Early detection & monitoring of memory decline in a representative sample of older adults at risk for Alzheimer's disease and related dementias

Project Summary/Abstract Early detection and sensitive tracking of cognitive changes related to Alzheimer’s disease (AD) pathology (amyloid-Aβ and tau), particularly those that are scaleable to the large at-risk population of older adults, are urgently needed. Promising digital tools to measure cognitive changes must be validated in

demographically diverse groups to ensure that research advancements are generalizable to those most at-risk for cognitive decline. Our recent work suggests that diminished learning over repeated evaluations (i.e., testing memory for the same content for 12min/day for 7 days) reveals subtle Aβ-related memory failures that are

otherwise undetectable using single timepoint measures. More specifically, 29 Aβ+ clinically unimpaired (CU) older adults failed to improve at the same rate as their 97 Aβ- CU peers when asked to learn and recall identical content daily with this group difference emerging after ~3 days. We now seek to determine whether

this Personal Learning Curve (PLC) paradigm can be used to detect early memory failures related to AD biomarkers in a larger and more diverse and representative sample and whether PLCs can sensitively track longitudinal cognitive decline when repeated bi-annually. We have the unique opportunity to recruit an

extremely well-characterized and representative at-risk sample (i.e., 32% from URG, family history of cognitive decline, hypertension, geographic diversity, English and Spanish speaking) with AD biomarkers (global Aβ, temporal tau quantified via Positron Emission Tomography-PET) and annual cognitive testing. Recruited

participants (n=300) will have completed the active phase of U.S. POINTER, a two-year clinical trial of two different multi-domain lifestyle interventions to protect brain health. We will explore whether a PLC, collected 12min/day for 7 days on personal devices, is a valid and sensitive marker of memory decline in this

representative population and whether repeating a PLC every 6 months for 12 months will reveal AD-relevant longitudinal cognitive decline. In exploratory analyses, we will examine PLCs in relation to cardiovascular risk factors (e.g., systolic blood pressure, white matter hyperintensities via Magnetic Resonance (MR) Imaging) and

non-specific markers of neurodegeneration (e.g., entorhinal tau, hippocampal atrophy). If successful, this proposal will provide a rapidly obtainable, repeatable, high-resolution snapshot of clinically relevant memory failures to facilitate early detection of cognitive decline as well as provide a novel method to assess treatment

response more rapidly. Doing so in a representative population will ensure that the most promising novel and accessible digital cognitive tools are generalizable to the broader at-risk population.