3064–3079 (2025). Tijms, B. et al. Defining the natural history of Alzheimer’s disease by longitudinal cerebrospinal fluid proteomics. at https://doi.org/10.21203/rs.3.rs-8544834/v1 (2026). Bellenguez, C. et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nat. Genet. 54 , 412–436 (2022). Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628 , 154–161 (2024). Yin, Z. et al. APOE4 impairs the microglial response in Alzheimer’s disease by inducing TGFβ-mediated checkpoints. Nat. Immunol. 24 , 1839–1853 (2023). Venegas, C. et al. Microglia-derived ASC specks cross-seed amyloid-β in Alzheimer’s disease. Nature 552 , 355–361 (2017). Zhang, Z.-Y. et al. TRIM11 protects against tauopathies and is down-regulated in Alzheimer’s disease. Science (80-. ). 381 , (2023). Samelson, A. J. et al. CRISPR screens in iPSC-derived neurons reveal principles of tau proteostasis. Cell (2026) doi:10.1016/j.cell.2025.12.038. Lorenz, S. M. et al. A fin-loop-like structure in GPX4 underlies neuroprotection from ferroptosis. Cell (2025) doi:10.1016/j.cell.2025.11.014. Woo, M. S. et al. The immunoproteasome disturbs neuronal metabolism and drives neurodegeneration in multiple sclerosis. Cell 188 , 4567-4585.e32 (2025). Additional Declarations Yes there is potential Competing Interest. M.S.W. received honoraria from Lilly for educational lectures outside the scope of this work. J.T. has served as a consultant for Neurotorium education, Alzheon Inc and Imagination AI, all outside of the scope of the present work. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZpath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Enigma, LabCorp, Merck Sharp & Dohme, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Quanterix, Red Abbey Labs, reMYND, Roche, Samumed, ScandiBio Therapeutics AB, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures sponsored by Alzecure, BioArctic, Biogen, Cellectricon, Fujirebio, LabCorp, Lilly, Novo Nordisk, Oy Medix Biochemica AB, Roche, and WebMD, is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, and is a shareholder of CERimmune Therapeutics (outside submitted work). K.B. has served as a consultant and at advisory boards for Abbvie, AC Immune, ALZPath, AriBio, Beckman-Coulter, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Neurimmune, Novartis, Ono Pharma, Prothena, Quanterix, Roche Diagnostics, Sanofi and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper. Supplementary Files 04ExtendedDataTable4.xlsx Extended Data Table 4 04ExtendedDataTable5.xlsx Extended Data Table 5 04ExtendedDataTable6.xlsx Extended Data Table 6 ExtendedData.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8960775","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Brief Communication","associatedPublications":[],"authors":[{"id":597107785,"identity":"b10109ac-c185-4000-be27-120f719c0ad1","order_by":0,"name":"Marcel Woo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAlElEQVRIiWNgGAWjYNCCCgYDIGlAipYzJGthbCNFi24Dj+GDj/MOG/MzMG98QJQWswM8xoYztx02k2xgKybOGrMDvNukebcdtjE4wGMmQYKWOYdt7A/wmP8gQUvDYTMDBh4zonQwmB3m/2w441i6scRhtmIiHXa8LfHBhxprw/725o0fiLOGGYMxCkbBKBgFo4ByAABlDCmchiLp3AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-1306-2708","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":true,"prefix":"","firstName":"Marcel","middleName":"","lastName":"Woo","suffix":""},{"id":597107786,"identity":"5ede7a29-8c86-421e-88d6-96450c917885","order_by":1,"name":"Seyyed Hosseini","email":"","orcid":"https://orcid.org/0000-0001-7542-7541","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Seyyed","middleName":"","lastName":"Hosseini","suffix":""},{"id":597107787,"identity":"7d855747-c218-472b-ab45-f6fab28c3470","order_by":2,"name":"Lukas Raich","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Lukas","middleName":"","lastName":"Raich","suffix":""},{"id":597107788,"identity":"42125dc3-0347-4997-88bc-1bf26fc44fbe","order_by":3,"name":"Nesrine Rahmouni","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Nesrine","middleName":"","lastName":"Rahmouni","suffix":""},{"id":597107789,"identity":"77ad053a-cfb8-4aa0-85a2-590ea40a6505","order_by":4,"name":"Etienne Aumont","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Etienne","middleName":"","lastName":"Aumont","suffix":""},{"id":597107790,"identity":"254fda18-c499-4aef-9e65-11feaecb0918","order_by":5,"name":"Arthur Macedo","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Arthur","middleName":"","lastName":"Macedo","suffix":""},{"id":597107791,"identity":"c0904195-1085-495d-b8a1-bc2f5f75b5c0","order_by":6,"name":"Stijn Servaes","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Stijn","middleName":"","lastName":"Servaes","suffix":""},{"id":597107792,"identity":"7b0a178e-05d4-48cc-8383-fbb7f6cb74a8","order_by":7,"name":"Brandon Hall","email":"","orcid":"https://orcid.org/0009-0007-4578-2033","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Brandon","middleName":"","lastName":"Hall","suffix":""},{"id":597107793,"identity":"648c658e-2a3a-4752-bf44-cc2f2264c988","order_by":8,"name":"Aurelie Lebrun","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Aurelie","middleName":"","lastName":"Lebrun","suffix":""},{"id":597107794,"identity":"ee7bb74c-cb1c-470e-94e5-a19d732d3350","order_by":9,"name":"Gleb Bezgin","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Gleb","middleName":"","lastName":"Bezgin","suffix":""},{"id":597107795,"identity":"0ad01712-44e8-467b-b7fe-136c7d6b64b1","order_by":10,"name":"Tevy Chan","email":"","orcid":"https://orcid.org/0009-0001-9134-5949","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Tevy","middleName":"","lastName":"Chan","suffix":""},{"id":597107796,"identity":"cd742861-1e52-43b9-bef9-c15146e88238","order_by":11,"name":"Cecile Tissot","email":"","orcid":"https://orcid.org/0000-0003-2711-3833","institution":"Lawrence Berkeley National Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Cecile","middleName":"","lastName":"Tissot","suffix":""},{"id":597107797,"identity":"238424e3-d6f5-4dcd-92e7-ba3cc37861da","order_by":12,"name":"Jaime Fernandez-Arias","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Jaime","middleName":"","lastName":"Fernandez-Arias","suffix":""},{"id":597107798,"identity":"717db83a-9ed6-4418-b0ea-d70abd4e1aa4","order_by":13,"name":"Kely Quispialaya-Socualaya","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Kely","middleName":"","lastName":"Quispialaya-Socualaya","suffix":""},{"id":597107799,"identity":"9e7c9035-e877-4502-87f2-7dc404565354","order_by":14,"name":"Yansheng Zheng","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Yansheng","middleName":"","lastName":"Zheng","suffix":""},{"id":597107800,"identity":"be1a44b8-aab1-47cc-abe1-7128faa2a22b","order_by":15,"name":"Delphine Oliva-Lopez","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Delphine","middleName":"","lastName":"Oliva-Lopez","suffix":""},{"id":597107801,"identity":"bfa663dc-432c-46c1-97f9-cd84c910054b","order_by":16,"name":"Stuart Mitchell","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Stuart","middleName":"","lastName":"Mitchell","suffix":""},{"id":597107802,"identity":"bddf0392-e6d9-4ba9-8aab-416f2fc152a4","order_by":17,"name":"Gabriela Baldasso","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Gabriela","middleName":"","lastName":"Baldasso","suffix":""},{"id":597107803,"identity":"be57fa07-34fe-47d4-abb5-99890ad75969","order_by":18,"name":"Rodrigo Paes","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"","lastName":"Paes","suffix":""},{"id":597107804,"identity":"b86c940e-eed6-416e-9bec-4b8808d35c50","order_by":19,"name":"Juliana Beker Goday","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Juliana","middleName":"Beker","lastName":"Goday","suffix":""},{"id":597107805,"identity":"993f05c8-616f-4791-b718-ca8d83f574c3","order_by":20,"name":"Marina Goncalves","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Goncalves","suffix":""},{"id":597107806,"identity":"0a80c515-4843-40f7-8670-ad9d39a3f5af","order_by":21,"name":"Jenna Stevenson","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Jenna","middleName":"","lastName":"Stevenson","suffix":""},{"id":597107807,"identity":"2861a153-a84c-4ccb-8aa0-50574f4de511","order_by":22,"name":"Robert Hopewell","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Hopewell","suffix":""},{"id":597107808,"identity":"a73a28a0-b992-4720-84bb-9048c7fc55b3","order_by":23,"name":"Lydia Trudel","email":"","orcid":"https://orcid.org/0009-0002-5593-7717","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Lydia","middleName":"","lastName":"Trudel","suffix":""},{"id":597107809,"identity":"a31a6362-43cc-4fe8-b53c-ff764a900c81","order_by":24,"name":"Joseph Therriault Therriault","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"Therriault","lastName":"Therriault","suffix":""},{"id":597107810,"identity":"b05bb5b2-eeee-44cf-b526-16dc64fef254","order_by":25,"name":"Ilaria Pola","email":"","orcid":"","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Ilaria","middleName":"","lastName":"Pola","suffix":""},{"id":597107811,"identity":"de923954-9383-44f0-b162-3150327bcdd9","order_by":26,"name":"Vladimir Fonov","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Vladimir","middleName":"","lastName":"Fonov","suffix":""},{"id":597107812,"identity":"17a72a28-dc05-492f-aac7-077e0444822f","order_by":27,"name":"Firoza Lussier","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Firoza","middleName":"","lastName":"Lussier","suffix":""},{"id":597107813,"identity":"bc5d360b-2823-4d14-bd51-c84e48255897","order_by":28,"name":"Tammo Potthast","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Tammo","middleName":"","lastName":"Potthast","suffix":""},{"id":597107814,"identity":"720dec7f-ff6d-4d41-945c-b81339bfa128","order_by":29,"name":"Eckhard Schlemm","email":"","orcid":"https://orcid.org/0000-0002-5729-2935","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Eckhard","middleName":"","lastName":"Schlemm","suffix":""},{"id":597107815,"identity":"74d22304-7f52-4f55-b959-68f0547b6679","order_by":30,"name":"Tim Magnus","email":"","orcid":"https://orcid.org/0000-0001-6232-9555","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Magnus","suffix":""},{"id":597107816,"identity":"754c37e8-53e9-404b-88b8-0ad416bb76a4","order_by":31,"name":"Goetz Thomalla","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Goetz","middleName":"","lastName":"Thomalla","suffix":""},{"id":597107817,"identity":"6772e75a-1f0d-4e5f-aec7-ec25a766f191","order_by":32,"name":"Markus Glatzel","email":"","orcid":"https://orcid.org/0000-0002-7720-8817","institution":"University Medical Center Hamburg-Eppendorf, Hamburg","correspondingAuthor":false,"prefix":"","firstName":"Markus","middleName":"","lastName":"Glatzel","suffix":""},{"id":597107818,"identity":"02da01c3-8845-4d03-a0c1-7066c3ea84a9","order_by":33,"name":"Gassan Massarweh","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Gassan","middleName":"","lastName":"Massarweh","suffix":""},{"id":597107819,"identity":"dc6c298e-d45f-4ac6-8506-cec33a13c1f1","order_by":34,"name":"Paolo Vitali","email":"","orcid":"https://orcid.org/0000-0001-8953-1542","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Paolo","middleName":"","lastName":"Vitali","suffix":""},{"id":597107820,"identity":"29111917-9c88-4d29-a3c0-7f6099aa7164","order_by":35,"name":"Jean-Paul Soucy","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Jean-Paul","middleName":"","lastName":"Soucy","suffix":""},{"id":597107821,"identity":"857595ea-1c69-465b-9574-b4a124c4f6ce","order_by":36,"name":"Serge Gauthier","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Serge","middleName":"","lastName":"Gauthier","suffix":""},{"id":597107822,"identity":"09e2ca95-427b-4eab-b432-ee113d7018a8","order_by":37,"name":"Andréa Benedet","email":"","orcid":"","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Andréa","middleName":"","lastName":"Benedet","suffix":""},{"id":597107823,"identity":"2ae5d785-585f-4553-b97d-3e52a0c6ca1d","order_by":38,"name":"Yasser Iturria-Medina","email":"","orcid":"https://orcid.org/0000-0002-9345-0347","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Yasser","middleName":"","lastName":"Iturria-Medina","suffix":""},{"id":597107824,"identity":"d294305e-5f35-4014-b490-ee58b15e434b","order_by":39,"name":"Kaj Blennow","email":"","orcid":"https://orcid.org/0000-0002-1890-4193","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Kaj","middleName":"","lastName":"Blennow","suffix":""},{"id":597107825,"identity":"1e114873-9c21-4d59-b508-c2270a195544","order_by":40,"name":"Tharick Pascoal","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Tharick","middleName":"","lastName":"Pascoal","suffix":""},{"id":597107826,"identity":"9390b219-b9b5-4372-bddd-82ec60f183ce","order_by":41,"name":"Henrik Zetterberg","email":"","orcid":"https://orcid.org/0000-0003-3930-4354","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Henrik","middleName":"","lastName":"Zetterberg","suffix":""},{"id":597107827,"identity":"b643ea26-58f2-4617-bff8-fa7be80bdcce","order_by":42,"name":"Pedro Rosa-Neto","email":"","orcid":"https://orcid.org/0000-0001-9116-1376","institution":"McGill Univeristy","correspondingAuthor":false,"prefix":"","firstName":"Pedro","middleName":"","lastName":"Rosa-Neto","suffix":""},{"id":597107828,"identity":"efcc1a01-9637-4dda-b46f-bd308b43a915","order_by":43,"name":"Ludivine Chamard-Witkowski","email":"","orcid":"https://orcid.org/0000-0002-2676-6392","institution":"McGill Univeristy","correspondingAuthor":false,"prefix":"","firstName":"Ludivine","middleName":"","lastName":"Chamard-Witkowski","suffix":""}],"badges":[],"createdAt":"2026-02-24 20:05:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8960775/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8960775/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103602310,"identity":"b9cf1a01-813a-4375-a9d8-a79ca8b78832","added_by":"auto","created_at":"2026-02-27 14:12:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":333920,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct amyloid-β and tau dominated molecular transition programs shape Alzheimer’s disease progression. \u003c/strong\u003e(a) Longitudinal neocortical amyloid-β accumulation measured by [\u003csup\u003e18\u003c/sup\u003eF]AZD4694 positron emission tomography (PET), and temporal meta-ROI tau-accumulation measured by [\u003csup\u003e18\u003c/sup\u003eF]MK6240 PET in six clinically and biomarker-defined stages spanning the Alzheimer’s disease (AD) continuum in TRIAD: cognitively unimpaired (CU) Aβ -negative (A−) non-converters (n = 69), CU A− converters to Aβ-positivity (A+; n = 4), CU A+ (n = 11), A+ with mild cognitive impairment (MCI; \u003cem\u003en\u003c/em\u003e = 12), A+ tau-positive (T+) with MCI (\u003cem\u003en\u003c/em\u003e = 10), and A+T+ dementia (\u003cem\u003en\u003c/em\u003e = 10). Concatenated disease time (CDT) was generated by integrating the longitudinal with cross-sectional measurements from TRIAD (\u003cem\u003en\u003c/em\u003e = 316) and ADNI (\u003cem\u003en\u003c/em\u003e = 526) across the six stages.\u003cstrong\u003e \u003c/strong\u003e(b) Neocortical [\u003csup\u003e18\u003c/sup\u003eF]AZD4694 PET and [\u003csup\u003e18\u003c/sup\u003eF]MK6240 PET in Braak stages I/II, III/IV and V/VI of TRIAD participants across the CDT. (c) Temporal protein clusters of 1367 (of 6094) CSF proteins measured by SomaScan in TRIAD and ADNI that showed a significant overall change across the CDT.\u003cstrong\u003e \u003c/strong\u003e(d) Identification of proteins that were associated with Aβ-transition (CDT -5 years to 0 years), and tau transition (CDT 0 years to 10 years). Proteins that were exclusively associated with Aβ or tau (Δpredicted value \u0026gt; 0.2) but not with the other pathology (Δpredicted value \u0026lt; -0.2) are labeled. (e) Heatmap of top 10 proteins with the strongest positive change during the Aβ transition (CDT -5 to 0 years), tau transition (CDT 0 to 10 years), and clinical transition (CDT 0 to 15 years), top 10 proteins with the strongest negative change in the clinical transition phase.\u003cstrong\u003e \u003c/strong\u003e(f-h) Gene ontology analysis of the top 50 proteins selectively associated with tau conversion (f), top 50 proteins associated with clinical progression (g), top 50 proteins selectively associated with Aβ conversion (h).\u003cstrong\u003e \u003c/strong\u003e(i-j) Kaplan-Meier survival analyses depicting time to conversion stratified by Aβ-transition (i) or tau-transition (j) signature scores (top tertile vs. rest). Aβ-transition signatures were tested in A– for conversion to A+, and tau-transition signatures in A+T– for conversion to A+T+. \u003cem\u003eP\u003c/em\u003e-values were calculated using log-rank tests. k-l) Voxelwise analyses of Aβ transition signature with longitudinal Aβ-PET (k; TRIAD, \u003cem\u003en\u003c/em\u003e = 117; ADNI, \u003cem\u003en\u003c/em\u003e = 198) change and the tau transition signature with longitudinal tau-PET change (l; TRIAD, \u003cem\u003en\u003c/em\u003e = 117; ADNI, \u003cem\u003en\u003c/em\u003e = 43).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/10fa41c7cd71dca1199b3866.png"},{"id":106401682,"identity":"4b642e0c-c9e5-4bcf-a11f-da7e07a989c3","added_by":"auto","created_at":"2026-04-08 09:09:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1149566,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/11e399bd-bba8-4685-a95f-6461fd583b11.pdf"},{"id":103602312,"identity":"eae46ee3-ffe2-48db-a8e4-18f8915894d2","added_by":"auto","created_at":"2026-02-27 14:12:54","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64608,"visible":true,"origin":"","legend":"Extended Data Table 4","description":"","filename":"04ExtendedDataTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/991a53220cd5ec571a33cf83.xlsx"},{"id":103602309,"identity":"9f79ac34-c663-4c79-af03-24bac106b183","added_by":"auto","created_at":"2026-02-27 14:12:54","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13930,"visible":true,"origin":"","legend":"Extended Data Table 5","description":"","filename":"04ExtendedDataTable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/b3a79d76abcbcd86df28e1f6.xlsx"},{"id":103602307,"identity":"b9307ae6-1bef-47d3-ad70-38f6224ee0b8","added_by":"auto","created_at":"2026-02-27 14:12:54","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":46043,"visible":true,"origin":"","legend":"Extended Data Table 6","description":"","filename":"04ExtendedDataTable6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/111af08b673aa05ff8e1158e.xlsx"},{"id":103602313,"identity":"4b344db5-dfe3-4193-b8eb-2fd4f224e9a4","added_by":"auto","created_at":"2026-02-27 14:12:54","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":980280,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendedData.docx","url":"https://assets-eu.researchsquare.com/files/rs-8960775/v1/6b0e72c3444953988c7be141.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nM.S.W. received honoraria from Lilly for educational lectures outside the scope of this work. J.T. has served as a consultant for Neurotorium education, Alzheon Inc and Imagination AI, all outside of the scope of the present work. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZpath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Enigma, LabCorp, Merck Sharp \u0026 Dohme, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Quanterix, Red Abbey Labs, reMYND, Roche, Samumed, ScandiBio Therapeutics AB, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures sponsored by Alzecure, BioArctic, Biogen, Cellectricon, Fujirebio, LabCorp, Lilly, Novo Nordisk, Oy Medix Biochemica AB, Roche, and WebMD, is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, and is a shareholder of CERimmune Therapeutics (outside submitted work). K.B. has served as a consultant and at advisory boards for Abbvie, AC Immune, ALZPath, AriBio, Beckman-Coulter, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Neurimmune, Novartis, Ono Pharma, Prothena, Quanterix, Roche Diagnostics, Sanofi and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper.","formattedTitle":"Distinct molecular trajectories precede amyloid-β and tau pathology in Alzheimer’s disease","fulltext":[{"header":"Main text","content":"\u003cp\u003eAlzheimer\u0026rsquo;s disease (AD) develops over decades, with pathological processes emerging before the onset of clinical symptoms\u003csup\u003e1\u003c/sup\u003e. Therapeutic strategies increasingly target early and preclinical stages\u003csup\u003e2\u003c/sup\u003e, yet treatment development remains constrained by an incomplete understanding of the longitudinal molecular dynamics that drive progression during these phases. Cross-sectional biomarker studies provide valuable snapshots of pathology\u003csup\u003e3\u003c/sup\u003e but are limited in their ability to resolve temporal ordering and transition dynamics of key biological processes, including inflammatory responses\u003csup\u003e4,5\u003c/sup\u003e, synaptic dysfunction\u003csup\u003e6\u003c/sup\u003e, and disturbances in proteasomal function\u003csup\u003e7,8\u003c/sup\u003e. These processes are thought to evolve sequentially over time, potentially defining stage-specific windows of vulnerability\u003csup\u003e9\u0026ndash;13\u003c/sup\u003e and therapeutic opportunity. Longitudinal molecular profiling across the early AD continuum is therefore essential to delineate the natural progression of amyloid-\u0026beta; (A\u0026beta;) and tau-associated biology and to inform mechanism-guided intervention strategies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo characterize the molecular progression across the AD continuum, we anchored disease time to six clinically and biomarker-defined stages spanning (1) preclinical A\u0026beta;-negative (A\u0026minus;) cognitively unimpaired (CU) individuals who did not convert to A\u0026beta;-positivity (A+), (2) preclinical CU A\u0026minus; individuals who converted to A+, (3) CU A+ individuals, (4) A+ individuals with mild cognitive impairment (MCI), (5) A+ tau-positive (T+) individuals with MCI, and (6) A+T+ individuals with dementia. This framework was applied to cerebrospinal fluid (CSF) SomaScan proteomic data spanning 6094 proteins from two independent cohorts, comprising 526 participants from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) and 316 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Longitudinal CSF proteomics were available for 114 TRIAD participants over a follow-up of 2-4 years, enabling within-person modelling of proteomic change (Demographics in \u003cstrong\u003eExtended Data Tables 1-3\u003c/strong\u003e). Disease stages were associated with the expected progression of established clinical, imaging, and fluid biomarkers, including cognitive decline, hippocampal atrophy, increasing A\u0026beta; and tau pathology measured by PET and CSF biomarkers (\u003cstrong\u003eFig. 1a\u003c/strong\u003e, \u003cstrong\u003eExtended Data Fig. 1-2\u003c/strong\u003e). This anchoring strategy enabled integration of cross-sectional and longitudinal proteomic data within a unified concatenated disease-time (CDT) framework (\u003cstrong\u003eFig. 1b\u003c/strong\u003e, \u003cstrong\u003eExtended Data Fig. 3a\u003c/strong\u003e), allowing reconstruction of molecular transition trajectories across early and late AD stages.\u003c/p\u003e\n\u003cp\u003eTo identify temporal patterns of proteomic change, we performed unbiased clustering of protein trajectories across the CDT. This analysis identified four clusters with distinct temporal profiles (\u003cstrong\u003eFig. 1c\u003c/strong\u003e, \u003cstrong\u003eExtended Data Fig. 3b-c\u003c/strong\u003e). While we detected inflammatory proteins like CD74, IL1B, and CLEC2D preceded A\u0026beta;-conversion, the largest proteomic changes were concentrated during the transition of A+T\u0026ndash; into A+T+, whereas a pronounced reversal of change was observed during later stages with established dementia in A+T+ (\u003cstrong\u003eExtended Data Fig. 3d-e\u003c/strong\u003e). Functional enrichment analysis revealed that cluster 1, exhibiting steady decline, was associated with RNA processing and transcriptional regulation while the clusters that start to increase in CU A+ were associated with synaptic and stress-response pathways (cluster 2) or inflammation-related processes (cluster 3). Cluster 4 followed a bi-phasic trajectory without significant pathway enrichment, consistent with heterogeneous, mixed-direction biology limiting pathway-level coherence (\u003cstrong\u003eExtended Data Fig. 3f-i\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTo disentangle A\u0026beta; and tau preceding molecular dynamics, we first identified proteins exhibiting significant longitudinal change across the full AD trajectory. For these proteins, we quantified stage-specific differences by comparing rates of change during the pre-A\u0026beta; stage (\u0026minus;5 to 0 years), the tau-conversion stage (0 to 10 years), and the period of clinical impairment (0 to 15 years). This framework enabled isolation of proteins showing preferential increases during A\u0026beta;-associated or tau-associated progression while remaining stable during the respective other stage, thereby capturing specific molecular changes that precede conversion to A\u0026beta; or tau positivity (\u003cstrong\u003eFig. 1d\u003c/strong\u003e, \u003cstrong\u003eExtended Data Fig. 3j-k\u003c/strong\u003e). We observed a clear separation of molecular trajectories into A\u0026beta;-dominated and tau-dominated transition signatures (\u003cstrong\u003eFig. 1e\u003c/strong\u003e). Proteins mostly increasing during the tau-conversion stage were associated with synaptic, proteasomal, redox and autophagic pathways, consistent with molecular programs\u0026nbsp;causing tau\u0026nbsp;spread and cognitive decline (\u003cstrong\u003eFig. 1f-g\u003c/strong\u003e). Strikingly, proteins increasing during the A\u0026beta; conversion stage were enriched for immune- and lipid-associated processes and rose prior to the transition to A\u0026beta; positivity, revealing early inflammatory engagement during the preclinical phase of AD (\u003cstrong\u003eFig. 1h\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Finally, we examined whether the stage-specific transition signatures captured biological processes that are already operative before biomarker-defined conversion. The elevated A\u0026beta;-transition signature was associated with a higher risk of conversion from A\u0026ndash; to A+ (\u003cstrong\u003eFig. 1i\u003c/strong\u003e), indicating that immune- and lipid-associated molecular programs precede A\u0026beta; conversion. Similarly, the increased tau-transition signature predicted progression from A+T\u0026ndash; to A+T+ (\u003cstrong\u003eFig. 1j\u003c/strong\u003e), demonstrating that synaptic, proteasomal, and autophagic pathways anticipate tau conversion rather than only emerge as a downstream consequence. Next, we assessed voxelwise associations of the A\u0026beta; and tau transition signatures with longitudinal A\u0026beta; and tau PET changes in ADNI and TRIAD. The A\u0026beta;-associated signature showed spatially distributed longitudinal associations with A\u0026beta; PET uptake, involving different cortical regions, consistent with widespread A\u0026beta; accumulation during preclinical disease stages (\u003cstrong\u003eFig. 1k\u003c/strong\u003e). The tau-associated signature exhibited longitudinal associations with tau PET uptake in mesiotemporal, temporal pole and limbic regions implicated in early tau propagation (\u003cstrong\u003eFig. 1l\u003c/strong\u003e). These findings demonstrate that distinct biological pathways are engaged prior to A\u0026beta; and tau conversion and that their molecular signatures predict biomarker conversion.\u003c/p\u003e\n\u003cp\u003eHere, we combined longitudinal CSF proteomics with repeated clinical, imaging, and biomarker assessments across two independent cohorts to reconstruct molecular trajectories spanning the AD continuum. We identified a pronounced A\u0026beta;-associated tissue response that exhausted in later disease stages with established dementia. Immune- and lipid metabolism-associated pathways were engaged during the preclinical A\u0026beta; stage and even preceded A\u0026beta; conversion, in line with genetic and preclinical evidence implicating microglial lipid handling and innate immune signaling as central risk mechanisms in AD\u003csup\u003e14\u0026ndash;17\u003c/sup\u003e. Synaptic, proteostatic, autophagic, and redox-related pathways rose during the A+T\u0026ndash; stage and anticipated tau positivity and clinical impairment, supporting that proteasomal and autophagic dysfunction facilitate tau aggregation, propagation, and neuronal vulnerability\u003csup\u003e7,18,19\u003c/sup\u003e. These pathways can synergize with inflammatory signaling to promote synaptic failure, oxidative stress and neuronal loss\u003csup\u003e20,21\u003c/sup\u003e, providing a mechanistic framework linking proteostasis failure to neurodegeneration. By demonstrating that stage-specific molecular pathways are engaged before overt A\u0026beta; or tau positivity and predict subsequent disease transitions, this longitudinal framework supports a stage-informed approach to therapeutic targeting and patient stratification in AD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the study participants and the McGill Center for Studies in Aging staff. Data used in preparation of this article were obtained from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. We thank the ADNI participants and their families who made this study possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Canadian Institutes of Health Research (CIHR) [MOP-11-51-31; RFN 152985, 159815, 162303], Canadian Consortium of Neurodegeneration and Aging (CCNA; MOP-11-51-31 -team 1), Weston Brain Institute, the Alzheimer\u0026rsquo;s Association [NIRG-12-92090, NIRP-12-259245], Brain Canada Foundation (CFI Project 34874; 33397), and the Fonds de Recherche du Qu\u0026eacute;bec \u0026ndash; Sant\u0026eacute; (FRQS; Chercheur Boursier, 2020-VICO-279314). A.C.M. is supported by the Mitacs Graduate Fellowship (IT27627), the Max E Binz Fellowship-Medicine (F225864C02) and the Grad Excellence Award in Neurology \u0026amp; Neurosurgery (M159875C51). M.S.W. is funded by the Corona Foundation (S0199/10110/2025), and German Research Foundation (WO 2835/1-1). H.Z. is a Wallenberg Scholar and a Distinguished Professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018 and #2019-02397), the European Union\u0026rsquo;s Horizon Europe research and innovation programme under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer\u0026apos;s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C), the European Partnership on Metrology, co-financed from the European Union\u0026rsquo;s Horizon Europe Research and Innovation Programme and by the Participating States (NEuroBioStand, #22HLT07), the Bluefield Project, Cure Alzheimer\u0026rsquo;s Fund, the Olav Thon Foundation, the Erling-Persson Family Foundation, Familjen R\u0026ouml;nstr\u0026ouml;ms Stiftelse, Stiftelsen f\u0026ouml;r Gamla Tj\u0026auml;narinnor, Hj\u0026auml;rnfonden, Sweden (#FO2022-0270), the European Union\u0026rsquo;s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme \u0026ndash; Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, the UK Dementia Research Institute at UCL (UKDRI-1003), and an anonymous donor. K.B. is supported by the Swedish Research Council (#2017-00915 and #2022-00732), the Swedish Alzheimer Foundation (#AF-930351, #AF-939721, #AF-968270, and #AF-994551), Hj\u0026auml;rnfonden, Sweden (#ALZ2022-0006, #FO2024-0048-TK-130 and FO2024-0048-HK-24), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-965240 and #ALFGBG-1006418), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), the Alzheimer\u0026rsquo;s Association 2021 Zenith Award (ZEN-21-848495), the Alzheimer\u0026rsquo;s Association 2022-2025 Grant (SG-23-1038904 QC), La Fondation Recherche Alzheimer (FRA), Paris, France, the Kirsten and Freddy Johansen Foundation, Copenhagen, Denmark, Familjen R\u0026ouml;nstr\u0026ouml;ms Stiftelse, Stockholm, Sweden, and an anonymous philanthropist and donor. The funding sources had no participation in the design of the study, in the collection, analysis, and interpretation of data or in the manuscript writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.S.W. received honoraria from Lilly for educational lectures outside the scope of this work. J.T. has served as a consultant for Neurotorium education, Alzheon Inc and Imagination AI, all outside of the scope of the present work. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZpath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Enigma, LabCorp, Merck Sharp \u0026amp; Dohme, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Quanterix, Red Abbey Labs, reMYND, Roche, Samumed, ScandiBio Therapeutics AB, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures sponsored by Alzecure, BioArctic, Biogen, Cellectricon, Fujirebio, LabCorp, Lilly, Novo Nordisk, Oy Medix Biochemica AB, Roche, and WebMD, is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, and is a shareholder of CERimmune Therapeutics (outside submitted work). K.B. has served as a consultant and at advisory boards for Abbvie, AC Immune, ALZPath, AriBio, Beckman-Coulter, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Neurimmune, Novartis, Ono Pharma, Prothena, Quanterix, Roche Diagnostics, Sanofi and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJack, C. R. \u003cem\u003eet al.\u003c/em\u003e Revised criteria for diagnosis and staging of Alzheimer\u0026rsquo;s disease: Alzheimer\u0026rsquo;s Association Workgroup. \u003cem\u003eAlzheimer\u0026rsquo;s Dement.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 5143\u0026ndash;5169 (2024).\u003c/li\u003e\n\u003cli\u003eCourade, J.-P., Zetterberg, H., H\u0026ouml;glinger, G. U. \u0026amp; Dewachter, I. The evolving landscape of Alzheimer\u0026rsquo;s disease therapy: From A\u0026beta; to tau. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e188\u003c/strong\u003e, 7337\u0026ndash;7354 (2025).\u003c/li\u003e\n\u003cli\u003eZetterberg, H. \u0026amp; Bendlin, B. B. Biofluid biomarkers in Alzheimer\u0026rsquo;s disease and other neurodegenerative dementias. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e650\u003c/strong\u003e, 49\u0026ndash;59 (2026).\u003c/li\u003e\n\u003cli\u003ePascoal, T. A. \u003cem\u003eet al.\u003c/em\u003e Microglial activation and tau propagate jointly across Braak stages. \u003cem\u003eNat. Med.\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 1592\u0026ndash;1599 (2021).\u003c/li\u003e\n\u003cli\u003eHeneka, M. T. \u003cem\u003eet al.\u003c/em\u003e Neuroinflammation in Alzheimer disease. \u003cem\u003eNat. Rev. Immunol.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 321\u0026ndash;352 (2025).\u003c/li\u003e\n\u003cli\u003eOh, H. S.-H. \u003cem\u003eet al.\u003c/em\u003e A cerebrospinal fluid synaptic protein biomarker for prediction of cognitive resilience versus decline in Alzheimer\u0026rsquo;s disease. \u003cem\u003eNat. Med.\u003c/em\u003e (2025) doi:10.1038/s41591-025-03565-2.\u003c/li\u003e\n\u003cli\u003eMyeku, N. \u003cem\u003eet al.\u003c/em\u003e Tau-driven 26S proteasome impairment and cognitive dysfunction can be prevented early in disease by activating cAMP-PKA signaling. \u003cem\u003eNat. Med.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 46\u0026ndash;53 (2016).\u003c/li\u003e\n\u003cli\u003eManiv, I. \u003cem\u003eet al.\u003c/em\u003e Altered ubiquitin signaling induces Alzheimer\u0026rsquo;s disease-like hallmarks in a three-dimensional human neural cell culture model. \u003cem\u003eNat. Commun.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 5922 (2023).\u003c/li\u003e\n\u003cli\u003eAli, M. \u003cem\u003eet al.\u003c/em\u003e Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum. \u003cem\u003eNeuron\u003c/em\u003e \u003cstrong\u003e113\u003c/strong\u003e, 1363-1379.e9 (2025).\u003c/li\u003e\n\u003cli\u003eTijms, B. M. \u003cem\u003eet al.\u003c/em\u003e Cerebrospinal fluid proteomics in patients with Alzheimer\u0026rsquo;s disease reveals five molecular subtypes with distinct genetic risk profiles. \u003cem\u003eNat. Aging\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 33\u0026ndash;47 (2024).\u003c/li\u003e\n\u003cli\u003eAfshar, S. \u003cem\u003eet al.\u003c/em\u003e Plasma proteomic associations with Alzheimer\u0026rsquo;s disease endophenotypes. \u003cem\u003eNat. Aging\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 2104\u0026ndash;2124 (2025).\u003c/li\u003e\n\u003cli\u003eWoo, M. S. \u003cem\u003eet al.\u003c/em\u003e Glia inflammation and cell death pathways drive disease progression in preclinical and early AD. \u003cem\u003eEMBO Mol. Med.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 3064\u0026ndash;3079 (2025).\u003c/li\u003e\n\u003cli\u003eTijms, B. \u003cem\u003eet al.\u003c/em\u003e Defining the natural history of Alzheimer\u0026rsquo;s disease by longitudinal cerebrospinal fluid proteomics. at https://doi.org/10.21203/rs.3.rs-8544834/v1 (2026).\u003c/li\u003e\n\u003cli\u003eBellenguez, C. \u003cem\u003eet al.\u003c/em\u003e New insights into the genetic etiology of Alzheimer\u0026rsquo;s disease and related dementias. \u003cem\u003eNat. Genet.\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 412\u0026ndash;436 (2022).\u003c/li\u003e\n\u003cli\u003eHaney, M. S. \u003cem\u003eet al.\u003c/em\u003e APOE4/4 is linked to damaging lipid droplets in Alzheimer\u0026rsquo;s disease microglia. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e628\u003c/strong\u003e, 154\u0026ndash;161 (2024).\u003c/li\u003e\n\u003cli\u003eYin, Z. \u003cem\u003eet al.\u003c/em\u003e APOE4 impairs the microglial response in Alzheimer\u0026rsquo;s disease by inducing TGF\u0026beta;-mediated checkpoints. \u003cem\u003eNat. Immunol.\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 1839\u0026ndash;1853 (2023).\u003c/li\u003e\n\u003cli\u003eVenegas, C. \u003cem\u003eet al.\u003c/em\u003e Microglia-derived ASC specks cross-seed amyloid-\u0026beta; in Alzheimer\u0026rsquo;s disease. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e552\u003c/strong\u003e, 355\u0026ndash;361 (2017).\u003c/li\u003e\n\u003cli\u003eZhang, Z.-Y. \u003cem\u003eet al.\u003c/em\u003e TRIM11 protects against tauopathies and is down-regulated in Alzheimer\u0026rsquo;s disease. \u003cem\u003eScience (80-. ).\u003c/em\u003e \u003cstrong\u003e381\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eSamelson, A. J. \u003cem\u003eet al.\u003c/em\u003e CRISPR screens in iPSC-derived neurons reveal principles of tau proteostasis. \u003cem\u003eCell\u003c/em\u003e (2026) doi:10.1016/j.cell.2025.12.038.\u003c/li\u003e\n\u003cli\u003eLorenz, S. M. \u003cem\u003eet al.\u003c/em\u003e A fin-loop-like structure in GPX4 underlies neuroprotection from ferroptosis. \u003cem\u003eCell\u003c/em\u003e (2025) doi:10.1016/j.cell.2025.11.014.\u003c/li\u003e\n\u003cli\u003eWoo, M. S. \u003cem\u003eet al.\u003c/em\u003e The immunoproteasome disturbs neuronal metabolism and drives neurodegeneration in multiple sclerosis. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e188\u003c/strong\u003e, 4567-4585.e32 (2025).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8960775/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8960775/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Alzheimer’s disease (AD) progresses over a prolonged preclinical phase marked by early amyloid-β pathology (Aβ), followed by tau spread and neurodegeneration. However, limited understanding of longitudinal, stage-specific molecular processes constrains therapeutic timing and patient stratification. Here, we reconstructed molecular trajectories across the AD continuum by integrating longitudinal cerebrospinal fluid (CSF) proteomics with Aβ and tau biomarkers from two independent cohorts. We identified distinct trajectories emerging prior to Aβ and tau conversion. Preclinical Aβ-dominated transitions were characterized by immune- and lipid-associated programs, whereas tau-dominated transitions at the mild cognitive impairment stage were linked to synaptic, proteostatic, and autophagy-related signatures. These stage-specific trajectories predicted biomarker conversion, including from the preclinical, pre-Aβ stage. Longitudinal voxelwise analyses further revealed spatially distinct cortical Aβ and tau patterns corresponding to inflammatory and proteostatic-synaptic signatures. Together, these findings define temporally ordered molecular pathways underlying AD progression and inform stage-specific therapeutic strategies.","manuscriptTitle":"Distinct molecular trajectories precede amyloid-β and tau pathology in Alzheimer’s disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 14:12:49","doi":"10.21203/rs.3.rs-8960775/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"43db648c-f995-49dc-9f0c-f2d3b454f915","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63540742,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease"},{"id":63540743,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":63540744,"name":"Biological sciences/Neuroscience/Neuroimmunology"}],"tags":[],"updatedAt":"2026-04-01T15:06:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 14:12:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8960775","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8960775","identity":"rs-8960775","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}