Using genomic data to make indirect (and unauthorized) estimates of disease risk.
The number of genetic factors associated with common human traits and disease is increasing rapidly, and the general public is utilizing affordable, direct-to-consumer genetic tests. The results of these tests are often in the public domain. A combination of factors has increased the potential for the indirect estimation of an individual's risk for a particular trait. Here we explain the basic principals underlying risk estimation which allowed us to test the ability to make an indirect risk estimation from genetic data by imputing Dr. James Watson's redacted apolipoprotein E gene (APOE) information. The principles underlying risk prediction from genetic data have been well known and applied for many decades, however, the recent increase in genomic knowledge, and advances in mathematical and statistical techniques and computational power, make it relatively easy to make an accurate but indirect estimation of risk. There is a current hazard for indirect risk estimation that is relevant not only to the subject but also to individuals related to the subject; this risk will likely increase as more detailed genomic data and better computational tools become available.
Queensland Institute of Medical Research, Brisbane, Qld., Australia. dale.nyholt@qimr.edu.au
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D000544:Alzheimer Disease / Q000235:genetics*; D053327:Apolipoprotein E4 / Q000235:genetics*; D001483:Base Sequence; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics* / Q000523:psychology; D005820:Genetic Testing / Q000941:ethics* / Q000706:statistics & numerical data*; D023281:Genomics; D006801:Humans; D008297:Male; D008969:Molecular Sequence Data; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D018570:Risk Assessment; D012307:Risk Factors
D053327:Apolipoprotein E4