The NHS and genetic technology: not so revolutionary?

By Mary Travers

The NHS must prepare for the genetic revolution.

So says Auntie BBC, based on the press release from a report into the effect of new sequencing technologies on public health, conducted by the Foundation for Genomics and Population Health. The report suggests that medicine is going to be transformed in the short term, with rare genetic diseases fully testable, common genetic diseases fully predictable, and treatment fully tailored to an individual’s genetic make-up. The NHS, so its line of argument runs, needs only to employ a few bioinformaticians (mathematicians and computer programmers who attempt to analyse the deluge of sequencing data) and send doctors on a few training courses to take full advantage of this impending revolution.

The trouble is, I’m not remotely convinced that the revolution is anything like impending. Don’t get me wrong, I work in disease genetics and am passionate about the benefits it will eventually bring to medicine and public health. But the key word here is eventually.

It is certainly true that technological advances in the past few years have genuinely transformed the speed, ease and cost of sequencing a human genome. The first human genome sequence (which celebrated its decade anniversary last year) took hundreds of researchers many years to complete, and cost upwards of $1million. Today, the same feat can be accomplished in a few hours for less than $1000 – and commercial companies are promising a $30 genome in the near future. All this means that it is now far more feasible to sequence multiple genomes – and research projects such as the “1000 genomes project” (does exactly what it says on the tin) are doing just that.

However, making sense these many terabytes of data is a whole different ball game; each human genome is about three billion letters long, and we barely understand what anything more than the ~3% of protein-coding letters actually do. The pilot phase of the 1000 genome project (published in October 2010 and based on the complete genomes of 179 individuals) identified upwards of 15 million letters which varied from person to person, and between 250 and 300 mutations probably affecting gene function in every participant – and these were healthy people.

The problems this creates for genetic diagnoses are obvious. According to the report, whole-genome sequencing will transform “any kind of undiagnosed rare condition where you suspect it to be genetic, but you don’t know where to look”. Well, yes, it may narrow the field from three billion, but a field of 300 is hardly small. Of course, where many individuals with the same disease carry the same causative mutation, it would be relatively easy to identify by comparing the genomes of disease sufferers and non-sufferers. But these mutations have, in the main, already been identified through other means – Cystic Fibrosis and Huntingdon’s Chorea being classic examples.

The rare genetic diseases left to “solve” are likely to be those caused by different mutations in different people. Here, having a whole genome sequence is little use without enormous amounts of comparative data and years of work in the laboratory to determine which of the many candidate mutations actually has a biological effect – and we just aren’t there yet.

And that’s without even opening the can of worms which is common, complex genetic diseases such as cancer and Type 2 diabetes. Here, genetic variants may alter an individual’s susceptibility to the disease, but by no means guarantee that they will or will not develop it – environment also has a huge role to play. So far, genetic studies of complex genetic diseases have only identified pretty common variation which confers a pretty small increase in disease risk: for example a variant carried by 20% of the population which increases disease risk by 5%. This information is as good as useless for predicting who will and will not develop an illness. Whole genome sequencing may well eventually uncover less common variants which confer a larger disease risk: for example a mutation carried by 2% of the population which increases disease risk by 20%. But getting there will take thousands more genomes and thousands more man-hours at computers, struggling to analyse a monumental amount of data. And even then, the predictive power of one of these variants would be paltry when compared to lifestyle factors such weight and exercise. Hardly the “clear clinical benefit” which the report promises.

I do not mean to be negative about the potential of whole-genome sequencing. It is a fantastic and exciting achievement, and will, in the fullness of time, impact upon the medical treatment in all our lives. But that time is not yet, and to suggest that could be is counter-productive. The idea that employing a few bioinformaticians will turn the NHS into a genetic powerhouse, when the best bioinformaticians at the best research institutions in the word are just beginning to grapple with this information, is frankly ridiculous. Raising vain hopes for an imminent genetic revolution in the NHS will, in my opinion, ultimately damage the standing of medical genetics with the public – and that is something which I am sure the report’s authors would not wish to be responsible for.

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