Even before the initial phases of the HGP were complete, the inception of the “postgenomic era” was claimed (Scangos 1997
). Although a scientific achievement of Herculean importance, the HGP provided only a single haploid genome sequence representing an individual who was healthy at the time the DNA sample was obtained. Countless questions concerning genomic variation among populations with differing ancestry, among persons afflicted with heritable disease, and even among healthy individuals within a family remained unanswered. The continuing insights provided by the International HapMap Project (International HapMap3 Consortium 2010
), 1000 Genomes Project (The 1000 Genomes Project Consortium 2010
), and other genomic studies large and small—and the new questions that arise from this work—remind us that we are most certainly in the genomic era, and that, as personal genomes are probed in various ways, personal genomics is becoming a reality.
Two current challenges that must be overcome are an incomplete reference genome (The 1000 Genomes Project Consortium 2010
) and incomplete or incorrectly annotated mutation databases. Particularly in the case of predictive genomic testing, it will be of the utmost importance for clinicians to thoughtfully consider the disease-causing potential of rare or novel mutations in view of published evidence. Prudent questions should include: did a study or studies reporting a mutation as disease-causing fail to find it in a statistically significant number of appropriately selected controls? Might there exist protective variants that reduce penetrance in certain ethnic groups or individuals? Have healthy family members been tested? Has mosaicism been considered? Has the patient’s mutation been confirmed by a second methodology? Wheeler et al. (2008)
, in sequencing the genome of an apparently healthy adult, found multiple risk alleles and purportedly disease-causing variants, and Lupski et al. (2010)
, in a patient with Charcot–Marie–Tooth disease, identified a purportedly pathogenic variant documented in a mutation database as being associated with a “persistent vegetative state;” these studies indicate that the above questions will need to be answered even in the case of screening and carrier testing.
Physicians must consider the clinical utility of a genomic test before
it is ordered. This is no different from ordering traditional medical tests. Unfortunately, in any genomic panel, the utility of each individual result will depend on the locus tested and the variant detected. Therefore, clinicians should become familiar with each component of a panel test and decide, in consultation with the patient, whether ordering it would be of greater potential benefit than harm. Given the vast amount of genomic variation that exists among healthy individuals (The 1000 Genomes Project Consortium 2010
; Conrad et al. 2010
; International HapMap3 Consortium 2010
), it is likely that no result of a genomic test will be completely ‘normal’ (i.e. completely free of carrier mutations, risk alleles, variants of unknown significance, or disease-causing mutations with reduced or age-dependent penetrance). Findings such as these may be unsettling to patients and should be considered before any genomic test is utilized.
We have attempted to provide evidence for both the promise and limitations of whole-genome resequencing and its potential for genomic medicine. This technology will soon become commonplace in both research studies and clinical practice. Even the most cheaply and easily obtainable sequence data requires proper analysis—a current and future challenge (Mardis 2010
). For example, one current difficulty for sequencing-based mutation detection is the identification of genomic inversions and variants within or consisting of repeated sequences. Another such hurdle to overcome is assigning significance to mutations found in non-coding regions of the genome (i.e. establishing the genomic code). Yet another is making sense of genomic contributions to complex traits: might multiple common mutations with minor effects interact to manifest a phenotype? Or might oligogenic inheritance in the individual with one or a few variants of major effects—but tremendous genetic heterogeneity in the population of patients—be at play? And what of gene–environment interactions? Both innovative bioinformaticists and computational biologists will be required to meet these and similar challenges.
The neurogenomics community—composed of clinicians, scientists, informaticists, and even patients and healthy volunteers—should be proud of the accomplishments of the past and excited about the prospects of the future to improve human quality of life and explain some of the mysteries of the human nervous system and brain—our most unique and defining organ.