Abstract

Models of Alzheimer pathology propose that amyloidosis, hypometabolism, and structural declines emerge not only over time, but also spatially in the brain. Autosomal dominant Alzheimer disease (ADAD) provides an elegant way to study the evolution of such pathology due to the ability to stage an individual relative to their years to expected symptom onset (EYO). Longitudinal neuroimaging data is a particularly powerful way to model such changes, as within-subject measures reduces between-subject variability caused by unobserved individual differences. We examined longitudinal PiB, FDG, and structural MRI data in a population of 400 individuals enrolled in the Dominantly Inherited Alzheimer's Network (DIAN). Data were processed examining 34 cortical and 7 subcortical regions. We utilized linear mixed effects models to explore changing pathology. Models were fit for each region included fixed effects for mutation status, time from baseline, baseline EYO, and all possible two and three-way interactions. To allow non-linearities, EYO was modeled as a restricted cubic spline. Analyses were run separately for each modality. The primary focus was on the first time point in the disease where biomarker change in that region differed between mutation carrier and non-carriers. Relative to non-carriers, rates of amyloid deposition were significantly higher in carriers at an average EYO across regions of -18.2, glucose metabolism began declining at an average EYO of -14.2, and MRI structural measures declined at an average EYO of -4.2. While this three-stage pattern was common across regions of the brain, it was not ubiquitous (Figure 1). Most prominently a subset of regions demonstrated elevated PiB PET accumulation and structural declines, but not abnormal glucose utilization. Further, the regional timing within a modality (e.g. PiB PET) was highly variable across brain regions (Figure 2).

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