Literature DB >> 32398359

The implications of different approaches to define AT(N) in Alzheimer disease.

Niklas Mattsson-Carlgren1, Antoine Leuzy2, Shorena Janelidze2, Sebastian Palmqvist2, Erik Stomrud2, Olof Strandberg2, Ruben Smith2, Oskar Hansson1.   

Abstract

OBJECTIVE: To compare different β-amyloid (Aβ), tau, and neurodegeneration (AT[N]) variants within the Swedish BioFINDER studies.
METHODS: A total of 490 participants were classified into AT(N) groups. These include 53 cognitively unimpaired (CU) and 48 cognitively impaired (CI) participants (14 mild cognitive impairment [MCI] and 34 Alzheimer disease [AD] dementia) from BioFINDER-1 and 389 participants from BioFINDER-2 (245 CU and 144 CI [138 MCI and 6 AD dementia]). Biomarkers for A were CSF Aβ42 and amyloid-PET ([18F]flutemetamol); for T, CSF phosphorylated tau (p-tau) and tau PET ([18F]flortaucipir); and for (N), hippocampal volume, temporal cortical thickness, and CSF neurofilament light (NfL). Binarization of biomarkers was achieved using cutoffs defined in other cohorts. The relationship between different AT(N) combinations and cognitive trajectories (longitudinal Mini-Mental State Examination scores) was examined using linear mixed modeling and coefficient of variation.
RESULTS: Among CU participants, A-T-(N)- or A+T-(N)- variants were most common. However, more T+ cases were seen using p-tau than tau PET. Among CI participants, A+T+(N)+ was more common; however, more (N)+ cases were seen for MRI measures relative to CSF NfL. Tau PET best predicted longitudinal cognitive decline in CI and p-tau in CU participants. Among CI participants, continuous T (especially tau PET) and (N) measures improved the prediction of cognitive decline compared to binary measures.
CONCLUSIONS: Our findings show that different AT(N) variants are not interchangeable, and that optimal variants differ by clinical stage. In some cases, dichotomizing biomarkers may result in loss of important prognostic information.
Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

Entities:  

Year:  2020        PMID: 32398359     DOI: 10.1212/WNL.0000000000009485

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  19 in total

1.  Prediction of future Alzheimer's disease dementia using plasma phospho-tau combined with other accessible measures.

Authors:  Sebastian Palmqvist; Pontus Tideman; Nicholas Cullen; Henrik Zetterberg; Kaj Blennow; Jeffery L Dage; Erik Stomrud; Shorena Janelidze; Niklas Mattsson-Carlgren; Oskar Hansson
Journal:  Nat Med       Date:  2021-05-24       Impact factor: 53.440

Review 2.  Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.

Authors:  Rachel F Buckley
Journal:  Neurotherapeutics       Date:  2021-03-29       Impact factor: 7.620

3.  A Computational Monte Carlo Simulation Strategy to Determine the Temporal Ordering of Abnormal Age Onset Among Biomarkers of Alzheimer's Disease.

Authors:  Xiaojuan Guo; Kewei Chen; Yinghua Chen; Chengjie Xiong; Yi Su; Li Yao; Eric M Reiman
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2022-10-10       Impact factor: 3.702

4.  ATN incorporating cerebrospinal fluid neurofilament light chain detects frontotemporal lobar degeneration.

Authors:  Katheryn A Q Cousins; Jeffrey S Phillips; David J Irwin; Edward B Lee; David A Wolk; Leslie M Shaw; Henrik Zetterberg; Kaj Blennow; Sarah E Burke; Nikolas G Kinney; Garrett S Gibbons; Corey T McMillan; John Q Trojanowski; Murray Grossman
Journal:  Alzheimers Dement       Date:  2020-11-23       Impact factor: 21.566

5.  Characterization of Alzheimer's tau biomarker discordance using plasma, CSF, and PET.

Authors:  Yu Guo; Yu-Yuan Huang; Xue-Ning Shen; Shi-Dong Chen; Hao Hu; Zuo-Teng Wang; Lan Tan; Jin-Tai Yu
Journal:  Alzheimers Res Ther       Date:  2021-05-04       Impact factor: 6.982

6.  Cerebral amyloid-β load is associated with neurodegeneration and gliosis: Mediation by p-tau and interactions with risk factors early in the Alzheimer's continuum.

Authors:  Gemma Salvadó; Marta Milà-Alomà; Mahnaz Shekari; Carolina Minguillon; Karine Fauria; Aida Niñerola-Baizán; Andrés Perissinotti; Gwendlyn Kollmorgen; Christopher Buckley; Gill Farrar; Henrik Zetterberg; Kaj Blennow; Marc Suárez-Calvet; José Luis Molinuevo; Juan Domingo Gispert
Journal:  Alzheimers Dement       Date:  2021-03-04       Impact factor: 21.566

Review 7.  Developing the ATX(N) classification for use across the Alzheimer disease continuum.

Authors:  Harald Hampel; Jeffrey Cummings; Kaj Blennow; Peng Gao; Clifford R Jack; Andrea Vergallo
Journal:  Nat Rev Neurol       Date:  2021-07-08       Impact factor: 44.711

Review 8.  Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group.

Authors:  Bruno Dubois; Nicolas Villain; Giovanni B Frisoni; Gil D Rabinovici; Marwan Sabbagh; Stefano Cappa; Alexandre Bejanin; Stéphanie Bombois; Stéphane Epelbaum; Marc Teichmann; Marie-Odile Habert; Agneta Nordberg; Kaj Blennow; Douglas Galasko; Yaakov Stern; Christopher C Rowe; Stephen Salloway; Lon S Schneider; Jeffrey L Cummings; Howard H Feldman
Journal:  Lancet Neurol       Date:  2021-04-29       Impact factor: 59.935

Review 9.  The human connectome in Alzheimer disease - relationship to biomarkers and genetics.

Authors:  Meichen Yu; Olaf Sporns; Andrew J Saykin
Journal:  Nat Rev Neurol       Date:  2021-07-20       Impact factor: 44.711

10.  Tau PET correlates with different Alzheimer's disease-related features compared to CSF and plasma p-tau biomarkers.

Authors:  Rik Ossenkoppele; Juhan Reimand; Ruben Smith; Antoine Leuzy; Olof Strandberg; Sebastian Palmqvist; Erik Stomrud; Henrik Zetterberg; Philip Scheltens; Jeffrey L Dage; Femke Bouwman; Kaj Blennow; Niklas Mattsson-Carlgren; Shorena Janelidze; Oskar Hansson
Journal:  EMBO Mol Med       Date:  2021-07-13       Impact factor: 12.137

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