Monday, 26 July 2010

Personalized medicine - hype or hope?

Firstly, apologies for the unannounced month-long sabbatical.  I've recently moved house and set up shop in my new residence in Leeds, in addition to starting my summer studentship working on the wonderfully complex FCGR locus (its the copy number variation that makes it so complex btw).  All this in combination with a little bit of first-blog burnout means I've been far too lax of late.

So I thought I'd return from self-imposed exile with a little bit of a discussion of a short article published online in the Financial Times.  An article written by a GP in Glasgow in which she claims that personalized medicine is just a load of hype.  This got me thinking a little bit, is personalized medicine truly hype, or is their really hope for a health-care revolution?  Naturally I'm a little bit biased in favour of personalized medicine, afterall I'm due to start a PhD in pharmacogenetics this coming October, so there is a little bit of vested interest in the field, as I feel that it truly can revolutionize global healthcare.

So to the article in question first of all.  Dr McCartney expresses her opinion that the genomic medicine revolution is all hype because of its inherent uncertainty.  I'd say that is a valid point to make, after all the known genetic associations to date are largely of very small effect sizes; odds ratios in the range of 1.2-1.6 for most associated variants.  She also mentions that smoking is one of the biggest, if not the biggest, risk factor for developing lung cancer, and thus the environment has a very important role to play.  Another perfectly valid point.  So why am I so bothered about this article?  Well, it's because of what she doesn't mention, and qutie markedley leaves unsaid.  The interactions between our genome and our life-time environment are very complex and poorly understood.  That is not a valid reason to malign personalized medicine when it has not even reached its infancy.  The current known associations have very little clinical utility because of their small effect size and individual minor influence.  Their possible interactions, that is geneXgene interactions, have not even been fully investigated.  Who is to say that a panel of 50 genetic markers doesn't have clinical utility?  I'm not saying that it definitely will, but we cannot say until such time that this route is explored in a rigorous and meangiful way.

Dr McCartney goes onto point out the pitfalls of HER2 testing as a predictor of response to Herceptin (trastuzumab).  Lack of sensitivity and specificity in a single test that relies on histology is not a basis for lambasting all of personalized medicine.  Response to Herceptin is likely under the influence of other genetic loci, after all there are pharmacodynamic factors to take into account alongside the usual clinical covariates of disease stage, patient age, BMI, dosage, etc that must be taken into account.  Afterall, personalized medicine is about the individual thus we are going to need to incorporate as many individual factors into the equation as possible to individualise each treatment.

She concludes that we may run the risk of creating more problems if we rely solely on genetic determinants (that's a misnomer, but this is not the place to discuss genetic determinism), and that prevention is ultimately better than cure - well said.  However, knowledge of our genetic make up is potentially a very useful tool in our arsenal against disease because it may highlight disease susceptibilities that we can overcome by manipulating our own environments, i.e. our lifestyles.  Overall, I'd say that Dr McCartney has some valid points to make about what barriers we need to overcome to reach the personalized medicine era, others she does not mention (perhaps due to pre-publication editing), however, the article is simplistic and comes across as very naive and ill informed.  After all, where is the mention of Warfarin dosing?  The known genetic influence on hepatitis treatment?  The role of the cytochrome P 450's and drug metablolism, not to mention adverse pharmacological reactions?  These are some of the targets of personalized medicine, and pharmacogenetics.  For instance ~30-40% or rheumatoid arthritis sufferers fail to respond to initial biologic treatment with anti-TNF therapeutics.  Does Dr McCartney believe that a genetic understanding, in collaboration with biochemical knowledge of the influences on biologic treatment as a tool for predicting treatment response, thus saving the patient from months of uncertainty and further pain, not to mention the potential savings for the health service where a single course of ineffectual treatment can cost upwards of £10,000.  Is that all hype?

We have not reached the personalized medicine era, we are still exploring the role of genetic susceptibility in disease and therapeutic response, but it is moving at a fast pace.  I agree that perhaps we need to be a little cautious, not succumb to zealotry, this is people's lives at stake, but the potential benefits are staggering.  Imagine being able to walk into a clinic in 10-15 years time and have the clinicians be able to predict any potential adverse side effects, and whether or not you are likely to need an altered dosage regime.  That requires more than just a knowledge of the underlying genetics and biology, it requires political and societal changes, the implementation of an infrastructure that can support and utlise such vast quantities of information, not to mention the educational requirements for both physicians and the general public.

We do need to see both sides of the story with regards to decisions that affect something as important as our personal and societal health.  A more balanced approach that investigate both the barriers still to overcome and the limitations is called for.  Sometimes it does seem like there is only ever fanfare surrounding the predictions of personalized medicine, however, a closer read of the blogosphere shows that this fanfare is well measured with caution and an understanding of the pitfalls of predicting disease susceptibility.