This topic is one that I’ve been wanting to write about for a while now, because it’s so intriguing. We all know by now that genetics and disease are often linked (for example a predisposition to breast cancer). But it has also become apparent that your genetics affect the way you respond to certain medicines – why a drug won’t work for one person, but will result in severe adverse reactions for another. This field is called pharmacogenetics.
A scale of reactions
Let’s take the painkiller, codeine, as an example. One person will feel little or no effect when they take codeine. However, another could end up in a coma from the same dose! This happens as a result of genetic differences, which affect the enzyme that transforms codeine into morphine.
When it enters the body, codeine is gradually transformed into morphine. So both codeine and morphine are circulating in the bloodstream at the same time. However, morphine is a much better painkiller than codeine, so the speed at which codeine is transformed into morphine is important. This is because it affects the amounts of codeine and morphine. If it is transformed very slowly, a minimal analgesic (painkiller) effect will be felt due to low levels of morphine. However, if it is transformed very quickly, then we could end up with the second case, with a patient going into coma.
There are a few drugs that are known to have interactions with a person’s genetics, including warfarin, which is used to thin the blood; isoniazid, which is a TB treatment; and abacavir, which is an ARV. And it gets more complicated – comedication of two drugs that are transformed by the same enzyme can also impact the effects of a drug. But let’s just work with one drug at a time for now. What’s the relevance of this? How does it help us?
A new concept has arisen, called personalised medicine, where drugs are specifically tailored to each individual’s needs. This involves looking at an individual’s genetic profile, and prescribing drugs accordingly. For example, if a doctor knows that someone will feel no painkiller effect from codeine because of a particular genetic variation, then they can prescribe a different painkiller for them. While this is not yet feasible across the board, sequencing your genome (or part of it) is becoming more and more accessible, and could one day form an integral part of the public health system. Already there is mandatory screening in the US before prescribing the use of the ARV abacavir.
In the meantime, a population strategy could be used. Many – though not all – genetic variations which affect how a drug works are linked to population groups. For example, tamoxifen, a breast cancer drug, is known to be less effective in Japanese populations due to a genetic variation that is common within this group of people. Thus a different breast cancer drug would be prescribed for these patients.
Pharmacogenetics is also important because it raises the question of where drugs are being trialled during their development, and in which population groups. For example, if drugs that are to be used mainly in Africa are trialled in Europe or America, because they are better resourced, will those drugs have the same effect in an African population?
Of course, genetic makeup is just one factor among many that can affect an individual’s response to a drug – including diet, comedication, and alcohol. However, in the same way that you shouldn’t drink alcohol when taking medication, or take contraindicated medicines together, it may be worth knowing where you stand on the genetic front before you take a particular drug. Because while our genetics are 99.9% the same, that 0.1% can make a big difference.
Gasche, Y. et al., 2004. Codeine Intoxication Associated with Ultrarapid CYP2D6 Metabolism. New England Journal of Medicine, 351(27), pp.2827–2831. Available at http://www.nejm.org/doi/full/10.1056/NEJMoa041888#t=article. doi: 10.1056/NEJMoa041888
Kiyotani, K. et al., 2008. Impact of CYP2D6*10 on recurrence-free survival in breast cancer patients receiving adjuvant tamoxifen therapy. Cancer Science, 99(5), pp.995–999. Available at http://onlinelibrary.wiley.com/doi/10.1111/j.1349-7006.2008.00780.x/full.
Sim, S., Kacevska, M. & Ingelman-Sundberg, M., 2013. Pharmacogenomics of drug-metabolizing enzymes: a recent update on clinical implications and endogenous effects. The Pharmacogenomics Journal, (13), pp.1–11. Available at http://www.ncbi.nlm.nih.gov/pubmed/23089672. doi: 10.1038/tpj.2012.45.