Ang a, A. Karim Ahmed a, Alex Zhu a, Alexander Perdomo-Pantoja a, Daniel M. Sciubba a, Timothy Witham a, Chun Hin Lee b, Kevin MacDonald b, Nicholas Theodore a,aDepartment of Neurosurgery, Johns Hopkins University School of Medicine, 600 N. Wolfe St., Meyer 7-113, Baltimore, MD 21287, USA b Sophisticated Genomic Options (AGS) LLC, Scottsdale, AZ, USAa r t i c l ei n f oa b s t r a c tHere we describe the dataset of your 1st report of pharmacogenomics profiling in an outpatient spine setting with the major aims to catalog: 1) the genes, alleles, and related rs Numbers (accession numbers for specific single-nucleotide polymorphisms) analysed and two) the genotypes and corresponding phenotypes with the genes involved in metabolizing 37 commonly utilised analgesic drugs. The present description applies to analgesic medicationmetabolizing enzymes and may be particularly worthwhile to investigators that are exploring approaches to optimize pharmacologic pain management (e.g., by tailoring analgesic regimens for the genetically identified sensitivities from the patient). Buccal swabs were made use of to acquire tissue samples of 30 adult sufferers who presented to an outpatient spine clinic with all the chief concern of axial neck and/or back discomfort. Array-based assays were then utilised to detect the al-Article history: Received 19 November 2020 Revised 28 January 2021 Accepted 29 January 2021 Out there on the net 3 February 2021 Keywords: Pharmacogenomics Pharmacogenetics Single nucleotide polymorphism Personalized medicine Analgesic regimen Drugs Neck and back pain Spine PLK4 drug surgeryDOI of original post: 10.1016/j.wneu.2020.09.007 Corresponding author. E-mail address: [email protected] (N. Theodore). (N. Theodore) Social media:https://doi.org/10.1016/j.dib.2021.106832 2352-3409/2021 Published by Elsevier Inc. This really is an open access report beneath the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)E. Cottrill, Z. Pennington and C.W.J. Lai et al. / Data in Brief 35 (2021)leles of genes involved in the metabolism of discomfort drugs, including all typical (wild form) and most rare variant alleles with recognized clinical significance. Each CYP450 isozymes such as CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 plus the phase II enzyme UDP-glucuronosyltransferase-2B7 (UGT2B7) were examined. Genotypes/phenotypes were then used to evaluate each patient’s relative capability to metabolize 37 normally made use of analgesic medicines. These drugs incorporated both non-opioid Adrenergic Receptor Agonist web 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 supplied are: 1) the genotypes and corresponding phenotypes with the genes involved in metabolizing 37 frequently employed analgesic drugs and 2) the mechanisms of metabolism in the analgesic drugs by primary and ancillary pathways. In supplemental spreadsheets, the raw and analysed pharmacogenomics data for all 30 patients evaluated inside the primary analysis report are additionall.
