TY - JOUR
T1 - Supervised Classification of CYP2D6 Genotype and Metabolizer Phenotype with Postmortem Tramadol-Exposed Finns
AU - Wendt, Frank R.
AU - Novroski, Nicole M.M.
AU - Rahikainen, Anna Liina
AU - Sajantila, Antti
AU - Budowle, Bruce
N1 - Publisher Copyright:
© Wolters Kluwer Health, Inc. All rights reserved.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) may be used to infer the metabolizer phenotype (MP) of an individual as poor, intermediate, extensive/normal, or ultrarapid. Metabolizer phenotypes may suggest idiosyncratic drug responses as contributing factors to cause and/or manner of death in postmortem investigations. Application of CYP2D6 has used long-range amplification of the locus and restriction enzyme digestion to detect single-nucleotide variants (SNVs) associated with MPs. This process can be cumbersome and requires knowledge of genotype phase. Phase may be achieved using long-read DNA sequencing and/or computational methods; however, both can be error prone, which may make it difficult or impractical for implementation into medicolegal practice. CYP2D6 was interrogated in postmortem autopsied Finns using supervised machine learning and feature selection to identify SNVs indicative of MP and/or rate of tramadol O-demethylation (T:M1). A subset of 18 CYP2D6 SNVs could predict MP/T:M1 with up to 96.3% accuracy given phased data. These data indicate that phase contributes to classification accuracy when using CYP2D6 data. Of these 18 SNVs, 3 are novel loci putatively associated with T:M1. These findings may enable design of small multiplexes for easy forensic application of MP prediction when cause and/or manner of death is unknown.
AB - Cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) may be used to infer the metabolizer phenotype (MP) of an individual as poor, intermediate, extensive/normal, or ultrarapid. Metabolizer phenotypes may suggest idiosyncratic drug responses as contributing factors to cause and/or manner of death in postmortem investigations. Application of CYP2D6 has used long-range amplification of the locus and restriction enzyme digestion to detect single-nucleotide variants (SNVs) associated with MPs. This process can be cumbersome and requires knowledge of genotype phase. Phase may be achieved using long-read DNA sequencing and/or computational methods; however, both can be error prone, which may make it difficult or impractical for implementation into medicolegal practice. CYP2D6 was interrogated in postmortem autopsied Finns using supervised machine learning and feature selection to identify SNVs indicative of MP and/or rate of tramadol O-demethylation (T:M1). A subset of 18 CYP2D6 SNVs could predict MP/T:M1 with up to 96.3% accuracy given phased data. These data indicate that phase contributes to classification accuracy when using CYP2D6 data. Of these 18 SNVs, 3 are novel loci putatively associated with T:M1. These findings may enable design of small multiplexes for easy forensic application of MP prediction when cause and/or manner of death is unknown.
KW - CYP2D6
KW - pharmacogenomics
KW - supervised machine learning
KW - tramadol
UR - http://www.scopus.com/inward/record.url?scp=85061138372&partnerID=8YFLogxK
U2 - 10.1097/PAF.0000000000000447
DO - 10.1097/PAF.0000000000000447
M3 - Article
C2 - 30507617
AN - SCOPUS:85061138372
SN - 0195-7910
VL - 40
SP - 8
EP - 18
JO - American Journal of Forensic Medicine and Pathology
JF - American Journal of Forensic Medicine and Pathology
IS - 1
ER -