Integrated algorithm combining plasma biomarkers and cognitive assessments accurately predicts brain β-amyloid pathology.

ABSTRACT:

Background

Accurate prediction of cerebral amyloidosis with easily available indicators is urgently needed for diagnosis and treatment of Alzheimer's disease (AD).

Methods

We examined plasma Aβ42, Aβ40, T-tau, P-tau181, and NfL, with APOE genotypes, cognitive test scores and key demographics in a large Chinese cohort (N = 609, aged 40 to 84 years) covering full AD spectrum. Data-driven integrated computational models were developed to predict brain β-amyloid (Aβ) pathology.

Results

Our computational models accurately predict brain Aβ positivity (area under the ROC curves (AUC) = 0.94). The results are validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Particularly, the models have the highest prediction power (AUC = 0.97) in mild cognitive impairm

SUBMITTER: Pan F 

PROVIDER: S-EPMC10172320 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature