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. 2012 May 9;4(133):133ra58.
doi: 10.1126/scitranslmed.3003380. Epub 2012 Apr 2.

The predictive capacity of personal genome sequencing

Nicholas J Roberts  1 , Joshua T Vogelstein, Giovanni Parmigiani, Kenneth W Kinzler, Bert Vogelstein, Victor E Velculescu
Affiliations

The predictive capacity of personal genome sequencing

Nicholas J Roberts et al. Sci Transl Med. .

Abstract

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.

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Figures

Fig. 1
Fig. 1. The fraction of cases (i.e., patients with disease) who would test positive by whole-genome sequencing
For each disease, the maximum and minimum fraction of cases that would test positive using the thresholds defined in table S2 are plotted.
Fig. 2
Fig. 2. Percentage of individuals in the general population who would test positive by whole-genome sequencing
For each disease, the maximum and minimum fraction of individuals in the population that would test positive using the thresholds defined in table S2 are plotted.
Fig. 3
Fig. 3. Relative risk of disease in individuals testing negative by whole-genome sequencing
A relative risk of 100% represents the same risk as the general population, i.e., the cohort risk. Relative risks were calculated using the genometype frequencies and genometype genetic risks that maximized or minimized sensitivity for disease detection.
See this image and copyright information in PMC

Comment in

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