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      The predictive capacity of personal genome sequencing.

      Science translational medicine

      Female, Genetic Predisposition to Disease, Genome, Human, High-Throughput Nucleotide Sequencing, trends, Humans, Individualized Medicine, methods, Male, Mathematical Concepts, Models, Genetic, Risk Factors, Sequence Analysis, DNA, Translational Medical Research, Twins, Monozygotic, genetics

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          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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          Author and article information

          Journal
          10.1126/scitranslmed.3003380
          3741669
          22472521

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