Do geriatric depression scale items predict amyloid PET status or other
biomarkers of Alzheimer's disease in individuals with subjective cognitive 
   Lead Investigator:    Louisa Thompson
   Institution      :    Brown University Medical School
   E-Mail           :    louisa_thompson@brown.edu
   Proposal ID      :    1142



   Proposal Description:
   Subjective cognitive decline (SCD), generally defined as the perception of worsening cognitive performance in the absence of objectively observed cognitive deficits, may be an important feature of early, preclinical AD changes in cognitive function (Jessen et al. 2014 Mitchell et al. 2014 Yates et al. 2015). However, the same features that lead many to assert that SCD is an established risk marker for preclinical AD, have also led to challenges for research on this topic. One such complication is that SCD often worsens with stress and commonly co-occurs with anxiety and depression (Yates et al., 2017).    While anxiety and depression have been associated with increased risk for AD, they are by no means specific to AD and are known to have independent deleterious effects on memory and other cognitive functions for individuals throughout the lifespan (Modrego  Ferrandez, 2004 Green et al., 2003). The utility of SCD and how to measure it is therefore not surprisingly a topic of some debate, and more research is needed (Molinuevo et al., 2017). The goal of the proposed research is to parse the unique and shared variance of SCD and self-reported depression symptoms (GDS total score) in the prediction of AD biomarkers, namely amyloid PET SUVr. Anxiety symptoms on the NPI will also be factored into the model. We predict that depression symptoms will explain a significant degree of unique variance in amyloid PET SUVr, supporting the argument that it is important to include both depression and SCD measures in AD predictive models.