RESUMO
Here we describe the dataset of the first report of pharmacogenomics profiling in an outpatient spine setting with the primary aims to catalog: 1) the genes, alleles, and associated rs Numbers (accession numbers for specific single-nucleotide polymorphisms) analysed and 2) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications. The present description applies to analgesic medication-metabolizing enzymes and may be especially valuable to investigators who are exploring strategies to optimize pharmacologic pain management (e.g., by tailoring analgesic regimens to the genetically identified sensitivities of the patient). Buccal swabs were used to acquire tissue samples of 30 adult patients who presented to an outpatient spine clinic with the chief concern of axial neck and/or back pain. Array-based assays were then used to detect the alleles of genes involved in the metabolism of pain medications, including all common (wild type) and most rare variant alleles with known clinical significance. Both CYP450 isozymes - including CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 - and the phase II enzyme UDP-glucuronosyltransferase-2B7 (UGT2B7) were examined. Genotypes/phenotypes were then used to evaluate each patient's relative ability to metabolize 37 commonly used analgesic medications. These medications included both non-opioid analgesics (i.e., aspirin, diclofenac, nabumetone, indomethacin, meloxicam, piroxicam, tenoxicam, lornoxicam, celecoxib, ibuprofen, flurbiprofen, ketoprofen, fenoprofen, naproxen, and mefenamic acid) and opioid analgesics (i.e., morphine, codeine, dihydrocodeine, ethylmorphine, hydrocodone, hydromorphone, oxycodone, oxymorphone, alfentanil, fentanyl, sufentanil, meperidine, ketobemidone, dextropropoxyphene, levacetylmethadol, loperamide, methadone, buprenorphine, dextromethorphan, tramadol, tapentadol, and tilidine). The genes, alleles, and associated rs Numbers that were analysed are provided. Also provided are: 1) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications and 2) the mechanisms of metabolism of the analgesic medications by primary and ancillary pathways. In supplemental spreadsheets, the raw and analysed pharmacogenomics data for all 30 patients evaluated in the primary research article are additionally provided. Collectively, the presented data offer significant reuse potential in future investigations of pharmacogenomics for pain management.
RESUMO
OBJECTIVE: Pharmacogenomics may help personalize medicine and improve therapeutic selection. This is the first study investigating how pharmacogenomic testing may inform analgesic selection in patients with spine disease. We profile pharmacogenetic differences in pain medication-metabolizing enzymes across patients presenting at an outpatient spine clinic and provide preliminary evidence that genetic polymorphisms may help explain interpatient differences in preoperative pain refractory to conservative management. METHODS: Adults presenting to our outpatient spine clinic with chief symptoms of neck and/or back pain were prospectively enrolled over 9 months. Patients completed the Wong-Baker FACES and numeric pain rating scales for their chief pain symptom and provided detailed medication histories and cheek swab samples for genomic analysis. RESULTS: Thirty adults were included (mean age, 60.6 ± 15.3 years). The chief concern was neck pain in 23%, back pain in 67%, and combined neck/back pain in 10%. At enrollment, patient analgesic regimens comprised 3 ± 1 unique medications, including 1 ± 1 opioids. After genomic analysis, 14/30 patients (47%) were identified as suboptimal metabolizers of ≥1 medications in their analgesic regimen. Of these patients, 93% were suboptimal metabolizers of their prescribed opioid analgesic. Nonetheless, pain scores were similar between optimal and suboptimal metabolizer groups. CONCLUSIONS: This pilot study shows that a large proportion of the spine outpatient population may use pain medications for which they are suboptimal metabolizers. Further studies should assess whether these pharmacogenomic differences indicate differences in odds of receiving therapeutic benefit from surgery or if they can be used to generate more effective postoperative analgesic regimens.