A pathway-driven predictive model of tramadol pharmacogenetics

Abstract

Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have welldocumented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathwaydriven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.

Clinical pharmacogenomics in action: design, assessment and implementation of a novel pharmacogenetic panel supporting drug selection for diseases of the central nervous system (CNS)

“…These results point towards a higher relevance of combined CYP2D6*4,*10 and MC4R variations as well as a correlation of CYP2D6*41 with UGT2B7 variations. This is in line with previous data showing a general combined co-occurence of CYP2D6 / UGT2B7 variability [ 54 ].…”

Pharmacogenetics of Lethal Opioid Overdose: Review of Current Evidence and Preliminary Results from a Pilot Study

“…These studies concluded that CYP2D6 genotyping may be important in identifying the cause of unexpectedly high or low tramadol-metabolite ratios in post-mortem blood samples [ 19 , 27 ]. Furthermore, one study looked at 16 variants from five genes involved in tramadol pharmacokinetics and pharmacodynamics and concluded that a set of 16 loci from these five genes can predict tramadol/metabolite ratio with over 90% accuracy, which is greater than using CYP2D6 alone [ 30 ]. Similarly, the oxycodone-to-oxymorphone concentration ratio showed a significant correlation with CYP2D6 activity when death was unrelated to intoxication and CYP2D6 PMs and IMs had significantly higher oxycodone concentrations compared to EMs and UMs [ 35 ].…”

Pharmacogenetics and the postmortem molecular autopsy

“…Blue rectangles and horizontal lines represent CYP2D6 exons and introns, respectively; single nucleotide polymorphism (SNP) rs numbers are provided for select * allele defining loci; designated SNP alleles are relative to the hg19 reference genome. CYP2D6*1A is the wild type * allele; CYP2D6*7 and CYP2D6*10A demonstrate how a single SNP, or a collection of SNPs along the length of the gene, confer different * alleles investigating genetic variability of trans-acting metabolic proteins, in particular those implicated in pain propagation/relief, opiate metabolism, and addiction (Altar, Carhart, Allen, Hall-Flavin, Dechairo, et al, 2015a;Altar, Carhart, Allen, Hall-Flavin, Winner, et al, 2015b;Crist & Berrettini, 2014;Fujita et al, 2010;Rahikainen et al, 2018;Rakvag et al, 2005;Wendt, Novroski, Rahikainen, Sajantila, & Budowle, 2019). These additional genes of interest include several members of the ABC and OPR families.…”

“…Altar et al demonstrated that combinatorial approaches to predicting MP have significantly more efficacious patient outcomes when compared to a single-gene single-phenotype model for psychiatric compounds (Altar, Carhart, Allen, Hall-Flavin, Dechairo, et al, 2015a;Altar, Carhart, Allen, Hall-Flavin, Winner, et al, 2015b). Pathway-driven pharmacogenetic studies have been performed in relatively few drug classes and typically utilize relatively few loci (i.e., genes or SNPs; Altar, Carhart, Allen, Hall-Flavin, Winner, et al, 2015a;Baber et al, 2015;Bastami et al, 2014;Sistonen et al, 2012;Wendt et al, 2019). The success of these models is still relatively low but the community is dedicating substantial resources to developing extended ADME-R predictive models using common and rare variants, copy-number variation, and various computational algorithms for performing the predictions (see also Jamei et al, 2009;Jornil et al, 2013 for existing workflows/software).…”

“…While CYP2D6 , and indeed other CYPs, play a substantial role in opioid metabolism, SNPs in other genes also contribute to metabolism and may inform postmortem investigations (Baber et al, ; Bastami et al, ; Diatchenko et al, ; Lam et al, ; Melis et al, ; Wendt et al, ). The personalized medicine community has recently been investigating genetic variability of trans‐acting metabolic proteins, in particular those implicated in pain propagation/relief, opiate metabolism, and addiction (Altar, Carhart, Allen, Hall‐Flavin, Dechairo, et al, ; Altar, Carhart, Allen, Hall‐Flavin, Winner, et al, ; Crist & Berrettini, ; Fujita et al, ; Rahikainen et al, ; Rakvag et al, ; Wendt, Novroski, Rahikainen, Sajantila, & Budowle, ). These additional genes of interest include several members of the ABC and OPR families.…”