The Predictive Capacity of Personal Genome Sequencing

A statistical method applied to monozygotic twin data assesses the ability of whole-genome sequencing to predict disease risk in the general population. Is It All in Your Genes? Imagine that everyone at birth could have their whole genome sequenced at negligible cost. Surely, this must be a worthwhile endeavor, given the list of luminaries that have already had this sequencing completed. But how well will such tests perform? Will we be able to predict what diseases individuals will develop, and die from, right from birth? In a study that seeks to answer these questions, Vogelstein and his colleagues present an unbiased assessment of the capacity of whole-genome sequencing to provide clinically relevant information assuming that future research will allow us to understand the significance of every genetic variant. Using previously published data on twins and a new mathematical framework, Vogelstein and his co-workers were able to estimate the maximum capacity of whole-genome sequencing to predict the risk for 24 relatively common diseases. They show that most of the tested individuals could be alerted to a predisposition to at least one disease. However, in any given individual, whole-genome sequencing will be relatively uninformative for most diseases, because the estimated risk of developing these diseases will be similar to that of the general population. Thus, for most patients, genetic testing will not be the dominant determinant of patient care and will not be a substitute for preventative medicine strategies incorporating routine checkups and risk management based on the history, physical status, and life-style of the individual. New DNA sequencing methods will soon make it possible to identify all germline variants in any individual at a reasonable cost. However, the ability of whole-genome sequencing to predict predisposition to common diseases in the general population is unknown. To estimate this predictive capacity, we use the concept of a “genometype.” A specific genometype represents the genomes in the population conferring a specific level of genetic risk for a specified disease. Using this concept, we estimated the maximum capacity of whole-genome sequencing to identify individuals at clinically significant risk for 24 different diseases. Our estimates were derived from the analysis of large numbers of monozygotic twin pairs; twins of a pair share the same genometype and therefore identical genetic risk factors. Our analyses indicate that (i) for 23 of the 24 diseases, most of the individuals will receive negative test results; (ii) these negative test results will, in general, not be very informative, because the risk of developing 19 of the 24 diseases in those who test negative will still be, at minimum, 50 to 80% of that in the general population; and (iii) on the positive side, in the best-case scenario, more than 90% of tested individuals might be alerted to a clinically significant predisposition to at least one disease. These results have important implications for the valuation of genetic testing by industry, health insurance companies, public policy-makers, and consumers.