Individualized genomics and the future of translational medicine

The age of genomic medicine is upon us. Sixty years have passed since Watson and Crick’s discovery about the double-helical structure of DNA (Watson and Crick 1953). Ten years have passed since the Human Genome Project’s (HGP) completion (International Human Genome Sequencing Consortium 2004). We now witness the translation of this basic science into direct patient care. With the cost of sequencing a human genome rapidly moving toward the $1000 mark, genomic evaluation in the everyday clinical setting is becoming a reality. Genomics has successfully been applied to many clinical areas, including rare disease diagnosis, pharmacogenetics, and a wide range of cancer diagnoses. Large databases and projects characterizing human variation such as the HapMap, the NHLBI Exome Variant Server, and the 1000 Genomes Project have been established and provide a touchstone for the interpretation of clinical genomic data. Despite these and many other milestones, we are still at the dawn of the genomic age. Three billion pieces of the DNA puzzle have been placed on the table, but the puzzle is far from complete. The aim of the journal Molecular Genetics & Genomic Medicine (MGGM) is to not only participate in the assembly of the puzzle but also to help interpret the image as it is revealed, thereby bringing a new level of understanding to human, medical, and molecular genetics. Rapidly evolving genomic technologies have given geneticists the tools to make efficient molecular diagnoses in diseases that had previously gone undiagnosed even after exhaustive genetic and clinical evaluations. At this moment, Online Mendelian Inheritance in Man (OMIM; http://www.omim.org) lists 4861 phenotypes with known molecular bases (Amberger et al. 2011; accessed March 2013). We see examples where a molecular diagnosis obtained from whole-exome sequencing (WES) has led to therapeutic benefit of the patient, such as the discovery of an inhibitor of apoptosis gene (XIAP) mutation that led to the successful allogeneic hematopoietic progenitor cell transplant in a boy with an unusually severe form of Crohn disease (Worthey et al. 2011). Investigations of rare disorders using WES have not only identified the respective causes but have led to biological insights that then impact on our knowledge about human disease architecture and our diagnostic capabilities. These successes have largely focused on single-gene mutations, each with large effect sizes. As whole-genome sequencing (WGS) becomes more affordable and its data analysis more robust, discoveries of this nature are envisioned to become commonplace. Despite the anticipated success of WES and WGS in rare diseases, the common complex diseases, such as some types of cardiovascular disease and behavioral conditions, have not yet been translated effectively into broadly useful clinical information. Our initial high expectations that genome-wide association studies (GWAS) would provide clearer understanding of the inherited basis of common disorders have been tempered by modest effect sizes. Height is an example of a well-studied heritable complex trait (heritability of 0.8) with only a small amount of its variation explained by genetic variants. GWAS identified 54 loci in almost 63,000 people that only explained 5% of height variation (Visscher 2008). One notable example of a GWAS providing a greater than modest association is the increased risk of age-related macular degeneration with certain alleles of complement factor H (OR 2.27; 99% CI 2.10–2.45) (Sofat 2012). Regardless of the largely small effect sizes revealed by GWAS, the information derived from the HapMap Project allowed the power of hypothesis-free GWAS and the ability to map complex disease loci as a tool to provide new information regarding disease mechanisms, contributing to bench-to-bedside efforts. GWAS have also exposed less characterized areas of the genome, as the majority of associated single-nucleotide polymorphic markers reside in non–protein-coding regions. Of the roughly three billion bases of the haploid