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Genetic Variation and Human Vision
Summary: Edwin Stone's research is focused on inherited eye diseases. In collaboration with Val Sheffield (HHMI, University of Iowa), he identified a number of genes responsible for important human eye diseases and characterized these in large international patient populations.
Our laboratory is interested in understanding how small variations in the genes of human beings can result in large variations in their vision. We are especially interested in finding and characterizing genes that are involved in three classes of human eye disease: macular degeneration, glaucoma, and photoreceptor degeneration (retinitis pigmentosa). We are also very interested in strategies for bringing new genetic discoveries to the clinic as rapidly as possible.
Macular Degeneration
Age-related macular degeneration (AMD) is a term used to refer to a group of disorders that are collectively the most common cause of irreversible severe vision loss in developed countries. There is ample evidence that genes play a significant role in these diseases, and many investigators believe that trying to identify these genes represents the most promising path to an improved understanding of the cellular and molecular mechanisms of these conditions. In the past decade, our laboratory, together with that of Val Sheffield (HHMI, University of Iowa), studied several large families affected with clearly heritable early-onset forms of macular degeneration in the hope that the genes that cause these diseases would lead us to the genes responsible for the more common late-onset disorders. For example, in 1992 we mapped the gene responsible for Best disease to chromosome 11, and in 1994 we mapped a gene for a more severe form of macular disease (Stargardt-like dominant macular dystrophy) to chromosome 6. In 1996 we mapped the gene responsible for the macular disease malattia leventinese to chromosome 2, and three years later, we identified the gene (EFEMP1) and showed that it encodes an extracellular matrix molecule known as fibulin 3.
Despite the similarity between malattia leventinese and typical AMD, we did not find any disease-causing variations in EFEMP1 when we screened more than 400 patients with AMD. However, when we evaluated five other members of the fibulin gene family in more than 400 AMD patients and 400 controls, plausible AMD-causing mutations were observed in all five genes (although the only gene for which the findings were statistically significant was fibulin 5). We found seven different fibulin 5 mutations among the AMD patients and none in controls (p<0.01). To identify still more AMD-causing genes, we are now evaluating 25 additional genes that encode extracellular matrix constituents. We are also using our fibulin gene findings as the basis for creating both murine and primate models of AMD, hoping that such models will not only teach us more about the pathogenesis of the disease but will also allow us to develop some novel therapies.
Glaucoma
Glaucoma, the second leading cause of irreversible blindness, is also similar to macular degeneration in four other important ways: (1) it becomes more prevalent with increasing age, (2) the cells that die are in the retina, (3) it is a collection of many similar diseases, and (4) it has a significant genetic component. For the past 15 years, our laboratory has studied the genetics of glaucoma. One of the major successes of this effort was the identification of the myocilin gene, the first gene associated with human glaucoma. We initially used positional cloning techniques to study large families affected with juvenile-onset glaucoma and discovered that mutations in the myocilin gene cause most cases of this relatively rare condition. Next, the availability of DNA samples from more than 2,500 well-characterized glaucoma patients allowed us to evaluate the role of the myocilin gene in the most common form of glaucoma, primary open-angle glaucoma (POAG). We have demonstrated that nearly 4 percent of all open-angle glaucoma worldwide is caused by mutations in this gene. Moreover, one variant, Gln368STOP, is responsible for glaucoma in nearly half of the affected individuals in these studies and represents the most common known cause of heritable glaucoma.
More recently, in collaboration with Abbot Clark and his colleagues (Alcon Laboratories) and Val Sheffield, we have explored the mechanism by which mutations in the myocilin gene cause glaucoma. Using a cell culture system, we have shown that wild-type myocilin protein is secreted, while mutant protein is retained within cells. We have replicated this in vitro finding with studies of surgical tissue samples from patients known to harbor glaucoma-causing myocilin mutations. Our studies indicate that abnormal intracellular accumulation of mutant myocilin protein is central to the development of glaucoma in individuals harboring myocilin mutations. We have investigated the process leading to intracellular retention of mutant myocilin, and these studies suggest that mutations in myocilin may cause glaucoma via an interaction with a peroxisomal targeting protein.
A major aim of our laboratory remains the identification and characterization of new glaucoma genes. We have developed a high-throughput system for screening large numbers of patients for glaucoma-causing mutations in dozens of candidate genes. Since disease-causing mutations are not evenly distributed across genes (they are concentrated in specific portions of genes, including promoter sequences, functional domains, and highly conserved sequences), we created a bioinformatic strategy to use gene annotation to focus our mutation-screening efforts on gene segments with a high probability of harboring disease-causing mutations and to avoid low-probability regions. We evaluated this method by using it to analyze 1,924 genes that collectively harbor 27,750 previously published mutations. Nearly 50 percent of the genes were recognized as disease-causing after screening less than 10 percent of their complete coding sequences. This suggests that bioinformatic prioritization of mutation screening will significantly accelerate disease gene identification through more efficient use of screening resources.
eQTL Mapping
Recent advances in microarray technology and bioinformatics have made it possible to perform experiments that examine the expression of thousands of genes in related individuals and to use the resulting data to identify the chromosomal locations of the genetic elements that are responsible for gene expression variation among individuals. This technique is known as expression quantitative trait locus (eQTL) mapping. To gain a broad perspective of mechanisms of gene regulation in the mammalian eye, and to use this perspective to find new genes that cause human eye disease, we embarked upon a large eQTL mapping experiment in collaboration with Val Sheffield, Thomas Casavant, Jian Huang, and others at the University of Iowa. We first crossed two well-characterized and highly inbred rat strains to generate 120 second-generation animals. The whole eyes from each of these rats were then individually analyzed with Affymetrix microarrays to assess the expression levels of approximately 31,000 genes. Genotyping with short tandem repeat polymorphisms was then performed to determine the genotype of each animal at more than 400 genetic markers evenly distributed across the genome. Two types of analyses were performed with the resulting data: (1) genetic linkage analysis to look for relationships between marker locus and expression and (2) pairwise analysis of each gene with all other genes to identify correlated variations in gene expression.
Of the 31,000 probes on the array, approximately 16,000 exhibited sufficient signal and variation in expression among the 120 F2 animals for reliable analysis. Significant linkage to at least one genetic marker was detected for thousands of genes. Both cis- and trans-acting loci were identified. The pairwise correlation analysis revealed clear relationships among genes involved in related functional pathways (glycolysis, phototransduction, etc.), which suggests that this approach will make it possible to detect currently unknown gene expression networks involved in human eye disease.
Nonprofit Genetic Testing
One of the major motivations for clinician scientists to search for and characterize disease-causing genes is the possibility that their discoveries will lead to improved diagnosis and treatment for their patients. In principle, the day a new disease gene is discovered, one is in a better position to diagnose an affected patient than the day before. In practice, however, there are significant obstacles to the development and widespread deployment of a practical genetic test for a rare disease. The main problem is that the rarity of a disease often limits the profitability of a test and makes it less likely that a commercial firm will develop and maintain it.
In the past few years, we have developed a nonprofit strategy for delivering affordable, clinically useful genetic tests for inherited eye diseases on a national scale. The key features of this strategy include (1) a multiplatform approach, (2) a focused testing effort that combines detailed clinical data and empirically derived mutation detection probability distributions, and (3) objective estimation of the pathogenic probability of observed variations before they are reported to referring physicians. More details about this effort can be found at www.carverlab.org.
This work was supported in part by the National Eye Institute, the Foundation Fighting Blindness, the Carver Endowment for Molecular Ophthalmology, and the Grousbeck Family Foundation.
Last updated: April 28, 2008
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