Advancing Genetics Through the AMDgene Consortium

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ABSTRACT Age-related macular degeneration (AMD) is the most common cause of severe vision loss among individuals over age 50 in the U.S. with millions of individuals around the world suffering severe vision loss. The influence of genetic variation on AMD is strong and through recent technological advances the genetic etiology of risk for AMD is being deconstructed. Independent studies have identified and confirmed variations in multiple genes that strongly affect risk to AMD, including CFH, HTRA1/ARMS2, C2/CFB, and C3 explaining a significant portion of the genetic risk for AMD. Initial efforts at genome-wide association studies have identified and/or confirmed several additional loci of more modest individual effect (CFI, LIPC, TIMP3), with many more loci providing suggestive associations. However, a substantial portion of the genetic architecture remains unexplained and detailed examination of effects specific to subtypes of AMD have been lacking. To address these deficiencies very large sample sizes of well characterized cases and controls and families are needed. Over the past year we have formed the AMDgene consortium to combine both samples and expertise. The initial goal of the consortium was a meta-analysis of existing GWAS data in a combined dataset of over 9,000 cases and 49,000 controls. Preliminary findings have identified new genome-wide significant loci. We have chosen an approach that maintains the primary data at each site, which promotes continued engagement by all participating sites, is cost and time efficient, and avoids potential consent, ethics, and privacy issues of sharing data collected under a wide variety of informed consent. The primary goal of this proposal is to support the AMDgene consortium effort through the following specific aims (1) Coordinate the activities of the AMDgene Consortium; (2) Add new datasets and augment current datasets; (3) Perform detailed meta-analyses on existing and new datasets:; and (4) Perform detailed secondary analyses on these data.