Approved Research

Integrative Neurobiological Bases of Brain Aging in Late Life

Lay summary

Even in the absence of neurodegenerative disorders like dementia or Alzheimer's disorder, aging is associated with changes in the brain as well as deficits in cognitive ability. However, brain aging does not occur at the same pace or in the same way for all individuals. Some may age "optimally" with little to no changes in memory or cognition, while others may experience severe forms of impairment. This project aims to identify factors that are most important for maintaining brain health through late adulthood. We will study individual differences in genetics, lifestyle, and environment in combination with measures of brain shape, size and function. By characterizing which factors are most important for promoting longevity, this work will help craft public health policy and identify specific biological targets for medical research and intervention. This study is expected to last a minimum of three years (2020-2023).

Scope extension:

Even in the absence of neurodegenerative disorders, aging is associated with brain atrophy and declines in cognitive ability. Cerebral deterioration in late life takes many forms, including loss of gray matter, increased neurovascular burden, changes in cellular state, and alterations of biological signaling pathways. However, the particular form and pace of age-related change in an individual depends upon their unique genetic predisposition, lifestyle, and environmental context. This project aims to understand how multi-level causes coalesce to influence individually variable brain age trajectories, integrating measures of macroscale brain anatomy and function with microscale genetic variation, functional genomics, and cellular change. Broadly, this work will construct a cross-level neuroscientific platform for studying normative neurobiological aging, with the goal of reducing barriers between historically siloed disciplines and data.

We request the scope to be extended / specified to allow us to specifically analyzed the effects of age on brain measures with specific focus on track stable and change trajectories that are influenced by lifestyle factors including estimates of sleep derived from the actigraphy data, common genetic variations associated with neurodegenerative disease (e.g., the presence of the APOE4 variant), and lifestyle factors (e.g., self-report of depression). All of these data types were downloaded as part of the original application. We are primarily specifying in more detail the "by age" analyses that we are conducting now that the project is underway.