How will knowledge of the human genome affect drug therapy?

I shall attempt to cover in principle, the impact of the understanding and mapping of the human genome with its attendant miraculous technologies on the application of traditional clinical pharmacology to the understanding and improvement of drug therapy as applied in individual patients.

There is nothing new about PHARMACOGENETICS, but the advent of genomic technologies [1] changes the face of the subject and with it comes a new molecular focus encompassed by the term PHARMACOGENOMICS.

For anyone interested in this subject an excellent source of reference with thought-provoking content is the book, Pharmacogenetics by Wendel Weber [2].

It is essential that the two scientific subjects and their cultures meet on this subject. The new molecular genetics, its techniques, statistical methodologies and the understanding of complex gene interactions is a professional scientist’s lifetime task in itself, and so, for that matter, is clinical pharmacology. If knowledge of the human genome is to be applied to improvements in drug therapy, then it is essential that clinical and non-clinical scientists from the two subjects speak to each other on equal terms and make it their jobs to understand the essentials of each others subjects. In Figure 1 is shown the panoply behind the routine use of drugs in the treatment of disease. Marked with asterisks are the points at which pharmacogenomics will influence drug use or development. As Sir Colin Dollery is dealing with drug discovery elsewhere in this issue I have chosen to examine the influence of pharmacogenomic knowledge on clinical pharmacology, which is defined here for convenience as the application of pharmacological science in the clinical situation to maximise the benefits and minimise the risks of drug therapy. In the analysis of those processes involved in drug action in man it has been useful for the purpose of analysis to break them down into the component phases shown in Figure 2.

Figure 1.

Drug development. **points at which pharmacogenomics will influence drug use or development.

Figure 2.

The phases of drug therapy and points of pharmacogenomic involvement. **disease interaction.

Pharmaceutical phase

I cannot see pharmacogenomics having much impact on the pharmaceutical chemistry and formulation of drug preparations.

Pharmacokinetic phase

In the pharmacokinetic phase, processes of absorption, first pass metabolism and general metabolism of drugs are points at which pharmacogenomics will have an influence. I know of no evidence of genetic influence on drug distribution but transport processes and body composition are likely to have a genetic background. It is probable that the processes of elimination of drugs and metabolites involving transport across membranes of excretory cells in the liver and the kidney will prove to have a genetic basis, therefore potentially influencing the pharmacokinetics of the relevant drugs.

Pharmacodynamic phase

With the arrival of the drug molecule at a site of action, one moves into the pharmacodynamic phase. For many types of drug therapy we now have to consider not only the acute actions of drugs but also their chronic actions when used over days, weeks and years.

In regard to the acute phase of pharmacodynamics, receptor polymorphisms have been described and undoubtedly those processes leading from receptor drug binding through signalling cascades to the pharmacological effect of the drug, will be shown to have genetic polymorphisms, for instance, perhaps in G-proteins.

As drug therapy becomes more chronic and tissues and cells produce adaptive responses to the acute effects of the drugs, so one moves into the chronic pharmacodynamic phase where altered gene expression occurs [3]. It is probable that the extent of these adaptive responses will vary between individuals, depending upon complex genetic processes determining the type of adaptive response in the individual. Whether or not the therapeutic action of interest results from the acute effect of a drug or its chronic effect, it is very likely that there will be variable links between the pharmacodynamic effect of the drug and the production of the therapeutic effect. These variable links will also have a genetic basis.

When one examines Evidence Based Medicine (EBM) data and looks for instance, at numbers needed to treat (NNT), then for example in the treatment of high blood pressure in the elderly to prevent stroke (BP 160–209/<115 mm Hg, age 65–74 years), the MRC trial [4] showed that the NNT to prevent one stroke was 70 (95%CI 36-997) and is the sort of achievement we accept in practice; figures which are reassuring to public health doctors and epidemiological thinkers but pretty poor for the individual patient. We do not know in molecular terms what it is that we are influencing when we try to prevent stroke by lowering the blood pressure and I do not know whether the rather high NNT is due to an inability to influence the disease process itself or due to some pharmacogenetic target variability which causes some patients to be unprotected and the drug treatment to be ineffective. This is shown in Figure 2 as ‘Disease interaction’, and is a conundrum which is going to need a great deal of investigation.

Having dealt with the principles, I will now like to highlight some recent examples which show the application of pharmacogenomics to the generalities just discussed.

Pharmacokinetic phase

Individual and ethnic variations in drug metabolism were clearly demonstrated in the 1960s and 1970s and many of these have now been shown to be due to genetically determined variations in metabolic enzyme activity, particularly cytochrome P450 enzyme subtype polymorphisms. The classical pharmacogenetic based poor metabolism of debrisoquine/sparteine is due to several mutant alleles of the CYP2D6 gene coding the debrisoquine 4-hydroxylase. This predisposes to drug toxicity with metoprolol, timolol, nortriptyline, perhexeline, propafenone, flecainide and codeine.

Drug acetylation polymorphism is also a classical pharmacogenetic example. Considerable structural heterogeneity exists at the N-acetyl transferase (NAT) loci. There are at least three allelic NAT1 variants with identified nucleotide sequences, some of these polymorphisms being selective for various substrates. There are at least 13 allelic variants in the NAT2 locus accounting for the bimodal and trimodal distribution patterns of the acetylation of isoniazid. It is curiously satisfying to see the molecular genetic explanation for the slow metabolism based, isoniazid-induced peripheral neuropathy. Another classical pharmacogenetic phenomenon is succinylcholine sensitivity and here at least one explanation for the inactivity of serum cholinesterase is a single amino acid substitution at codon 70 because of a point mutation in the serum cholinesterase gene at nt209 which causes a nucleotide change from GAT→GGT. This produces an amino acid change from a charged aspartate to an uncharged glycine residue which presumably causes reduced substrate affinity for the atypical enzyme.

Pharmacodynamic phase

In the pharmacodynamic phase many receptor polymorphisms have been reported. These can cause variable drug responses. At least 23 single nucleotide polymorphisms have been described in the insulin receptor gene which may have functional implications. There are at least 14 single nucleotide polymorphisms in the arginine-vasopressin receptor gene with functional changes.

Receptor polymorphisms with functional implications which have yet to be fully worked out occur in steroid receptor and in β-adrenoceptor genes. Rarely resistance to coumarin anticoagulants may be due to a genetic mutation of the vitamin K anticoagulant receptor site though the molecular basis for this at the DNA and protein levels is yet to be determined.

A multidisciplinary example involving molecular immunology, molecular genetics and clinical pharmacology is resistance to hepatitis B vaccine. Production of the hepatitis B surface antigen is a dominant trait and the inability to respond is recessive. This inability to respond is associated with the extended haplotype, HLA-B8, SCO1, DR3, which is coded by HA-DR3 a/w52a, DQw2a, and DPw1.

Recently the long-QT syndrome has come in for functional and genetic analysis. Several possible pheno-types predisposing to a long QT interval have been proposed, although an abnormality of potassium channel function and a calcium/calmodulin-dependent protein kinase II mutation appear to be favoured. This is a very important pharmacogenomic finding because people with these functional genetic abnormalities may be predisposed to ventricular arrhythmias induced by certain drugs such as the H₁-receptor antihistamines, terfenadine and astemizole.

There has been some excitement recently about polymorphisms in the multiple 5-HT receptor subtypes and in 5-HT uptake sites being associated with either a predisposition to depressive illness or therapeutic responses to antipsychotics and antidepressants. More work needs to be done before one can be definite about this.

In cancer chemotherapy the problem of multi-drug resistance (MDR) is important. One important functional locus underlying this, is transmembrane drug transport: either a decreased transport in or an increased transport out of the cancer cell can result in insufficient concentrations of the chemotherapeutic agent at the site of action.

There are several potential transport related components to multidrug resistance each of which have an identified gene locus. Important amongst these are a p-glycoprotein-ABC transporter-superfamily, MDR1 gene and a MDR protein gene which when expressed lead to resistance to certain chemotherapeutic agents.

It will be possible to type tumours genetically to see whether cells express these genes and thereby go some way to predicting response to chemotherapy. AntiRNAs to these genes are capable of reversing MDR in certain resistant cancer cells which may lead to new approaches to treatment.

Two adverse drug reactions are of interest. Firstly malignant hyperthermia appears to be caused by mutations in the ryanodine receptor gene (RYR1) which cause heightened sensitivity to halothane resulting in increased calcium release and increased muscle contraction which results in severe and potentially fatal hyperthermia.

In some cases there is a familial background to ototoxic deafness caused by aminoglycosides. It is thought that the mitochondrial ribosome in the cochlea is the likely target for aminoglycoside ototoxicity. Studies of one large Arab/Israeli pedigree have revealed a mutation in a mitochondrial ribosomal RNA which is thought to render the cells of the cochlea more sensitive to aminoglycosides.

The link between pharmacodynamic effect and therapeutic response

Kuivenhoven et al. [5] have suggested that a variant in the cholesterol ester transfer protein (CETP) gene, may play a role in the progression of coronary artery atherosclerosis. They asked the question, why don’t all patients on statins who lower their cholesterol, benefit clinically from them? They propose that a polymorphism in the Tac1B gene leads to a CETP variant which is associated with a greater benefit from pravastatin, as judged by progression of coronary atheroma on coronary angiography, despite a no more than usual lowering of plasma cholesterol and lipid fractions. This may be a good example of a variable between the pharmacodynamic effect of the drug, (i.e. plasma cholesterol and lipid fraction lowering by statins), and the therapeutic response, (i.e. reduction in the progression of coronary artery atherosclerosis), which has an important influence on a therapeutic outcome.

Other variables may be involved in the efficacy of ACE inhibitors in heart failure, of anti-asthmatic therapy, antidepressant therapy, and of anti-hypertensive therapy in the prevention of stroke and heart disease. Is a genetic component involved in variability in drug-induced adaptive responses? There has been much discussion as to whether drug addiction has a genetic basis particularly addiction to cocaine and alcohol. The addictive state is an adaptive drug response so that if this proves to have a genetic basis the implication for adaptive responses to other drug therapy are considerable. The therapeutic situations in which this might be important are the drug therapy of manic-depressive disease with medium and long-term antidepressants and mood stabilisers, the production of tardive dyskinesias with neuroleptics in the treatment of psychotic states, the lifelong response to antihypertensive drug therapy, long-term drug therapy of asthma and long-term drug treatment of heart failure with ACE inhibitors with re-modelling effects upon heart and blood vessels.

Finally, the application of pharmacogenomic knowledge to the tailoring of drug therapy to the individual patient will depend upon the development of cheap, widely applicable, reliable, quick, technically simple, genomic technologies which will allow screening of the patient’s genome. This is an exciting new area of clinical pharmacology for which our subject must prepare.