Highlights from day one of the Boston Consumer Genetics Show

Not my highlights, sadly - I would have loved to attend the Consumer Genetics Show but was curiously unable to get anyone to pay for my plane tickets...

Fortunately for me, others have done a sterling job of covering day one of the meeting. The freshest coverage by far is coming in 140-character bursts from Dan Vorhaus and Emily Singer, who are both live-tweeting the conference with gusto (for Twitter afficianados, commentary on the meeting is being aggregated with the hash-tag #CGS). Emily Singer also has an overview piece in MIT Technology Review with the promise of more to come.

Meanwhile Steve Murphy, who isn't at the conference, has taken strong exception to deCODE Chief Scientific Officer Jeff Gulcher's discussion of the utility of genetic data for reclassifying women into risk categories for heart disease.

I also wanted to point to an earlier article from Emily Singer reviewing the state of consumer genomics as a lead-in to the meeting. I particularly liked the final paragraph:

Most direct-to-consumer genetic-testing companies have declined to
release sales figures, so despite the public attention, it's unclear
whether their business models are succeeding. But most people seemed
unconcerned. "If you look at the first commercial transactions on the
Internet, few of the early companies necessarily survived intact, but
the ideas they invented became the industry," says James Heywood,
cofounder of PatientsLikeMe, a company based in Cambridge, MA, that
collects, shares, and analyzes data on patients with different
diseases. "It's like going back to the invention of the computer: was
it the computer that was important, or was it the applications that
were invented to use on it? Who knows what application will effectively
build this new market?"

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I too seem to have been a bit short for the airfare but have found the Twitter and blog postings about the CGS to be quite informative.
DTC genetic tests have come a long way in a short time and the view that there will be an application or advance that will break the market open is probably spot on.
The fact there is even a Consumer Genetics Show indicates the market is gaining momentum but that doesn't mean all is rosey.
For the average consumer the results of a 23andME or deCODE test can be tough to fathom. 'Average' being he key word here because many of the attendees seem to be far from average nor are the bloggers or people posting to Twitter. They're experts.
I've had 23andMe and deCODe tests done and posted the summaries, raw data, and Promethease results to the web and use it for public speaking and to help in raising awareness about genomics. But then I work for a non-for-profit genomics research organization and have experts to call on so I'm not average either.
When confronted with a mass of data, probablities that at first seem scarey (or comforting ) consumers aren't always going to react in a reasonable or informed manner. That's where researchers, clinicians, and policy makers start to get a little twitchy.
There is a fine line between marketing and offering an objective testing service and even when the companies walk the line carefully, you can't count on everyone walking the same line with them.
Looking forward to more post out of #CGS.

Mike

I live in town and couldn't bring myself to pay the registration fee.

Thanks for the collection of information.

Daniel,

Long time [reader] first time [poster].

I just wanted to share what for me were two stand-out moments at the CGS. First was Zak Kohane's discussion of the "Incidentalome"--a great turn of phrase that captures something I've been mulling over myself. (A less eloquent statement of this idea made it into the recent Nick Wade NYT article on genetic risk prediction). Basically, the idea is that even if you have great tests with high clinical validity [accuracy]--which is not the case right now by a long shot with genetic risk models--if you do lots of tests, then your chance of at least one false positive goes up--and so does the risk of unnecessary testing/interventions.

From Zak's JAMA article on the "Incidentalome" (12jul2006):

"Physicians know that as the number of tests increases, the chance that a spurious abnormal test result will arise also increases. They also know that it is difficult to ignore abnormal findings, and they often must embark on a sequence of more expensive tests to investigate the findings."

This was a theme of several presentations: that, despite the potential of "personalized medicine" to reduce costs and improve health, its immediate impact may be to increase costs by leading to increased testing [or just increased demands on clinicians' time explaining why these tests are not clinically useful] without a decrease in disease burden. [See "Raiding the medical commons," JAMA. 2008;300(22):2669-2671].

Kari Stefansson pushed back a little, saying [if I understood correctly] that the risk of false positives is not a problem, as what DecodeMe [etc.] give the consumer are estimates of their risk [not binary tests of high/low risk], and that these estimates are unbiased. I'll concede the last point here, modulo the fact that these estimates are based on current knowledge which is incomplete and changing quickly [cf my NEJM article with David Hunter]. But I don't think providing unbiased estimates of relative or absolute risk solves the problem of the Incidentalome. To me, everybody [after discussions with their clinician, of course] has a set of risk thresholds above which they will take action [if there's an action available]. So in practice you end up with a set of decision rules: do nothing, watch more carefully, intervene aggressively.

The other high point for me was RC Green's talk on the results of the REVEAL (Risk Evaluation and Education for Alzheimer's Disease) study. This is one of the few studies [that I know of] that has measured how folks react to genetic risk testing--whether intensive counseling pre- and post-test minimizes adverse psychological effects or maximizes information recall/understanding, how folks interpret and act on risk estimates. Lots of ink has been spilled about these things, but there has not been much empirical research along these lines--although that is sure to change soon. In his keynote, Francis Collins highlighted this [empirical research into how best to convey information from genetic tests, how these tests are used by physicians and patients] as an important area for future research.

Thanks for the coverage of the meeting. I picked up the brochures from Interleukin genetics but missed the whole Amway angle.

By Peter Kraft (not verified) on 12 Jun 2009 #permalink

Hi Peter,

Great comment! In fact, so good that I think it requires its own post - hopefully this afternoon.