Posting hiatus

Posting will be light to non-existent for the next couple of weeks.

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Good times for Illumina

Genetic analysis company Illumina has just reported a very good quarter: a 66% increase in both revenue and profits. What are they doing right?

I've posted a number of times recently about the wave of genome-wide association studies (GWAS) that has surged through the field of human genetics over the last two years. Put simply, GWAS involve looking at up to a million sites of common genetic variation throughout the genomes of thousands of disease patients (cases) and healthy people (controls), and identifying variants that are more common in cases than controls.

Although I've tended to focus somewhat on the failures of the GWAS approach (see the notable examples of height and bipolar disease, and a list of the major pitfalls of GWAS), it's worth noting that this approach has nonetheless yielded more information about the genetic basis of common diseases and complex traits in the last two years than we learnt from decades of previous research. A recent review of the field listed nearly 100 genetic variants that have been reliably associated with risk for a total of almost 40 different common diseases or traits, compared to a mere handful of well-validated genetic risk factors prior to the GWAS era - and those numbers are already seriously out of date, with new GWAS being published at an amazing rate.

The technological magic that has enabled the GWAS explosion is the development of genotyping chips: tiny glass chips covered with probes, which - when bound to fluorescently tagged DNA - provide extremely accurate read-outs of the sequence at hundreds of thousands of common variable sites (called SNPs). The picture on the left shows the Illumina Human 1M-Duo chip, which can simultaneously analyse over one million SNPs from two different samples in a single run.

The two major rival chip-makers on the market for quite some time have been Affymetrix and Illumina, both of whom produce chips to analyse genetic variation and also to look at gene expression levels (using a technique called microarray analysis).

You don't need to be a financial expert (luckily, because I'm not one!) to see that Illumina is doing something better than Affymetrix: over the last twelve months Illumina shares have more than doubled (and are currently at an all-time high), while those of its rival have halved over the same period:

(Chart from Nasdaq; both lines normalised to 100% at beginning of period.)

As I said, I'm unqualified to comment on the financial aspects of this increasingly one-sided race, but there are a few scientific issues that distinguish between the two companies. Firstly, when it comes to genome-wide SNP chips, Illumina seems to offer a superior product, at least according to an interesting paper in Nature Genetics a couple of weeks ago.

The paper, from a group at the University of Washington, set out to evaluate the performance of large-scale genotyping data (the type used in GWAS) to capture the totality of human genetic variation. They did this using full sequencing data from 76 genes in individuals from various human populations, generated as part of the ongoing SeattleSNPs project, which they could then use as a test set to determine the true coverage of each of the competing genotyping platforms.

Illumina came out of the analysis a clear winner. In the image below I've reformatted data from two separate figures from the supplementary data of the paper to make the comparison easier:

The figure compares the two current cutting-edge chips (the Illumina 1M and Affymetrix 6.0, both of which survey over one million SNPs). Each graph shows the proportion of the total genetic variation (dark lines) or common variation (light lines) that could be captured by the chips at varying levels of tagging stringency (r²) for Europeans in blue and African-Americans in red.

There's a lot of data in those graphs, but I want to use them to illustrate two points: (1) for both populations the line for the Illumina 1M chip falls more gradually than that for the Affymetrix chip, indicating that the Illumina chip provides better coverage overall; and (2) this is probably most important for the African-American samples, in whom the genetic heterogeneity of their African ancestors makes SNP-based analysis generally more challenging.

The extra coverage provided by the Illumina 1M chip was presumably a factor in the announcement a few weeks ago that the Wellcome Trust Case Control Consortium (WTCCC) - the largest GWAS consortium in the world - will be using this chip for at least part of its planned analysis of over 90,000 common disease patients, which I wrote about back in April. That sort of order must have put a smile on the faces of Illumina executives. Increased sales of genotyping chips for GWAS applications have played a substantial role in the companies' success, according to GenomeWeb News.

However, while genome-wide genotyping is currently a major feature of large-scale human genetic research, it's also a technology with a limited life expectancy: in essence, it's just a temporary place-holder for the moment when whole-genome sequencing becomes feasible. Over the next few years we will no doubt see chips with increasingly large numbers of markers crammed in, including rare variants, small insertions and deletions, and structural variation - but no matter how good these chips get they will be rendered completely obsolete by cheap sequencing technology. Why be content with assaying one or two or even ten million markers, when you can have the sequence at every position in your genome for a few thousand dollars?

Cheap sequencing also threatens the other major application of chip technology, microarray analysis of gene expression: using a new approach called RNA-Seq, researchers can now effectively use large-scale sequencing technology to read out which genes are being expressed in a tissue, and at what levels. The advantages of this technology over traditional chip-based microarray are considerable: the approach provides information on essentially every gene expressed in the cell (while microarray is limited by whether or not a probe exists on the chip for that gene); it is able to detect exactly which version (alternative splice form) is being expressed; and it has a much higher dynamic range for expression levels, which is limited for chips by the binding capacity of each probe.

A couple of weeks ago we saw an application of RNA-Seq to human cells (reported in GenomeWeb News): in an analysis of gene expression in just two cell lines, the authors identified a swathe of novel expressed regions of the genome, and over 4,000 previously unknown positions of alternative splicing (a mechanism used by genes to make multiple proteins from the same DNA sequence). It's clear from the power of this technology that the days of chip-based microarrays are numbered.

Luckily, Illumina has a backup plan. Even as its chip business has grown, Illumina has been fostering the very technology that will make its own chips redundant: next-generation sequencing. Illumina's range of next-gen sequencing machines, the Genome Analyzer series (left), represent one of the big three platforms currently competing furiously for the large-scale sequencing market. In addition, this week the company announced the acquisition of a second sequencing technology, a long-read pyrosequencing platform developed by Avantome.

Affymetrix also has a large-scale sequencing technology, using a chip-based approach - but the limited scale and inflexibility of this system means it has been rapidly overshadowed by the more powerful next-gen sequencing platforms.

Anyway, it's clear that the genetic analysis industry is currently at an inflection point, with chip-based technology still on the ascendant but visibly doomed by the simultaneous explosion of next-generation sequencing. Illumina seems well-placed to make a successful - and profitable - transition through this chaotic period.

Am I being over-optimistic about Illumina's success? Let me know what I'm missing in the comments.


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Duffy-HIV association: an odd choice of ancestry markers

p-ter at GNXP does a great job of explaining a complex topic: how ancestry can confound a genetic association study, potentially leading to a false positive result.

The subject is a recent study suggesting an association between a loss-of-function (null) variant of the Duffy gene with increased susceptibility to HIV infection. The study examined African-American personnel in the US Air Force, and found that individuals who carried two copies of the null variant had a 40% increase in risk of contracting HIV, but paradoxically also display slower progression of the disease once infected. The study is summarised nicely by Nick Wade in the NY Times.

p-ter expands on this paragraph from Wade's article:

Dr. Goldstein said that in parts of the United States, African-Americans have a higher infection rate than European-Americans, and that patients with a higher proportion of African genes may be more vulnerable to H.I.V. for reasons unconnected to the SNP. Nonetheless, the SNP would show up in a greater proportion of infected people simply because of their African heritage. If so, the gene’s apparent association with H.I.V. infection could be just coincidental, not causal.

Basically, the problem is that the Duffy null variant is vastly more common in Africans than Europeans. In fact, the difference is about as large as it's possible to be, with frequencies of close to zero in Europeans and approaching 100% in many African populations; African-Americans, being an admixture of European and African ancestry, have a frequency of around 70%. So here's the danger: because the null variant correlates so well with African ancestry, it will likely also show a correlation with any trait that varies between individuals of European and African ancestry - potentially including HIV susceptibility.

p-ter notes:

...it's quite possible that the authors have simply shown a correlation between level of African ancestry and susceptibility to HIV (which could be due to any number of sociological, demographic, or genetic factors), rather than an association between Duffy null and susceptibility to HIV.

This sort of false positive is a well-known danger in genetic association studies, and is traditionally guarded against by genotyping a set of ancestry-informative markers (AIMs) that differentiate between African and European ancestry, and using this information to correct for any possible effects of confounding by population structure. This step is routine in genome-wide association studies, where the presence of information for hundreds of thousands of genetic markers make this correction straightforward.

In the Duffy study the authors attempt to perform this type of correction using a set of just 11 markers they describe as "differentially distributed between European and African populations". p-ter notes that several of these markers are not particularly ancestry-informative, and indeed on closer inspection it's clear why this is: these genes weren't originally selected on the basis of ancestry informativeness, but rather because they are associated with HIV biology. Every single one of the 11 markers has some association with HIV: three of them have previously been associated with HIV infection, progression, or response to treatment (CCR5 delta32, APOBEC3G H186R, GNB3 C825T); most of the remaining markers are in genes that are known binding targets or modulators of HIV (CCR5, CXCR4, PD1, TRIM5, IL-2, IL-4).

I can't find anywhere in the article where the authors mention that all of their "ancestry" markers also just happen to be associated with HIV biology; in the supplementary data they're described as "genetic markers that we found and/or have been reported elsewhere (NCBI SNP data bases) to be more prevalent in an ethnic background compared to others." Yet it's obvious that this wasn't the original motivation for selecting these markers. Actually, it seems most plausible that the authors genotyped all of these markers as candidates for association with HIV infection risk; when only the Duffy gene emerged as significant, they instead re-badged their unsuccessful candidates (or at least those with frequency differences between Europeans and Africans) as "ancestry markers".

If that's true - and it's difficult to see any other rationale for using these HIV markers rather than a set of validated AIMs - this is poor form for at least two reasons. Firstly, it's unlikely that using such a weak set of ancestry-informative markers provides an effective correction for a marker with as strong a correlation with ancestry as Duffy (as p-ter notes, all of the supposed ancestry markers are far weaker predictors of ancestry than the Duffy variant). Secondly, testing several different variants for an association with HIV and then only reporting the one that achieved significance creates the perfect conditions for a false positive due to multiple comparisons. I'll be discussing this second point in more detail in a separate post.

Anyway, the ultimate test will be independent replication - I'm sure we'll all be watching with interest to see if this association holds up in studies where the effects of ancestry are adequately controlled.


HE, W., NEIL, S., KULKARNI, H., WRIGHT, E., AGAN, B., MARCONI, V., DOLAN, M., WEISS, R., AHUJA, S. (2008). Duffy Antigen Receptor for Chemokines Mediates trans-Infection of HIV-1 from Red Blood Cells to Target Cells and Affects HIV-AIDS Susceptibility. Cell Host & Microbe, 4(1), 52-62. DOI: 10.1016/j.chom.2008.06.002

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Company revokes breast cancer gift, freezes puppies

Presumably in an attempt to solidify its reputation as the evil corporation du jour, Genetic Technologies has followed up on its decision a fortnight ago to tear back its "gift to the people of Australia and New Zealand" with the purchase of Frozen Puppies Dot Com.

They'll be sorely disappointed when they realise the company actually specialises in "the collection, freezing, exchange and insemination of canine sperm" rather than dunking puppies in liquid nitrogen while cackling evilly.


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Genetic Technologies takes back its "gift to the people of Australia"

A quick bit of news from my side of the world. An Australian company, Genetic Technologies, obtained exclusive Australian and New Zealand testing rights for the breast cancer genes BRCA1 and BRCA2 from Myriad Genetics back in 2003; amidst public furore about the prospect of increased costs to women of having these tests done, the company announced that it would refrain from enforcing the patent as a "gift to the people of Australia and New Zealand".

Now it's taking that gift back. On July 7, familial cancer screening laboratories around Australia and New Zealand received letters from the company ordering that they cease offering the tests within seven days. The people I've spoken to in these labs were shocked by the letter - there was no prior warning, and there's now considerable uncertainty about what will happen next. The concern, of course, is that this move will grant a complete monopoly to Genetic Technologies as the sole testing facility in the region, driving prices up.

It's likely that there will be legal challenges to the decision over the next few months, which I will follow with interest.

So why did Genetic Technologies make this move now, after five years of inaction? I'm not sure, but this graph from the Australian Stock Exchange sheds some light on the issue:

The red line tracks the drop in the price of Genetic Technologies shares over the last six months, relative to the overall performance of the Australian stock market over the same period in blue. It's also worth noting that Genetic Technologies has never actually made a profit. So perhaps the company feels that this move - which will certainly create a surge of negative publicity - is simply required to keep itself afloat.

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Which baby do you want? A dilemma for the 21st century parent-to-be

Nature News has an intriguing article on the next three decades of reproductive medicine: essentially a series of short musings from scientists working in the field about the issues we will be facing in 30 year's time.

It's worth reading through in full, but this statement from Susannah Baruch at Johns Hopkins caught my eye:

There's speculation that people will have designer babies, but I don't think the data are there to support that. The spectre of people wanting the perfect child is based on a false premise. No single gene predicts blondness or thinness or height or whatever the 'perfect baby' looks like. You might find genetic contributors but there are so many environmental factors too.

More likely is that you'll have a set of embryos and you'll know every single thing about every gene in every embryo. For example, one embryo will have three genes associated with tallness, two for weakness, three for poor vision and some for disease; and the second embryo will have some other set. They're very complicated data. This is not creating a baby from scratch. None of us is a perfect specimen and none of our embryos will be either. [my emphasis]

I'm unsure how selecting amongst these embryos doesn't count as making "designer babies" (it's still a choice, even if it's between a set of imperfect options), but I think Baruch's second paragraph is spot-on. It's clear from recent genome-wide association studies (GWAS) for height and weight that many (if not most) traits are hideously complex at the genetic level - a mess of common and rare genetic variants scattered throughout the genome, each contributing only the tiniest proportion of the overall variation.

Height is a great example: GWAS results from more than 30,000 individuals have uncovered dozens of contributing variants, which together predict less than 5% of the variation in height. There's no doubt we'll uncover much of the remaining variation with emerging technologies (analysis of structural variation, and large-scale sequencing) and larger cohorts, by which time we'll likely have hundreds of contributing variants. The same will hold more or less true for other complex traits, including susceptibility to common diseases like diabetes or hypertension.

The point is not that we will never understand the genetic basis of complex traits - we will, at least to a pretty good approximation, given advanced tools and sufficiently large cohorts. The point is that even once we understand the genetics of complex traits perfectly, that won't be enough to generate a "perfect baby" through embryo screening alone.

To illustrate this, imagine - ten or fifteen years from now - a couple who have just had IVF to generate perhaps two dozen embryos, and want to use genetic testing to decide which one(s) to implant. There won't be a single, stand-out embryo, perfect and disease-free, because generating a "perfect" embryo - one with the "desirable" variant at every single position in the genome - runs up against a pretty serious probabilistic challenge. Let's say there are only 5,000 DNA variants that negatively affected human health (an under-estimate) each with a frequency of just 1%: that means you would get a "perfect" embryo around once in every 10²² attempts (that's a 1 followed by 22 zeroes, a stupidly large number).

It's likely that methods to generate large numbers of embryos will be developed, particularly once stem cell technology enables sperm and egg cells to be created from adult tissue, but generating and screening 10²² embryos is no mean feat: at the rate of one every second, this would take you about 200,000,000,000,000 years, ten thousand times longer than the current age of the universe.

So it's safe to say that there will be no perfect baby. Instead, the prospective parents will face a tough choice between embryo A, who will likely be tall, slim, smart and cancer-free but have a higher-than-average chance of bipolar, early-onset dementia, and infertility; embryo B, who will be a little shorter, dark-haired, probably fairly gregarious, resistant to coronary artery disease, susceptible to bowel cancer, hypertension and early deafness; embryo C, who will be of average intelligence, unlikely to suffer premature baldness, prone to mild obesity and diabetes, but not at a high risk of any of the other major common diseases; and embryos D-N, who present a similar panel of competing probabilities.

Of course, a few embryos may carry mutations with known, severe health outcomes - those associated with rare diseases like muscular dystrophy, for instance. Embryo screening will have a very real impact on the frequencies of these conditions, just as we are already seeing following pre-natal diagnosis of conditions such as Down syndrome. But for the complex, common diseases there will be no easy answers; just a set of trade-offs.

The parents-to-be will sit down together with dossiers listing a huge set of statistical predictions for each of their potential children, and make a decision as to which (if any) of these abstract collections of traits and risks they wish to bring into this world. Decisions don't get much more emotionally traumatic than this: not only will they be making a decision that will shape their own lives and that of their future offspring, parents will carry a new, extra burden of responsibility for the fate of their children. If they decide on embryo A, and their child goes on to develop severe bipolar disease, they will carry the guilt of that decision in addition to the trauma of the disease itself.

That's not to say that embryo selection is unworkable - in fact, I think it's inevitable - but rather that this process is likely to require a degree of agonising trade-offs on the part of parents-to-be that is seldom fully appreciated. While I have no moral problem with the notion of embryo selection, part of me is glad that my child-bearing years are likely to be over before I have the chance to face this particular dilemma...


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The billion-dollar question: is big science worth the money?

Dan Koboldt from MassGenomics has a great article on the Cancer Genome Atlas (TCGA) project, an ambitious and seriously expensive endeavour to catalogue the genetic changes that occur during the transition of well-behaved human cells into the sprawling, anarchic lethality of cancer.

How expensive? Well, the pilot project cost $100 million, so this is going to be a costly effort even by genomics standards; the total expense, over the next ten years or so, may reach $1.5 billion according to a recent news article in the journal Science.

Dan uses the project as a springboard to weigh up the merits of the Big Science approach - research performed on a massive scale by large, multi-centre collaborations rather than the traditional small-scale, more focused work performed by individual labs. The benefits of the Big Science approach are obviously embodied in the public Human Genome and HapMap projects, both of which have utterly changed the way human genetics is done.

In fact, it's hard to think of a recent Big Science project in human genetics that hasn't exceeded expectations, to the horror of its inevitable early detractors. Dan hints that Evan Eichler's recent $40 million grant to categorise structural variation in the human genome may be an example of Big Science money that could have been more effectively spent on other projects, but it's probably too soon to judge this with any certainty. And while it's true that the recent rash of genome-wide association collaborations such as the Wellcome Trust Case Control Consortium have captured a disappointingly small (indeed, sometimes non-existent) fraction of the genetic risk for many common diseases, they have also provided powerful insight into the genetic architecture of human traits, novel information about disease mechanisms, and a set of massive cohorts with high-quality DNA samples to drive future large-scale sequencing projects.

Perhaps the biggest danger of the phenomenal success of the Human Genome and HapMap projects is that this success provides a fully general counter-argument to wield against nay-sayers for any future Big Science endeavour, however foolish. ("Oh, so you claim that my proposed project to sequence the human [whatever]ome is too expensive and technically impossible? Well, they said the same thing about the HapMap project!" Opponents exit, broken, stage right; funding agencies enter with bags of cash, stage left.)


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Next-next-gen sequencer raises $100M

As I've mentioned a couple of times here, the current crop of personal genomics products (which scan a meagre 500,000 to a million DNA positions - a fraction of 1% of your complete genome) are basically place-holders for the rapidly approaching era of affordable whole-genome sequencing.

At the moment the rapid sequencing market is being dominated by three "next-generation" sequencing platforms: Roche's 454, Illumina's Solexa, and the SOLiD platform from Applied Biosystems (which was recently gobbled up by consumables giant Invitrogen). These three platforms are currently enthusiastically jostling for position - for instance, competing with each other to offer their services to the international 1000 Genomes Project - in an attempt to establish themselves as the technology of choice as the age of medical genomics looms ever closer. With each evolutionary iteration of these technologies their sequencing capacity and accuracy improves, enabling truly mind-boggling amounts of sequence to be generated (exhibit A: the Sanger Institute's recent one trillion base pair milestone).

But while these next-gen technologies - each with hefty financial backing from a major company - are stacking up the bases, a new generation of upstart "next-next-generation" platforms is developing their own revolutionary approaches to sequencing. One of the most promising of these platforms is the SMRT system from Pacific Biosciences, which uses fictional-sounding technology called zero-mode waveguides to detect the incorporation of fluorescent bases into a single, immobilised DNA molecule (you can see for yourself how the PacBio system works in this pretty promotional video).

Apparently PacBio's technology (along with the fancy graphics, and the fact that it has zero-mode waveguides!) has convinced the people that matter: GenomeWeb News notes that the company has raised a hefty $100 million from investors to develop a commercial platform, which is expected to hit the market in 2010. In other words, the already-seething large-scale sequencing market will soon be getting even more interesting.

As I've noted before, I really don't care who wins this technological arms race: all that matters to me is that so long as it's being run my own genome sequence (and yours) is becoming rapidly more affordable.

(Image from Pacific Biosciences.)


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Predicting responses to genetic testing

In a letter published in Nature last week, Kenneth Kosik and Francisco Lopera argue, based on their experiences with a large Colombian family with high rates of Alzheimer's disease, that responses to genetic risk information can vary hugely between individuals.

Kosik and Lopera criticise a recent Nature news article that questioned whether genetic test results actually have any lasting negative impact on recipients, noting that one of the members of the Alzheimer's family they study said he would "shoot himself in the head" if he discovered he carried the same mutation that had afflicted his mother with early dementia.

Arguing with anecdotes is a fun game; perhaps next week I can get a letter in Nature questioning the tobacco-lung cancer connection using the longevity of my chain-smoking great-grandfather as evidence. However, what really interested me was this paragraph, which lovingly describes the dawning of a new era of techno-paternalism:

Seeking predictive genetic testing can be a risky behaviour, and an individual's likely response to genetic risk is hard to foretell. Functional magnetic resonance imaging activity patterns may be able to define people who are more comfortable with risk, and genetic polymorphisms seem to contribute to risk-taking behaviour. Defining the scientific basis for how individuals handle volatile genetic information may help guide our decisions about the best setting for delivering predictive-testing news.

So if a person tests positive for a genetic variant that indicates they'll respond badly to genetic testing results, should you tell them?


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Arguing against GM food gets harder

It's relatively easy to dismiss genetically modified crops as dangerous "Frankenfoods" when their major benefits are to farmers and corporations (increased yields and resistance to pesticides and insects, for instance). These types of modifications play easily into the hands of anti-GM activists wishing to portray all genetic engineering of crops as a tool for evil, ruthless businesses to make profits at the expense of our health.

This glib dismissal will become harder as new engineered crops start to offer benefits to nutrition and health:

Scientists have genetically engineered fruit and vegetables capable of providing most of a day’s nutrients in a single meal.

Heading towards the market are potatoes with 33% more protein content, modified tomatoes that could be capable of protecting against cancer and peanuts without the chemicals that cause deadly nut allergies.

Cassava has been packed with new genes that help the plant accumulate extra iron and zinc from the soil, and synthesise vitamins E and A.

No doubt some of the claims made for the health benefits of these particular crops are exaggerated, but the point is that there's nothing in biology to stop crops from being engineered to boost nutrient content or reduce unwanted molecules (like the proteins that cause allergic reactions), and there are considerable commercial incentives to do so. That makes it inevitable that solid, reliable products like these will be hitting the market soon.

Consumers are fickle creatures: if genetic engineering visibly allows them to get better food (preferably at a lower price) the scare-mongering of anti-GM activists will start to sound less convincing. So long as agri-biotech firms are careful enough about safety to avoid any serious health panics, it won't be long before the hardcore anti-GM movement - which has enjoyed dominance in the UK for far too long - has the rug pulled out from underneath it.

(Image from here.)


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Writing for informavores

Slate has a great article about the way people read online.

Apparently the typical internet reader doesn't tolerate big slabs of uninterrupted text, so I should really be writing fewer posts like this one, and more posts like the one you're reading now.


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Genetic testing: the end of private health insurance?

From a recent editorial in Nature:

In the future, [privacy] concerns will become more sensitive as genetic testing becomes more predictively powerful. Yet, at the same time, as that era blossoms, it will bring the risk-pooling benefits of universal health-care to the fore. As long as people do not have to share genetic data with private insurers, as is the case in the United Kingdom until at least 2014, those who anticipate bad health will do well to buy insurance cover. The genetically lucky, meanwhile, might as well save money and rely on the state. This will squeeze private insurers, suggesting that the [UK National Health System's] golden period may be yet to come. [my emphasis]

It's not a new argument by any means, but I was a little surprised to hear it in Nature.

Essentially, the argument goes, allowing consumers to engage in genetic testing while simultaneously barring insurance companies from accessing the results will lead to an inequality in the distribution of information: consumers will be able to predict their risk of certain chronic (and expensive) diseases much better than their insurers. As the predictive power of genetic testing increases so will this disparity, until it maxes out at the point where all remaining disease risk is non-genetic in origin.

In countries with a reasonable public health system, such as the UK, Australia or most of Europe, private health insurance is a luxury rather than a necessity - so people with a low genetic risk of chronic illness won't bother joining*. This will then increase the average risk to insurance companies of each new customer, forcing them to raise their premiums, and thus driving the next group of low-disease risk individuals out of the system. Repeat this for a few cycles and the whole system would ultimately collapse, or at least contract, leading to a widespread exodus to the public health system (which the editor somewhat bizarrely describes as a "golden period").

So, will accurate genetic testing, combined with legislation protecting customers from disclosure of genetic information, lead to the downfall of the private health insurance industry? I have too little economic knowledge to even hazard a guess, but this seems to me like something I really should know more about - so I would welcome informed suggestions in the comments.


* Obviously for readers living in countries without effective public health systems (such as Somalia, Tajikistan, and apparently the USA - or so I was told when I suggested that GINA might not be all good) the equation will be different.


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Navigenics has a blog

I just noticed that personal genomics company Navigenics has been rather quietly running a blog, "The Navigator", for a week or so.

A quick perusal of the posts so far highlights the differences in attitude between Navigenics and its peppier rival, 23andMe: while the long-running 23andMe blog, The Spittoon, conveys a real sense of a group of bright people who enjoy sharing advances in genetics with the public, the Navigator so far feels more sober, careful and considered.

This fits with the differing target audiences of the two companies: whereas 23andMe has the right mix of technical information and bright colours to draw in the young Wired crowd, Navigenics has marked itself from the start as being a serious company providing serious health-centred information to busy, serious people who don't have time to learn what a SNP is, and certainly are far too busy and serious to worry about frivolous things like genes for eye colour. 23andMe's blog is thus much more relevant to the company's target audience than Navigenics' (in fact I'm unsure whether the Navigenics target customer even knows what a blog is).

I do note that Navigenics chose to comment on the recent regulatory scuffle in California on their blog, a topic on which the Spittoon has been unexpectedly silent so far - so perhaps their blog will be used as an official communication channel as well as a means of drawing attention to new SNPs being added to Navigenics' serious list of Diseases They Think You Need To Know About.

Anyway, I won't be too harsh given that the blog has only just launched - anyone following the industry will probably want to subscribe, or at least drop by occasionally.


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Sanger Institute sequences its trillionth DNA base

The Wellcome Trust Sanger Institute, a major genetics research institute set in idyllic countryside a few miles south of Cambridge, UK, has reached a symbolic milestone: the sequencing of over one trillion DNA letters in just six months.

That's the equivalent of almost 350 entire human genomes. At the current rate (which is rapidly increasing) the Sanger is churning out more DNA sequence every two minutes than was generated by the entire research community from 1982-1987. This obscene rate of data generation has been enabled by the development of next-generation DNA sequencing platforms, which can each churn out one human genome equivalent in less than a week.

About a third of the trillion bases was generated for the 1000 Genomes Project, a massive international collaboration that will ultimately sequence the entire genomes of over 1,000 individuals drawn from multiple human populations. I commented last month on the fact that this project has become an important proving ground for the three major next-gen sequencing platforms on the market (454, Solexa and SOLiD), each of which is keen to position itself early as the technology of choice as the era of medical genomics draws ever closer.

From the data posted on the Institute's web site the Sanger actually reached the milestone a few weeks ago - the graph below shows the cumulative amount of purity-filtered (high-quality) sequence data generated since August 2007, with the curve crossing the magic "1000 Gb" mark in early June.



It's worth noting that there are also several other large sequencing facilities around the world (such as the Broad Institute) that are churning out roughly comparable amounts of sequencing data.

The brief window of time in which celebrity genomics was enough to get you into Nature is already closing; it's time for population genomics.

Update: Wired has a concise and timely review of progress in sequencing technology.


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