A new method of forensic DNA analysis has created an unexpected headache for scientists investigating the genetic roots of common diseases.
David Craig of the Translational Genomics Research Institute in Phoenix, Arizona, has designed a statistical method that allows the identification of individual DNA profiles from a mixture of DNA of more than 1000 people.
The danger is that the method allows possible violations of the privacy of volunteers in genetic studies. To avoid this, research organisations led by the US National Institutes of Health (NIH) have abruptly pulled genome data from off the web.
Craig's method uses sophisticated algorithms to analyse between 10,000 and 50,000 genetic variants called single-nucleotide polymorphisms, or SNPs. These can be detected using standard DNA microarray "chips".
The SNP technique is unlikely to replace conventional forensic DNA analysis, which identifies individuals using just 13 different, highly variable genetic markers.
However, these markers can be difficult to interpret in samples where DNA from several people is present. So if police need to determine whether a particular individual's DNA is present in a mixed sample, the SNP method could prove valuable.
Craig suggests that the technique might find use in high-profile missing-persons cases - such as the 2007 disappearance in Portugal of the British girl Madeleine McCann. In such investigations, he says, it might reveal whether the person had been present in a particular location, from DNA left behind on surfaces they touched.
But further studies will be needed to see whether the method gives reliable results in samples of DNA that have been biochemically amplified from the tiny quantities that would be present in such circumstances.
SNPs are most commonly used in studies to locate genes associated with susceptibility to disease.
The problem for these studies is that someone armed with an individual's SNP profile - or that of a close relative - could use Craig's new statistical method to determine whether that individual had participated in a genetic study, and whether they were in the group diagnosed with the disease, by analysing information on overall frequencies of each SNP in the case and control groups.
Participants in such "genome-wide association" studies have been told that it was impossible to gain any information about individuals from these summary statistics. So after being informed about Craig's method, the NIH last week decided to remove summary data from its genome-wide association studies from the web (see the NIH statement, pdf format).
Britain's Wellcome Trust, and the Broad Institute in Cambridge, Massachusetts, also took steps to remove their summary data from public view.
"NIH did the right thing in applying the precautionary principle," says Kathy Hudson, director of the Genetics and Public Policy Center in Washington DC.
Scientific journals will now have to consider how to handle the issue, as they typically publish summary statistics online as supplementary information to papers on genome-wide association studies. "Of course we need to think about it," says Monica Bradford, managing editor of Science.
Statisticians at NIH are trying to find ways to release an edited version of the summary statistics without risking a breach of privacy. But for now, scientists who want to obtain these results from NIH will have to apply from them individually, and agree to strict confidentiality rules.
There is a strong demand for the summary data sets, as they provide a quick way for geneticists to check whether an association they have found is borne out in other studies. "Summary statistics are a very powerful away to validate a finding, without having to collect samples from 5000 people, which can take four years," Craig explains.
Even if the NIH hadn't removed the information from public display, the threat to the privacy of research volunteers would have been fairly small, as no information about individuals could be gleaned unless someone already had access to their SNP profile.
In an explanation of its decision posted on the web last week, the NIH also reassured research volunteers that there was never any risk to their financial or other personal information (see the explanation, pdf format).
Journal reference: PLoS Genetics DOI: 10.137/journal.pgen1000167
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