4.6 Article

Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity

Journal

FRONTIERS IN AGING NEUROSCIENCE
Volume 15, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2023.1126799

Keywords

Alzheimer's disease; beta-Amyloid; positron emission tomography; cerebrospinal fluid; plasma; apolipoprotein E

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This study aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma A beta and CSF A beta levels for A beta PET positivity. The results showed that both plasma A beta and CSF A beta can accurately predict A beta PET status, especially when considering clinical information such as APOE genotype and cognitive stage, plasma A beta has better predictive performance.
Background: Early detection of beta-amyloid (A beta) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) A beta for predicting A beta deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma A beta is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma A beta and CSF A beta levels for A beta PET positivity. Methods: We recruited 488 participants who underwent both plasma A beta and A beta PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) A beta and A beta PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma A beta and CSF A beta, respectively, logistic regression and receiver operating characteristic analyses were performed. Results: When predicting A beta PET status, both plasma A beta 42/40 ratio and CSF A beta 42 showed high accuracy (plasma A beta area under the curve (AUC) 0.814; CSF A beta AUC 0.848). In the plasma A beta models, the AUC values were higher than plasma A beta alone model, when the models were combined with either cognitive stage (p<0.001) or APOE genotype (p=0.011). On the other hand, there was no difference between the CSF A beta models, when these variables were added. Conclusion: Plasma A beta might be a useful predictor of A beta deposition on PET status as much as CSF A beta, particularly when considered with clinical information such as APOE genotype and cognitive stage.

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