估计阿尔茨海默病生物标志物变化的时间进程

Recent advancements in biomarkers have transformed Alzheimer's disease (AD) diagnosis from being purely symptom-based to include biological criteria. With new treatments targeting the core biology of Alzheimer's disease, understanding the timeline of biological changes is crucial as the disease progresses over decades. Longitudinal data from amyloid-beta (Aβ) PET and cognitive tests [Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog)] from the Alzheimer's Disease Neuroimaging Initiative (n = 1448) and BioFINDER (n = 2088) were used to stage patients against an estimated continuous disease timeline (predicted time since Aβ-PET positivity). The estimated timeline was validated by comparing correlations with unseen biomarkers and cognitive measures against alternative staging approaches. Trajectories for plasma, CSF, MRI and PET biomarkers, measuring Aβ, tau and neurodegeneration, were mapped along this Alzheimer's disease continuum. The proposed staging approach was found to produce stronger correlations with unseen cognitive measures and biomarkers compared to alternative staging methods, including amyloid and tau PET clocks (all pairwise P < 0.05). Findings related to biomarker trajectories were highly consistent across cohorts. The period from Aβ-PET positivity to end-stage Alzheimer's disease dementia (MMSE = 0) was estimated at 20-25 years, with a presymptomatic phase of 7-11 years. CSF Aβ42/Aβ40 became abnormal about a year before Aβ-PET positivity, CSF phosphorylated-tau (p-tau)231, p-tau217 and plasma phosphorylated/neuritic plaque-tau217 1-3 years after, and tau-PET about 8 years after. Neurodegenerative biomarkers, such as hippocampal volume, became clearly abnormal in early dementia stages, 14-16 years after Aβ-PET positivity. The progression from initial biomarker abnormality to severe Alzheimer's disease spans two decades. Disease progression modelling elucidates the evolution of AD biomarkers and cognition, highlighting the relative timing of biomarker abnormalities. These models can determine disease stages, aiding in prognosis and the evaluation of disease-modifying treatments.