Pharmacogenomics in the context of

Pain Management

Anna Ratka, Ph.D., Pharm.D., RPh, CPEProfessor

Wegmans School of Pharmacy, St. John Fisher College

LEARNING OBJECTIVES

1. Explain the role of genetics in pain and analgesia.

2. Describe pharmacogenomics of common analgesics.

3. Discuss potential applications of pharmacogenomics to pain management.

DISCLOSURE

No conflict of interest to report.

PRE-TEST

True or False? T/F

1 SNPs contribute to variation in the genome.

2 A118G is a variant of the mu-opioid receptor gene.

3 Pharmacogenetics describes genetic influences on drug pharmacokinetics and pharmacodynamics.

4 CYP2D6 genetic polymorphism has substantial influence on opioids.

5 CPIC guidelines include morphine.

PREVALENCE OF PAIN

116 million total cases in USA

>76 million cases of chronic pain

Compared to …

23.6 million – diabetes (ADA)

23.3 million – heart disease (AHA)

11.0 million – cancer (ACA)

57.9 million

Pain is a major public health care problem.www.efic.org/eap.htm

$635 billion/year – cost of painhttps://www.iprcc.nih.gov/sites/default/files/IOM_Pain_Report_508C.pdf

PAIN UNDERTREATMENT

50% post-operative pain is adequately managed

50-75% cancer patients are dying in moderate to severe pain

15% children with cancer are in pain

70% chronic pain patients reported pain despite treatment

20% patients claimed that treatment worsened pain

https://www.painconsortium.nih.gov/Resource_Library/IOM_Relieving_Pain

Public Health Crisis in Pain Management

COMPETITIVE

PAIN MANAGEMENT

Strategies for pain relief:• acute care (diagnostic, procedural analgesics)

• integrative approach (alternatives methods)

• Effective pain management is a challenge.• high rate of pain undertreatment, patient suffering and dissatisfaction

• large variability of pharmacological combinations to treat pain

• difficult problems with opioid therapy

• cannot issue a consistent regimen for all pain conditions

• no predictable markers of analgesic response

Pain management is a major public health care crisis.www.efic.org/eap.htm

PAIN COMPLEXITY

Pain is …

• subjective in nature

• multidimensional

• incredibly complex

pathophysiological process

• very diverse, many types

• evolving

https://cor-kinetic.com/have-we-

ballsed-up-the-biopsychosocial-model

Pain is the most common presenting symptom in medicine.

PAIN VARIABILITY

• Patients vary in pain perception, pain-copying behaviors, and responses to analgesics.

• Inter-individual variability in patient responses to pain and pain medications is remarkable, unpredictable, and difficult to explain.

• What can explain variability in pain processing, perception, and clinical manifestations of pain?

age race

environment

gendergenetics

physiology

psychology

epigenetics

other

HERITABILITY AND PAIN

Genetics can explain variability in:

• 50% experimental pain

• 68% low back pain

• 58% neck pain

• 39-58% migraines

• 55% menstrual pain

• 50% chronic postsurgical pain

• 30-70% animal pain behavior

Genetics contributes to up to half of inter-individual variation in pain.[Beller, I 2015]

PHARMACOGENOMICS

Pharmacogenomics

• examines the inherent variations in genes that dictate drug responses; study genes that determine drug behavior

Pharmacogenetics

• describes the genetic influence on both PK and PD; study inherited differences in drug metabolism and responses; use of pharmacogenomics in conjunction with drug therapy

both have overlapping goals and can be used interchangeably

BASIS FOR GENETIC INDIVIDUALITY

• Genome – all DNA in an organism • comprises a sequence of four nucleotides along the two strands of DNA

• DNA – molecule that carries all genetic information

• Genes – located in DNA, carry information for making proteins

• Nucleotides (A, C, G, T) – encode information on genes• 25,000 – 40,000 to encode 100,000 proteins• two people differ on average at about 1 nucleotide in every 1,000• 3 billion nucleotides in genome

• Polymorphism – normal differences in DNA sequences among individuals

• SNPs – single nucleotide polymorphism – variation in DNA sequence• one nucleotide exchanged for another• contribute to the genetic architecture of the genome (the SNPs sequence)

PHENOTYPES OF METABOLIZERS

Phenotypes based on number of copies of normal or abnormal alleles:

• Extensive Metabolizers (EM) 2 normal functional alleles

• Intermediate Metabolizers (IM) 1 normal + 1 reduced or 2 partially deficient alleles

• Poor Metabolizers (PM) 2 mutant alleles

• Ultra rapid Metabolizers (UM) multiple copies of functional alleles

Individuals with EM phenotype reported more 'good opiate effects’ and fewer ‘bad effects’ than PM or EM individuals. [Trescor, 2013]

How pharmacogenomics can affect pain management?

PAINphysiology (pain pathways and components)

psychology (pain perception, ability to cope and respond)

ANALGESICS

• Pharmacodynamics (PD)

receptors and downstream transduction

• Pharmacokinetics (PK)

distribution/transport, metabolism, elimination

PAIN GENOME

• Biological polymorphisms involved in pain:

– Enzymes

COMT, GTP cyclooxygenase, CYP2D6

– Ion channels

transient receptor potential (TRP), potassium, calcium

– Cytokines

pro-inflammatory (IL-6, TNF alpha); anti-inflammatory (IL-10)

– Receptors

opioid receptors, alpha-adrenergic, dopamine

– Transporters

for dopamine, serotonin, ATP-binding cassette[Kaye AD et al., 2019]

PAIN GENES

Genes (over 200) involved in pain processing and perceiving:

– affect pain independently, jointly, by interaction with environmental factors

– affect susceptibility to a disease that may be painful

– affect susceptibility to more severe and more chronic pain

– reduce or protect from pain

Genes that may reduce/protect from pain - COMT, OPRM1, TRPV1

Genes for chronic pain - encoding K+ and Ca+2 channels[Clarke et al., 2015]

OPIOID RECEPTORS POLYMORPHISM

Mu opioid receptor gene (OPRM1)

most common: A118G polymorphism; SNP that exchange A for G

results in increased binding of beta-endorphins [Kaye et al, 2019]

• 38% in Asians

• 16% in Europeans

• 3% in African-Americans

- GG genotype - require higher does of morphine 24 hrs after knee arthroplasty

- AA genotype - need lower dose of morphine; higher N&V, in post-op pain

- G allele (AG or GG) - pregnant women require less fentanyl

[Crist and Berrettini, 2014]

OPIOID RECEPTORS POLYMORPHISM

• Kappa opioid receptor gene - OPRK1

• Delta opioid receptor gene - OPRD1

Ongoing study on role and application in:

• gene variations associated with dependence and addiction

• potential future targets for therapy of addiction

METABOLIC PATHWAYS OF OPIOID ANALGESICS

CYP = cytochrome

P450;

UGT = uridine-

diphospho glucuronyl

transferase.

[Obeng et al., 2017]

PHARMACOGENOMICS OF OPIOIDS

Cytochrome P450 (CYP) enzymes

- involved in over 90% of current therapeutic agents

- 57 CYP genes identified in humans

- CYP genes are highly polymorphic

- CYP2D6 and CYP2D9 – consequences in pain management

- CYPs clinically significant in interactions

[Ting and Schug, 2016]

[Horton & Howard, US Pharmacist, May 1, 2016]

PHARMACOGENOMICS OF OPIOIDS

CYP2D6 genetic polymorphism has substantial influence on opioids.

• mutations in CYP2D6 gene

• mutant alleles (CYP2D *3, *4, *6, *6) account for 93-97% of PM

• phenotypes: PM, IM, EM, UM

• 7-10% of population does not express functional CYP2D6

Tramadol by CYP2D6 to more potent metabolite

Hydrocodone by CYP2D6 to hydromorphone (stronger mu binding)

Oxycodone by CYP2D6 to oxymorphone

Opioids NOT metabolized by CYP2D6:

morphine, oxymorphone, buprenorphine, fentanyl, methadone, hydromorphone

[Yiannakopoulou, 2015; Trescot, 2013]

PHARMACOGENOMICS OF OPIOIDS

Genes influencing Morphine

UGT genetic polymorphism - influence on Phase II metabolism• UGT2B7 • metabolites: morphine-3-glucuronide and morphine-6-glucoronide

UGT2B7 polymorphisms • UGT2B7 900G>A

– greater UGT activity – lower morphine plasma levels – higher M3G:morphine

• UGT2B7 900G/G (wild type) – lower glucuronidation – lower ADEs

[Ting and Schug, 2016]

PHARMACOGENOMICS OF OPIOIDS

Genes influencing Codeine

CYP2D6 (and UGT2B7)

- clinically significant in PM and UM

- has actionable CPIC guidelines https://cpicpgx.org/guidelines/

Codeine effects in experimental pain model and post hysterectomy:

– analgesic in EM

– no analgesia in PM

– ADEs same in EM and PM

– greater risk for ADEs in UM [Yiannakopolou, E, 2015]

PHARMACOGENOMICS OF NSAIDs

Genes influencing NSAIDs

CYP2D9 genetic polymorphism• highly polymorphic• 50 variants identified• PM have CYP2C9*2 and CYP2C9*3 (highest in Caucasians)• PM – reduced NSAIDs clearance

– increased AUC – higher risk for ADEs

PTGS1 & PTGS2 - prostaglandin endoperoxides synthases• homogenous allele (G/G) – improved response to COX-2 agents

[Ting and Schug, 2016]

IMPLEMENTATION OF PHARMACOGENETICS

Clinical Pharmacogenetics Implementation Consortium (CPIC)

- dedicated to facilitating use of pharmacogenetic tests for patient care

- 21 gene/drug clinical practice guidelines;

- freely available, peer-reviewed, evidence-based

Guidelines for Analgesics

– 2012 CYP2D6 codeine

– 2014 update CYP2D6 codeine

– 2019 CYP2C9/NSAIDS

– 2019 update CYP2D6 codeine (to include other opioids) https://cpicpgx.org/guidelines/

IMPLEMENTATION OF PHARMACOGENOMICS

Codeine

CPIC - strongly recommended for UMs

- avoid in PMs

FDA (2017) - contraindicated in patients younger than 12 years

- warning against use in obese adolescents

Tramadol

FDA (2017) - contraindicated in in patients younger than 18 years

[Kaye et al. 2019]

IMPLEMENTATION OF PHARMACOGENOMICS

Codeine recommendations based on CYP2D6 phenotype.

[Crews et al, 2014]

IMPLEMENTATION OF PHARMACOGENOMICS

Codeine and Tramadol

STUDY CYP2D6-guided versus usual management of chronic pain- primary care settings- proof-of-concept trial- chronic pain patients- assigned CYP2D6 phenotypes

Finding

- IM/PMs had greater improvement in the CYP2D6-guided care arm

- NM (normal metabolizers) showed no difference[Smith DM et al. 2019]

IMPLEMENTATION OF PHARMACOGENETICS

Prediction for fentanyl requirements.

Formula based on genetic polymorphism & clinical data.

y = 1.356 + 0.530 x [CREB1] + 0.283 x [GIRK2] + 0.164x[OPRM1] + 0.155 x [ADRB2] + (-0.0120) x [PPL(log-transformed)] + (-0.0060) x [bwt (kg)]

y = the predicted value of 24-hr postop fentanyl requirements (µg/kg log transformed) PPL = pain perception latenciesCREB1, GIRK2, OPRM1, ADRB2 = genes

[Yoshida K et al., 2015]

IMPLEMENTATION OF PHARMACOGENOMICS

Vanderbilt Pharmacogenomics PREDICT program

St. Jude’s Children Research Hospital

University of Florida Center for Pharmacogenomics

Ubiquitous Pharmacogenomics Consortium (U-PGx)- collaborative effort of experts across 16 organizations in European countries Goal: Make effective treatment optimization accessible to every European citizen. www.U-PGx.eu

JUST EXAMPLES

CLINICAL CASE

Case 1

• BC, 50-yo male, complained of inadequate pain control while on oxycodone 70 mg daily. The physician rotated oxycodone to fentanyl patch 50 mcg/h every 72 hrs. BC’s wife contacted physician’s office 24 hrs after the first patch application stating that her husband was heavily sedated and having difficulty breathing.

What could cause these ADEs in BC?

CLINICAL CASE

Case 2

• After elective outpatient surgery, AN, a 26-yo female, was given prescription for oxycodone 5-mg every 4 hrs as needed for pain. The next day, after six doses within a 24-hour period, AN called her surgeon stating that she was receiving minimal pain relief, causing her to get very little or no sleep. She has complained about minimal pain relief since her operative pain medications wore off.

Why AN has no pain relief from oxycodone?

CONCLUSIONS

• Genetic makeup contributes to individual susceptibility to pain and responses to analgesics.

• Several pain genes are associated with PK and PD of analgesic agents.

• Benefits from application of pharmacogenomics in pain management:

– bring consistency to the subjective nature of pain

– provide guide to opioid crisis (identify opioid vulnerable patients)

• Pharmacogenomics can revolutionize pain management

POST-TEST

True or False? T/F

1 SNPs contribute to variation in the genome.

2 A118G is a variant of the mu-opioid receptor gene.

3 Pharmacogenetics describes genetic influences on drug pharmacokinetics and pharmacodynamics.

4 CYP2D6 genetic polymorphism has substantial influence on opioids.

5 CPIC guidelines include morphine.

REFERENCES

• Belfer, I. Pain Medicine News, September 2015.

• Clarke, H et al. Can J Anaesth, 2015,62:294-303.

• Crews, KR et al. Clin Pharmacol Therap, 2014,95(4):376-382.

• Crist RC, Berrettini, WH. Pharmacol Biochem Behav 2014, doi:10.1016/j.pbb.2013.10.018

• Gregg, R, et al. Br J Pain 2013, 7(4): 189-208.

• Kaye AD et al. Pharmacogenomics and Personalized Medicine, 2019,12:125-143

• Obeng O et al. Pharmacotherapy, 2017:37(9):1105-1121.

• Smith DM et al. Genet Med 2019;21(8):1842-1850

• Ting, S, Schug, S. J Pain Res 2016;6:49-56.

• Trescot AM. Pain Medicine News, April 2013

• Yiannakopoulou, E. Int J Genomics 2015, http://dx.doi.org/10.1155/2015/368979

• Yoshida K et al. PLoSONE 2015; 10(1):e0116885

THANK YOU

Anna Ratka, Ph.D., Pharm.D., RPh, CPEProfessor and Associate Dean of Academic Affairs

Wegmans School of Pharmacy, St. John Fisher Collegearatka@sjfc.edu