participant-driven research

Why I'm releasing my genetic data online [Genetic Future]

sb admin — Tue, 12 Oct 2010 06:45:00 +0000

Why I'm releasing my genetic data online [Genetic Future]

Back in June I launched a new blog, Genomes Unzipped, together with a group of colleagues and friends with expertise in various areas of genetics. At the time I made a rather cryptic comment about "planning much bigger things for the site over the next few months".

Today I announced what I meant by that: from today, all of the 12 members of Genomes Unzipped - including my wife and I - will be releasing their own results from a variety of genetic tests, online, for anyone to access. Initially those results consist of data from one company (23andMe) for all 12 members; deCODEme for one member; and Counsyl for two of us (my wife and I). As the project proceeds, we plan to obtain and release the results from a far wider range of genetic tests, up to and including complete genome sequences.

In all, the group is currently releasing over 7 million pieces of genetic data mined from our own genomes. Anyone can download the data in raw form, or view it on a custom browser that two of the group assembled using the open-source JBrowse software. Already the data is being used: blogger Dienekes yesterday published an analysis of our ancestry using his own program, EURO-DNA-CALC.

We have plenty more planned over the next few weeks, including discussion of the ethical issues associated with releasing data publicly, especially given the potential impact on family members. We'll also be presenting analyses of our own data: many of us are active researchers in genetics, and relish the opportunity to apply our research tools to our own genomes. We'll be releasing software code allowing others to run the same analyses on their own data.

So, why on Earth are we doing this?

I summarised some of the key motivations for members of the group in my Unzipped announcement post:

we want to share the results of scientific analysis of our own genomes, and as proponents of open data access most of us believe that doing good science means releasing complete data for others to investigate;
we hope that releasing our data publicly will help to guide useful discussions about genetic privacy and the benefits, risks and limitations of genetic information in general;
many of us believe that the ideal resource for genetic research is large open-access, non-anonymous research databases such as the Personal Genome Project, and that sharing linked genetic and trait information openly with the wider community is a public good - and we hope that our own experiences will encourage others to participate in open research projects;
we all believe that many of the fears expressed about the dangers of genetic information are exaggerated, and see this project as an opportunity to have a constructive public discussion about the truth behind these fears;
given the ease with which a dedicated snoop could obtain genetic information surreptitiously (via shed skin, hair or saliva, for instance), some of us argue that the whole notion of genetic privacy is illusory anyway - while releasing our data online makes it easier for people to get hold of it, this is a difference of degree rather than kind.

I wanted to spend a bit of time here expanding on that third point, as this is probably my own primary motivation for engaging in the project.

Any researcher working in genetics or genomics will be all too familiar with the cumbersome bureaucratic obstacles associated with subject privacy and anonymity. Under the traditional research model subject anonymity and data privacy must be protected fiercely, and that leads to substantial hurdles in two key areas: firstly, data sharing between researchers is hindered by the need to ensure that data privacy is maintained; and secondly, layers of protection on subject anonymity mean it is extremely difficult to return research results to participants, even when those results might have health implications.

This is not to say that huge advances in data access have not been made over the last decade, particularly in the field of genomics. Both individual researchers and funding bodies (notably the Wellcome Trust and NIH) have done a commendable job of ensuring that many large genomics data-sets are made available to other researchers through large databases and data access agreements.

However, can we go further? Researchers such as George Church advocate a bold alternative model: recruit research participants who are willing to share their data completely openly with the world. Find large enough numbers of people willing to sacrifice their privacy for public good, and you suddenly have an amazingly powerful resource: a data-set that can be analysed by any researcher in the world with access to the internet, including participants who can play an active role in the research process.

It can't be emphasised enough just how powerful such a resource would be. Right now, virtually all human genetic and medical data is effectively locked away behind tight consent agreements. That means a given data-set only has a certain number of eyes passing over it, with a restricted circle of expertise; one cohort's data might contain valuable insights into the mechanisms by which cholesterol affects heart disease, but if the researchers holding the keys are eye specialists those will probably never be uncovered.

Science moves fastest when people from diverse backgrounds are allowed access to rich data-sets. The closer we hew to the traditional model of tightly restricted access to human data, the slower we will uncover the associations we need to move into the era of personalised, evidence-based healthcare.

Are there enough people in the world willing to forego their privacy in the name of science? That remains to be seen, but flagship studies like the Personal Genome Project - which seeks to recruit 100,000 volunteers willing to share their genomes and clinical data with the world - are already suggesting that this number is far higher than many would have expected. However, visceral opposition to the idea of releasing such information - based often on an exaggerated sense of the power of genetic data, or its potential for abuse - continue to hold sway over the vast majority of the public.

We're under no illusions here: the data from the 12 of us in Genomes Unzipped aren't in and of themselves of tremendous scientific value. However, if we can get people starting to think about the genuine public good that can be achieved by sharing their data with science, and to weigh that good against a realistic sense of the potential harms, then the project has been a success.

Edited 13/10/2010 to clarify that major progress has been made in data-sharing agreements over the last decade, especially in genomics - I apologise to anyone who interpreted my views as minimising the work that has been done in this area.

sb admin Tue, 10/12/2010 - 02:45

Why I'm releasing my genetic data online

dgmacarthur — Tue, 12 Oct 2010 06:45:00 +0000

Why I'm releasing my genetic data online

So, why on Earth are we doing this?

I summarised some of the key motivations for members of the group in my Unzipped announcement post:

we want to share the results of scientific analysis of our own genomes, and as proponents of open data access most of us believe that doing good science means releasing complete data for others to investigate;
we hope that releasing our data publicly will help to guide useful discussions about genetic privacy and the benefits, risks and limitations of genetic information in general;
many of us believe that the ideal resource for genetic research is large open-access, non-anonymous research databases such as the Personal Genome Project, and that sharing linked genetic and trait information openly with the wider community is a public good - and we hope that our own experiences will encourage others to participate in open research projects;
we all believe that many of the fears expressed about the dangers of genetic information are exaggerated, and see this project as an opportunity to have a constructive public discussion about the truth behind these fears;
given the ease with which a dedicated snoop could obtain genetic information surreptitiously (via shed skin, hair or saliva, for instance), some of us argue that the whole notion of genetic privacy is illusory anyway - while releasing our data online makes it easier for people to get hold of it, this is a difference of degree rather than kind.

I wanted to spend a bit of time here expanding on that third point, as this is probably my own primary motivation for engaging in the project.

dgmacarthur Tue, 10/12/2010 - 02:45

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diy genetics

genomes unzipped

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participant-driven research

Personal Genome Project

transparency

A short but glorious rant

dgmacarthur — Tue, 24 Nov 2009 17:30:00 +0000

A short but glorious rant

Misha Angrist has a very brief but eloquent rant in response to the genomics nay-sayers in this Nature News piece on the bankruptcy of deCODE Genetics.

Here's a taste:

I agree: GWAS is of limited value and this probably contributed to deCODE's demise. But whatever deCODE's fate, if whole human genomes can be sequenced for < $2000, isn't it about time we stopped kicking GWAS's ever-stiffening corpse? Second, just because something is not a medical necessity, does it follow that it is worthless?

Here's the rest.

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dgmacarthur Tue, 11/24/2009 - 12:30

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if whole human genomes can be sequenced for $2000, isn't it about time we stopped kicking GWAS's ever-stiffening corpse?

Does she just mean hey-- let's forget about it it's old news? Well on the one hand there are still plenty of me too GWAS studies appearing last time I looked.

On the other hand perhaps our experience of GWAS should inform how we continue with genome sequencing.

Second, just because something is not a medical necessity, does it follow that it is worthless?

No, but no-one is making this strong statement. Rather they are making a statement questioning it's cost benefit ratio (i.e. high cost little benefit). My own feelings are that the initial GWAS studies were important and pioneering but once it became clear that they seldom uncovered key or medically useful heritable traits, then its use should have diminished as the costs should have been seen to outweigh the benefits of spending the money on other approaches.

Clearly however Nature Genetics feel that if something was expensive, high-tech- and time consuming then it belongs in their journal regardless of the interest of the result.

Regarding WGS its clear that this is very powerful for finding high penetrance mutations at relatively low cost. Pioneering studies will no doubt tell us how good it is at finding low or medium penetrance variants from large banks of patients. Once we know we should sit down and question whether we have got value for money before pursuing this willy nilly for the next 5 years.

Hi Stephen:

First, a slight correction: Now that I've had my genome sequenced, I can say definitively that I do indeed have a Y chromosome, however humble and shrinking it may be (I'd hate to have to change my blog to "GenomeGirl" at this stage of the game).

1) I think it's important to distinguish between GWAS as research and GWAS as a means to make solid predictions about traits in the absence of other information. I'm saying that to keep belittling GWAS for its failure to deliver the latter has, IMHO, become tedious. Maybe I read the New England Journal too much.

2) "No one is making this strong statement." I would need more than two hands to count the number of clinical geneticists I've interviewed for my book, seminars and meetings I've attended, and screeds I've read that either explicitly say or insinuate that, for the moment, personal genomics is essentially worthless. I'd be happy to send you a reading list.

3) "Value for money"...Prior to the launch of the Human Genome Project, the critics complained that the HGP would be too expensive and deprive small science (aka "real science") of scarce resources. Today, despite genuine disappointment in genome-based drug development, diagnostics, GWAS etc., I'm hard-pressed to find anyone complaining about the $3 billion we spent on the HGP. I'd say that at $2000 a pop, pursuing WGS "willy nilly" is exactly what we should be doing.

The problem with GWA studies is that they have been done by geneticists with very little account of epidemiological principles eg misclassification, confounding and the effects of incomplete penetrance. To collect thousands of cases and believe that these represent the same gene effects is far too simplistic. The cases should be subclassified based on biochemical, histological or physiological grounds - not all breast cancer is the same disease and different genes will be relevant. To then gather controls (ie someone not affected) in the belief this will represent those not genetically disposed to the disease in question is too stupid for words. None of these studies have considered the role of environment on gene penetrance. This means the controls are a mix of peolple who might some day get the disease in question or someone with susceptibility genes who has not had sufficient environmental exposure for their genotype to express the illness. The controls in these studies are poorly selected, poorly defined and full of potential cases. Defining cases based on a "clinical diagnosis" is according doctors far more in sight into disease pathophysiology than they deserve. Until GWA studies are better designed using better phenotypes, then they will fall far short of their potential.

Rob

Misha
Apologies for misinterpreting your name.
1) Despite your clarification I'm confused as to your meaning. GWAS means 'genome wide association study'-- which take at least hundreds and more likely thousands of cases. Personal genomics seems to be what you mean.
2) I'm unconcerned by people who want to have a SNP chip done for them. Personally I see it as an interesting medical curiosity but -- except in very rare cases--you would get far more predictive info from a few simple blood tests.
3) The human genome project is nothing like GWAS. The first was a pioneering project that invented all our modern sequencing technologies, made possible all high throughput techniques and produced a blueprint for us to compare all personal genomics against. Likewise the HapMap project, the ENCODE project, and even the 1000 genomes project are all important pioneering attempts to understand variation and meaning within the genome. GWAS for weak heritable traits is just flogging a dead horse. My fear is that even if WGS proves equally poor at finding the 'missing heritability' we will continue to flog the dead horse -- but with a new whip.

Rob,

So your argument is that the major problems with GWAS are:

1. Incomplete penetrance of disease risk variants;
2. Heterogeneity of disease phenotype in cases;
3. Presence of unknown disease cases in control cohorts; and
4. Gene by environment interactions.

Every single one of these issues is discussed at length in the GWAS literature. In some cases (e.g. incomplete penetrance) the issue is explicitly accounted for in the analysis of GWAS data, while in others (e.g. presence of cryptic disease cases in the control cohort) the magnitude of the problem has been modelled and shown to have relatively small effects on power for most diseases. Disease heterogeneity is being tackled by increasingly more sophisticated endophenotype analyses. Gene by environment interactions will be extremely difficult to tease out, but a lot of ink has been spilled on this issue in the literature, and very large longitudinal cohort studies will provide data to help start teasing these things out.

There are plenty of problems facing GWAS, just as there are for any other scientific technique. However, the notion that these problems are being ignored by the researchers doing the studies is totally false.

GWAS for weak heritable traits is just flogging a dead horse.

The heritability of a trait has little to do with the underlying genetic architecture. Recall that human height has a heritability of ~80%, but it influenced by many loci of small effect, while (for example) macular degeneration has lower heritability (see twin study here--50% concordance for MZ twins, and 25% concordance for DZ twins) but is influenced by at least one locus of large effect.

It a trait is heritable, the only way to see what the genetics underlying it is like is to look (more or less).

Dear All,

1. In spite of the tremendous efforts carried out by the scentific and very clever medical communities during centuries, the pathogenesis of complex diseases is mostly unknown.
2. GWAS is a consequence, and essentially derived, from the Human genome project. To date is the most powerful (and unbiased) strategy to pick up genes for complex diseases.
3. GWAS is based on epidemiological and statistical methods and theories (the same technologies employed to discover the relationships between smoking and lung cancer)
4. We are facing with a huge amount of data and variables and we are looking for the best methods to organize and integrate the information. The idea is to improve the knowledge of many complex traits. This is the true challenge irrespective you are employing hundred thousand variables (GWAS) or complete genomes (3 billion variables per individual).
5. Most of GWAS researchers are working into a multidisciplinary teams ie integrating clinical, molecular, epidemiology, statistical, informatics, mathematics researchers.
6. Genetics research is not panacea for medicine is just a novel technology that HAVE TO HELP US to improve the management of disease and health states.
7. So we are not flogging a dead horse, we are just applying new technologies (as usual in medical research) to discover whether or not that new methods can help us to prevent, diagnose and treat medical problems without any solutions to date.

GWAS was originally used to discover genes that are involved in complex diseases. The facts show that it does this job superbly, over 200 new loci were "discovered" in the last few years compared to less than a hundred discovered in the last 30 years. This gives a lot of new targets for researcher to conduct research about how these new loci are functionally linked to the diseases.

We should expect that as the sample size of GWAS increases, we will have the statistical power to detect rarer variants that can cause diseases. I believe that then more heritability can then be explained.

But if you are talking about applying GWAS results to personal genomics, then that's another story. But this is not what GWAS was set out to do in the first place.

In regards to the above comments, which company offers a $2,000 fully sequenced human genome?

I really, really like the Single Molecule Sequencing approach (http://www.helicosbio.com/), given how important micro RNAs are to protein expression. When might this technology be available for the masses (the $1,000 personal genome)?

I have A LOT of relatives with cancer and severe cardiovascular disease, despite a healthy lifestyle... after a lot of genetics courses including human pedigrees, I am anxious to know my genome.

The $2000 figure is misleading - Complete Genomics recently reported sequencing a human genome at this cost, but the figure only includes reagent costs. The cheapest retail whole genome sequence currently available is $48,000 from Illumina, but it's likely that sequencing will become available for well below $10,000 in 2010.

I would concede that if we're talking about a whole euchromatic human genome sequence then yes, $2000 is still misleading. But if Knome is doing exomes for $24k, I expect that DIYbio types will be doing their own exomes within a year. I don't think anyone doubts Daniel's prediction.

The other point that bears making is that if we're talking about finding disease susceptibility genes, a whole genome is probably gratuitous in most cases. I would bet dollars to donuts that if you asked someone working on your favorite common disease what genomic data would be most useful to have from patients, she would be more likely to want sequence from a list of 50 or 100 or 1000 genes than a complete diploid sequence at high coverage.

We're all becoming cyborgs anyway. Rant or no.

Thanks to Misha and Daniel for these great posts.

I have to point out to Stephen (who apologized for "misinterpreting" Misha's name) that the name Misha is an extremely common male nickname for Michael or Mikhail in Russia and elsewhere - similar to Mike here in the US. It helps to pay attention.

A friend told me about this link. Looks like deCODE is not fully dead by now.

www decodeme com / data-upload

What are the lessons we can learn from deCODEme's demise?

23andMe presents novel genetic associations at American Society of Human Genetics meeting

dgmacarthur — Sun, 25 Oct 2009 04:30:26 +0000

23andMe presents novel genetic associations at American Society of Human Genetics meeting

It's been an intensive week of genomics here at the American Society of Human Genetics meeting, and I haven't been able to grab time to blog as much as I'd have liked. In fact there's a whole load of genomics news I'll be trying to cover in some detail over the next couple of weeks; for the moment, though, I couldn't let today's presentation from personal genomics company 23andMe go by without at least some comment. (For other coverage of the conference, do check out Luke Jostins' blog coverage and the stream of live analysis on Twitter.)

The 23andMe presenter (Nick Eriksson) delivered an overview of the potential of the 23andMe cohort for association studies: all 23andMe customers have genetic information for over 500,000 common genetic variants, and they are also encouraged to provide self-reported phenotype data on a wide range of traits ranging from the presence of detached earlobes to longitudinal tracking of Parkinson's disease symptoms. Eriksson reported that the company now had sufficient numbers of returned surveys to perform genome-wide association studies for 22 traits, with sample sizes ranging between 2500 and 6000 individuals - reasonable sample sizes for an initial look at the genetic architecture of a complex trait.

The company seems to be doing a reasonable job of identifying and controlling for the various potential confounders that plague genome-wide association studies, such as population structure. However, 23andMe faces an unusual challenge that standard academic GWAS consortia don't: the possibility that a subject will give a biased trait report after seeing their own genetic data.

This was powerfully illustrated by results from the "athlete gene" ACTN3 (a gene close to my own heart). There was no association between the athletic performance-associated variant in this gene and self-reported sprinter/endurance preference in individuals who hadn't seen their genetic data - but in individuals who had already seen their genotype there was a marked shift towards carriers of the "sprint" or "endurance" allele self-identifying with those respective categories. In other words, people were altering their self-reported athletic affiliation on the basis of their genotype; Eriksson estimated that around 25% of individuals must be shifting their self-identification to explain the effect, a staggeringly large number.

Eriksson played down the potential impact of this effect, but this is still a rather worrying finding for a company relying on self-reported (and often quite subjective) phenotype data from a customer base that has often peeked at their genetic data before ever filling in a survey; at the very least there is potential for inflation of apparent association with known markers already in the 23andMe database. One way around this might be to provide some kind of incentive for customers to complete phenotype surveys before they ever see their genotype data, perhaps by providing discounts on future product updates.

Aside from this niggling concern, the major message from the talk is that 23andMe's approach works in terms of generating genome-wide significant associations for complex traits: the company has successfully replicated a series of known associations with eye, skin and hair colour, for instance. More interestingly, 23andMe has also nailed down a handful of genuinely novel genetic associations: a massively significant association between an olfactory receptor region and "asparagus anosmia" (the inability to smell asparagus in one's own urine), and two regions associated with hair curl.

These traits seem pretty trivial, but this is precisely the sort of area where 23andMe will be able to out-compete academic consortia, and these types of associations are also extremely (perhaps perversely) attractive to personal genomics customers; it's just cool to be able to see the region of the genome that underlies a trait you can see in yourself, and to follow the inheritance of these traits through a family. These types of associations won't contribute to clinical genetics, but they are likely to non-trivially boost 23andMe's appeal to consumers.

Will 23andMe be able to uncover novel associations with a greater relevance to disease genetics? I suspect their impact here will be much more modest, at least in the near future; academic consortia are generally vastly more well-powered to pick up disease risk associations given their more stringent quality control and phenotype definitions. However, it's important not to underestimate the importance of 23andMe's ability to recruit and maintain an active base of participants, and their Facebook-like viral marketing appeal (in which customers have an incentive to recruit other people). This may make it possible for 23andMe to tap long-term phenotypic change, such as the progression of symptoms in patients suffering from diseases such as Parkinson's.

It's been interesting to watch the perception of the genomics community towards 23andMe shift over time. There's still some hostility out there - and indeed, the first question directed towards Erikson was a needlessly combative and rather incoherent question about the ascertainment bias in 23andMe's sample towards wealthier individuals - but the strangeness of the 23andMe model is starting to wear off, and presentations like this one will no doubt help to convince scientists that this is a company that at least is capable of doing solid science.

There's one other small nugget of data worth mentioning. It's always been hard to get a solid estimate of the number of customers in 23andMe's database, but we now have a conservative lower bound: the company has at least 6,000 unrelated individuals of European ancestry enrolled who have taken phenotype surveys, suggesting a total active (i.e. engaged in phenotype surveys) customer base substantially higher than this. I don't think this number would surprise many regular readers, but it's a useful antidote to the sorts of ridiculously low recruitment numbers I've heard quoted by personal genomics critics.

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dgmacarthur Sun, 10/25/2009 - 00:30

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23andMe offers free genome scans to 4,500 senior athletes, seeking genetic fountain of youth

dgmacarthur — Wed, 12 Aug 2009 13:50:00 +0000

23andMe offers free genome scans to 4,500 senior athletes, seeking genetic fountain of youth

A tweet from personal genomics company 23andMe (see screenshot below) sparked my interest:

I knew 23andMe had been successful in recruiting Parkinsons patients as part of its targeted drive, and the 337 unspecified "patients" are the product of their broader recruitment drive for diseased genomes, Research Revolution (which I've dissected in a previous post) - but the athletes were news to me.

A little Google-trawling revealed (see page 15 of this PDF article from Palo Alto Online) that 23andMe offered free genome scans to all of the participants in the currently ongoing Palo Alto Senior Games, a massive sporting event that only permits participants over the age of 50.

Here's a picture of the 23andMe booth at the games, courtesy of the event's official Flickr page:

Giving away 4,500 free genome scans is a pretty heavy investment - at the current retail price of $399 per kit, that's an astonishing $1.8 million worth of testing. What does 23andMe expect in return? From the Palo Alto Online article:

23andme did not target the 2009 Senior Games solely for its numbers, but because the company wants to find the genetic factors for healthy aging, [23andMe spokesman Rajiv] Mahadevan said. What's better than some 12,000 healthy, active athletes all over age 50?
The beautiful thing about this group is that they epitomize healthy living," Mahadevan said.

Basically, 23andMe is looking for the genetic secrets to a healthy, active old age, and they're willing to spend a hefty chunk of money to get it. They haven't simply relied on the attraction of free stuff to attract participants, either - here's their highly targeted advertisement to Games participants, placed strategically below the Palo Alto Online article linked above:

Now, it would be easy to portray this strategy in sinister tones - the evil corporation stealing the genetic secrets of elderly athletes - but it seems to me that 23andMe has been fairly open about their intentions here, and I'm also genuinely intrigued about the potential of this set of individuals as research subjects. Physical activity extending into later life is a powerful protective factor against a multitude of common diseases, and digging into the molecular basis of variation in late-life physical performance could provide some genuinely useful and health-relevant insights.

That's not to say that getting useful results out of this cohort will be easy; but it seems plausible to me that many of the interesting traits that could be mined for this cohort would be determined by common variants (for reasons involving natural selection and post-reproductive traits, which are a topic for another post), and if a reasonable fraction of the 4,500 recruits end up progressing into the research stage that's a decent-sized cohort to draw on.

I've been fairly optimistic about the prospects of 23andMe's participant-driven research approach in the past. If this study is done well - and 23andMe certainly has access to the expertise and resources required to do it well - then we might very well see some intriguing (and publishable) results coming out of this cohort in the next year or so...

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Edit 12/08/09: I somehow wrote "skeptical" when I meant precisely the opposite...

dgmacarthur Wed, 08/12/2009 - 09:50

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Interestingly enough, there's already a healthy aging project going on here at the Genome Science Centre in Vancouver, although i think the qualifying age was something like 90+ years, here, rather than 50. As far as I know, I think the project has been going on here for a little over 2 years, so 23andme has a bit of catching up to do.

Hey Anthony,

Good point - I think there are a few of these studies going on right now, mostly (as you say) focused on the extreme elderly.

However, the genetic basis of healthy survival into extreme old age may well differ markedly from the genetic basis of physical fitness at earlier ages (say 50-70), so 23andMe isn't necessarily in direct competition with these consortia.

Hi Daniel,

It's true that they're not in direct competition, but I suspect the genes that have the greater impact will be the ones that keeps you alive and in good health till your 90's, rather than your 50's. (=

Anyhow, my point isn't that there shouldn't be competition, but that the project is far from unique - although it seems you already knew that. (Which is exactly why I read your blog in the first place!)

I am by no means a 23andMe detractor, but ascertaining samples through the Senior Games seems a little naÃ¯ve. I mean, these are self-selecting individuals that actively engage in environmental modifications (e.g. exercising, healthy eating, etc...). Taking a random sample of 90-year-olds is a much better approach for studying the underpinnings of "healthy aging" (whatever that means). The whole thing appears to be a marketing/science hodgepodge, a truly "worst of both worlds" scenario.

It may be lousy hypothesis driven science, but it makes for excellent data mining, and that is probably a more immediate goal. You replicated matched controlled experiment can get much strong statistics if it doesn't have to consider all 550,000 snps. If they tagged all of the senior athlete kits, and just visually compared that to every other sample in the database, some trends would standout. The statisticians would argue about the best methodology, but it shouldn't particularly matter if you just want to find the 10,000 snps worthy of a second round. Thanks to the reduced number of snps, that can be done in a
much smaller group.

I think 23andMe is trying to combat poor reliability on self reported data. They could do a second project and give kits to 4500 people who buy a "senior scooter" before age 50. How much do these two data clouds intersect. The ability to tell 23andMe customers what genetic distance they have from each of these two clouds might also be informative. The data they have gets more valuable as it grows, but well labeled data is a multiplier.

I have a favourite quote I carry in my wallet

"I am in better shape now than when I was 100" - 103 year old Ben Levinson competing in shotput, rock climbing and archery in the World Masters Games

Meh,
Shitty Science, Great Marketing......
-Steve

cariaso,

I hate to disagree with you, but, for $3.6 million, I think that looking at 50-year-old athletes versus 50-year-old scooter drivers is a little risky. There is no doubt that data mining will turn up something; however, my guess is that socioeconomic factors will explain differences in outcome. I mean, these are the Palo Alto, a place with a median home sale price greater than $1 million, Senior Games. The athletes congregate in the AstraZeneca Athlete Village and enjoy entertainment on the Euflexxa Entertainment Stage in front of the Humana Celebration Plaza (seriously). I would say this "study" is primarily a marketing gimmick. Most of the DTC companies believe that their market is the baby boomers since they have money and they want to stay healthy as they age. It would be more interesting to know if it is too late to act on the information in a genetic profile if one receives it at the age of 50.

Matthew, the exact location of the Senior Games is irrelevant. They've been held all over the country at two-year intervals since 1987. I do agree that it is not a random socioeconomic sample, since participants must have the means to travel.

However, it's a unique opportunity to collect information about a distinctive group -- they're not merely healthy, they are functioning at a very high level. Some will set national records for their age group in their sport. Some of the participants are in their 90's, BTW.

What's so distinctive about senior athletes? We have bundles of them here in Greenwich CT.......

Marketing to old people, plain and simple.

Ann, I wonder if you think the HR bill for healthcare reform is great too?

-Steve

Steven --

Maybe you don't appreciate what the Senior Games are. They used to be called the Senior Olympics, if that gives you a better flavor. When I said the athletes were functioning at a very high level, I was not exaggerating for effect. If you care to investigate, take a look at the results for some of the T & F events, which I find quite impressive. These are not just seniors who are active for casual enjoyment or basic fitness reasons. They are serious, dedicated, and exceptional athletes who don't want to quit competing just because they are growing older.

http://www.sml1.com/recordtiming/seniorgames09/

As to the leap in your last line to my opinion of the HR bill, your logic (?) baffles me.

I would like to order the Full Edition Personal Genome Service Kit. Ihad correspondence from the North Carolina Senior Games that this material was available to members.

I had a fractured hip and could not participate this summer in Raleigh. But I am back in the pool now .

I understand that this material is available fot the special price of $350. Is my spouse eligible also?

Please advise. Thank you for your kind attention. Boyd C. Campbell

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Helpful article...making sure to bookmark this blog so I can visit in the future, it's so hard to discover beauty blogs with quality content!

If they tagged all of the senior athlete kits, and just visually compared that to every other sample in the database, some trends would standout.

The future of participant-driven genomic research

dgmacarthur — Thu, 12 Mar 2009 12:10:59 +0000

The future of participant-driven genomic research

Over at the 23andMe blog The Spittoon, company co-founder Linda Avey expands on her vision for a novel model of genomic research, in which personal genomics customers contribute their genetic and health data to fuel research into the inherited and environmental triggers for disease.

This is a model that 23andMe has been building towards for a long time. In May last year the company launched 23andWe, a cutely-named effort to obtain detailed health and trait data from their existing customers through online surveys which could then be combined with genetic data to find novel gene-trait associations.

In today's post Avey formally announces a drive to recruit 10,000 Parkinson's disease patients for a targeted analysis of the genetic and environmental causes of this disease, which is backed by the Michael J. Fox Foundation and The Parkinson's Institute, and will apparently be largely funded by Google co-founder Sergey Brin.

The model is simple: Parkinson's patients get access to the full features of a 23andMe genome scan for $25 (compared to the standard retail price of $400), in return for participation in online surveys. The company will then combine their recruits' genetic and survey data to look for unexpected associations with disease status, using volunteers from among their existing customers as controls.

So, will 23andMe uncover new genes for Parkinson's disease?

It's certainly possible; previous genome-wide association studies
(GWAS) of Parkinson's have been seriously under-powered (just a few hundred
cases and controls), so there's every chance that there are still low-hanging
common risk variants that could be captured with a sample of 10,000 cases. Building an active community of participants may also provide substantial advantages in terms of making it easier to explore environmental risk factors and to chase down promising leads with further rounds of targeted surveys.

However, there are also caveats: the self-reported disease status and health data from
participants will never be as rigorous as information collected in a clinical
setting; and it may well turn out that the bulk of the genetic risk for
Parkinson's is due to rare genetic variants that will be
essentially invisible to 23andMe's common variant-focused chip.

All in all, though, my guess is that this study will contribute at least something of value to our understanding of the etiology of Parkinson's. But this will perhaps prove to be less important than the precedent that this study sets for future genomic research: perhaps I'm just a sucker for 23andMe's hype, but I think the model of participant-driven research is a novel and powerful one, that will increasingly come to dominate the genomic research landscape.

23andMe has unique advantages in a study of this type: it provides an incentive for patients to enroll in the study (access to information about their ancestry and genetic disease risk); motivation for enrollees to continue to participate (as new features and updated association data are added); and a slick interface and experienced team for returning data back to participants. Few academic consortiums can match this set-up; yet it seems inevitable that participants in genomic research will increasingly demand some return (in terms of genetic information) for their participation in large-scale studies.

This really hit home to me during a presentation by the NHGRI's Len Biesecker at the AGBT meeting last month. Biesecker presented on the ongoing ClinSeq project, during which he noted the ethical and logistical challenges of data return for academic genomics consortiums. For genomic researchers to generate genome-wide genetic data - with health implications well outside the current study - and then not return it to participants seems frankly unethical, but few if any genomics consortiums are in any way equipped to return whole-genome data to participants in a useful format.

I immediately wondered: why don't genomics consortiums simply take advantage of the databases and graphical interfaces already generated by personal genomics companies? Basically, once a study is complete the researchers can send anonymised data to a personal genomics company and provide each participant with a unique, anonymous login code; then the research subjects can access their complete genomic data through the company's interface.

This seems like a winning solution all round: academic scientists can fulfil their ethical obligations in terms of data return without attempting to build their own complex interfaces; research participants get their data back in a useful format; and personal genomics companies get an additional, stable stream of revenue for little more than the cost of some data storage and bandwidth.

So, will we see future funding proposals for disease genomics projects include an extra allocation to pay a personal genomics company to return genomic data to participants? I suspect it will take a while before academic researchers overcome their (quite understandable) suspicion of the consumer genomics industry; but the combination of the ethical imperative of data release and the logistical challenges of building their own data release infrastructure may well force their hand.

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dgmacarthur Thu, 03/12/2009 - 08:10

Tags

23andMe

participant-driven research

personal genomics

Kari has to be loving this.......Not.

-Steve
www.thegenesherpa.blogspot.com

wouldn't there be a risk of self-selection bias?