F4‐01‐04: Amyloid Imaging in the Multimodal Evaluation of MCI

An important question in determining the predictive utility of amyloid imaging in MCI is evaluating it in relation to other biomarkers. Furthermore, associations between biomarkers change as disease progresses, adding further complexity to the multimodal evaluation of patients. Here, we evaluated amyloid imaging and its relationship with other biomarkers in a longitudinal analysis of MCI subjects in the ADNI population. We examined associations between amyloid deposition (measured with 18F-florbetapir) and a variety of other biomarkers (FDG-PET, hippocampal volume, APOE-ε4 status) in early MCI and MCI subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). A subset of these subjects was followed longitudinally prior to amyloid imaging, which allowed us to evaluate which markers were linked to conversion from MCI to AD and longitudinal cognitive decline. Amyloid positivity increased with disease severity, with approximately 40-60% of early MCI and MCI subjects showing substantial florbetapir uptake, compared with approximately 30% of normal subjects and 80% of AD patients. In early MCI, florbetapir was moderately associated with FDG but closely linked to concurrent memory function, whereas the reverse was true for MCI, where florbetapir was strongly related to FDG but only moderately associated with memory function. During follow-up, nearly 50% of MCI subjects converted to AD. Atrophy, FDG-PET, amyloid, and APOE status were all useful in predicting conversion status and cognitive decline. However, differences in biomarkers were more evident in models that tracked longitudinal decline rather than conversion, perhaps because continuous measures of cognitive function make it possible to examine incremental changes in function from the subject's own baseline. Associations between amyloid and cognitive function may be stronger in the earliest phases of disease (normal and early MCI individuals) despite minimal cognitive dysfunction in these populations. In MCI, hypometabolism may be more directly linked than amyloid to cognitive ability. These findings support a model in which amyloid deposition is associated with the earliest stages of subtle cognitive impairment, followed by metabolic, synaptic, and structural dysfunction that parallels further cognitive decline. Tracking future (prospective) changes in cognitive function and other biomarkers will be critical for determining the predictive role of amyloid imaging.