The objective of this application is to determine how cognitive deficits in patients with age-related macular degeneration (AMD) are related to differences in functional connectivity and white matter integrity in the brain. AMD affects nearly 30% of Americans over age 75 and is associated with a two-fold increased risk of dementia. This team's previous NIH-funded work identified a strikingly prevalent cognitive deficit, even in non- demented AMD patients: poor verbal fluency. Yet there is a fundamental knowledge gap regarding the etiology of the link between AMD and cognitive deficits, and this gap impedes the development of strategies to reduce cognitive impairment in AMD. Our central hypothesis is that brain connectivity plays a critical role in understanding the link between AMD and cognitive deficits (e.g., verbal fluency). Specifically, the link may arise via two mechanisms: #1) vision changes from macular disease could have a negative effect on cognitive performance, or #2) a shared risk factor could promote damage in the brain and eye concurrently. These two mechanisms, which may both be at play, should be distinguished by different patterns of brain connectivity associated with AMD-related cognitive deficits. This will be the first study to combine longitudinal neurocognitive testing and brain imaging to better understand the extent and locus of brain changes in AMD. The study will include 120 people with AMD plus 120 age-, gender-, and education-matched adults without AMD. All participants will receive baseline and 2-year neurocognitive tests and a subset will provide structural and resting state functional magnetic resonance images (MRIs) at each time point.
Aim 1 uses a neurocognitive battery developed and piloted by the applicants to define AMD-related differences in cognition without using tasks that require vision.
Aims 2 & 3 use measures of functional brain connectivity and region- specific white matter integrity derived from functional MRI (fMRI) and diffusion tensor imaging (DTI).
Aim 1. Characterize cognitive processes that contribute to verbal fluency deficit in AMD. We will construct regression models to test the extent to which verbal fluency performance in AMD reflects underlying cognitive deficits in semantic organization, processing speed, attention-switching, and memory.
Aim 2. Identify differences in brain connectivity associated with verbal fluency, or its cognitive contributors. We will relate measures of cognitive ability to measures of intrinsic functional and structural connectivity in the brain. We will examie whether brain signatures associated with cognitive deficits differ among older adults with and without AMD.
Aim 3. Identify cognitive profiles and brain signatures associated with cognitive decline in AMD patients. We will determine whether certain cognitive patterns or differences in specific neural networks, or both, predict AMD-related cognitive decline. Our working hypothesis is based on results of our pilot imaging study and favors mechanism #1: Verbal fluency deficit in AMD reflects problems in semantic organization and is related to differences in white matter tracts (primarily ventral) that support language, semantics, and vision.

Public Health Relevance

People with age-related macular degeneration are more likely to develop dementia, which leads to worse disability and greater healthcare utilization. This research will yield new knowledge about the reasons for cognitive problems in patients with age-related macular degeneration and is a necessary step toward developing early detection plans, treatments, and solutions. As such, this study is relevant to the NIH's mission to reduce the burdens of human illness and disability.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG043438-03
Application #
8875561
Study Section
Cognition and Perception Study Section (CP)
Program Officer
St Hillaire-Clarke, Coryse
Project Start
2013-08-01
Project End
2016-05-31
Budget Start
2015-07-01
Budget End
2016-05-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Duke University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Garg, Tullika; Anzuoni, Kathryn; Landyn, Valentina et al. (2018) The AGING Initiative experience: a call for sustained support for team science networks. Health Res Policy Syst 16:41
Whitson, Heather E; Cohen, Harvey J; Schmader, Kenneth E et al. (2018) Physical Resilience: Not Simply the Opposite of Frailty. J Am Geriatr Soc 66:1459-1461
Zhuang, Jie; Madden, David J; Duong-Fernandez, Xuan et al. (2018) Language processing in age-related macular degeneration associated with unique functional connectivity signatures in the right hemisphere. Neurobiol Aging 63:65-74
Chan, Victor T T; Sun, Zihan; Tang, Shumin et al. (2018) Spectral-Domain OCT Measurements in Alzheimer's Disease: A Systematic Review and Meta-analysis. Ophthalmology :
Chou, Ying-Hui; Sundman, Mark; Whitson, Heather E et al. (2017) Maintenance and Representation of Mind Wandering during Resting-State fMRI. Sci Rep 7:40722
Polans, James; Keller, Brenton; Carrasco-Zevallos, Oscar M et al. (2017) Wide-field retinal optical coherence tomography with wavefront sensorless adaptive optics for enhanced imaging of targeted regions. Biomed Opt Express 8:16-37
Lea, Colby; QuiƱones, Ana; Whitson, Heather et al. (2016) Changes in Self-Rated Health During the Transition to Retiring Living Among Medicare Managed-Care Recipients. J Hous Elderly 30:76-88
Liu, Phillip L; Cohen, Harvey Jay; Fillenbaum, Gerda G et al. (2016) Association of Co-Existing Impairments in Cognition and Self-Rated Vision and Hearing With Health Outcomes in Older Adults. Gerontol Geriatr Med 2:
Whitson, Heather E; Duan-Porter, Wei; Schmader, Kenneth E et al. (2016) Physical Resilience in Older Adults: Systematic Review and Development of an Emerging Construct. J Gerontol A Biol Sci Med Sci 71:489-95
Zullig, Leah L; Whitson, Heather E; Hastings, Susan N et al. (2016) A Systematic Review of Conceptual Frameworks of Medical Complexity and New Model Development. J Gen Intern Med 31:329-37

Showing the most recent 10 out of 18 publications