Unraveling the intersection of synaptic biology, lifestyle, and cognitive resilience
Funded Grant
Overview
Affiliation
View All
Overview
description
PROJECT SUMMARY / ABSTRACT Brain pathology begins accumulating in early adulthood and is detectable in almost all brains by older age. Yet, there is remarkable heterogeneity in cognitive aging, and most aged adults do not evidence cognitive impairment or dementia. Uncovering the naturally occurring processes that support this cognitive resilience to neuropathology burden may yield potent targets to prevent or slow Alzheimer's disease and related dementias (ADRD). We hypothesize that maintained synaptic integrity and physical activity may represent two such protective factors. Synaptic communication is the foundational underpinning of cognition. Increasing data suggest that preserved synaptic integrity may support clinical functioning regardless of pathology presence or etiology. Further, physical activity is a highly implicated resilience behavior that has also been linked to synaptic maintenance in animals. Our goal is to determine the synaptic biology that may underlie cognitive resilience and physical activity in humans. We will collaborate across two ADRC programs to leverage their unique strengths. In the Rush Memory and Aging Project (R-MAP), brain tissue samples from autopsied adults followed in life will be used to quantify >150 synaptic protein markers (n=869). In the UCSF Memory and Aging Center (UC-MAC), cerebrospinal fluid samples from longitudinally followed living older adults will be used to quantify seven synaptic protein markers (n=200). Both cohorts complete longitudinal actigraphy monitoring as an index of physical activity levels, and comprehensive neurobehavioral assessments. Cognitive resilience will be operationalized as the discrepancy between neuropathology markers and cognitive performances. Aim one will identify the in-depth synaptic networks (R-MAP) and the longitudinal, dynamic nature (UC-MAC) between synaptic markers and cognitive resilience. Aim two will apply innovative machine learning techniques to identify precise actigraphy features that most robustly relate to in-depth synaptic networks (R-MAP), longitudinal synaptic marker changes (UC-MAC), and cognitive resilience (both). Accomplishing these aims will significantly impact the ADRD field. We are designed to carefully identify synaptic and exercise features that support sustained cognitive resilience using cutting edge measurement technologies, analytics, and exceptional collaborative expertise. This proposal represents a bridging between two national ADRCs to more powerfully address high impact questions than could be answered by either individually.