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Results of Nature poll on personal genetic analysis by scientists

Last month we pointed to a poll over at Nature looking primarily at the use of personal genetic tests among scientists (Nature‘s Brendan Maher was kind enough to consult us when designing the poll, so we were able to pass on some of the lessons we learned when doing our own reader survey last year). The results are now in, and Brendan has a brief article taking a look at the results.

Firstly, there was a fantastic response to the survey – nearly 1,600 participants. Of those, 289 (18%) had taken some kind of genetic test; interestingly, a further 54% said they’d be interested in doing so if given the opportunity. The vast majority of genetic tests done were genome scans (50% 23andMe). The motivations of those who had tests done were very similar to those from our readers – intellectual curiosity ranked at the top, with interest in health, genealogy and ancestry ranking lower.

Brendan’s piece has some nice vignettes from survey respondents. He was also kind enough to pass on the raw (anonymised) data to us for further analysis, and we’ll be poking around in there over the next week or so. Some immediately interesting results emerge from the comparison of the results from participants who fell into the “biology” vs “medicine” discipline: of those who had taken genetic tests, biologists were far more likely to have been tested by 23andMe (73.3% vs 47.2%) and were more likely to have cited “intellectual curiosity” as a major factor in their decision (71.1% vs 42.6%), whereas “medicine” respondents were more likely to cite a specific health risk as a major factor (34.4% vs 18.7%), were more likely to have consulted a clinician beforehand (23.0% vs 7.8%) and were more likely to report negative outcomes to testing (8.2% vs 4.8%). Of those who hadn’t yet had a genetic test done, biologists were more likely to be interested in doing so if given the opportunity (74.4% vs 67.6%). Nothing terribly shocking, but some useful insight into the basis of the “culture war” between basic and medical researchers over the issues surrounding personal genomics.

Anyway, kudos to Brendan and the Nature team – and to their readers, of course – for generating such an interesting data-set. No doubt you’ll be hearing more about the results of this survey soon.

Nature poll for scientists on personal genomic analysis

Brendan Maher from Nature has alerted us to a new poll that may well be of interest to many of our readers – an investigation of the attitudes of researchers towards personal genetic testing. Here’s the summary:

We aim to get a sense of how many researchers are actually peering into their own genomes. The responses will be analysed in aggregate to aid in a news story, and no identifying individual information will be used unless you agree to be contacted by a reporter. At the end of the survey you will have the chance to enter our prize draw to win a £100/$150 Amazon gift card.

You can fill in the survey here.

Excessive regulation of DTC genomics will come at a cost

Caroline and I have an opinion piece in this week’s New Scientist arguing that regulators should consider the benefits of personal genomics (in terms of increasing genetic literacy and innovation) before imposing excessive regulation on the direct-to-consumer genetic testing industry. Here’s the take-home message:

We don’t yet know what role personal genomics will play in the future of medicine. However, we do know that it has great potential for innovation and education, and we must ensure that neither excessive regulation nor medical paternalism get in the way.

Unfortunately due to space restrictions several sections of our argument were cut – for instance, we spent some time arguing against the idea of arbitrary divisions of tests into “medical” and “non-medical” categories, with the former requiring supervision of a medical professional to receive results. Here’s the original wording:

Unlike many commentators, including the HGC, we do not support an unsustainable division of tests into separate categories, one for health-related tests that require counselling from a medical professional and another for everything else with no such requirement. It is hard to justify the argument that results suggesting a mildly elevated predisposition to obesity require a professional intermediary to provide support, while those indicating unexpected paternity do not.

In general, we would argue that people should be free to access their own genetic data unless there is good reason to believe that doing so will cause them real harm – and as long as the information is accurate and transparent. Companies should ensure that customers have access to expert advice if they want it, but medical supervision should not be a requirement for access to your own genome.

In a similar vein, if you missed the editorial on DTC genetics in last week’s Economist, you should go read it now. The final two paragraphs warrant quoting in full:

But three things argue against wholesale regulation. First, the level of interference needs to be based on the level of risk a test represents. The government does not need to be involved if someone decides to trace his ancestry or discover what type of earwax he has. Second, the laws on fraud should be sufficient to deal with the snake-oil salesmen who promise to predict, say, whether a child might be a sporting champion. And third, science is changing very fast. Fairly soon, a customer’s whole genome will be sequenced, not merely the parts thought to be medically relevant that the testing companies now concentrate on, and he will then be able to crank the results through open-source interpretation software downloadable from anywhere on the planet. That will create problems, but the only way to stop that happening would be to make it illegal for someone to have his genome sequenced—and nobody is seriously suggesting that illiberal restriction.

Instead, then, of reacting in a hostile fashion to the trend for people to take genetic tests, governments should be asking themselves how they can make best use of this new source of information. Restricting access to tests that inform people about bad reactions to drugs could do harm. The real question is not who controls access, but how to minimise the risks and maximise the rewards of a useful revolution.

It’s great to see these issues getting sensible discussion in the wider media; let’s hope the FDA is paying attention.

Testing for traces of Neanderthal in your own genome

I’m guessing everyone reading this post is familiar with recent research from Svante Paabo’s group indicating that modern humans interbred with Neanderthals during their long co-existence in Eurasia between 30,000 and 80,000 years ago. According to the researchers’ calculations, somewhere between 1 and 4% of the DNA in modern non-African humans is derived from these interbreeding events – in other words, many of us are walking around with Neanderthal DNA sitting in our genomes.

So how much of your genome is Neanderthal? Over at The Genetic Genealogist, Blaine Bettinger takes a look at the options currently available to those interested in digging for Neanderthal ancestry in their own genetic backyard. Blaine notes that one company is already offering a test labelled as looking for Neanderthal ancestry based on a limited number of variable (microsatellite) markers. However, this test doesn’t actually look directly for putative Neanderthal-derived variants; instead, it (rather quaintly) tests for “strong matches between your DNA fingerprint […] and populations identified as “archaic,” that is, whose composition retains the earliest earmarks of out‐of‐Africa genetics.” This is a very rough approach to the problem, to put it mildly.

Added in edit 15/07/10: John Hawks has a justifiably scathing review of the test on his blog; I’ve removed links to the company from this post to avoid giving them extra publicity.

People who have already had their genomes scanned by a company like 23andMe theoretically have sufficient data already available to perform a much higher-resolution analysis. However, sadly there’s not yet any readily available algorithm out there for doing this, despite there being (as Blaine notes) substantial interest for such a test from amongst the 23andMe community.

Seems like there’s some real scope for a DIY genomics tool here. Is anyone out there already working on this? Let us know in the comments.

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