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APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline.

ABSTRACT: Vascular contributions to dementia and Alzheimer's disease are increasingly recognized1-6. Recent studies have suggested that breakdown of the blood-brain barrier (BBB) is an early biomarker of human cognitive dysfunction7, including the early clinical stages of Alzheimer's disease5,8-10. The E4 variant of apolipoprotein E (APOE4), the main susceptibility gene for Alzheimer's disease11-14, leads to accelerated breakdown of the BBB and degeneration of brain capillary pericytes15-19, which maintain BBB integrity20-22. It is unclear, however, whether the cerebrovascular effects of APOE4 contribute to cognitive impairment. Here we show that individuals bearing APOE4 (with the ?3/?4 or ?4/?4 alleles) are distinguished from those without APOE4 (?3/?3) by breakdown of the BBB in the hippocampus and medial temporal lobe. This finding is apparent in cognitively unimpaired APOE4 carriers and more severe in those with cognitive impairment, but is not related to amyloid-? or tau pathology measured in cerebrospinal fluid or by positron emission tomography23. High baseline levels of the BBB pericyte injury biomarker soluble PDGFR?7,8 in the cerebrospinal fluid predicted future cognitive decline in APOE4 carriers but not in non-carriers, even after controlling for amyloid-? and tau status, and were correlated with increased activity of the BBB-degrading cyclophilin A-matrix metalloproteinase-9 pathway19 in cerebrospinal fluid. Our findings suggest that breakdown of the BBB contributes to APOE4-associated cognitive decline independently of Alzheimer's disease pathology, and might be a therapeutic target in APOE4 carriers.

SUBMITTER: Montagne A

PROVIDER: S-EPMC7250000 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline.

Montagne Axel A Nation Daniel A DA Sagare Abhay P AP Barisano Giuseppe G Sweeney Melanie D MD Chakhoyan Ararat A Pachicano Maricarmen M Joe Elizabeth E Nelson Amy R AR D'Orazio Lina M LM Buennagel David P DP Harrington Michael G MG Benzinger Tammie L S TLS Fagan Anne M AM Ringman John M JM Schneider Lon S LS Morris John C JC Reiman Eric M EM Caselli Richard J RJ Chui Helena C HC Tcw Julia J Chen Yining Y Pa Judy J Conti Peter S PS Law Meng M Toga Arthur W AW Zlokovic Berislav V BV

Nature 20200429 7806

Vascular contributions to dementia and Alzheimer's disease are increasingly recognized1-6. Recent studies have suggested that breakdown of the blood-brain barrier (BBB) is an early biomarker of human cognitive dysfunction7, including the early clinical stages of Alzheimer's disease5,8-10. The E4 variant of apolipoprotein E (APOE4), the main susceptibility gene for Alzheimer's disease11-14, leads to accelerated breakdown of the BBB and degeneration of b ...[more]

PMID: 32376954

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Project description:BackgroundIn light of advancements in machine learning techniques, many studies have implemented machine learning approaches combined with data measures to predict and classify Alzheimer's disease. Studies that predicted cognitive status with longitudinal follow-up of amyloid-positive individuals remain scarce, however.ObjectiveWe developed models based on voxel-wise functional connectivity (FC) density mapping and the presence of the ApoE4 genotype to predict whether amyloid-positive individuals would experience cognitive decline after 1 year.MethodsWe divided 122 participants into cognitive decline and stable cognition groups based on the participants' change rates in Mini-Mental State Examination scores. In addition, we included 68 participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) database as an external validation data set. Subsequently, we developed two classification models: the first model included 99 voxels, and the second model included 99 voxels and the ApoE4 genotype as features to train the models by Wide Neural Network algorithm with fivefold cross-validation and to predict the classes in the hold-out test and ADNI data sets.ResultsThe results revealed that both models demonstrated high accuracy in classifying the two groups in the hold-out test data set. The model for FC demonstrated good performance, with a mean F 1-score of 0.86. The model for FC combined with the ApoE4 genotype achieved superior performance, with a mean F 1-score of 0.90. In the ADNI data set, the two models demonstrated stable performances, with mean F 1-scores of 0.77 in the first and second models.ConclusionOur findings suggest that the proposed models exhibited promising accuracy for predicting cognitive status after 1 year in amyloid-positive individuals. Notably, the combination of FC and the ApoE4 genotype increased prediction accuracy. These findings can assist clinicians in predicting changes in cognitive status in individuals with a high risk of Alzheimer's disease and can assist future studies in developing precise treatment and prevention strategies.

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APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline.

Publications

APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline.

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