Predictive pharmacogenetics

Many people agonize about the predictivity of the science of pharmacogenetics. Somehow there is an expectation that pharmacogenetics should somehow lead to position where we can stop thinking.

Sounds a bit harsh but true.

Pharmacogenetics began as a science to understand the genetic basis for outlier behaviour. In much earlier experiences, outliers were characterized principally by phenotypic behaviour. As it is now, phenotypes tended to be classified in binary fashion - rapid/slow, fast/slow, extensive/poor. Such binary depictions of reality can only be predictive when the reaction or process in point is singular, critical or both. In some situations drug response can be described binarily as 'at risk for toxicity', or 'not at risk', e.g. G6PD deficiencies or HLA B*1502 for carbamazepine-SJS. For the most part however, pharmacogenetics data only helped explain genetic bases for limited aspects of drug response.

FDA classification: +, for information only; ++, recommended; +++, required

Gervasini et al, Eur J Clin Pharmacol (2010) 66:755–774

In highly controlled experiments, it can be easily shown that genetic variants can result in either loss or gain in function in specific processes related to drug response, e.g. drug metabolism and clearances. However since drug response/metabolism/

pharmacokinetics is seldom the result of a singular process, genotyping a genetic variant almost never provides a clear prediction of what the final drug response would be like.

Unfortunately the market place has misled many to believe that we can somehow construct a genetic testing panel that will predict with some degree of finality, what the patient's drug response and hence his drug dosage requirements will be. Hooray.... and we can therefore stop thinking! This line of thinking is clearly fallacious. The concept of 'personalized medicine' has been hijacked (biotech commercialism?) to refer to a one step genotyping approach to therapeutics when correctly it should refer to the ability to look at the patient in totality, i.e. the entire person - not just from the perspective of his constitutive make-up, but the totality of contributions of his altered physiology and environmental effects.

The more correct and rational approach is that of 'optimization', but the term sadly is far more mundane and less commercially sexy compared to 'personalized medicine'.

The rofecoxib (Vioxx) story - an interesting case study

The selective COX-2 inhibitor rofecoxib, marketed as Vioxx, tells an interesting story. You can read more about it here at Wikipedia.

Rofecoxib was an initially successful drug that had been used as an anti-inflammatory analgesic for the management of inflammatory joint disease, acute pain and dysmenorrhoea since 1999. The selective inhibition of COX-2 meant that rofecoxib could be used effectively as an anti-inflammatory analgesic but with minimal side effects on the gastric mucosae.

In 2001, rofecoxib was proposed to be used in the prevention of adenomatous polyps in the colon. The 3-year (APPROVe) trial to investigate the prophylactic role of rofecoxib for colorectal polyps was terminated prematurely because rofecoxib was observed to be associated with increased relative risk of thrombotic cardiovascular events beginning after 18 months of treatment. Data in the first 18 months did not reveal any increased risk. In 2004, Merck voluntarily withdrew rofecoxib from the market following the report of this increased risk.

The clinical use of rofecoxib is not without variability issues with respect to its pharmacokinetics. Although it is not substantially metabolized by CYP450 enzymes, it was nevertheless glucuronidated by UGT2B7 and UGT2B15, both of which are genetically polymorphic. It is not clear to what extent these genetic variants are associated with variability in clinical response to rofecoxib.

Although variability in clinical response to NSAIDs are well known, there has not been a major concern about genetic polymorphisms affecting NSAID pharmacokinetics. This has been, I believe, largely related to the the dependence in clinical practice to adjusting dosages and drug choices to the anti-inflammatory clinical drug response. And there is currently a plethora of 'clinical joint scores' that can allow the rheumatologist to adjust for response variability. The toxicities with NSAIDs have also been largely manageable, and with the COX-2 inhibitors, GI toxicity was not perceived to be a significant problem.

The recognition that rofecoxib was associated with cardiovascular toxicity changed all that.

It is interesting that as the use of rofecoxib moved from rheumatology to polyp prevention, the clinical use of rofecoxib also lost its ability to manage any response variability. Rofecoxib use in preventing colorectal polyps was largely based on prophylactic fixed dose regiments. There was an assumption that this was relatively acceptable because rofecoxib was relatively safe.

But this was apparently not so. There was an association with cardiovascular toxicity. Eventually it was the cardiovascular risk that did rofecoxib in, and caused it to be withdrawn. It is not clear to what extent this was due to pharmacokinetic variability. Or individual susceptibilities at the vascular level, but the practical reality was the clinical use of rofecoxib for colorectal polyp prevention did not allow the clinician any means to adjust dosages for any kind of PK or PD variability. Essentially people were flying blind.

It is probably acceptable to fly blind with a drug that had a very high therapeutic index, but not when there is a risk of cardiovascular death for the drug that was being used in a prophylactic setting.

CYP2C9

The CYP2C family of enzymes is the second most abundant of the CYP enzymes represented in the hepatocyte. The commonest is CYP3A4/5. Correspondingly they are also the second most important enzymes involved in drug metabolism.

There are 4 members of this family, 2C8, 2C9, 2C19 and 2C18, whose genes are all located on chromosome 10. The 2 members of this family that are of greatest importance for us are CYP2C9 and CYP2C10. CYP2C8 came into prominence initially in an association with the cerivastatin induced rhabdomyolysis and later in association with irinotecan metabolism. There has not been a lot of discussions about it lately because of the limited range of substrates linked with it. There is also little known about drug substrates associated with CYP2C18.

CYP2C9, originally known as tolbutamide hydroxylase, has been shown to be involved extensively in the metabolism of many pharmaceuticals. Of topical interest is its involvement with the metabolism with warfarin, particularly the S-isomer.

The Pharmacogenomics Journal (2005) 5, 193–202

The S:R isomeric ration of warfarin concentrations is routinely used as a convenient way of phenotyping the 2C9 activity. The common loss of function genetic variants are the *2 and *3 variants. These variants are much more common among Caucasian populations as compared to East Asians, e.g. Chinese, Japanese and Koreans. In Singapore, the ethnic group which had the highest frequencies of the *2 and *3 variants are the Indians, who had similar frequencies to the Caucasian populations.

CYP2C19 is much more of a preoccupation for us as the *2 and *3 variants are much more common among Chinese than Caucasians. The *2 alleleic variants is particularly common at about 25%. The CYP2C19 was earlier known by the original studied substrate, mephenytoin hydroxylase. The CYP2C19 genetic polymorphism has been discussed largely because if the association of the enzyme with the metabolism of proton pump inhibitors, and lately with the

antiplatelet drug clopidogrel.

Comparison of prasugrel 60 mg and clopidogrel 600 mg loading dose exposure of active metabolite by CYP2C19 genetic classification. Box represents median, 25th, and 75th percentiles and whiskers represent the most extreme values within 1.5 times inter-quartile range of the box. AUC, area under the concentration–time curve; EM, extensive metabolizer; RM, reduced metabolizer.

Eur Heart J (2009) 30 (14): 1744-1752