No abstract

Patients homozygous for the 118 G allele of the mu-opioid receptor need higher morphine doses to achieve pain control. Thus, genetic variation at the gene encoding the mu-opioid receptor contributes to variability in patients' responses to morphine.

Catechol-O-methyltransferase (COMT) inactivates dopamine, epinephrine and norepinephrine in the nervous system. A common functional polymorphism (Val158Met) leads to a three- to-four-fold variation in the COMT enzyme activity, the Met form displaying lower enzymatic activity. The Val158Met polymorphism affects pain perception, and subjects with the Met/Met genotype have the most pronounced response to experimental pain. Based on this information we analyzed the influence from the COMT Val158Met polymorphism on the efficacy of morphine in a cohort of patients suffering from cancer pain. We genotyped 207 Caucasian cancer patients on morphine treatment with respect to the Val158Met polymorphism and compared the morphine doses, serum concentrations of morphine and morphine metabolites between the genotype groups. Patients with the Val/Val genotype (n=44) needed more morphine (155+/-160 mg/24 h) when compared to the Val/Met (117+/-100 mg/24 h; n=96) and the Met/Met genotype (95+/-99 mg/24 h; n=67) groups (P=0.025). This difference was not explained by other factors such as duration of morphine treatment, performance status, time since diagnosis, perceived pain intensity, adverse symptoms, or time until death. These results suggest that genetic variation in the COMT gene may contribute to variability in the efficacy of morphine in cancer pain treatment.

Cancer pain patients need variable opioid doses. Preclinical and clinical studies suggest that opioid efficacy is related to genetic variability. However, the studies have small samples, findings are not replicated, and several candidate genes have not been studied. Therefore, a study of genetic variability with opioid doses in a large population using a confirmatory validation population was warranted. We recruited 2294 adult European patients using a World Health Organization (WHO) step III opioid and analyzed single nucleotide polymorphisms (SNPs) in genes with a putative influence on opioid mechanisms. The patients' mean age was 62.5 years, and the average pain intensity was 3.5. The patients' primary opioids were morphine (n=830), oxycodone (n=446), fentanyl (n=699), or other opioids (n=234). Pain intensity, time on opioids, age, gender, performance status, and bone or CNS metastases predicted opioid dose and were included as covariates. The patients were randomly divided into 1 development sample and 1 validation sample. None of 112 SNPs in the 25 candidate genes OPRM1, OPRD1, OPRK1, ARRB2, GNAZ, HINT1, Stat6, ABCB1, COMT, HRH1, ADRA2A, MC1R, TACR1, GCH1, DRD2, DRD3, HTR3A, HTR3B, HTR2A, HTR3C, HTR3D, HTR3E, HTR1, or CNR1 showed significant associations with opioid dose in both the development and the validation analyzes. These findings do not support the use of pharmacogenetic analyses for the assessed SNPs to guide opioid treatment. The study also demonstrates the importance of validating findings obtained in genetic association studies to avoid reporting spurious associations as valid findings. To elicit knowledge about new genes that influence pain and the need for opioids, strategies other than the candidate gene approach is needed.