Introductory Chapter: Pharmacogenomics and Pharmacogenetics in Drug Therapy

1. Introduction

There is a wide variation in drug response of different individuals of different ethnic groups. Till recently, drug therapeutics was based on average pharmacokinetic data collected by response to a particular drug in a group of people. Such approach, many a times resulted, in adverse drug reactions, or inept drug response in individuals of different ethnic groups. In fact, adverse drug reactions (ADRs) have been reported to be a major cause of hospitalization and mortality worldwide. Also, the treatment for several diseases such as hypertension, depression etc. is still empirical as it is based on hit and trial, resulting in delays in effective treatment and high cost. The variability in drug response has been attributed to race, ethnicity, poor compliance, lack of target specificity of drug and drug-drug interactions.

Pharmacogenomics refers to the application of genomics information of an individual in determining how genome of an individual may respond to treatment with a particular drug. On the other hand, the term ‘Pharmacogenetics’ refers to the role that genes of an individual play in determining drug response of that individual. According to world-wide pharmacological consortium, ‘Pharmacogenomics’ involves the study of variations in genome (DNA polymorphisms) and changes in RNA characteristics as related to drug response, and ‘Pharmacogenetics’ addresses the role of genetic variations in relation to drug response [1]. Both pharmacogenetics and pharmacogenomics are very effective tools in the field of precision medicine. Precision medicine personalizes the medical treatment based on patient’s genetic makeup and the way, body processes a particular drug at biological and molecular levels. It helps in minimizing adverse drug reactions and optimizing drug responsiveness at personalized level. It is a rapidly expanding area of research with wide translational applications in drug therapies for various diseases such as cardiovascular diseases, renal diseases, cancer, hypertension, and mental health.

With the rapid progress in Next generation sequencing techniques like microarray, transcriptomics and whole exome sequencing, choice of drug therapy is now increasingly made based on genetic profiling, lifestyle, and environmental factors. The major limitation of current usage of pharmacogenomics is that it is being used in very few health conditions due to lack of availability of data for many diseases in different populations.

Pharmacokinetics and Pharmacodynamics of the drug are the two important components of drug response. Pharmacokinetics involve studying the role of factors such as drug absorption, metabolism, excretion etc. in determining the concentration of drug or its active metabolites. Pharmacodynamics of a drug addresses the interaction of the drug or its active metabolite with its target molecule(s) or its downstream effector molecules. Studies have shown that both pharmacogenomics and pharmacogenetics modulate pharmacodynamics and pharmacokinetics parameters of the associated drugs.

2. Role of genetic variations in drug response

Drug concentration is an important factor which contributes to variable drug response. It has been observed that genetic variations such as single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) in genes of drug metabolizing and transport enzymes can significantly modulate drug concentrations. For example, polymorphism in CYP2C19 gene has been shown to modulate clopidrogel response, while polymorphism in CYP2C9 gene alters warfarin response by altering its pharmacokinetic parameters. On the other hand, polymorphism in CYP4F2 gene has been shown to modulate pharmacodynamics of warfarin [2]. The CYP2C19 metabolizes clopidrogel to its bioactive compound and this depends on its genetic variants. Homozygous variants for CYP2C19*2 code for loss-of-function proteins which completely lack CYP2C19 activity and thus are not good responders to warfarin. Heterozygous carriers, on other hand show response on increasing the dose as they possess some enzyme activity. Thus, response based on gene variants shows variability depending on the gene locus as well as genetic variant(s) at a particular locus.

Many effects of gene variants in drug metabolizing enzymes have been associated with gain or loss of function of the gene activity, with predominance linked to gain of function effect. This has been well described for increased copy numbers of CYP2D6, a morphine metabolizing enzyme, resulting in enhanced effect of morphine during codeine therapy [2].

Genetic variants of certain drug metabolizing enzymes may also increase susceptibility to drug toxicity by modulating its plasma concentrations. This is apparent in case of some drugs which show a very small margin between effective and toxic concentrations. Thus, a genetic variant may result in increased or decreased concentration of the active drug metabolite. For example, some of thiopurine S-methyltransferase (TPMT) gene variants have been reported to enhance toxicity of immunosuppressant drug, azathioprine. Toxicity of several anticancer drugs has also been shown to be influenced by polymorphisms in TPMT and other drug metabolizing enzymes [2]. Further, toxic effects of the gene variants are also dependent on how a specific drug is metabolized. It has been observed that those drugs which are metabolized by a single enzyme show less modulation by gene variants [2] and the drugs metabolized by multiple enzymes/pathways are not influenced by gene polymorphisms unless the polymorphism affect more than one enzyme of the drug metabolizing pathway [2]. Further genetic variations leading to loss or gain of function of genes coding for enzymes involved in drug transport into or out of a cell can also alter drug efficacy/response and sometimes its toxicity. This is seen in case of SNP SLCO1B1*5 of SLCO1B1 gene which results in loss of function leading to increased Simvastatin plasma levels and myopathy [2].

The ancestry has a big role in determining the response to a drug due to prevalence of certain genotypes in a specific community/race. Some genotypes affecting loss or gain of function of a gene involved in drug metabolism, or drug receptor interaction may be solely present in a particular population, thereby affecting drug response/toxicity or efficacy. For example, HLA-B*15:02 genotype is more prevalent in Southeast Asia and has been found to be associated with carbamazepine-related drug toxicity, however, this allele is rare in European population, leading to less adverse carbamazepine-related drug reactions [2].

3. Clinical applications of pharmacogenomics and pharmacogenetics

Due to availability of vast data supporting role of pharmacogenomics and pharmacogenetics in modulating response to drugs, several pre-clinical and clinical trials have been carried out in this direction. In February 2020, FDA published a ‘Table of Pharmacogenetic Associations which provides clinically useful information on drug-gene interactions and their clinical outcomes [3]. This table provides detailed scientific evidence for genotype-phenotype associations of several clinical drugs. There is also detailed information on pharmacogenomics of drugs in clinical use compiled by Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. These guidelines have also been annotated in Pharmacogenomics Knowledgebase [4].

The major applications of pharmacogenomics/genetics in the field of cardiovascular diseases, oncology, psychiatry, diabetes, antiretroviral and immunological therapies have been discussed in the subsequent chapters of this book.

3.1 Cardiovascular diseases

Antiplatelet drug, Clopidogrel is widely used in patients undergoing percutaneous coronary intervention (PCI). This drug is metabolized to its active compound in a two-step enzymatic reaction catalyzed by CYP2C19. Three gene variants of this enzyme, CYP2C19 *1/*2/*3 are associated with normal (*1) or loss of function (*2/*3) activity. This results in either normal metabolism (NM) or poor metabolism (PM) of the drug, resulting in varied drug availability in different genotypes. This results in increasing the risk of adverse events in *2 and *3 genotype carriers at normal doses. Tripling the drug dose in *2 and *3 genotype carriers has been found to be effective. Hence, it is now mandatory in several countries to genotype patients before prescribing this drug [5]. In fact, it is one of the most common pharmacogenetic applications in a clinical condition. Another drug, Warfarin, a vitamin K antagonist is used for treating thromboembolic disorders. This drug shows varied genotype-phenotype response, which is dependent on gene variants of CYP2C9 and VKORC1. Another example is statins, which are commonly prescribed drugs in dyslipidaemia. In some patients, they can cause adverse drug reactions like myopathy, as in case of Simvastatin. The gene variants of SLCO1B1 have been reported to be associated with this adverse reaction [6].

In addition to above drugs, there is emerging evidence of pharmacogenetic based response to β-blockers. β-blockers are commonly used drugs in hypertension and in heart diseases. They function by blocking β1-adrenergic receptor coded by the ADRB1 gene. Two gene variants in ADRB1, Ser49Gly and Arg389Gly have been shown to be associated with increased adrenergic activity and increased mortality in patients treated with Verapamil [7]. β-blocker treatment in patients carrying these alleles has been found to reduce mortality and is recommended over calcium channel blockers. Several other ADRB1 gene variants have also been found to modulate response to β-blockers [7]. Polymorphisms in GRK4 (G protein coupled receptor gene), have also been shown to modulate β blocker activity and associated cardiovascular outcomes. Polymorphisms in several other genes involved in mechanism/metabolism of β-blockers such as CYP2D6 are plausible candidate genes being explored for their effect on B blocker response [8]. Similarly, activity of ACE inhibitors, Angiotensin Type II receptor blockers (ARBs), diuretics etc. has been shown to be modulated by polymorphisms in genes associated with pharmacokinetics, pharmacodynamics, and metabolism of the target molecules.

3.2 Mental health disorders

Mental diseases such as depression, schizophrenia, anxiety are major health disorders associated with general morbidity, mortality, and disability worldwide. Research in the past decade has documented that treatment with antidepressant drugs is often not effective and may elicit varied response. This has been partly attributed to genetic factors, especially in the target genes of anti-psychotic drugs, namely SLC6A4, HTR2A, HTR2C, DRD2, ABCB1, CYP2C19, CYP2D6, and COMT genes which code for serotonin reuptake, transporters, dopamine D2 receptor, P-glycoprotein that control uptake of drugs into the brain and drug-metabolizing enzymes respectively. As reviewed recently, genetic polymorphisms in drug metabolizing genes CYP2C19 and CYP2D6 have maximal clinical application and patients are stratified into normal, intermediate, and poor metabolisers based on the carrier status of functional gene variants, which in turn determine the activity of the metabolizing enzymes. It has been observed that genotype affects the success of antidepressant or antipsychotic therapy in patients. It has been suggested that genotyping based dosing of patients receiving these drugs may result in better treatment response [9]. A recent systematic review has shown that blood levels of several drugs such as aripiprazole, haloperidol, risperidone, escitalopram, and sertraline were significantly associated genetic variants of CYP2C19 and CYP2D6 and could be a useful tool for precision drug dosing in patients [10]. However, it was concluded that more studies are needed for this to be implemented as a clinical tool. Thus, pharmacogenetics of psychiatric drugs has the potential to develop as a useful and cost-effective tool for precision medicine and compliance with minimal adverse effects.

3.3 Oncotherapy

Cancer is one of the major health concerns, prevalent in all the parts of the world. The major issue with the cancer treatment is due to prevalence of non-responders and relapse cases. As many as 75% of the cancer patients are non-responsive towards the conventional therapy [11]. For example, 5-fluorouracil is one of the most widely preferred therapy for colorectal and gastric cancer [12]. In the human liver cells, dihydro-pyrimidine dehydrogenase (DPD) is the main enzyme responsible for the metabolism of 5-fluorouracil [13]. DPD expression is the major gene which decides the response and the tolerability to 5-FU-based chemotherapy [12]. Previous studies have shown that four DPYD variants are very important, taking into consideration their impact on enzyme function and toxicity risk: rs3918290, rs55886062, rs67376798, and rs75017182 [14]. In particular, rs3918290 and rs55886062 have deleterious effect on DPD activity; whereas rs67376798 and rs75017182 have mild to moderate effect on its activity [15]. Low activity of these enzymes leads to more toxic reactions. rs895819 A/G polymorphism in the DPYD-regulatory microRNA miR-27a is also associated with lower DPD activity [16].

Another well studied anti-cancer drug is Sunitinib, a tyrosine kinase inhibitor [17]. Sunitinib is converted into its active component, N-desethyl metabolite (SU12662) by CYP3A4 [17]. Teo et al. [18] also suggested that the variations in CYP3A5 may not affect the of the sunitinib metabolism as there is redundancy present between CYP3A5 and CYP3A4 enzymes. Although, CYP3A4 has better affinity towards sunitinib as compared with CYP3A5 [19]. In a Caucasian population, it was observed that the CYP3A4*22 polymorphism is crucial in clearance of sunitinib [20]. However, this polymorphism is not important in Asian population. There are various reports suggesting that these polymorphisms and genetic variations and their outcome vary within different populations so it can be implied that pharmacogenomics is a better approach as compared to pharmacogenetics.

In this chapter, we have tried to elucidate the importance of genetics in the drug therapy. The two important streams of pharmacological sciences: pharmacogenomics and pharmacogenetics, provide important insights into the personalized medicine. Their workflow includes the right drug selection, identification of optimal drug dosing, increasing the efficacy and minimization of drug toxicity. With advancement of basic research, there are better opportunities for the designing ‘personalized’ gene panels based on genetic and/or genomic profiles to improve the treatment for an individual. However, the integration and implementation of these panels into routine clinical practice remains a major multidisciplinary challenge. Here, we emphasize role of policy makers in incorporation of pharmacogenetics and pharmacogenomics into mainstream clinical practice to improve the drug therapy.