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Record W4394800620 · doi:10.1016/s1474-4422(24)00084-x

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study

2024· article· en· W4394800620 on OpenAlexfundno aff
Julie K. Wisch, Nicole S. McKay, Anna H. Boerwinkle, James L. Kennedy, Shaney Flores, Benjamin L. Handen, Bradley T. Christian, Elizabeth Head, Mark Mapstone, Michael S. Rafii, Sid E. O’Bryant, Julie C. Price, Charles M. Laymon, Sharon J. Krinsky‐McHale, Florence Lai, H. Diana Rosas, Sigan L. Hartley, Shahid Zaman, Ira T. Lott, Dana Tudorascu, Matthew Zammit, Adam M. Brickman, Joseph H. Lee, Thomas D. Bird, Annie Cohen, Patricio Chrem, Alisha Daniels, Jasmeer P. Chhatwal, Carlos Cruchaga, Laura Ibáñez, Mathias Jucker, Celeste M. Karch, Gregory S. Day, Jae‐Hong Lee, Johannes Levin, Jorge J. Llibre‐Guerra, Yan Li, Francisco Lopera, Jee Hoon Roh, John M. Ringman, Charlene Supnet, Christopher H. van Dyck, Chengjie Xiong, Guoqiao Wang, John C. Morris, Eric McDade, Randall J. Bateman, Tammie L.S. Benzinger, Brian A. Gordon, Beau M. Ances, Howard Aizenstein, Howard Andrews, Karen L. Bell, Rasmus M. Birn, Peter Bulova, Amrita K. Cheema, Kewei Chen, I. C. H. Clare, Lorraine N. Clark, Ann D. Cohen, John N. Constantino, Eric Doran, Eleanor Feingold, Tatiana Foroud, Christy Hom, Lawrence S. Honig, Miloš D. Ikonomović, Sterling C. Johnson, Courtney Jordan, M. Ilyas Kamboh, David B. Keator, William E. Klunk, Julia Kofler, William Charles Kreisl, Patrick J. Lao, Victoria Lupson, Chester A. Mathis, Davneet Minhas, Neelesh Nadkarni, Deborah Pang, Melissa Petersen, Eric M. Reiman, Batool Rizvi, Marwan N. Sabbagh, Nicole Schupf, Rameshwari V. Tumuluru, Benjamin Tycko, Badri Varadarajan, Desirée A. White, Michael A. Yassa, Fan Zhang, Laura Courtney, Chengie Xiong, Xu Xiong, Ruijin Lu, Yan Li, Emily Gremminger, Richard J. Perrin, Erin Franklin, Gina Jerome, Elizabeth Herries, Jennifer L. Stauber, Bryce Baker, Matthew Minton, Alison Goate, Alan E. Renton, Danielle M. Picarello, Russall Hornbeck, Jason Hassenstab, Jennifer S. Smith, Sarah H. Stout, Andrew J. Aschenbrenner, Jacob Marsh, David M. Holtzman, Nicolas R. Barthélemy, Jinbin Xu, James M. Noble, Sarah Berman, Snežana Ikonomović, Neelesh K. Nadkarni, Neill R. Graff‐Radford, Martin Farlow, Takeshi Ikeuchi, Kensaku Kasuga, Yoshiki Niimi, Edward D. Huey, Stephen Salloway, Peter R. Schofield, William S. Brooks, Jacob Bechara, Ralph N. Martins, Nick C. Fox, David M. Cash, Natalie S. Ryan, Christoph Laske, Anna Hofmann, Elke Kuder-Buletta, Susanne Gräber‐Sultan, Ulrike Obermueller, Yvonne Roedenbeck, Jonathan Vöglein, Raquel Sánchez‐Valle, Pedro Rosa‐Neto, Ricardo Allegri, Patricio Chrem Méndez, Ezequiel Surace, Silvia Vázquez, Yudy Milena Leon, Laura Ramírez, David Aguillón, Allan I. Levey, Erik C. B. Johnson, Nicholas T. Seyfried, Hiroshi Mori

Bibliographic record

VenueThe Lancet Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Mental HealthInstituto de Salud Carlos IIIAvid RadiopharmaceuticalsNational Institutes of HealthGrifolsDeutsches Zentrum für Neurodegenerative ErkrankungenNational Institute of Child Health and Human DevelopmentGHR FoundationFondation Brain CanadaMinistry of Health and WelfareEisaiUniversity of OxfordKorea Health Industry Development InstituteNational Institute on AgingNational Institute for Health and Care ResearchU.S. Department of DefenseEli Lilly and CompanyAlzheimer's AssociationBiogenCanadian Institutes of Health ResearchAutism SpeaksNIHR Cambridge Biomedical Research Centre
KeywordsCross-sectional studyAlzheimer's diseaseDiseaseMedicineDown syndromeInternal medicinePathologyPsychiatry

Abstract

fetched live from OpenAlex

Background In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. Methods In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium–Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. Findings We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. Interpretation Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. Funding None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.410
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2024
Admission routes1
Has abstractyes

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