Correlation Between Brain Structure Atrophy and Plasma Amyloid-β and Phosphorylated Tau in Patients With Alzheimer’s Disease and Amnestic Mild Cognitive Impairment Explored by Surface-Based Morphometry
Notice bibliographique
Résumé
Objective To investigate the changes in the cortical thickness of the region of interest (ROI) and plasma Aβ40, Aβ42, and phosphorylated Tau (P-Tau) concentrations in patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) as the disease progressed with surface-based morphometry (SBM), to analyze the correlation between ROI cortical thickness and measured plasma indexes and neuropsychological scales, and to explore the clinical value of ROI cortical thickness combined with plasma Aβ40, Aβ42, and P-Tau in the early recognition and diagnosis of AD. Methods This study enrolled 33 patients with AD, 48 patients with aMCI, and 33 healthy controls (normal control, NC). Concentration changes in plasma Aβ42, Aβ40, and P-Tau collected in each group were analyzed. Meanwhile, the whole brain T1 structure images (T1WI-3D-MPRAGE) of each group of patients were collected, and T1 image in AD-aMCI, AD-NC, and aMCI-NC group were analyzed and processed by SBM technology to obtain brain regions with statistical differences as clusters, and the cortical thickness of each cluster was extracted. Multivariate ordered logistic regression analysis was used to screen out the measured plasma indexes and the indexes with independent risk factors in the cortical thickness of each cluster. Three comparative receiver operating characteristic (ROC) curves of AD-aMCI, AD-NC, and aMCI-NC groups were plotted, respectively, to explore the diagnostic value of multi-factor combined prediction for cognitive impairment. The relationship between cortical thickness and plasma indexes, and between cortical thickness and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were clarified by Pearson correlation analysis. Results Plasma Aβ40, Aβ42, and P-Tau proteins in the NC, aMCI, and AD groups increased with the progression of AD ( P < 0.01); cortical thickness reductions in the AD-aMCI groups and AD-NC groups mainly involved the bilateral superior temporal gyrus, transverse temporal gyrus, superior marginal gyrus, insula, right entorhinal cortex, right fusiform gyrus, and cingulate gyrus. However, there were no statistical significances in cortical thickness reductions in the aMCI and NC groups. The cortical thickness of the ROI was negatively correlated with plasma Aβ40, Aβ42, and P-Tau concentrations ( P < 0.05), and the cortical thickness of the ROI was positively correlated with MMSE and MoCA scores. Independent risk factors such as Aβ40, Aβ42, P-Tau, and AD-NC cluster 1R (right superior temporal gyrus, temporal pole, entorhinal cortex, transverse temporal gyrus, fusiform gyrus, superior marginal gyrus, middle temporal gyrus, and inferior temporal gyrus) were combined to plot ROC curves. The diagnostic efficiency of plasma indexes was higher than that of cortical thickness indexes, the diagnostic efficiency of ROC curves after the combination of cortical thickness and plasma indexes was higher than that of cortical thickness or plasma indexes alone. Conclusion Plasma Aβ40, Aβ42, and P-Tau may be potential biomarkers for early prediction of AD. As the disease progressed, AD patients developed cortical atrophy characterized by atrophy of the medial temporal lobe. The combined prediction of these region and plasma Aβ40, Aβ42, and P-Tau had a higher diagnostic value than single-factor prediction for cognitive decline.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».