The application of technology in Anaesthetic practice in the 21st century

Barry Singleton UCD School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland



Genetic factors have been known to influence the individual's response to anaesthetic drugs for nearly 60 years. Advances in genetic sequencing have allowed researchers to identify many more variations within individual genes that can affect a person’s response to drugs, including many of those used in anaesthesia. Since the first sequencing of the human genome in 2003, it has now become possible for researchers to study the effects of multiple genes, or even an entire genome, on individual pharmacodynamics and pharmacokinetics. The historically high cost of genetic sequencing has meant that pharmacogenomics has seen little clinic application, but this soon may change. In March 2016, the $1000 genome became a reality. This was long considered to be the benchmark for routine, affordable personal genome sequencing. This then raises the question of how this developing technology may impact anaesthetic practice in the centuries ahead. What follows is a brief review of pharmacogenomic literature that relates to the classic three components of anaesthesia: hypnosis, muscle relaxation, and analgesia, and aims to give an idea of what may be possible.





In the first two decades of the 21st century we have already seen new technologies make a significant difference in anaesthetic practice. These have included the use of ultrasound in regional anaesthesia, video laryngoscopy for difficult airways, and EEG monitoring to measure the depth of anaesthesia, to name only a few. If the current trends of falling production costs and increased investment in research and development are sustainable, it seems likely that technological advances will continue to have an exponential impact on anaesthetics throughout the rest of the century. Thus, it is difficult to imagine what technologies will have made the greatest difference by the end of the 21st century. It is possible, however, to speculate about what technologies the next two decades are likely to bring. This review will examine one such up-and-coming technology: pharmacogenomics, the study of how a person’s genome affects that person’s response to drugs.

Pharmacogenomics: The Relevance for the Anaesthetist

Pharmacogenomics will have implications for all of medicine, but anaesthetics is one of the few specialties in which powerful and potentially dangerous drugs play such a central and regular role. Modern anaesthetic practice owes its origin to the discovery of drugs capable of affecting general anaesthesia in the 19th century 1. Moreover, many of the major developments since have been driven by the isolation of compounds capable of having other profound effects on the body’s physiology, such as neuromuscular blocking drugs. Needless to say, the medicines in the armamentarium of today’s anaesthetist have changed considerably since the specialty’s inception, and continue to be refined to this day. Furthermore, advances in patient monitoring and drug administration have enabled drugs to be used with greater and greater care. Nevertheless, not all the drugs work for everyone, and they can also cause serious harm. If we are to continue to make progress in this area, we need to look more to the other variable of the drug-patient interaction, that is, we need to know more about the drug needs of our individual patients.

We have long since realized how important it is to take into account factors such as age, sex, tolerance, and co-morbidity when predicting a patient’s response to drugs – but we are left with poor surrogate markers for a person’s genome such as family history and ethnicity. This is a problem because we know that, for some drugs, a person’s genes make a significant, or the most significant, contribution to how they will respond to those drugs. For example, up to two-thirds of the variability in the inter-individual response to morphine has been attributed to genetics 2. A person’s genes can also predispose a rare but serious adverse reaction to a drug: for example, mutations in the ryanodine receptor gene (RYR1) are associated with the dangerous complication of malignant hyperthermia 3. Hence, pharmacogenomics has particular relevance for optimizing anaesthesia for individual patients and for avoiding serious adverse outcomes.

The Century of Personalized Medicine

Genetic factors have been recognised to influence individual patient response to drugs used in anaesthesia for nearly 60 years 4. The concept of pharmacogenomics is considerably older still, with some arguing the modern concept can be traced back as far as 510 BCE, when the ancient Greek philosopher Pythagoras noted that ingestion of fava beans resulted in a potentially deadly reaction in some, but not all, individuals [5]. The basic science and theory of pharmacogenomics, therefore, are not new. However, the cost of sequencing a human genome has been falling exponentially since the turn of the century [6]; the Human Genome Project completed the first sequencing of a human genome in 2003 at a cost of $2.7 billion [7], and in March 2016, the $1000 genome became a reality – long considered to be the benchmark for routine, affordable personal genome sequencing 8. Consequently, the notion of pharmacogenomics as a technology with widespread clinical application will soon be viable. Furthermore, Barack Obama launched the Precision Medicine Initiative in his State of the Union Address on January 20, 2015 [9], the mission of which is to enable an era of personalised medicine whereby treatments and approaches are tailored to individual patients and their genes. Soon, whole genome sequencing could be performed as quickly and as easily as any other standard blood test. The 21st century, therefore, looks set to be the century of personalised medicine – and of personalised anaesthesia.

What follows is a review of some of the pharmacogenomic literature that relates to the classic three components of anaesthesia, namely: hypnosis, muscle relaxation, and analgesia. We will look at a selection of drugs under the headings of drug metabolism, receptor variability, and other genetic factors.

Drug metabolism

The Cytochrome P450 (CYP) family of isozymes is by far the most important enzyme system in terms of drugs metabolism, with approximately seven clinically relevant CYP enzymes responsible for the metabolism of the majority of currently used drugs. A number of different CYP genes encode for the respective CYP enzymes, and there are many variations or alleles within each of these genes in the population. The result is that the effectiveness of each of the CYP enzymes can vary greatly from person to person, depending on how many copies of and the specific alleles that they inherit [10].

With regards to the CYP2D6 enzyme, which is responsible for metabolizing many opioids, persons can be classified as normal metabolisers (NM), intermediate metabolisers (IM), poor metabolisers (PM), or ultrarapid metabolisers (UM) [11]. As the name would suggest, most persons are normal metabolisers, as mutant alleles that increase or decrease the activity of the enzyme are, by definition, relatively rare compared to the normal “wild-type” alleles. For those who are not NMs, opioids can have a very different effect to that which is intended.  Codeine, for example, is a prodrug that must be metabolised by CYP2D6 into its active form, morphine, in order to have any significant affinity for the μ receptor. This means that PMs who are given standard dose paracetamol and codeine are, in effect, only receiving paracetamol, while with UMs the result might be dangerously high levels of morphine [12]. Similar concerns apply with regards to tramadol and hydrocodone and CYP2D6, as the respective metabolites of these are much more potent than the original drugs [13, 14].  The analgesic effects of other opioids, such as oxycodone, also depend on the amount of certain metabolites present [15]. In other words, patients may receive opioid analgesics without receiving sufficient analgesia: Yang et al. (2012) looked at a group of post-op patients with acute severe pain and found that 71% were PM for CYP2D6 [16]. Equally, standard doses of these opioid medications may actually be dangerous to some individuals.

Many hypnotic agents are also subject to CYP metabolism, though the research in this area has been less extensive. Approximately 5% of sevoflurane is metabolised by CYP2E1 to hexafluoroisopropanol and fluorides, with the remaining 95% being secreted unchanged [17, 18]. It is suspected that these fluoride metabolites may exhibit nephrotoxic action [19]. Thirteen variants of the CYP2E1 gene, with varying frequencies in the population have been described [20]. It is therefore conceivable that such variations may result in a larger or smaller percentage of sevoflurane undergoing biotransformation, resulting in more or less nephrotoxicity.

Enzymes other than CYPs are also involved in the metabolism of certain drugs. Approximately 70% of propofol metabolism, for example, is performed by UPD-glucuronosyltransferase, encoded for by UGT1A9 21, a non-CYP gene, while CYP2B6 and CYP2C9 are responsible for the rest of propofol metabolism 17. Experiments have indicated a relationship between a person’s response to propofol and alleles of UGT1A9 and these CYP genes [17, 22, 23, 24, 25, 26, 27, 28].

Suxamethonium, a depolarizing muscle relaxant, owes its short duration of action to its normally rapid metabolism by nonspecific plasma cholinesterases. However, plasma cholinesterase activity can be reduced in some persons, again due to genetic variation, resulting in a prolonged duration of neuromuscular block. The normal (Eu:Eu) genotype is present in 96% of the population, with the remaining 4% having one abnormal gene (Ea, Es, Ef), or various combinations of two abnormal genes. All of the abnormal genes result in a longer duration of neuromuscular block, ranging from 20 minutes up to several hours, depending on the combination [3].

Receptor variability

The effectiveness of opioids is also subject to inter-individual variation in the genes that encode for the various opioid receptors. For instance, genetic variations in the μ opioid receptor gene OPRM1, have been shown to correlate with the amount of morphine required after lower abdominal surgery. Liu and Wang (2012) reported that persons carrying the GG genotype (10.4% of the population) required much higher opioid doses to achieve pain relief [29]. In addition, variations in OPRK1, which encodes for the kappa opioid receptor, have been demonstrated to influence the risk of opioid addiction [30].

The ryanodine receptor is located on the membrane of the sarcoplasmic reticulum, and isoform 1 (RYR1) is located primarily in skeletal muscle. Variations in the RYR1 gene have long been suspected to be the culprit in malignant hyperthermia (MH), a rare life-threatening condition that is usually triggered in response to suxamethonium and volatile anesthetic agents. The RYR1 receptor functions as the primary Ca2+ channel, allowing stored Ca2+ from the sarcoplasmic reticulum into the cytoplasm, which in turn triggers the contractile mechanisms within the muscle cell. Abnormal RYR1 receptors, however, allow excessive amounts of Ca2+ to pass, resulting in generalized muscle rigidity. ATP is consumed rapidly, as it is used in the process to return Ca2+ to the sarcoplasmic reticulum, and the result is an increase in CO2, heat, and lactate production. Unless treated promptly with dantrolene, the inevitable result is break down of the muscle cells, resulting in myoglobinaemia and hyperkalaemia 3. Unfortunately, this disorder has eluded a simple genetic test: at least six different loci on the RYR1 gene are known to be involved, each of which can contribute a large number of variations, and MH is also associated with variations in other genes [31]. However, such a complex genetic phenomenon is precisely the type of problem that the pharmacogenomic approach is designed to solve: in time, we should be able to predict a person’s risk of MH based upon the number of contributing variations present in their genome.

Other genetic factors

There are other genetic factors still that may influence an anesthetist’s prescribing: it has been established, for example, that a person’s pain perception and disposition to pain are also partly hereditary. Take the enzyme Catechol-O-methyltransferase (COMT), which metabolises catecholamines: it has been estimated that approximately 10% of the variability in pain sensitivity is related to single nucleotide polymorphisms (SNPs) in this gene [32]. Hence, a person’s genome may influence their need for, as well as their response to, analgesics.


The value of a pharmacogenomic approach to anaesthetics is clear: it would enable us to take into account the contributions of many different variations, in many different genes, that influence the pharmacodynamics and pharmacokinetics of a particular drug to optimize the experience of an individual patient. When widespread whole genome sequencing becomes a reality, it will enable genome association studies with larger sample sizes than ever before. Thus, greater use of the technology will drive research, and in turn, the results of that research will drive greater use of the technology. Moreover, not only will it transform the use of drugs employed in anaesthetic practice today, but it will also have implications for drugs currently in development and drugs not even yet discovered or conceived of. The future impact of pharmacogenomics cannot be underestimated, and anaesthetics has the potential to lead the way.




1.         Robinson, D.H. & Toledo, A.H. Historical development of modern anesthesia. Journal of investigative surgery : the official journal of the Academy of Surgical Research 25, 141-149 (2012).

2.         Ross, J.R., et al. Clinical response to morphine in cancer patients and genetic variation in candidate genes. The pharmacogenomics journal 5, 324-336 (2005).

3.         Peck, H.W. Pharmacology for Anaesthesia and Intensive Care, (Cambridge University Press, 2008).

4.         Kalow, W. & Staron, N. On distribution and inheritance of atypical forms of human serum cholinesterase, as indicated by dibucaine numbers. Canadian journal of biochemistry and physiology 35, 1305-1320 (1957).

5.         Pirmohamed, M. Pharmacogenetics and pharmacogenomics. British Journal of Clinical Pharmacology 52, 345-347 (2001).

6.         Wetterstrand, K. DNA Sequencing Costs: Data fro the NHGRI Genome Sequencing Program (GSP).  (2016).

7.         NHGRI. The Human Genome Project Completion: Frequently Asked Questions. Vol. 2016 (2003).

8.         Regaldo, A. The $1,000 genome is a reality. Actually, you’ll save a dollar. It’s $999., Vol. 2016 (MIT Technology Review, 2016).

9. The Precision Medicine Initative. Vol. 2016 (2015).

10.       Ingelman-Sundberg, M. Polymorphism of cytochrome P450 and xenobiotic toxicity. Toxicology 181-182, 447-452 (2002).

11.       Trescot, A.M. Genetics and implications in perioperative analgesia. Best practice & research. Clinical anaesthesiology 28, 153-166 (2014).

12.       Kirchheiner, J., et al. Pharmacokinetics of codeine and its metabolite morphine in ultra-rapid metabolizers due to CYP2D6 duplication. The pharmacogenomics journal 7, 257-265 (2007).

13.       Grond, S. & Sablotzki, A. Clinical pharmacology of tramadol. Clinical pharmacokinetics 43, 879-923 (2004).

14.       Kaplan, H.L., et al. Inhibition of cytochrome P450 2D6 metabolism of hydrocodone to hydromorphone does not importantly affect abuse liability. The Journal of pharmacology and experimental therapeutics 281, 103-108 (1997).

15.       Samer, C.F., et al. Genetic polymorphisms and drug interactions modulating CYP2D6 and CYP3A activities have a major effect on oxycodone analgesic efficacy and safety. British journal of pharmacology 160, 919-930 (2010).

16.       Yang, Z., et al. CYP2D6 poor metabolizer genotype and smoking predict severe postoperative pain in female patients on arrival to the recovery room. Pain medicine (Malden, Mass.) 13, 604-609 (2012).

17.       Restrepo, J.G., Garcia-Martin, E., Martinez, C. & Agundez, J.A. Polymorphic drug metabolism in anaesthesia. Current drug metabolism 10, 236-246 (2009).

18.       Kharasch, E.D. & Thummel, K.E. Identification of cytochrome P450 2E1 as the predominant enzyme catalyzing human liver microsomal defluorination of sevoflurane, isoflurane, and methoxyflurane. Anesthesiology 79, 795-807 (1993).

19.       Mikstacki, A., et al. The impact of genetic factors on response to anaesthetics. Advances in medical sciences 58, 9-14 (2013).

20.       Solus, J.F., et al. Genetic variation in eleven phase I drug metabolism genes in an ethnically diverse population. Pharmacogenomics 5, 895-931 (2004).

21.       Vanlersberghe, C. & Camu, F. Propofol. Handbook of experimental pharmacology, 227-252 (2008).

22.       Villeneuve, L., Girard, H., Fortier, L.C., Gagne, J.F. & Guillemette, C. Novel functional polymorphisms in the UGT1A7 and UGT1A9 glucuronidating enzymes in Caucasian and African-American subjects and their impact on the metabolism of 7-ethyl-10-hydroxycamptothecin and flavopiridol anticancer drugs. The Journal of pharmacology and experimental therapeutics 307, 117-128 (2003).

23.       Saeki, M., et al. Three novel single nucleotide polymorphisms in UGT1A9. Drug metabolism and pharmacokinetics 18, 146-149 (2003).

24.       Takahashi, H., et al. Effect of D256N and Y483D on propofol glucuronidation by human uridine 5'-diphosphate glucuronosyltransferase (UGT1A9). Basic & clinical pharmacology & toxicology 103, 131-136 (2008).

25.       Girard, H., et al. The novel UGT1A9 intronic I399 polymorphism appears as a predictor of 7-ethyl-10-hydroxycamptothecin glucuronidation levels in the liver. Drug metabolism and disposition: the biological fate of chemicals 34, 1220-1228 (2006).

26.       Kansaku, F., et al. Individual differences in pharmacokinetics and pharmacodynamics of anesthetic agent propofol with regard to CYP2B6 and UGT1A9 genotype and patient age. Drug metabolism and pharmacokinetics 26, 532-537 (2011).

27.       Kirchheiner, J., et al. Bupropion and 4-OH-bupropion pharmacokinetics in relation to genetic polymorphisms in CYP2B6. Pharmacogenetics 13, 619-626 (2003).

28.       Lang, T., et al. Extensive genetic polymorphism in the human CYP2B6 gene with impact on expression and function in human liver. Pharmacogenetics 11, 399-415 (2001).

29.       Liu, Y.C. & Wang, W.S. Human mu-opioid receptor gene A118G polymorphism predicts the efficacy of tramadol/acetaminophen combination tablets (ultracet) in oxaliplatin-induced painful neuropathy. Cancer 118, 1718-1725 (2012).

30.       Yuferov, V., et al. Redefinition of the human kappa opioid receptor gene (OPRK1) structure and association of haplotypes with opiate addiction. Pharmacogenetics 14, 793-804 (2004).

31.       Kim, J.H., Schwinn, D.A. & Landau, R. Pharmacogenomics and perioperative medicine--implications for modern clinical practice. Can J Anaesth 55, 799-806 (2008).

32.       Reyes-Gibby, C.C., et al. Exploring joint effects of genes and the clinical efficacy of morphine for cancer pain: OPRM1 and COMT gene. Pain 130, 25-30 (2007).