Leveraging Neuroimaging Biomarkers to Understand the Role of Social Networks in Alzheimer's Disease Funded Grant uri icon

description

  • PROJECT SUMMARY The goal of the proposed project is to understand the role of personal social network dynamics in the etiology and clinical progression of mild cognitive impairment (MCI) and Alzheimer disease (AD). We propose to characterize social-behavioral and biological mechanisms underlying relationships between social networks and aging-related neuropathology. AD and dementia takes a devastating toll on individuals, families, and the health care system. A critical point of intervention in AD is the social environment, which has the potential to moderate underlying neuropathology, altering the typical cognitive course of dementia. Positive social interaction – including number of confidants, frequency of social contact, support, and social engagement – is associated with reduced risk for dementia and a slower trajectory of cognitive decline among diagnosed individuals. However, the existing literature relies on limited and unidimensional measures of social interaction, and has yet to consider the role of underlying biological neurodegeneration, which manifests long before observable clinical cognitive symptoms of dementia. The proposed project addresses these gaps via three specific aims: Aim 1 is to identify baseline associations between social network characteristics and neurodegeneration (QNPs). Aim 2 is to examine longitudinal relationships between personal social network dynamics and neurodegenerative changes. Aim 3 is to evaluate alternative models of the coevolution of personal social networks and neurodegenerative changes in trajectories of clinical cognitive decline. The proposed study is interdisciplinary, combining leading-edge methods from the social and biomedical sciences, and leveraging the resources of funded centers for AD, neuroimaging, and network science. By increasing our understanding of the links between biological and social processes, this project may help identify novel targets for intervention to reduce the burden of AD on individuals, families, and the health care system.

date/time interval

  • 2018 - 2023