The quest for genes causing complex traits in ocular medicine: successes, interpretations, and challenges

Gene mapping and positional cloning have gained acceptance as state-of-the-art methods to identify molecules that cause common complex diseases. However, the use of specialized technology, varying study designs, and misconceptions about the role of novel findings in genetics has led to confusion among basic scientists and health care professionals alike regarding the importance of these findings in molecular diagnostics and individualized medicine. To alleviate this confusion, the successes achieved in the past few years in mapping of genes for complex traits such as age-related macular degeneration and glaucoma are interpreted in the context of the appropriate population biology framework. The current article veers away from propagating the overly simplistic belief of a linear relationship between a specific gene and age-related macular degeneration, particularly one that equates possession of a specific risk allele as the only precursor to end-stage disease. Ascribing predictive properties to a single gene without consideration of its network partners, timing of action, or environmental correlates argues for a static view of gene action. Modern viewpoints of the mechanisms of action of a gene are contextual and encompass more cohesive frameworks, ranging from the developmental timing of action, to the genomic and environmental milieu. In this regard, gene mapping studies that have been so immensely successful in the gene detection phase of a study provide biased perspectives on the importance of these genes and the corresponding risk alleles in the general population because of their limited sample size and constrained design. To move the field of gene-based diagnosis forward, it will be necessary to conduct additional cohort and longitudinal studies using the original gene finding studies as a knowledge base to develop predictive models. In summary, while we have achieved great successes in finding genes for complex traits, the application of these findings to clinical medicine is not straightforward. The key question of who will develop disease in the future remains.