Alzheimer's disease diagnostic accuracy by fluid and neuroimaging ATN framework

ObjectivesThe ATN's different modalities (fluids and neuroimaging) for each of the A & beta; (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. MethodsBased on the availability of plasma ATN biomarkers (plasma-derived A & beta;(42/40), p-tau181, NFL, respectively), CSF ATN biomarkers (CSF-derived A & beta;(42)/A & beta;(40), 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. ResultsOur 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. ConclusionsCollectively, 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.

Automated summary

The study aims to determine the most accurate biomarkers within the ATN framework for diagnosing Alzheimer's disease (AD) and predicting longitudinal cognitive decline. Results show that CSF-A, neuroimaging-T, and neuroimaging-N have the highest potential for accurate diagnosis of AD. Neuroimaging-T and CSF-N also demonstrate excellent predictive ability for cognitive decline. Overall, plasma, CSF, and neuroimaging biomarkers differ significantly within the ATN framework, with CSF-A, neuroimaging-T, and neuroimaging-N being the most accurate target biomarkers for diagnosing AD.