This new genetic study involved complex computational analysis of more than 12 million genetic variations across the human genome, identified 52 variations associated with the disease. By identifying these genetic variations, spread across 34 gene regions, scientists are a step closer to developing diagnostics that identify which patients are at high risk for acquiring the disease and formulating therapeutics either to prevent or treat the disease caused by these genetic variations.
In a quintessential example of precision medicine, an international team of more than 100 scientists from nine countries scanned the genes from more than 33,000 individuals searching for genetic variants responsible for age-related macular degeneration (AMD), the leading cause of vision loss among people age 50 or older.
“The enormity and complexity of studying the genetics behind AMD required a large-scale computational analysis study of the disease that could only be performed by bringing together the world's leading researchers,” explained Jonathan Haines, Ph.D., chair of epidemiology and biostatistics at Case Western Reserve University (CWRU), whose team also helped guide the complex computational analysis of the data from those study participants with advanced AMD and those without AMD.
The findings from this study were published recently in Nature Genetics through an article entitled “A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.”
“The investigation is akin to looking at a Google map of the United States and attempting to pinpoint several leaders and satellite operations in a crime syndicate,” stated co-leader of the study, Anand Swaroop, Ph.D., chief of the National Eye Institute’s (NEI) Neurobiology-Neurodegeneration and Repair Laboratory. “It's possible to find the key players by zooming in and seeing specific regions in rich detail, but first you have to know where to look. Pooling the genetic information from such a large population is what allowed us to look across the genome for possible culprits in AMD, even very small, very rare ones.”
As criteria for their analysis, investigators chose to study both common and rare genetic variations. These genetic variations affect physical traits such as eye color or susceptibility to specific diseases, and due to the millions of genetic variations present in the human genome, it took genetic, computational analysis from multiple centers to pinpoint the variations specific to AMD.
“Almost every study up until now has only looked at common variations that are pervasive in the population,” noted co-lead author Jessica Cooke Bailey, Ph.D., a post-doctoral fellow in the School of Medicine's Department of Epidemiology and Biostatistics at CWRU. “Our robust big data techniques allowed us to look for the rare variations that occur, for example, in one in 1,000 individuals. In the genetics world, those really rare genetic variations are important because those significantly increase the risk of a disease such as AMD in individuals who have them.”
After exhaustively sifting through the genetic data, the researchers discovered 52 genetic variants that were associated with AMD. These variants are located among 34 loci, 16 of which had not been previously associated with AMD.
“If you think of these loci as points on our Google map in our search for the crime syndicate members or the genetic causes of AMD, in some cases they are as big as a zip code, but in other cases they pinpoint an area as narrowly defined as a few houses within a neighborhood subdivision,” Dr. Swaroop added.
Interestingly, 10 of the variants were associated with genes involved in maintaining the extracellular matrix, structural biomaterial between cells that provides support and nutrients. Researchers have theorized that abnormalities within the extracellular matrix occur in people with a subtype of AMD that develops without early-stage signs, or that quickly worsens before such signs are detected
“The possible connection between AMD and these extracellular matrix genes may allow for predictive genetic tests and more effective therapies for people with this type of AMD,” Dr. Cooke Bailey remarked.
“These variants provide a foundation for genetic studies of AMD going forward,” said Dr. Haines. “The next step is to investigate what the variants are doing to the genes and how they affect gene function. Do they turn them on or off? Do they interact with other genes spurring a series of events along a pathway that leads to AMD?”
Now that the scientists have this plethora of genetic information, they believe the next, most logical steps will be functional mechanistic studies to determine why and how key gene variations activate to cause AMD.
“More than 10 million Americans are affected by AMD and more than 2 million individuals over the age of 50 have the advanced disease, adding billions of dollars to healthcare costs,” Dr. Cooke Bailey stated. “With more people entering their senior years, the AMD-affected population will only continue to grow—making this research particularly crucial.”