AI Article Synopsis
- The study investigates the effectiveness of various ATN (Aβ, tau, neurodegeneration) biomarkers in diagnosing Alzheimer's disease and predicting cognitive decline.
- Using data from 2,340 participants, researchers found that CSF-A (Aβ in cerebrospinal fluid), neuroimaging-T (tau neuroimaging), and neuroimaging-N (neurodegeneration neuroimaging) ranked highest for accurate diagnosis.
- The findings reveal significant differences in how plasma, CSF, and neuroimaging biomarkers function within the ATN framework, with neuroimaging-T showing a strong correlation with cognitive performance and the fastest decline seen in CSF-N positive individuals.
Article Abstract
Objectives: The ATN's different modalities (fluids and neuroimaging) for each of the Aβ (A), tau (T), and neurodegeneration (N) elements are used for the biological diagnosis of Alzheimer's disease (AD). We aim to identify which ATN category achieves the highest potential for diagnosis and predictive accuracy of longitudinal cognitive decline.
Methods: Based on the availability of plasma ATN biomarkers (plasma-derived Aβ , p-tau181, NFL, respectively), CSF ATN biomarkers (CSF-derived Aβ /Aβ , p-tau181, NFL), and neuroimaging ATN biomarkers (18F-florbetapir (FBP) amyloid-PET, 18F-flortaucipir (FTP) tau-PET, and fluorodeoxyglucose (FDG)-PET), a total of 2340 participants were selected from ADNI.
Results: Our data analysis indicates that the area under curves (AUCs) of CSF-A, neuroimaging-T, and neuroimaging-N were ranked the top three ATN candidates for accurate diagnosis of AD. Moreover, neuroimaging ATN biomarkers display the best predictive ability for longitudinal cognitive decline among the three categories. To note, neuroimaging-T correlates well with cognitive performances in a negative correlation manner. Meanwhile, participants in the "N" element positive group, especially the CSF-N positive group, experience the fastest cognitive decline compared with other groups defined by ATN biomarkers. In addition, the voxel-wise analysis showed that CSF-A related to tau accumulation and FDG-PET indexes more strongly in subjects with MCI stage. According to our analysis of the data, the best three ATN candidates for a precise diagnosis of AD are CSF-A, neuroimaging-T, and neuroimaging-N.
Conclusions: Collectively, our findings suggest that plasma, CSF, and neuroimaging biomarkers differ considerably within the ATN framework; the most accurate target biomarkers for diagnosing AD were the CSF-A, neuroimaging-T, and neuroimaging-N within each ATN modality. Moreover, neuroimaging-T and CSF-N both show excellent ability in the prediction of cognitive decline in two different dimensions.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10848089 | PMC |
| http://dx.doi.org/10.1111/cns.14357 | DOI Listing |
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