Literature DB >> 26203136

Cognitive and Brain Profiles Associated with Current Neuroimaging Biomarkers of Preclinical Alzheimer's Disease.

Florent L Besson1, Renaud La Joie2, Loïc Doeuvre2, Malo Gaubert2, Florence Mézenge2, Stéphanie Egret2, Brigitte Landeau2, Louisa Barré3, Ahmed Abbas2, Meziane Ibazizene3, Vincent de La Sayette4, Béatrice Desgranges2, Francis Eustache2, Gaël Chételat5.   

Abstract

Neuroimaging biomarkers, namely hippocampal volume loss, temporoparietal hypometabolism, and neocortical β-amyloid (Aβ) deposition, are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our aim was to characterize the cognitive and brain profiles of elders classified as positive or negative for each biomarker to further our understanding of their use in the preclinical diagnosis of AD. Fifty-four cognitively normal individuals (age = 65.8 ± 8.3 years) underwent neuropsychological tests (structural MRI, FDG-PET, and Florbetapir-PET) and were dichotomized into positive or negative independently for each neuroimaging biomarker. Demographic, neuropsychological, and neuroimaging data were compared between positive and negative subgroups. The MRI-positive subgroup had lower executive performances and mixed patterns of lower volume and metabolism in AD-characteristic regions and in the prefrontal cortex. The FDG-positive subgroup showed only hypometabolism, predominantly in AD-sensitive areas extending to the whole neocortex, compared with the FDG-negative subgroup. The amyloid-positive subgroup was older and included more APOE ε4 carriers compared with the amyloid-negative subgroup. When considering MRI and/or FDG biomarkers together (i.e., the neurodegeneration-positive), there was a trend for an inverse relationship with Aβ deposition such that those with neurodegeneration tended to show less Aβ deposition and the reverse was true as well. Our findings suggest that: (1) MRI and FDG biomarkers provide complementary rather than redundant information and (2) relatively young cognitively normal elders tend to have either neurodegeneration or Aβ deposition, but not both, suggesting additive rather than sequential/causative links between AD neuroimaging biomarkers at this age. Significance statement: Neuroimaging biomarkers are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our findings suggest that MRI and FDG-PET biomarkers should be used in combination, offering an additive contribution instead of reflecting the same process of neurodegeneration. Moreover, the present study also challenges the hierarchical use of the neuroimaging biomarkers in preclinical AD because it suggests that the neurodegeneration observed in this population is not due to β-amyloid deposition. Rather, our results suggest that β-amyloid- and tau-related pathological processes may interact but not necessarily appear in a systematic sequence.
Copyright © 2015 the authors 0270-6474/15/3510403-10$15.00/0.

Entities:  

Keywords:  Alzheimer's disease; FDG; MRI; PET; amyloid; biomarkers

Mesh:

Substances:

Year:  2015        PMID: 26203136      PMCID: PMC6605120          DOI: 10.1523/JNEUROSCI.0150-15.2015

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  47 in total

Review 1.  FDG-PET Contributions to the Pathophysiology of Memory Impairment.

Authors:  Shailendra Segobin; Renaud La Joie; Ludivine Ritz; Hélène Beaunieux; Béatrice Desgranges; Gaël Chételat; Anne Lise Pitel; Francis Eustache
Journal:  Neuropsychol Rev       Date:  2015-08-30       Impact factor: 7.444

2.  Temporal Order of Alzheimer's Disease-Related Cognitive Marker Changes in BLSA and WRAP Longitudinal Studies.

Authors:  Murat Bilgel; Rebecca L Koscik; Yang An; Jerry L Prince; Susan M Resnick; Sterling C Johnson; Bruno M Jedynak
Journal:  J Alzheimers Dis       Date:  2017       Impact factor: 4.472

Review 3.  Detectable Neuropsychological Differences in Early Preclinical Alzheimer's Disease: A Meta-Analysis.

Authors:  S Duke Han; Caroline P Nguyen; Nikki H Stricker; Daniel A Nation
Journal:  Neuropsychol Rev       Date:  2017-05-11       Impact factor: 7.444

4.  Intranasal Insulin Ameliorates Cerebral Hypometabolism, Neuronal Loss, and Astrogliosis in Streptozotocin-Induced Alzheimer's Rat Model.

Authors:  Yanxing Chen; Zhangyu Guo; Yan-Fang Mao; Tingting Zheng; Baorong Zhang
Journal:  Neurotox Res       Date:  2017-09-19       Impact factor: 3.911

5.  Free-water metrics in medial temporal lobe white matter tract projections relate to longitudinal cognitive decline.

Authors:  Derek B Archer; Elizabeth E Moore; Niranjana Shashikumar; Logan Dumitrescu; Kimberly R Pechman; Bennett A Landman; Katherine A Gifford; Angela L Jefferson; Timothy J Hohman
Journal:  Neurobiol Aging       Date:  2020-05-12       Impact factor: 4.673

Review 6.  Using Administrative Data to Examine Health Disparities and Outcomes in Neurological Diseases of the Elderly.

Authors:  Allison W Willis
Journal:  Curr Neurol Neurosci Rep       Date:  2015-11       Impact factor: 5.081

7.  PET imaging of the influence of physiological and pathological α-synuclein on dopaminergic and serotonergic neurotransmission in mouse models.

Authors:  Elise Levigoureux; Caroline Bouillot; Thierry Baron; Luc Zimmer; Sophie Lancelot
Journal:  CNS Neurosci Ther       Date:  2018-05-20       Impact factor: 5.243

8.  Clinical Application of Automatic Segmentation of Medial Temporal Lobe Subregions in Prodromal and Dementia-Level Alzheimer's Disease.

Authors:  Eske Christiane Gertje; John Pluta; Sandhitsu Das; Lauren Mancuso; Dasha Kliot; Paul Yushkevich; David Wolk
Journal:  J Alzheimers Dis       Date:  2016-10-04       Impact factor: 4.472

Review 9.  Neurodegeneration and Alzheimer's disease (AD). What Can Proteomics Tell Us About the Alzheimer's Brain?

Authors:  Guillermo Moya-Alvarado; Noga Gershoni-Emek; Eran Perlson; Francisca C Bronfman
Journal:  Mol Cell Proteomics       Date:  2015-12-11       Impact factor: 5.911

10.  Morphometric network differences in ageing versus Alzheimer's disease dementia.

Authors:  Alexa Pichet Binette; Julie Gonneaud; Jacob W Vogel; Renaud La Joie; Pedro Rosa-Neto; D Louis Collins; Judes Poirier; John C S Breitner; Sylvia Villeneuve; Etienne Vachon-Presseau
Journal:  Brain       Date:  2020-02-01       Impact factor: 13.501

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