Progress Toward Personalized Medicine for Age-related Macular Degeneration

Abstract

In our future, a patient will present to our offices with an electronic card bearing his/her medical record and personal sequenced genome. After the clinical examination, how will you respond when the patient asks, “Doc, what can I do to prevent my going blind from macular degeneration (AMD) like my mother?” Even today, we can begin to answer this straightforward, but “loaded” question. Currently, we know that each cell has about 30,000 “nuclear” genes distributed on 46 chromosomes (i.e., 22 pairs of autosomes and 1 pair sex chromosomes) and 37 “mitochondrial” genes encoded in the circular mitochondrial DNA that is passed maternally. Genetic linkage-based studies in families have discovered over 1,300 “singledisease genes” that cause rare diseases with clearly recognized Mendelian inheritance patterns (e.g., autosomal dominant, autosomal recessive and X-linked diseases). However, this methodology fails to identify genetic variations (i.e., risk alleles) that influence an individual’s likelihood of developing a common disease, the rate of disease progression, or the patient’s response to treatment. In the past decade there have been major advances in genomic technologies, bioinformatics, and statistical genetics. These advances have led to significant accomplishments with the Human Genome Project (Available at http://www. genome.gov/10001772 Accessed April 15, 2008) and the International HapMap Project (Available at http://www. hapmap.org/ Accessed April 15, 2008). With these accomplishments and the push to discover genetic variants in common diseases, there has been a shift from the simple monogenic disease model to a complex multigenic and environmental disease model in order to answer this patient’s question. Using genome-wide association (GWA)based studies, there has been considerable excitement to discover genetic determinants that provide insight into disease pathogenesis. Similar approaches can be used to understand variations in treatment response. There are three fundamental components that are shared among GWA studies. First, the genetic blueprint of complex diseases is based on the common disease-common variant (CDCV) model. In other words, there are a limited number of common alleles with each allele contributing a small risk to the common disease in the individual. Second, from a human evolutionary perspective there are very few genetic recombination events or mutations located close to the common, conserved, or “ancient” variants. In other words, there are very few new gene variants between the conserved variants due to the limited interactions among the world populations over time, which reflects admixture of populations. Third, approximately 80% of the human genome represents “conserved” 10 kb regions or haplotypes. Using single nucleotide polymorphism (SNPs)-based GWA