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Enregistrement 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 sur 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

Notice bibliographique

RevueThe Lancet Neurology · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueDown syndrome and intellectual disability research
Établissements canadiensnon disponible
Organismes subventionnairesEunice 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
Mots-clésCross-sectional studyAlzheimer's diseaseDiseaseMedicineDown syndromeInternal medicinePathologyPsychiatry

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,010
Score d'incertitude au seuil0,850

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,098
Tête enseignante GPT0,410
Écart entre enseignants0,312 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations36
Publié2024
Routes d'admission1
Résumé présentoui

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