Volume 39, Issue 1 , Pages e8-e11, January 2010
Pharmacogenetic Testing Is of Limited Utility for Predicting Analgesic Response to Morphine
Article Outline
To the Editor:
Interindividual differences in analgesic drug response can complicate the clinical management of pain because of an unsatisfactory response in 10%–30% of the patients treated.1, 2 Genetic factors regulating the drug's pharmacodynamics (neurotransmitter receptors, neurotransduction systems) and pharmacokinetics (transport proteins, metabolizing enzymes) contribute to this variability, because their function and expression may be influenced by variation in the gene sequence.3, 4, 5
We present a case that allowed investigation of those genetic polymorphisms with previous evidence of clinical relevance and the potential to partially explain the variable sensitivity to morphine in a nonresponsive patient.6, 7 It also illustrates the difficulties related to the poor standardization of pharmacogenomic analysis used to individualize drug therapy in pain management.
Once morphine arrives at its site of action, it activates the G-protein-coupled mu-opioid receptor (MOR, OPRM1 gene) crossing the blood-brain barrier (BBB). This is regulated by the P-glycoprotein, a membrane-bound drug transporter (multidrug resistance transporters MDR1/ABCB1 gene) that pumps the drug out of the central nervous system (CNS).8, 9 Activation of the MOR inhibits neural pain transmission through a signaling cascade that includes the central interaction with catecholamines, such as dopamine, noradrenaline, or adrenaline (metabolized by the enzyme cathecol-O-methyltransferase [COMT] gene).10, 11 Furthermore, another G-protein-coupled receptor, the GPR74 (NPFF2 receptor gene), is activated during early inflammatory pain, and acute morphine administration produces a rapid mRNA upregulation in the brainstem region.12 With regard to metabolizing enzymes, hepatic glucuronidation of morphine is mainly mediated by another polymorphic gene (the uridine diphosphate [UDP] glucuronosyltransferase 2B7 gene).13
Case Report
A 47-year-old man had undergone surgery for a gastrointestinal stromal tumor. He had received morphine for the treatment of his severe postoperative pain but had a very poor analgesic response. Despite a rapid increase in the dose of intravenous morphine (50 mg for the first two hours followed by 30 mg for the next three hours), a patient-controlled analgesia morphine pump (basal infusion rate of 1.0 mg/hour and rescue doses of 0.5 mg with a lockout period of 10 minutes; total dose 4.5 mg/hour) was required. The heart rate, arterial blood pressure, ventilatory frequency, sedation, and visual analogue scale (VAS) pain scores were evaluated.
The poor analgesic effect of morphine was not related to the clinical characteristics of the patient. For that reason, we considered it beneficial to identify the genetic variants suspected of affecting the drug response (Table 1): mu-opioid receptor (OPRM1), adenosine triphosphate-binding cassette B1 (ABCB1/MDR1), COMT, neuropeptide FF receptor (NPFF2), and UDP glucuronosyltransferase 2 family polypeptide B7 (UGT2B7) genes. Any of them could have been associated with the low morphine sensitivity, but this pharmacogenomic analysis could not explain the poor response to morphine in our patient.
Table 1. Genetic Variations (SNPs) in the Case, Contigs That Contain the SNPs, dbSNP Reference Sequence (rs), % in Caucasian Population, and Disorder/Phenotype Associations of the Variants
| Gene | SNP | Contig/rs | Caucasian | Case SNP | Disorder/Phenotype |
|---|---|---|---|---|---|
| Mu-opioid receptor gene (OPRM1, chr 6q24-q25, exon 1) | A118G | NT_025741.14 | 10%–14% | A/A Hom | Requires 18% (AG alleles) and 93% (GG alleles) higher morphine doses7, 19 |
| Asn40Asp | rs 1799971 | Asn Hom | |||
| Adenosine triphosphate-binding cassette B1 (ABCB1/MDR1, chr 7q21.1, exon 26) | C3435T | NT_007933.14 | 50%–60% | T/T Hom | Decreased intestinal P-glycoprotein expression. A reduction in mRNA stability and in ABCB1 levels involved in opioid absorption and distribution9, 20 |
| Noncoding | rs 1045642 | ||||
| Catechol-O-methyltransferase (COMT, chr 22q11.21, exon 4) | G1222A | NT_011519.10 | G 52% | A/A Hom | Val form has a three- to fourfold variation in the enzyme activity and Met a lower enzymatic activity17 |
| Val158Met | rs 4680 | A 48% | Met Hom | ||
| Neuropeptide FF receptor gene (NPFF2, chr 4, exon 1) | Del/Ins-/A | NT_006216.14 | No data | A/A Hom | mRNA NPFFR2 upregulation during pain. Acute morphine activated the genes supraspinally12 |
| Ins69Lys | rs 35424833 | Ins69Lys | |||
| UDP glucuronosyltransferase 2 family, polypeptide B7 (UGT2B7, chr 4, promoter and exon 1) | A-842G | NT_077444 | G 50% | A/A Hom | Significantly increased promoter activity, resulting in elevated levels of the metabolizing enzyme21 |
| Promoter | rs 7438135 | A 50% | |||
| G211T | NT_077444.3 | G 100% | G/G Hom | T allele associated with low morphine sensitivity22 | |
| Ser71Ala | rs 12233719 | Ser Hom |
Comment
Our case supports the idea of a complex genetic basis of pain. The patient's requirement for morphine was apparently not explained by the interplay of the selected candidate genes, and it must be explained by other or nongenetic conditions (age, organ function, concomitant therapy, drug interactions, or nature of the disease).14 Furthermore, several other conditions can influence the pain experienced by humans to which they adapt or respond, which is regulated by interactions between multiple regions within the brain through different neurochemical pathways or psychosocial factors.15
According to the patient's genotype combination depicted in Table 1 (homozygote for MOR1: A118 allele and for MDR1: T3435 allele), a larger amount of morphine would be absorbed crossing the BBB and binding to a functional MOR, as a result of the less effective drug extrusion from cells.16 The MDR1 3435T allele is associated with a reduction in mRNA stability and the production of differing concentrations of morphine transporter P-glycoprotein. Consequently, the ineffective pump could increase the concentration of morphine and its CNS's glucuronide.7 This will have a greater effect when the basal expression of the MOR gene is upregulated by the presence of the Met variant (A1222 allele) of the COMT gene, thus increasing the receptor-binding potential. This would lead to the morphine being more effective.11, 17 Also, homozygosity for the Met158 allele of the COMT gene has been associated with three- to fourfold reduced enzyme activity. Under these conditions, the patient would, therefore, need a lower dose of morphine to gain pain relief.4, 17 In the same way, the “G” allele in UGT2B7 G211T single nucleotide polymorphisms conserved the binding site and enzymatic domain, whereas the “A” allele in the A-842G promoter region did not affect promoter activity or morphine-metabolizing enzyme levels. However, the “A” insertion in the NPFF2-R gene, which causes an amino acid insertion (69Lys ins), could disrupt one of the regulatory elements affecting mRNA processing, translation, or degradation, thus causing a change in the level or activity of a second messenger or other downstream target of the complex signaling cascade.
In our case, the variability in morphine response was not associated with the known genetic variability documented. Genetic tests in pain management need to find their way into clinical practice, which may make a proactive approach to individualized therapy possible. More research is necessary, however, because nowadays, there is not any solid procedure that applies the known polymorphisms to the prediction of analgesic response to morphine.
Even though the mapping of the gene variations is predicted to be a personalized profiling tool for improvement in the clinical outcome of pain therapy, the exact molecular consequences of most functional variants reported are not yet known, and the expectations of the few genetic variants with positive results should be relatively low.18 Some genetic variants provide small alterations to the level of pain, but as we found, this is sometimes difficult to reproduce. For this reason, advances in data collection and modeling techniques are ongoing challenges that are essential for translating the strands of information generated into a better understanding of those biological factors that influence the patient's need for opioids.
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PII: S0885-3924(09)00796-9
doi:10.1016/j.jpainsymman.2009.08.004
© 2010 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.
Volume 39, Issue 1 , Pages e8-e11, January 2010
