Age-related macular degeneration (AMD) is the leading cause of vision loss among people aged 65 and older in the US. Since the advanced form of this disease affects central vision function, reading difficulties are one of the most common complaints of AMD patients. Most research on reading in AMD has focused on people with advanced disease, who already have significant central vision losses. However, research suggests that reading and other non-standard functional vision measures are afected earlier in the disease, prior to losses in standard visual acuity. This project aims to examine the contribution of visual, motor and cognitive factors to reading performance in elderly individuals with early AMD. This study also seeks to determine whether reading performance and other non-standard vision function measures can be used to predict which participants will go on to develop the advanced forms of the disease. Current clinical metrics (such as fundus appearance) provide little guidance on how much risk a given patient with early signs of AMD has of progressing to advanced disease and the accompanying central vision loss. Better, more accurate methods of identifying those at risk are needed. Our approach is to apply simple, inexpensive vision function tests, requiring minimal special equipment, and little time to administer, that can improve the ability to predict AMD progression. Previous research strongly suggests that some combination of such simple tests, in conjunction with existing clinical protocols identifying fundus risk factors, could boost the clinician's chances of prognostic success significantly. To examine these questions, individuals with early AMD will take part in test sessions consisting of vision, motor, and cognitive testing, along with an extensive reading assessment. These measures will also be compared in control groups with no retinal disease and with advanced AMD. Participants will also undergo a comprehensive eye exam by a retinal specialist. Study participants will be followed over time, and analyses will determine the best predictors of advanced disease progression. Understanding the causes of reading problems will allow us to identify the specific skills lacking in people with early AMD, which will aid in better understanding of the course of the disease, and suggest appropriate rehabilitative strategies. The significance of improving predictive ability is two-fold: As emerging AMD treatments that can be applied in the earliest stages of the disease become available, it will be absolutely vital to have appropriate and practical tools to identify which patients should receive them. This is key since all medications have costs and side effects. Second, availability of simple predictive tools will greatly simplify and streamline clinical trials of AMD treatments by reducing the number of subjects needed for statistical power and length of time over which the studies must be carried out.

Public Health Relevance

Health Relevance Statement Age-related macular degeneration, a retinal disease that has devastating effects on vision, is a leading cause of vision loss and blindness in the US. A comprehensive examination of reading performance and other non- standard vision function measures in people with early signs of the disease will improve our understanding of the course of the disease and help guide reading remediation efforts. Furthermore, by identifying eyes at risk for progression to advanced disease with greater certainty than is currently possible and at earlier stages, there is a greater likelihood of saving sight once new preventative or early treatments are in place.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
1R01EY023320-01
Application #
8480769
Study Section
Special Emphasis Panel (BNVT)
Program Officer
Kurinij, Natalie
Project Start
2013-06-01
Project End
2018-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
1
Fiscal Year
2013
Total Cost
$378,693
Indirect Cost
$128,693
Name
Smith-Kettlewell Eye Research Institute
Department
Type
DUNS #
073121105
City
San Francisco
State
CA
Country
United States
Zip Code
94115