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Lipid testing and cardiovascular risk assessment: cut-off points

, 26 August 2020/in Featured Articles /by 3wmedia

Dyslipidemia is one of the major risk factors for the development of cardiovascular disease (CVD). However, which lipoproteins to measure and what cut-off points to use in order to accurately assess this risk remains debatable.

by Mohamed S. Elgendy and Dr Mohamed B. Elshazly

Cardiovascular disease (CVD) mortality in the US in 2011 was estimated at 786 641 deaths representing approximately 33% of total annual deaths [1]. It remains the leading cause of mortality and morbidity in the developed world. Over many years of study, dyslipidemia has been identified as one of the major risk factors for developing CVD that can be modified through behavioral modifications as well as medications.

Lipoproteins
Lipoproteins are small particles formed of lipids and proteins, which play an important role in the transport and metabolism of cholesterol. Based on their relative density, they are divided into five major categories: high-density lipoprotein (HDL), low-density lipoprotein (LDL), intermediate density lipoprotein (IDL), very low-density lipoprotein (VLDL), and chylomicrons. LDL carries 60–70% of total serum cholesterol, HDL carries 20–30%, and VLDL carries 10–15% [2]. The remaining lipoproteins, namely triglyceride-rich lipoproteins such as VLDL, remnants and IDL, in addition to lipoprotein(a), carry a relatively small fraction of total cholesterol. Numerous studies have shown that LDL is the most atherogenic lipoprotein particle and lowering its levels has been the cornerstone of dyslipidemia management and CVD risk reduction in recent years. However, there is emerging evidence indicating that other lipoproteins also play a significant role in the process atherogenesis [23].

Relationship between lipoproteins and CVD risk
Several studies have reported a continuous relationship between LDL reduction and CVD risk reduction [3]. No threshold was identified below which a lower LDL concentration is not associated with lower risk [4]. For example, in the recent IMPROVE-IT trial, the incidence of CVD morbidity and mortality was lower in the ezetimibe/simvastatin group (with a median LDL-C follow-up of 53.7 mg/dL) compared to the simvastatin-alone group (with a median LDL-C follow-up of 69.5 mg/dL) [5]. In another study, individuals with hypobetalipoproteinemia, who have LDL-C levels less than 70 mg/dL, show prolonged longevity and very minimal rates of myocardial infarctions [6]. All of this supports the notion of ‘lower is better’.

LDL-C levels in the range of 25–60 mg/dL are considered physiologically adequate [7]. Even levels below 25 mg/dL have failed to show any adverse effects in a couple of recent trials [8, 9]. Although adverse effects of very low LDL, like hemorrhagic stroke and neurocognitive deficits, have been reported in some studies, they were neither significant nor consistent [10, 11]. Therefore, the benefits of achieving very low levels of LDL outweigh the risks. On the one hand, the lack of randomized clinical trials comparing the outcome of different LDL goals has made it difficult to reach a consensus among different guidelines on the optimal goals for high-risk patients or those with coronary disease equivalents with the commonly used target still being <70 mg/dL [12–14]. On the other hand, in the most recent American College of Cardiology (ACC)/American Heart Association (AHA) guidelines, targets were abandoned because of the notion that the benefit of statin is independent of LDL level [15]. Despite these differences, we believe that the conglomerate of evidence suggests that your LDL can never be too low although data examining patients with extremely low levels <25 mg/dL is still limited. The potential re-establishment of new even lower LDL targets in upcoming guidelines will require careful examination of data from proprotein convertase subtilisin kexin-9 (PCSK-9) trials to identify specific LDL levels below which risk outweighs benefit. Other factors contribute to total atherogenic risk
Despite the established recognition of LDL as the most atherogenic lipoprotein, it is not representative of total atherogenic risk. Elevated triglycerides were found to be associated with increased risk for CVD and this suggests that triglyceride-rich lipoproteins (TGRLs), especially the remnants, are atherogenic. These lipoproteins include VLDL, IDL, and chylomicrons (only in the non-fasting state). As LDL standard measurement by the Friedewald formula [Total cholesterol – HDL – triglycerides/5] [1] only includes LDL-C and lipoprotein(a), non-HDL has been proposed as a more inclusive parameter of atherogenic risk because it also incorporates VLDL-C, IDL-C and remnants in addition to LDL-C. In fact, several studies have demonstrated that non-HDL-C is more strongly associated with CVD than LDL-C and is a more powerful risk predictor [16–21]. Moreover, non-HDL measurement comes at no extra cost, as it is calculated from the standard lipid profile by subtracting HDL from total cholesterol, and does not require prior fasting. Nevertheless, due to the smaller number of studies examining non-HDL as a target of therapy, compared to that examining LDL, most of the current guidelines recommend non-HDL as a secondary target of therapy [2, 12, 14, 22]. Only the National Lipid Association recommends non-HDL as a primary target of therapy as well as LDL [22]. We believe this current situation represents a transitional phase toward using non-HDL as a primary target of therapy, just like the past transition from total cholesterol to LDL-C. This is most important when discordance exists between LDL and non-HDL levels within individuals, a relatively common finding particularly in patients with low LDL and high triglyceride levels [23]. The currently recommended non-HDL treatment goal is 30 mg/dL higher than that of LDL-C based on the rationale that ‘normal’ VLDL exists when triglycerides level is <150 mg/dL, which is <30 mg/dL [2]. However, in a recent study of 1.3 million US adults, non-HDL level of 93 mg/dL was percentile equivalent to LDL of 70 mg/dL [23] suggesting that a lower non-HDL goal should be targeted. Particle-based measures such as apolipoprotein-B (Apo-B) and LDL particle concentration (LDL-P) also have the potential to replace cholesterol-based measures such as LDL or non-HDL as predictors of risk and targets of therapy. Apo-B constitutes the protein component of almost all the known atherogenic lipoproteins: VLDL, IDL, and LDL,;therefore, Apo-B measurement has been suggested to better estimate particle concentration, a more accurate reflection of subendothelial atherogenesis. Apo-B has been shown to be a better risk marker than LDL in multiple studies [17, 21, 24–29]. Many guidelines currently recommend Apo-B as an optional risk marker and target of therapy [12, 14, 22, 30]. Similarly, almost all the studies comparing LDL-P to LDL-C have shown superiority of particle concentration in terms of CVD risk assessment [31–34]. In the LUNAR trial and Framingham Offspring Study, there was a strong correlation between Apo-B and LDL-P with non-HDL, respectively, suggesting that non-HDL, available from the standard lipid profile, can be used satisfactorily for risk assessment [31, 35] keeping in mind that Apo-B may be superior in instances when discordance exists [36]. Whereas individual lipid parameters are important in risk prediction, summary estimates that assess the ratio of pro-atherogenic to anti-atherogenic lipoproteins also add important prognostic information regarding CVD risk. Out of the ratios that have been considered, total cholesterol to HDL cholesterol ratio (TC/HDL) and Apo-B/A1 are the most propitious. Despite TC/HDLs strong association with CVD risk [37–43], some have argued against any additional benefit this ratio might have, given that its two variables are included in estimating LDL by the Friedewald formula, in calculating non-HDL-C and in CVD risk estimation scores in addition to the contentiousness of HDL raising therapeutic strategies. However, in a recent 1.3 million population study, it has been documented that there is significant TC/HDL patient-level discordance in relation to LDL and non-HDL [44, 45]. This implies that TC/HDL may carry additional information reflecting atherogenic particle size and concentration [44, 45]. Notably, a TC/HDL ratio of 2.6 was percentile equivalent to an LDL level of 70 mg/dL (Table 1). Outcome data examining the clinical impact of TC/HDL discordance is still in progress and thus current guidelines do not currently recommend using TC/HDL. Summary
There is no doubt that the field of dyslipidemia management has been one of the most dynamic fields in cardiology over the last 3 decades. With the recent advent of PCSK-9 inhibitors, we need to re-evaluate our understanding of lipoprotein reduction and ask ourselves important questions: Should guidelines re-establish treatment targets? What is the best lipoprotein parameter for predicting risk? Is it one parameter that is superior or is it the input of multiple parameters? What do we do when discordance between lipid parameters within individuals exists? Although a lot of data necessary to answer these questions is still a work in progress, recent data may be able to provide some insightful answers. First, LDL-C is not the optimal marker for total atherogenic risk. Second, instead of evaluating the performance of individual lipid parameters at a population level, we should evaluate their performance at an individual level where identifying discordance within individuals is key to understanding which marker may be superior. Third, particle-based measures such as Apo-B and LDL-P may be superior to cholesterol-based measures; however, summary estimates such as TC/HDL or Apo-B/A1 ratios also add significant information to individual parameters. Fourth, identifying new lipoprotein treatment goals is dependent on identifying certain lipoprotein levels below which risk may outweigh benefit. Therefore, it seems likely that a future where very low percentile-equivalent cut-off points of several lipoprotein parameters and ratios may be set as simultaneous goals for treatment.

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The authors
Mohamed S. Elgendy¹ and Mohamed B. Elshazly*² MD
¹Kasr Al Ainy School of Medicine, Cairo University, Cairo, Egypt
²Cleveland Clinic, Heart and Vascular Institute, Cleveland, OH 44195, USA

*Corresponding author
E-mail: elshazm@ccf.org

Apolipoproteins – new perspectives for lipid profiling, but other challenges remain

, 26 August 2020/in Featured Articles /by 3wmedia

Atherosclerotic cardiovascular diseases (CVD) are the leading cause of death in the West, and dyslipidemia is considered to be one of their key risk factors. The majority of CVD cases could be prevented by effective management of dyslipidemia. The use of new biomarkers like apolipoproteins as part of extended lipid profiles may be among the most significant new tools for such a task.

Dyslipidemias
Dyslipidemias cover a broad spectrum of lipid abnormalities. Clinicians have so far paid maximum attention to elevated levels of total cholesterol (TC) and low-density lipoprotein-cholesterol (LDL-C). Many other types of dyslipidemias, however, also appear to enhance the risk of CVD.

Lipid metabolism can become imbalanced or disturbed in several ways, resulting in changes to plasma lipoprotein function and thereafter to the development of atherosclerosis. Many patients who have high cardiovascular risk still have unfavourable lipid profiles.
Given the fast-growing interest in lipidology, clinicians have sought ways to apply evidence-based medicine daily in dyslipidemia management. There are several lipid guidelines from professional societies in different parts of the world to diagnose and make assessments of dyslipidemia.

The role of apolipoproteins
In recent years, both Europe and the US have witnessed revisions in CVD guidelines and in the approach to lipid profiling. One major new area of attention is the role of apolipoproteins.

Apolipoproteins serve to bind lipids (fat and cholesterol) to form lipoproteins. Lipids are insoluble in water. However, apolipoproteins have amphiphilic (detergent-like) properties, which make them both fat- and water-soluble. As a result, the lipoprotein particle effectively becomes water-soluble, allowing for the transport of lipids through the lymph and circulatory systems. Apolipoproteins also regulate lipoprotein metabolism.
So far, most efforts have been focused on two apolipoproteins, apolipoprotein B (apo B) and apo A-I.

From a technical viewpoint, there are numerous advantages in determining concentrations of apo B and apo A-I. Robust immunochemical methodologies are possible to attain with conventional assays using appropriate reagents. These methodologies have also been shown to provide required levels of analytical performance. Moreover, apo assays do not require fasting conditions and are not sensitive to moderately high levels of triglycerides (TG).

Apo B
Apo B is the main protein in LDL-C and directly associated with cholesterol uptake. Elevated apo B indicates an increased risk of CVD even when total cholesterol and LDL-C levels are otherwise normal.
In the laboratory, apo B concentration provides a good indicator of the number of particles in plasma of VLDL (very low-density lipoprotein), IDL (intermediate-density lipoprotein) and LDL (low-density lipoprotein).

Apo B has aroused especially high interest given its presence in high concentrations of small dense LDL. The latter is seen to be “an important predictor of cardiovascular events and progression of coronary artery disease (CAD)” and it has been endorsed as an emerging cardiovascular risk factor by the US National Cholesterol Education Program Adult Treatment Panel III in 2007.

Some contradictory evidence indicates need for more study
A host of prospective studies have shown apo B to be equal to LDL-C in risk prediction. Post-hoc analyses of numerous statin trials suggest that apo B may be not only a good biomarker but also a better treatment target than LDL-C.
However, verifying this is likely to take some more years. Apo B is yet to be included in risk calculation algorithms. Meanwhile, data about its utility remains contradictory.
For example, a meta-analysis by the Emerging Risk Factor Collaboration in 2009 indicates that apo B does not provide any benefit beyond non-high-density lipoprotein cholesterol (non-HDL-C) or traditional lipid ratios. A year later, apo B showed no benefit compared to traditional lipid markers in diabetics in the so-called FIELD study (Fenofibrate Intervention and Event Lowering in Diabetes). On the other hand, in 2011, another meta-analysis of LDL-C, non-HDL-C and apo B conducted by Canadian researchers found the apolipoprotein to be a superior marker of CV risk. Indeed, the authors, from the Royal Victoria Hospital at McGill University concluded that apo B would prevent more than one-and-a-half times the number of CV events compared to a non-HDL-C strategy alone.

Apo A-I and HDL
Unlike apo B (and LDL cholesterol), apo A-I is the major protein of HDL and provides a good estimate of HDL concentration. One HDL particle could carry several apo A-I molecules. So far, plasma apo A-I correspondences have been established (with levels of <120 mg/dL for men and <140 mg/dL for women) correlating to ‘low’ HDL-C.
Apo A-I is sometimes tested alongside apo B. The ratio between apo B and apo A-I can be used as an alternative to the total cholesterol/HDL cholesterol ratio or non-HDL-C/HDL-C ratio for indicating risk. However, as with the latter, for diagnosis and treatment, the components of the ratio have to be considered separately.

Other apolipoproteins
Research is also under way into the other apolipoproteins. Indeed, several clinical labs already offer analysis of their concentrations. These include apo A-II, apo C-II and C-III and apo E and have also provoked interest in clinical researchers.

Like apo A-I, apo A-II is also a major constituent of HDL-C, and the distribution of the former in HDL is primarily determined by the rate of production of apo A-II. Apo A-II has an important role in reverse cholesterol transport and lipid metabolism. Its increased production promotes atherosclerosis by decreasing the proportion of anti-atherogenic HDL containing Apo A-I.

Apo C-II is a co-factor for lipoprotein lipase, which breaks down lipoproteins and hydrolyses triglycerides and VLDL for absorption into tissue cells. Low concentrations of apo C-II have been linked with hypertriglyceridemia.
Apo C-III modulates uptake of triglyceride-rich lipoproteins by LDL receptor related proteins through inhibition of lipoprotein lipase. Elevated apo C-III levels are associated with both primary and secondary hypertriglyceridemia.

Apo E is found in IDLs and has several functions. These include transporting triglycerides to the liver and distributing cholesterol between cells. Apo B affects the formation of atherosclerotic lesions by inhibiting platelet aggregation and its deficiency provokes high serum cholesterol and triglyceride levels, leading to premature atherosclerosis.

CVD guidelines and apolipoproteins
In spite of the growing interest in other apolipoproteins, the highest level of interest is on apo B and A-1. Both are covered by recent modifications in certian CVD guidelines.

In 2011, the European Atherosclerosis Society (EAS) and the European Society of Cardiology (ESC) updated several CVD guidelines. Changes included doubling the stratification of cardiovascular risk from two to four categories – “very high”, “high”, “moderate” and “low”, along with the tightening of therapeutic targets for each category.
While acceptable LDL-C levels were reduced significantly across risk groups, two new therapeutic targets were recommended for patients in “very high” and “high” risk categories, especially those with combined dyslipidemia. These consisted of non-HDL cholesterol and apolipoprotein (apo) B levels.
In Europe, updated EAS/ESC guidelines recommend baseline lipid evaluation be made either on the basis of TC (total cholesterol), TG, HDL-C, and LDL-C. These are typically calculated by the so-called Friedewald formula. The new guidelines also propose using “apo B and the apo B/apo A1 ratio,” which it acknowledges are “at least as good risk markers compared with traditional lipid parameters.”

Meanwhile, in the US, professional endocrinology bodies have directly enhanced their focus on dyslipidemia since 2012, when the American Association of Clinical Endocrinologists (AACE) released new clinical practice guidelines (CPG) on the ‘Management of Dyslipidemia and Prevention of Atherosclerosis’.
The AACE’s aim was to update its existing CPGs and to complement the Diabetes Mellitus Comprehensive Care Plan CPG. Nevertheless, the AACE emphasizes that the ‘landmark’ National Cholesterol Education Program (NCEP) guidelines of 1993 continued to serve as the ‘backbone’ of its revised recommendations.
Though the new CPGs from the AACE continue to emphasize the importance of LDL-C reduction and support the measurement of inflammatory markers to stratify risk in certain situations, they nevertheless have several noteworthy features. What makes them unique for endocrinologists is their recommendation on the use of apo B or LDL particle number measurements in order to “achieve effective LDL-C lowering, provide screening recommendations for persons of different ages, and identify special issues for pediatric patients.”

Need to harmonize lipid guidelines
In spite of growing enthusiasm about apolipoproteins, some endocrinologists have said there first needs to be more harmony in lipid guidelines. It is no secret that lipid guidelines have critical differences, including recommended lipoprotein levels for risk assessment, CVD risk estimation methodologies and the need for a treatment target or the use of drugs other than statins.
Though LDL-C remains a primary target in most guidelines, the International Atherosclerosis Society (ISA) favours non-HDL-C for dyslipidemia management, as does the AACE in certain conditions. Non-HDL-C is also considered to have higher predictive capability than LDL-C in a wide variety of clinical situations, and be more practical since it can be performed in a non-fasting state.

Yet another source of much debate concerns differences in approach to CVD risk assessment. Time frames for risk vary from 10-years to life time. On their part, the American College of Cardiologists (ACC) and American Heart Association (AHA) recommend measuring 30-year risk in patients aged 20–59.
CVD risk is defined as the risk of both mortality and morbidity in most guidelines. However, the joint (and revised) EAS/ESC guidelines mentioned above calculate fatal CVD risk only. Many guidelines calculate 10-year risk of CVD. However, ISA recommends measuring the lifetime risk.

Physicians ‘bewildered’
A recent issue of ‘European Endocrinology’ poses some candid questions: Today, “physicians are bewildered by a multitude of guidelines written by different professional societies, which have more diversities than commonalities.” The author calls for “organizing a working group in dyslipidemia management and integrating existing guidelines into a general consensus document.” However, he concludes, “owing to the number of controversial areas, this is not likely to occur soon.”
Healthcare portal Medscape puts the ball back in the clinician’s court – in some senses, restating the obvious. Lipid guidelines do not “override the individual responsibility of health professionals to make appropriate decisions in the circumstances of the individual patients, in consultation with that patient, and, where appropriate and necessary, the patient’s guardian or carer”.

Pharmacogenomics: implications for drug safety

, 26 August 2020/in Featured Articles /by 3wmedia

The increased burden of hospital admissions due to adverse drug reactions (ADRs) carries significant implications for patients and healthcare systems. Understanding the correlations between genetics and drug safety may improve clinical outcomes through the realization of personalized medicine. This article outlines a practical approach to pharmacogenomics with examples in clinical practice.

by Dr Marcin Bula and Prof. Sir Munir Pirmohamed

Introduction
The World Health Organization (WHO) defines an adverse drug reaction (ADR) as a response to a drug which is harmful and unintended and which occurs at doses normally used in man for prophylaxis, diagnosis or treatment of disease or the modification of physiological function.

There are several classifications used to describe ADRs taking into account severity, source of reported data, reaction time and location of reaction. In this article, we focus on the most-widely used classification and divide ADRs into two major groups: dose-related (type A – ‘Augmented’) and apparently non-dose-related (type B – ‘Bizarre’). Type A reactions are predictable, more common and usually less serious. They can be managed by simply reducing the dose or withholding the drug. Type B reactions are uncommon, unpredictable and usually more serious. They may either be immunologic or non-immunologic in nature, and because we do not understand pathogenesis, this makes the reactions more difficult to predict and prevent.

The overall incidence of ADR-related hospital admissions is approximately 6.5% [1, 2] although this figure might be an underestimate due to complexity of cases presenting to hospitals, compounded in real-world settings, by the poor reporting of ADRs by healthcare professionals. A previous systematic review of drug-related hospital admissions showed that antiplatelets, NSAIDs and anticoagulants were responsible for more than 50% of the total ADR-related hospitalizations [3]. It has been estimated that ADRs cost the UK National Health Service (NHS) approximately £1 billion annually, and studies in the USA have suggested that ADRs are the fourth to sixth leading cause of death [4].

Type B adverse drug reactions
Type B ADRs are a major concern for healthcare because of their unpredictable multifactorial nature, and potentially life threatening clinical outcomes. The most common organs affected are the skin, liver and blood cells. Some type B ADRs have been found to have a genomic component; the most striking example is the association between abacavir hypersensitivity and human leukocyte antigen (HLA). Abacavir is a guanosine analogue used in combination therapy with other antiretroviral medications in the treatment of human immunodeficiency virus (HIV). Previous studies have shown that approximately 4–8% [5] of patients develop a hypersensitivity reaction (HSR) within the first 6 weeks of treatment, characterized by fever, rash, gastrointestinal symptoms, general malaise, and other less common manifestations, such as headaches, respiratory and musculoskeletal symptoms [6]. The association between abacavir hypersensitivity and the HLA Class I allele, HLA-B*57:01 was first reported in 2002 by two independent research teams in Australia and North America, followed by a study in the United Kingdom. This has been complemented by functional studies that have shown that abacavir hypersensitive HLA-B*57:01 carriers show increased proliferation of CD8+ T lymphocytes following drug exposure. The exact mechanisms underlying the reaction are still not fully understand but in vitro models have shown how abacavir interacts with HLA-B*57:01, and with T cell receptors forming an immunological synapse that results in an immune response. Interestingly approximately 50% patients who are carriers of HLA-B*57:01 do not develop abacavir hypersensitivity, but the reasons for this are unknown. A study in the NHS (UK) showed that genetic testing before abacavir initiation is cost-effective [7]. Both the Food and Drug Administration (FDA) and European Medicines Agency (EMA) recommend screening for HLA-B*57:01 even though the carriage rate varies according to ethnicity from 5–8% in Europeans to 2.4% in African Americans [8]. Pre-prescription genotyping has been shown to be highly cost-effective and has reduced the incidence of abacavir hypersensitivity from over 5% to less than 1%.

It is estimated that epilepsy affects 1% of the population worldwide. Carbamazepine is an aromatic anticonvulsant that is also used for trigeminal neuralgia and bipolar disease. Cutaneous adverse reactions to carbamazepine are wide-ranging, and can manifest as maculopapular eruptions at the mild end, to the more severe cutaneous adverse reactions (which include drug reactions with eosinophilia and systemic symptoms (DRESS), Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). SJS/TEN are the most serious ADRs with mortality rates of 5% for SJS and 35% for TEN [9]. SJS and TEN represent a continuum of cutaneous reactions, with the degree of skin detachment able to differentiate between the two (SJS involves less than 10% of the body surface area, whereas TEN affects more than 30% of the body surface area). A study in 2004 found a strong association between HLA-B*15:02 and SJS induced by carbamazepine in Han Chinese. This has been replicated by many other studies undertaken in Han Chinese, Thai and Malays, and a prospective study by Chen et al. [10] subsequently showed that genetic testing prior to treatment significantly reduced the incidence of carbamazepine-induced SJS. The association with HLA-B*15:02 is limited to South East Asian populations, and has not been demonstrated in Northern Europeans because the population prevalence of this allele is very low (<0.5%). Currently regulatory bodies including the FDA and EMA recommend genotyping for HLA-B*15:02 in South East Asian populations before starting treatment with carbamazepine, although various commentaries have questioned what is exactly meant by a South East Asian population. This reflects the difficulties in assigning screening based on self-reported ethnicity as it does not take into account admixture that occurs in almost all populations, and can exclude populations that may also be susceptible but would not be considered to be South East Asian. There is some evidence to show that HLA-B*15:02 may also predispose to SJS/TEN with phenytoin although the risk estimates are much less than with carbamazepine.

More recently, the HLA-A*31:01 allele, which is common in most ethnic groups has been associated with a range of carbamazepine hypersensitivity phenotypes including DRESS and SJS/TEN. In a Han Chinese population, an association with HLA-A*31:01 and carbamazepine-induced DRESS was demonstrated but not with SJS/TEN (where HLA-B*15:02 is predominant). In terms of mechanisms, it is not clear why HLA-B*15:02 only predisposes to SJS/TEN with carbamazepine, whereas HLA-A*31:01 predisposes to a wider range of phenotypes; cooperativity between different HLA alleles, for example with the HLA-DRB1*04:04, and with T-cell receptor clonotypes may be important in determining the phenotype (11). Genetic testing of HLA-A*31:01 is not mandatory at the moment; however, a UK study has recently shown that genotyping before initiating carbamazepine in the NHS would be cost effective (12).

Type A adverse drug reactions
Two interesting examples of the modern use of pharmacogenomics to prevent type A ADRs are with eliglustat and warfarin. Gaucher’s disease (GD) is the most common lysosomal storage disorder, which is inherited in an autosomal recessive fashion with an incidence of 1 in 40 000–60 000 in the general population, and 1 in 450 in Ashkenazi Jews [13]. Type 1 GD is the most common variant affecting more than 90% of all patients without neurological involvement, opposite to the manifestations observed with types 2 and 3 GD. Reduced activity of the β-glucocerebrosidase enzyme as a result of the GBA gene mutation leads to lysosomal accumulation of undegraded glucosylceramide causing dysfunction of various organs. For the last 20 years, the standard treatment for GD has been enzyme replacement therapy (ERT) requiring twice weekly intravenous infusions with a recombinant form of human β-glucosidase. Eliglustat represents an example of a new therapeutic strategy in GD – substrate reduction therapy (SRT), which is characterized by inactivation of glucosylceramide synthase involved in glucosylation of ceramide [14]. Eliglustat undergoes extensive metabolism by cytochrome P450 enzymes, in particular by CYP2D6 and to a lesser extent by CYP3A4. Studies have confirmed a strong correlation between the CYP2D6 metabolizer status and drug exposure. Eliglustat has recently been approved by both the FDA and EMA for the treatment of patients with type I GD – interestingly, given the strong effect of the CYP2D6 gene polymorphism on drug exposure patients need to be genotyped for their CYP2D6 metabolizer status, and the dose needs to be reduced by 50% in poor metabolizers. Furthermore, co-administration of drugs inhibiting CYP2D6 needs to be prescribed with extreme caution to prevent dose-dependent ADRs.

Warfarin is a vitamin K antagonist that is a mainstay of anticoagulation treatment in venous thromboembolism (VTE) and stroke prevention in atrial fibrillation (AF). Vitamin K antagonist therapy (despite high clinical effectiveness) has significant disadvantages and limitations including a narrow therapeutic index, drug and food interactions, routine coagulation monitoring and dose adjustments. Polymorphisms in CYP2C9 and VKORC1 genotypes and inter-individual variability can significantly influence warfarin metabolism and pharmacodynamic (PD), hence the increased risk of significant adverse reaction such as hemorrhage (Fig. 1) [15, 16]. The genetic determinants of warfarin metabolism have been heavily investigated since 1990. CYP2C9 and VKORC1 are the two main genes associated with warfarin dose requirements. Additional genetic variants, such as CYP4F2, contribute to warfarin metabolism; however, their role is less significant. The International Warfarin Pharmacogenetics Consortium proved that, based on previous studies, algorithms incorporating genetics factors (CYP2C9 and VKORC1) are more precise in prediction warfarin dosing algorithms. However, two recent large randomized controlled trials, EU-PACT and COAG, showed conflicting evidence of the role of pharmacogenetics compared to clinically guided warfarin dosing [17]. It is estimated that different outcomes in the EU-PACT and COAG trials are due to various factors including ethnic heterogeneity, genotype information on day one dosing and different control arms. The clinical utility of genotype-based warfarin dosing would need further research in particular in populations other than Caucasians.

Conclusions
Pharmacogenomics is an important area of study in understanding and preventing ADRs. It can be used throughout the whole cycle of drug development. During the pre-clinical stages, determination of how a drug is metabolized and eliminated from the body can provide valuable information on how polymorphisms in drug metabolizing enzymes and transporters affect drug pharmacokinetics and will lead to valuable prescribing information in the summary of product characteristics. This could be followed by specific, subsequent studies that may lead to genotype-dependent dosing, as in the case of eliglustat. Such precise dosing is not commonplace now, but is likely to become more important in the future. Dosing is a key determinant of the risk of ADR, and one that is still ignored. Rare and often more serious ADRs such as hypersensitivity are often not detected until phase IV, and this will require post-marketing studies. This is beautifully exemplified by abacavir hypersensitivity and the different studies that showed an association with HLA-B*57:01.

Implementation of pharmacogenomics into clinical practice has been patchy overall. This is because of many reasons, including poorly replicated gene-drug associations. However, even when the associations have been replicated and are biologically convincing, implementation has sometimes not occurred. This may be because pharmacogenetics (and the whole area of personalized medicine) represents a disruptive innovation that changes the whole clinical pathway. Changing behaviour through re-engineering the clinical pathways in a healthcare setting will require changes in the systems currently employed to deliver clinical care, which can be likened to turning around a supertanker – i.e. it will take time, money and cooperation of every part of the whole healthcare system. Of course, further research is also need in many other areas, and it is important that research in pharmacogenomics is combined with other modalities to ensure that we are covering all possible factors that can affect a response to a drug.

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The authors
Marcin Bula* MBBS, MRCP(L); Munir Pirmohamed MB ChB (Hons), PhD, FRCP, FRCP(E), FBPhS, FMedSci
Institute of Translational Medicine, University of
Liverpool, Liverpool L69 3GL2, UK