Full-gene haplotypes refine CYP2D6 metabolizer phenotype inferences

CYP2D6 is a critical pharmacogenetic target, and polymorphisms in the gene region are commonly used to infer enzyme activity score and predict resulting metabolizer phenotype: poor, intermediate, extensive/normal, or ultrarapid which can be useful in determining cause and/or manner of death in some autopsies. Current genotyping approaches are incapable of identifying novel and/or rare variants, so CYP2D6 star allele definitions are limited to polymorphisms known a priori. While useful for most predictions, recent studies using massively parallel sequencing data have identified additional polymorphisms in CYP2D6 that are predicted to alter enzyme function but are not considered in current star allele nomenclature. The 1000 Genomes Project data were used to produce full-gene haplotypes, describe their distribution in super-populations, and predict enzyme activity scores. Full-gene haplotypes generated lower activity scores than current approaches due to inclusion of additional damaging polymorphisms in the star allele. These findings are critical for clinical implementation of metabolizer phenotype prediction because a fraction of the population may be incorrectly considered normal metabolizers but actually may be poor or intermediate metabolizers.

[1]  M Ingelman-Sundberg,et al.  Frequent distribution of ultrarapid metabolizers of debrisoquine in an ethiopian population carrying duplicated and multiduplicated functional CYP2D6 alleles. , 1996, The Journal of pharmacology and experimental therapeutics.

[2]  Roderic D. M. Page,et al.  TreeView: an application to display phylogenetic trees on personal computers , 1996, Comput. Appl. Biosci..

[3]  J. Lafitte,et al.  Polymorphism of the cytochrome P450 CYP2D6 gene in a European population: characterization of 48 mutations and 53 alleles, their frequencies and evolution. , 1997, Pharmacogenetics.

[4]  J. Brockmöller,et al.  Cytochrome P450 2D6 variants in a Caucasian population: allele frequencies and phenotypic consequences. , 1997, American journal of human genetics.

[5]  T Varilo,et al.  Molecular genetics of the Finnish disease heritage. , 1999, Human molecular genetics.

[6]  S. Henikoff,et al.  Predicting deleterious amino acid substitutions. , 2001, Genome research.

[7]  G. Kerr,et al.  Tricyclic antidepressant overdose: a review , 2001, Emergency medicine journal : EMJ.

[8]  J. Kere,et al.  Human population genetics: lessons from Finland. , 2001, Annual review of genomics and human genetics.

[9]  M. Ingelman-Sundberg,et al.  Characterization of the CYP2D6*29 allele commonly present in a black Tanzanian population causing reduced catalytic activity. , 2001, Pharmacogenetics.

[10]  L. Bertilsson,et al.  Molecular genetics of CYP2D6: clinical relevance with focus on psychotropic drugs. , 2002, British journal of clinical pharmacology.

[11]  S. Henikoff,et al.  Accounting for human polymorphisms predicted to affect protein function. , 2002, Genome research.

[12]  Steven Henikoff,et al.  SIFT: predicting amino acid changes that affect protein function , 2003, Nucleic Acids Res..

[13]  Donna Karolchik,et al.  The UCSC Genome Browser , 2003, Current protocols in human genetics.

[14]  W. Koch Technology platforms for pharmacogenomic diagnostic assays , 2004, Nature Reviews Drug Discovery.

[15]  M Ingelman-Sundberg,et al.  Genetic polymorphisms of cytochrome P450 2D6 (CYP2D6): clinical consequences, evolutionary aspects and functional diversity , 2005, The Pharmacogenomics Journal.

[16]  A. Gaedigk,et al.  Identification and characterization of novel sequence variations in the cytochrome P4502D6 (CYP2D6) gene in African Americans , 2005, The Pharmacogenomics Journal.

[17]  S. Henikoff,et al.  Predicting the effects of amino acid substitutions on protein function. , 2006, Annual review of genomics and human genetics.

[18]  Gideon Koren,et al.  Pharmacogenetics of morphine poisoning in a breastfed neonate of a codeine-prescribed mother , 2006, The Lancet.

[19]  Pardis C Sabeti,et al.  Common deletion polymorphisms in the human genome , 2006, Nature Genetics.

[20]  A. Sajantila,et al.  CYP2D6 and CYP2C19 genotypes and amitriptyline metabolite ratios in a series of medicolegal autopsies. , 2006, Forensic science international.

[21]  A. Sajantila,et al.  A Fatal Doxepin Poisoning Associated With a Defective CYP2D6 Genotype , 2007, The American journal of forensic medicine and pathology.

[22]  Magnus Ingelman-Sundberg,et al.  Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. , 2007, Pharmacology & therapeutics.

[23]  A. Gaedigk,et al.  The CYP2D6 Activity Score: Translating Genotype Information into a Qualitative Measure of Phenotype , 2008, Clinical pharmacology and therapeutics.

[24]  Wei Duan,et al.  Clinical pharmacogenetics and potential application in personalized medicine. , 2008, Current drug metabolism.

[25]  Masahiro Hiratsuka,et al.  Functional Characterization of 17 CYP2D6 Allelic Variants (CYP2D6.2, 10, 14A–B, 18, 27, 36, 39, 47–51, 53–55, and 57) , 2008, Drug Metabolism and Disposition.

[26]  Pekka Ellonen,et al.  Genetic markers and population history: Finland revisited , 2009, European Journal of Human Genetics.

[27]  Howard S. Smith,et al.  Opioid metabolism. , 2009, Mayo Clinic proceedings.

[28]  C. Béroud,et al.  Human Splicing Finder: an online bioinformatics tool to predict splicing signals , 2009, Nucleic acids research.

[29]  S. Henikoff,et al.  Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm , 2009, Nature Protocols.

[30]  P. Bork,et al.  A method and server for predicting damaging missense mutations , 2010, Nature Methods.

[31]  G. Jiménez-Sánchez,et al.  Resequencing, haplotype construction and identification of novel variants of CYP2D6 in Mexican Mestizos. , 2011, Pharmacogenomics.

[32]  J. Miller,et al.  Predicting the Functional Effect of Amino Acid Substitutions and Indels , 2012, PloS one.

[33]  Yongwook Choi,et al.  A fast computation of pairwise sequence alignment scores between a protein and a set of single-locus variants of another protein , 2012, BCB.

[34]  R. Emsley,et al.  Next-generation sequencing of pharmacogenes: a critical analysis focusing on schizophrenia treatment , 2013, Pharmacogenetics and genomics.

[35]  I. Adzhubei,et al.  Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2 , 2013, Current protocols in human genetics.

[36]  H. Gréen,et al.  Influence of CYP2D6 and CYP2C19 genotypes on venlafaxine metabolic ratios and stereoselective metabolism in forensic autopsy cases , 2014, The Pharmacogenomics Journal.

[37]  Andres Metspalu,et al.  Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population , 2014, PLoS genetics.

[38]  Chunlei Du,et al.  Corrigendum to ‘Nanopore-based Fourth-generation DNA Sequencing Technology’ [GPB 144 (2015) – GPB 13/1 (4–16)] , 2015, Genom. Proteom. Bioinform..

[39]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[40]  A. Papp,et al.  Functional characterization of CYP2D6 enhancer polymorphisms. , 2015, Human molecular genetics.

[41]  Yongwook Choi,et al.  PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels , 2015, Bioinform..

[42]  Chunlei Du,et al.  Nanopore-based Fourth-generation DNA Sequencing Technology , 2015, Genom. Proteom. Bioinform..

[43]  R. Gibbs,et al.  Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. , 2015, Human molecular genetics.

[44]  F. Cunningham,et al.  The Ensembl Variant Effect Predictor , 2016, Genome Biology.

[45]  Jean Amos Wilson,et al.  CYP2D6 copy number distribution in the US population , 2016, Pharmacogenetics and genomics.

[46]  M. Whirl‐Carrillo,et al.  Prediction of CYP2D6 phenotype from genotype across world populations , 2016, Genetics in Medicine.

[47]  A. Sajantila,et al.  Global genetic variation of select opiate metabolism genes in self-reported healthy individuals , 2017, The Pharmacogenomics Journal.

[48]  M. Hayden,et al.  The global spectrum of protein-coding pharmacogenomic diversity , 2016, The Pharmacogenomics Journal.