Translating genomics into the clinic: moving to the post-Mendelian world

The main issue currently facing the translation of genomics research into clinical practice is that it will require researchers, clinicians and patients to make a significant conceptual shift from Mendelian ways of thinking to a post-Mendelian world. Ironically, in this new world, genes have a lesser role as we study ever more complex diseases and traits and begin to understand the interplay of gene-gene and gene-environment interactions and epigenetics. It is nearly 100 years since Wilhelm Johanssen first coined the word 'gene' and posited a relationship between genotype and phenotype. Since then, we have learned that there is a lot more to this relationship than we initially envisaged.Currently, genome-wide association studies increasingly identify the contribution of multiple genetic loci to phenotypes by providing clues as to the biological pathways and interactions involved. However, we are far from knowing how the results of these studies are clinically relevant. As a result, we also do not yet know how to explain these results in a meaningful way to patients.The shift to post-Mendelian genomics will require different ways of thinking about the validation, interpretation and explanation of genomic studies, especially with respect to their application to clinical practice. Recent comprehensive, large-scale studies such as that by the Wellcome Trust Case Control Consortium [1] have been very valuable at connecting biochemical pathways with diseases, such as age-related macular degeneration [2]. The challenge of establishing and replicating genotype-phenotype associations remains, however [3,4], leading to cautions about how to design and interpret genome-wide association studies [5-7].Validation of genotype-phenotype associations is of course critical to the successful translation of genomic data to clinical practice. Basic issues of analytical validity must be addressed, especially as new analytical platforms are developed, such as array comparative genomic hyb