Background: Alzheimer's disease (AD) is a major public health issue. Atrophy assessed with structural MRI, hypometabolism and amyloid load have been recently proposed as neuroimaging biomarkers for the preclinical diagnosis of the disease, consistently with the amyloid cascade hypothesis. However the meaning and the relevance of each neuroimaging biomarker remain not completely understood. Our objective was to characterize populations defined according to each neuroimaging biomarker (i.e. positive vs negative cases) to further our understanding of their use in the preclinical diagnosis of AD.
      Methods: We prospectively included 54 healthy controls (HC) over 50 years old who all performed structural MRI, FDG-PET and Florbetapir-PET in the same neuroimaging center. All HC were then dichotomized into positive or negative independently for each of the three biomarkers considering the regions of greatest changes in AD. Then, demographic, neuropsychological and neuroimaging data were compared between positive and negative cases classified from MRI, FDG-PET or Florbetapir PET data.
      Results: Amongst the 54 HC, 12 (22%), 12 (22%) and 8 (15%) individuals were positive for atrophy, hypometabolism and amyloid deposition, respectively. Demographic and neuropsychological data were not statistically different between the positive and the negative subgroups, except for age that was higher in the amyloid positive versus negative subgroup. Interestingly, the atrophy positive subgroup showed both hippocampal and frontal atrophy, and posterior cingulate, temporoparietal and frontal hypometabolism compared to the atrophy negative subgroup. There was no difference in amyloid load between atrophy or hypometabolism positive versus negative subgroups and the amyloid positive group didn't differ from the amyloid negative in terms of grey matter atrophy or hypometabolism. However, when considering individuals with atrophy and/or hypometabolism together, there seems to be an inverse relationships between amyloid and neurodegenerative biomarkers such that those with more neurodegeneration tend to show lower amyloid deposition and reversely.
      Conclusions: The atrophy biomarker is associated with a mixed pattern of AD-like and frontal. The three biomarkers provide independent rather than redundant information. Our findings show that individuals tend to have either neurodegeneration or amyloid load but not both, suggesting additive rather than sequential/causative links between the current neuroimaging biomarkers in the pathological process of AD.