Literature DB >> 32585492

Single-subject gray matter networks predict future cortical atrophy in preclinical Alzheimer's disease.

Ellen Dicks1, Wiesje M van der Flier2, Philip Scheltens3, Frederik Barkhof4, Betty M Tijms3.   

Abstract

The development of preventive strategies in early-stage Alzheimer's disease (AD) requires measures that can predict future brain atrophy. Gray matter network measures are related to amyloid burden in cognitively normal older individuals and predict clinical progression in preclinical AD. Here, we show that within individuals with preclinical AD, gray matter network measures predict hippocampal atrophy rates, whereas other AD biomarkers (total gray matter volume, cerebrospinal fluid total tau, and Mini-Mental State Examination) do not. Furthermore, in brain areas where amyloid is known to start aggregating (i.e. anterior cingulate and precuneus), disrupted network measures predict faster atrophy in other distant areas, mostly involving temporal regions, which are associated with AD. When repeating analyses in age-matched, cognitively unimpaired individuals without amyloid or tau pathology, we did not find any associations between network measures and hippocampal atrophy, suggesting that the associations are specific for preclinical AD. Our findings suggest that disrupted gray matter networks may indicate a treatment opportunity in preclinical AD individuals but before the onset of irreversible atrophy and cognitive impairment.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer's disease; Amyloid; Atrophy; Preclinical; Single-subject gray matter networks

Mesh:

Substances:

Year:  2020        PMID: 32585492     DOI: 10.1016/j.neurobiolaging.2020.05.008

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  6 in total

Review 1.  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

2.  Multiplex Connectome Changes across the Alzheimer's Disease Spectrum Using Gray Matter and Amyloid Data.

Authors:  Anna Canal-Garcia; Emiliano Gómez-Ruiz; Mite Mijalkov; Yu-Wei Chang; Giovanni Volpe; Joana B Pereira
Journal:  Cereb Cortex       Date:  2022-08-03       Impact factor: 4.861

3.  Brain Structural Network Compensation Is Associated With Cognitive Impairment and Alzheimer's Disease Pathology.

Authors:  Xiaoning Sheng; Haifeng Chen; Pengfei Shao; Ruomeng Qin; Hui Zhao; Yun Xu; Feng Bai
Journal:  Front Neurosci       Date:  2021-02-25       Impact factor: 4.677

4.  Grey matter network markers identify individuals with prodromal Alzheimer's disease who will show rapid clinical decline.

Authors:  Wiesje Pelkmans; Ellen M Vromen; Ellen Dicks; Philip Scheltens; Charlotte E Teunissen; Frederik Barkhof; Wiesje M van der Flier; Betty M Tijms
Journal:  Brain Commun       Date:  2022-02-08

5.  Rich-Club Connectivity of the Structural Covariance Network Relates to Memory Processes in Mild Cognitive Impairment and Alzheimer's Disease.

Authors:  Gerhard S Drenthen; Walter H Backes; Whitney M Freeze; Heidi I L Jacobs; Inge C M Verheggen; Martin P J van Boxtel; Erik I Hoff; Frans R Verhey; Jacobus F A Jansen
Journal:  J Alzheimers Dis       Date:  2022       Impact factor: 4.160

Review 6.  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

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.