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Pain 2.0.pptx
1. Pain…It’s In My DNA:
Pharmacogenomic
Considerations For Pain
Management
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2. Disclosure Statement
All relevant financial relationships with any ACPE- defined commercial
interests have been mitigated
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3. Objectives
Review chronic pain management
Discuss CYP2D6, OPRM1, and COMT polymorphism
Evaluate literature regarding genomic testing
Recommend treatment options based on current literature
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4. Etiology
Chronic pain is pain that lasts for over three months.
Types of chronic pain
Neuropathic
Nociceptive
Musculoskeletal
Inflammatory
Psychogenic
Mechanical
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5. Knowledge Check
Approximately how much does chronic pain cost the United States each year?
A. Over 1 billion dollars
B. Over 10 billion dollars
C. Over 500 billion dollars
D. Over 900 billion dollars
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6. Epidemiology
Pain is the number 1 reason why Americans access the healthcare system
An estimated 50 million adults in the United States experienced chronic pain
Chronic pain cost the United States approximately $560 billion to $635 billion
per year
About 20% of patients with chronic pain who visit physicians’ offices receive
an opioid prescription.
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11. What is Pharmacogenomics?
The study of how variations in the human genome dictate an individuals
response to medications.
https://www.zibdy.com/pharmacogenomics-and-the-future-of-medicine/
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12. Importance of Individualized
Medications
Improved drug efficacy
Avoiding adverse reactions
Reducing trial and error
Cost savings
Greater patient satisfaction
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13. Genetic Testing for Chronic Pain
Management
Comprehensive pharmacogenomic panels
GeneSight
Genomind
Opioid-specific genetic testing
Proove opioid risk
Proove pain perception
Single gene testing
CYP2D6 testing
Whole exome sequencing (WES) and whole genome sequencing (WGS)
Reserved for complex cases or when broad genetic evaluation is needed
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14. CYP2D6 Polymorphism and Activity Score
Ultrarapid metabolizers (UM) have a genotype with an activity score greater
than 2.25
Normal metabolizers (NM) have an activity score of 1.25 to 2.25
Intermediate metabolizers (IM) have an activity score of 0.25 to 1
Poor metabolizers (PM) have an activity score of 0
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15. Knowledge Check
Patient 1 is found to have the genotype CYP2C9*1/*1 with an activity score of
2 and patient 2 is found to have the genotype CYP2C9*1/*3 with an activity
score of 1. How would you classify their phenotypes?
A. Ultraraipd and normal metabolizers
B. Both normal metabolizers
C. Normal and intermediate metabolizers
D. Intermediate and poor metabolizers
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16. OPRM1 and COMT Polymorphism
Opioid receptor mu 1 (OPRM1)
SNP from Asparagines to Aspartate leads to a 3 fold higher binding affinity for
opioid ligands
Increased sensitivity to opioids
Catechol-o-methyltransferase (COMT)
S-COMT and MB-COMT
SNP from Valine to Methionine leads to a 4 fold reduction in enzymatic activity
Increase in dopamine levels in the prefrontal cortex
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17. Knowledge Check
What are the receptors that consist of the endogenous opioid system?
A. Alpha, Beta1, Beta2
B. Mu, Delta, Kappa,
C. Muscarinic and nicotinic
D. alpha, lambda, sigma
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19. CYP2D6 Phenotype Codeine
Recommendations
Tramadol
Recommendations
Hydrocodone
Recommendations
Ultra rapid metabolizer Avoid use due to
increased metabolism of
codeine to morphine
Avoid tramadol due to
increased metabolism of
tramadol to O-
desmethyltramadol
No recommendation.
Limited evidence on
pharmacokinetics
Normal Metabolizer Use codeine according to
pt age/weight
Use tramadol according
to pt age/weight
Use hydrocodone
according to pt
age/weight
Intermediate Metabolizer Use codeine according to
pt age/weight. If no
response switch to
alternative analgesic.
Decreased metabolism of
codeine to morphine can
lead to potentially
decreased analgesia
Use tramadol according
to pt age/weight. If no
response switch to
alternative analgesic.
Decreased metabolism of
tramadol to O-
desmethyltramadol can
lead to potentially
decreased analgesia
Use hydrocodone
according to pt
age/weight. If no
response switch to
alternative analgesic.
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20. CYP2D6 Phenotype Codeine
Recommendations
Tramadol
Recommendations
Hydrocodone
Recommendations
Poor Metabolizer Avoid use due to
diminished analgesia.
Greatly decreased
metabolism of codeine
to morphine
Avoid use due to
diminished analgesia.
Greatly decreased
metabolism tramadol
to O-
desmethyltramadol
Use hydrocodone
according to pt
age/weight. If no
response switch to an
alternative analgesic
Indeterminate
Metabolizer
No recommendation.
Effect on codeine
unknown
No recommendation.
Effect on tramadol
unknown
No recommendation.
Effect on hydrocodone
unknown
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23. Agullo et al. 2023
P 60 chronic pain patients who were
referred from primary care to pain
focused care
I Prescribing guided by CYP2D6, OPRM1,
and COMT genotypes vs. one with
clinical routine
C Prescribing guided by clinical routine
O Pain intensity, quality of life, average
occurrence of clinically relevant
adverse events, and total opioid dose
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24. Agullo et al. 2023
Results Reduced pain intensity (76 vs. 59 mm, p < 0.01)
by improving pain relief (28 vs. 48 mm, p <
0.05), increased quality of life (43 vs. 56
mm p < 0.001), and lowered the incidence of
clinically relevant adverse events (3 [1–5] vs. 1
[0–2], p < 0.01) and 42% opioid dose (35 [22–61]
vs. 60 [40–80] mg/day, p < 0.05) as opposed to
usual prescribing arm.
Limitations Small study group that only included Caucasian
pts. Concomitant medications. Pts with
psychiatric diagnoses were excluded
Conclusions Results support the efficacy and safety of the
clinical implementation of genotype-guided
opioid use for pain, lowering the risk of adverse
effects and opioid dose requirements compared
to usual care 24
26. Smith et al. 2020
P 370 pts with chronic pain from 7 pain
clinics
I CYP2D6-guided prescribing of
tramadol/codeine
C Standard of care prescribing of
tramadol/codeine
O Composite pain intensity at baseline
and at 3 months
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27. Smith et al. 2020
Results Tramadol/codeine had greater improvement in the
CYP2D6-guided versus usual care arm (−1.01±1.59
versus −0.40±1.20; adj-P=0.016); 24% of CYP2D6-
guided versus 0% of usual care participants reported
≥30% (clinically meaningful) reduction in the
composite outcome.
Limitations Non-randomized, pts were not blinded, difficulty in
assigning phenotype for heterozygous genotypes
with copy number variation, OTC analgesics were
not recorded
Conclusion The implementation of CYP2D6-guided care was
shown to be feasible and yielded clinically relevant
improvements in pain control among the subset of
patients most expected to benefit. 27
29. Fujita et al. 2023
P 134 morphine-naïve pts with advanced
malignancies
I C-C motif chemokine ligand 11 (CCL11),
histamine N-methyltransferase (HNMT)
and transient receptor potential V1
(TRPV1) guided therapy driven
morphine and oxycodone prescribing
C COMT based morphine and oxycodone
prescribing
O Pain relief by change in numerical
rating scale
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30. Fujita et al. 2023
Results Oxycodone tended to provide superior analgesic
effects over morphine in patients carrying the
genotype AA for the CCL11 SNP [-0.55 (-0.94 to -
0.16) P=0.012]
Limitations SNPs were selected based off sensitivity to
morphine, incompatibility between morphine
and oxycodone dosage forms
Conclusions Successfully identified 3 SNPs as biomarkers,
and found that the CCL11 SNP, in particular, was
highly correlated with the pain controllability in
patients treated with morphine or oxycodone.
Further studies using larger sample sizes are
needed to analyze and confirm the individual as
well as synergistic effects of these SNPs. 30
31. Recommendations for the Future
Routine clinical integrations
Pharmacogenomic testing in the primary care setting
Standardization
More detailed guideline on pharmacogenomic results
Expanded test panels
Limited amount of medications that are effected by pharmacogenomics
Research and clinical trials
PK/PD
Cost effectiveness
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32. References
Robinson, Ann. “Causes and Management of Chronic Pain.” Prescriber, vol. 27, no. 7, July 2016, pp. 39–43,
https://doi.org/10.1002/psb.1482
Whirl-Carrillo, M, et al. “Pharmacogenomics Knowledge for Personalized Medicine.” Clinical Pharmacology and Therapeutics, vol.
92, no. 4, 2012, pp. 414–7, www.ncbi.nlm.nih.gov/pubmed/22992668, https://doi.org/10.1038/clpt.2012.96. Accessed 19 Aug.
2019.
Schug, Stephan, and Sonya Ting. “The Pharmacogenomics of Pain Management: Prospects for Personalized Medicine.” Journal of
Pain Research, Feb. 2016, p. 49, https://doi.org/10.2147/jpr.s55595. Accessed 4 May 2020.
Cornett, Elyse M., et al. “Pharmacogenomics of Pain Management: The Impact of Specific Biological Polymorphisms on Drugs and
Metabolism.” Current Oncology Reports, vol. 22, no. 2, 6 Feb. 2020, p. 18, pubmed.ncbi.nlm.nih.gov/32030524/,
https://doi.org/10.1007/s11912-020-0865-4.
Crews, Kristine R., et al. “Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2D6 , OPRM1 ,
and COMT Genotypes and Select Opioid Therapy.” Clinical Pharmacology & Therapeutics, vol. 110, no. 4, Wiley, Feb. 2021, pp. 888–
96. https://doi.org/10.1002/cpt.2149.
Agulló, Laura et al. “Pharmacogenetic Guided Opioid Therapy Improves Chronic Pain Outcomes and Comorbid Mental Health: A
Randomized, Double-Blind, Controlled Study.” International journal of molecular sciences vol. 24,13 10754. 28 Jun. 2023,
doi:10.3390/ijms241310754
Smith, D Max et al. “CYP2D6-guided opioid therapy improves pain control in CYP2D6 intermediate and poor metabolizers: a
pragmatic clinical trial.” Genetics in medicine : official journal of the American College of Medical Genetics vol. 21,8 (2020): 1842-
1850. doi:10.1038/s41436-018-0431-8
Fujita, Yoshihiko et al. “Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain.” Oncology
letters vol. 26,2 355. 4 Jul. 2023, doi:10.3892/ol.2023.13941
Lauschke, Volker M., et al. “Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future
Developments.” The AAPS Journal, vol. 20, no. 1, 27 Nov. 2017, https://doi.org/10.1208/s12248-017-0161-x. Accessed 22 Nov.
2020.
Kennedy, Mary Jayne. “Personalized Medicines – Are Pharmacists Ready for the Challenge?” Integrated Pharmacy Research and
Practice, vol. Volume 7, Sept. 2018, pp. 113–123, www.ncbi.nlm.nih.gov/pmc/articles/PMC6166757/,
https://doi.org/10.2147/iprp.s133083. Accessed 26 May 2019.
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Editor's Notes
Chronic pain (i.e., pain lasting ≥3 months) is a debilitating condition that affects daily work and life activities for many adults in the United States and has been linked with depression (1), Alzheimer disease and related dementias (2), higher suicide risk (3), and substance use and misuse (4).
Neuropathic Pain
Peripheral neuropathic pain as the case post-herpetic neuralgia or diabetic neuropathy
Central neuropathic pain - cerebral vascular accident sequella
Nociceptive Pain
Pain due to actual tissue injuries such as burns, bruises, or sprains
Musculoskeletal Pain
Back pain
Myofascial pain
Inflammatory Pain
Autoimmune disorders (rheumatoid arthritis)
Infection
Psychogenic Pain
Pain caused by psychologic factors such as headaches or abdominal pain caused by emotional, psychological, or behavioral factors
Mechanical Pain
Expanding malignancy
estimated cost was $560 billion to $635 billion per year,2 composed of direct health care costs ($261 billion to $300 billion), days of work missed ($11.6 billion to $12.7 billion), hours of work missed ($95.2 billion to $96.5 billion), and lower wages ($190.6 billion to $226.3 billion.) T
painful stimuli arising in the periphery are received by specialized nociceptors that selectively respond to a range of aversive stimuli (eg, temperature, pressure, pH). Peripheral nociceptive input is transmitted through the dorsal horn of the spinal column where interneurons modulate and project signals to a distributed range of central nervous system (CNS) structures, including brainstem, limbic, subcortical, associative, and somatosensory brain regions. Pain is a dynamically linked spatiotemporal event, experienced through multi-segmental [20] descending inhibitory and facilitatory signals arising from both the periphery and from the brain https://pubmed.ncbi.nlm.nih.gov/25240653/
Transmission of pain and modulatory signaling involves multiple dynamic and widely distributed bidirectional pathways of excitatory and inhibitory receptors and neurotransmitters, which are targets for the treatment of pain. Drug treatment for chronic pain can target several sites, including neuroreceptors (eg, opioid receptors), ion channels (eg, calcium and sodium channels), and neurotransmitters (eg, norepinephrine and serotonin).
While the exact cellular mechanisms of chronic pain can vary depending on the specific condition, there are some common cellular causes and processes associated with chronic pain. For example: peripheral and central nerves can be overly sensitive after an initial injury, neurotransmitters such a substance P or glutamate can be over produces leading to increased pain perception, or receptors such as NMDA can be upregulated which will yield greater pain receptions
For example, a randomized controlled trial published in Pain Medicine in 2020 investigated the efficacy of paravertebral block (PVB) in managing cancer-related pain in patients with advanced lung cancer. The study found that PVB provided significant pain relief and improved functional status, with a lower opioid consumption ( bupivacaine or levobupivacaine 0.5% and ropivacaine)
Pharmacogenomics refers to the role of various components of the genome on response to a drug. Among the most commonly studied are genetic sequence variants, structural changes in chromosomes (eg, translocations), epigenetic variants (eg, changes in gene methylation), and variation in the expression profile of genes (changes in messenger RNA [mRNA] levels) or noncoding RNA (eg, changes in microRNA). The genetic variation can be inherited through the germline or acquired (eg, somatic mutation in a tumor). The availability of high-throughput techniques to interrogate the entire genome has facilitated many pharmacogenomic studies.
In a validation study with 258 subjects with diagnosed opioid use disorder (OUD) and 650 controls who reported using opioids, the POR successfully categorized patients at high and moderate risks of opioid misuse or abuse with 95.7% sensitivity.
The combination of CYP2D6 alleles a person harbors determines their genotype. Examples are CYP2D6*1/*2 or CYP2D6*4/*5. Based on function, each allele can be assigned a value to calculate the activity score of the genotype, which in turn is often used to assign phenotype. Briefly, a value of 1 is assigned to each allele of a CYP2D6*1/*2 genotype giving rise to an activity score of 2 (NM), while both alleles of the CYP2D6*4/*5 diplotype receive a value of 0, which results in an activity score of 0 (PM). If an individual has a gene duplication at the CYP2D6 locus, then the additional copy is also counted toward the total activity score. An individual who has no detected variants and is determined to have triplication of the CYP2D6 gene would thus be genotyped as CYP2D6*1x3 and have an activity score of 3. This CPIC-recommended genotype to phenotype translation method was developed to facilitate standardization, it is however, not consistently utilized across clinical laboratories for reporting CYP2D6 pharmacogenetic test results.
COMT is an enzyme that is involved in metabolizing various catecholamine neurotransmitters, including dopamine and epinephrine. There are two isoforms expressed from two promoters, the soluble S-COMT isoform that is expressed in most tissues, such as liver, blood, and kidneys, and the membrane-bound form MB-COMT that is more common in the brain. The MB-COMT form is of particular interest because of its role in regulating extracellular dopamine levels in the prefrontal cortex. A common SNP changes the 158th amino acid residue of the membrane-bound isoform (or 108th amino acid of the soluble form) from Valine (Val) to Methionine (Met). The presence of the Met variant leads to a four-fold reduction in COMT enzyme activity due to increased thermolability at physiological temperature. This in turn increases the dopamine levels in the prefrontal cortex
The endogenous opioid system consists of Mu (µ), delta (δ) and kappa (κ) receptorsThe polymorphism is located within exon 1 region of the OPRM1 gene and causes amino acid exchange from asparagines to aspartate at position 40 of the µ opioid receptor. µ opioid receptors carrying aspartate instead of asparagines receptors demonstrate increased sensitivity to opioids which contributes towards the development of opioid addiction
Half of the individuals who work to develop these guidelines are actually pharmacist