by Sethu Poswa
Let us set the scene, an individual has just been diagnosed with depression, making them part of the 280 million other people who suffer with it worldwide. Should they decide to go on treatment, the next step would involve the healthcare professional selecting the appropriate treatment for them, which should be easy right? Wrong. Often times patients are subjected to clinical trials which is based trial and error to find the appropriate treatment. The problem with this method is its inefficiency, in that treatment only starts to work after 4-6 weeks of the trial and during that time period, there is no reliable way of predicting whether the patient will respond to the treatment or whether they will experience drug-induced adverse events, starting the entire process from scratch until appropriate treatment is determined. The danger with this is that recovery is delayed, and the patient may prematurely stop taking medication. Fortunately, pharmacogenetics provides a potential tool in successfully predicting treatment response.
With National Mental Health Awareness Month approaching soon in October, it is only appropriate that we discuss the steps being taken by science to improve the clinical outcome of patients suffering from depression. Pharmacogenetics studies how an individual’s genetic make-up affects their response to drugs (in this case, SSRIs) and aims to improve disease outcome while preventing the occurrence of drug-related adverse events such as suicide attempts. The most commonly prescribed class of antidepressants are the selective serotonin reuptake inhibitors (SSRIs). This is because SSRIs such as citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline display efficacy and are generally tolerable. Although SSRIs are commonly prescribed, there has been variable responses to them, with only about 33% of people on treatment experiencing an effective response to SSRIs. It is estimated that genetic factors account for approximately 42% of the variability in response to SSRIs, which is why pharmacogenetic studies mainly analyse the genes involved in the metabolism of SSRIs.
SSRIs work by reducing the reuptake of the neurotransmitter serotonin by the presynaptic neurons and it does so by inhibiting the serotonin transporter (SERT). This results in serotonin remaining in the synapse for an extended period of time so that it can act even more on the postsynaptic serotonin receptors. In the past, it was hypothesised that depression was caused by lower levels of serotonin in the body, but modern scientific literature rejects that hypothesis, although it is interesting that literature has observed that people whose serotonin levels have been increased by SSRIs showed improvement with regards to experiencing symptoms. It is also worth mentioning that serotonin plays a role in mood regulation so that feelings of anxiety and depression are reduced within an individual.
SSRIs are mainly metabolised by the enzymes cytochrome P450 2D6 (CYP2D6) and CYP2C19 and is transported by P-glycoprotein (P-gp). CYPD2D6, CYP2C19 and P-gp are encoded by the CYP2D6 gene, the CYP2C19 gene and the ATP Binding Cassette B1 (ABCB1) gene, respectively. Genes have a reference nucleotide sequence and differences from those reference sequences among individuals are referred to as polymorphisms. Polymorphisms exist in different forms such as insertions/deletions, length variation, single nucleotide polymorphisms (SNPs), etc. with some polymorphisms being beneficial while others have detrimental consequences. All of the different polymorphisms of a particular gene forms different versions of the same gene namely, alleles.
Polymorphisms typically alter the structure of the protein for which it encodes, which results in altered protein function. A polymorphism can either affect enzyme activity and/or expression. Polymorphisms in the highly polymorphic CYP2D6 and CYP2C19 genes can determine an individual’s ability to metabolise SSRIs. An individual can be a poor (PM), intermediate (IM), extensive (EM) or ultrarapid metabolizer (UM). Literature has reported that UMs relates to the number of copies of the CYP2D6 gene that a person possesses while PMs are associated with the possession of alleles that are known to correspond with decreased or deficient CYP2D6 activity. UMs are going to display no response to a standard dose of SSRIs since UMs display a high enzyme activity and so UMs will have low concentrations of the drug and its active metabolites, meaning they will experience no effect from the SSRI. On the other hand, UMs are also at risk of SSRI toxicity since active metabolites can accumulate in the body, leading to adverse drug reactions (ADRs) such as the development hypertension or anxiety. PMs are will inefficiently convert the parent drug to its active metabolite, and they will therefore not respond to treatment and are at risk of the toxic accumulation of the parent drug in the body as well experiencing more side effects such as nausea, diarrhoea, etc.
Literature has reported that IMs for CYP2D6 have shown better response to antidepressants, while UMs have been associated with a higher risk of not responding to treatment and higher suicide cases. PMs and IMs of CYP2D6 or CYP2C19 were reported to experience more severe side effects and side effects occurred the most in individuals with these metaboliser statuses. PMs of CYP2D6 and CYP2C19 have also been linked to having higher plasma concentrations of the parent drug.
The same pharmacogenetic principles can be applied to the ABCB1 gene, which encodes for P-gp. P-gp is a transporter protein that limits drug intake of certain drugs into the brain by active transport and therefore plays a role in regulating the availability of SSRIs at the brain, which is the action of site of SSRIs. A polymorphism in the ABCB1 gene could result in increased/decreased P-gp expression or increased/decreased functioning. This means that either more or less SSRIs will be removed from the brain, and this will affect the treatment outcome. Resistance to SSRIs is hypothesised to be linked to P-gp hyperactivity, by removing a large enough concentration to have no effect on the patient. Other polymorphisms in ABCB1 have also been linked to treatment response as well as a decreased/increased occurrence of side effects, depending on whether the SSRI is a substrate of P-gp, which includes fluoxetine, citalopram, sertraline fluvoxamine and paroxetine.
With pharmacogenetics being a relatively new field in science, there is still a lot more knowledge to harvest, for example, the physiological role of several genes are unknown as well as the mode of action of a high proportion of drugs, including antidepressants. Of course, pharmacogenetics cannot be the only tool used to determine what antidepressant would be safe and affective for an individual to use., as there are other factors to take into consideration as well as epigenetics. For example, gene and environment interactions have to be taken into consideration, as well as drug-drug interactions, because the patient could also be on medication that is metabolised by CYP2D6 or CYP2C19, for example and they could potentially be potent inhibitors of those enzymes and affect the efficiency with which the SSRI is metabolised. Believe it or not, but an individual’s ethnicity will also affect their metaboliser status since the alleles that determine metaboliser status as well as P-gp functioning are distributed differently, depending on what population the person is part of, for example, approximately 5-10% of people who are of European descent are PMs of CYP2D6 and it is rarer in people of African and Asian descent (approximately 3%) in non-European populations.
The field of pharmacogenetics is providing valuable information that is sure to become even more valuable in the future as technologies develop and more is known about how xenobiotics interact with biological systems. This information will help improve clinical outcomes in an efficient and less intrusive manner.
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