Literature DB >> 31346756

Subcortical amyloid relates to cortical morphology in cognitively normal individuals.

Shady Rahayel1,2, Christian Bocti3, Pénélope Sévigny Dupont4,5, Maude Joannette4,5, Marie Maxime Lavallée4,5, Jim Nikelski6, Howard Chertkow6,7, Sven Joubert4,5.   

Abstract

PURPOSE: Amyloid (Aβ) brain deposition can occur in cognitively normal individuals and is associated with cortical volume abnormalities. Aβ-related volume changes are inconsistent across studies. Since volume is composed of surface area and thickness, the relative contribution of Aβ deposition on each of these metrics remains to be understood in cognitively normal individuals.
METHODS: A group of 104 cognitively normal individuals underwent neuropsychological assessment, PiB-PET scan, and MRI acquisition. Surface-based cortical analyses were performed to investigate the effects of cortical and subcortical Aβ burden on cortical volume, thickness, and surface area. Mediation analyses were used to study the effect of thickness and surface area on Aβ-associated volume changes. We also investigated the relationships between structural metrics in clusters with abnormal morphology and regions underlying resting-state functional networks and cognitive performance.
RESULTS: Cortical Aβ was not associated with cortical morphology. Subcortical Aβ burden was associated with changes in cortical volume, thickness, and surface area. Aβ-associated volume changes were driven by cortical surface area with or without thickness but never by thickness alone. Aβ-associated changes overlapped greatly with regions from the default mode network and were associated with lower performance in visuospatial abilities, episodic memory, and working memory.
CONCLUSIONS: In cognitively normal individuals, subcortical Aβ is associated with cortical volume, and this effect was driven by surface area with or without thickness. Aβ-associated cortical changes were found in the default mode network and affected cognitive performance. Our findings demonstrate the importance of studying subcortical Aβ and cortical surface area in normal ageing.

Entities:  

Keywords:  Amyloid beta; Cognitive ageing; Default mode network; Pittsburgh compound B; Subcortical

Mesh:

Substances:

Year:  2019        PMID: 31346756     DOI: 10.1007/s00259-019-04446-w

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  68 in total

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Authors:  Lena Palaniyappan; Peter F Liddle
Journal:  Neuroimage       Date:  2011-12-28       Impact factor: 6.556

2.  In vivo characterization of the early states of the amyloid-beta network.

Authors:  Jorge Sepulcre; Mert R Sabuncu; Alex Becker; Reisa Sperling; Keith A Johnson
Journal:  Brain       Date:  2013-07       Impact factor: 13.501

Review 3.  Adaptation and maladaptation insights from brain plasticity.

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Journal:  Prog Brain Res       Date:  2011       Impact factor: 2.453

4.  Cognitive reserve proxies relate to gray matter loss in cognitively healthy elderly with abnormal cerebrospinal fluid amyloid-β levels.

Authors:  Eider M Arenaza-Urquijo; José-Luis Molinuevo; Roser Sala-Llonch; Cristina Solé-Padullés; Mircea Balasa; Beatriz Bosch; Jaume Olives; Anna Antonell; Albert Lladó; Raquel Sánchez-Valle; Lorena Rami; David Bartrés-Faz
Journal:  J Alzheimers Dis       Date:  2013       Impact factor: 4.472

5.  Striatal amyloid plaque density predicts Braak neurofibrillary stage and clinicopathological Alzheimer's disease: implications for amyloid imaging.

Authors:  Thomas G Beach; Lucia I Sue; Douglas G Walker; Marwan N Sabbagh; Geidy Serrano; Brittany N Dugger; Monica Mariner; Kim Yantos; Jonette Henry-Watson; Glenn Chiarolanza; Jose A Hidalgo; Leslie Souders
Journal:  J Alzheimers Dis       Date:  2012       Impact factor: 4.472

6.  Brain atrophy in healthy aging is related to CSF levels of Aβ1-42.

Authors:  Anders M Fjell; Kristine B Walhovd; Christine Fennema-Notestine; Linda K McEvoy; Donald J Hagler; Dominic Holland; Kaj Blennow; James B Brewer; Anders M Dale
Journal:  Cereb Cortex       Date:  2010-01-04       Impact factor: 5.357

7.  Intrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain.

Authors:  R Nathan Spreng; Jorge Sepulcre; Gary R Turner; W Dale Stevens; Daniel L Schacter
Journal:  J Cogn Neurosci       Date:  2012-08-20       Impact factor: 3.225

8.  Joint associations of β-amyloidosis and cortical thickness with cognition.

Authors:  David S Knopman; Emily S Lundt; Terry M Therneau; Prashanthi Vemuri; Val J Lowe; Kejal Kantarci; Jeffrey L Gunter; Matthew L Senjem; Michelle M Mielke; Mary M Machulda; Rosebud O Roberts; Bradley F Boeve; David T Jones; Ronald C Petersen; Clifford R Jack
Journal:  Neurobiol Aging       Date:  2018-02-02       Impact factor: 4.673

9.  Permutation inference for the general linear model.

Authors:  Anderson M Winkler; Gerard R Ridgway; Matthew A Webster; Stephen M Smith; Thomas E Nichols
Journal:  Neuroimage       Date:  2014-02-11       Impact factor: 6.556

10.  Cerebrospinal fluid analysis detects cerebral amyloid-β accumulation earlier than positron emission tomography.

Authors:  Sebastian Palmqvist; Niklas Mattsson; Oskar Hansson
Journal:  Brain       Date:  2016-03-02       Impact factor: 13.501

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  1 in total

1.  Age-related episodic memory decline and the role of amyloid-β: a systematic review.

Authors:  Jandirlly Julianna Souto; Gabriella Medeiros Silva; Natalia Leandro Almeida; Irina Ivanovna Shoshina; Natanael Antonio Santos; Thiago Paiva Fernandes
Journal:  Dement Neuropsychol       Date:  2021 Jul-Sep
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