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Cytochrome P450 (CYP450) enzymes are a superfamily of heme-containing monooxygenases that play a pivotal role in Phase I drug metabolism by catalyzing oxidation and reduction reactions.These enzymes transform lipophilic xenobiotics into more hydrophilic metabolites, facilitating subsequent Phase II conjugation and eventual excretion. The CYP450 family is classified into families (e.g., CYP1–CYP3) and subfamilies (e.g., CYP2A, CYP2C), based on amino acid sequence homology.CYP450...
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Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
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Genetic polymorphism in drug metabolism is crucial to the inter-individual variability observed in drug responses. Drug metabolism primarily involves the chemical modification of drugs and other xenobiotics to enhance their elimination by increasing their polarity. Two main classes of enzymes mediate this biotransformation process: Phase I enzymes, primarily cytochrome P450s, catalyze oxidation and reduction reactions, while other enzymes, such as esterases, mediate hydrolysis, and Phase II...
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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Functional characterization of CYP2D6 enhancer polymorphisms.

Danxin Wang1, Audrey C Papp2, Xiaochun Sun2

  • 1Center for Pharmacogenomics, School of Medicine, The Ohio State University, Columbus, OH 43210, USA wang.808@osu.edu.

Human Molecular Genetics
|November 9, 2014
PubMed
Summary
This summary is machine-generated.

Genetic variations near the CYP2D6 gene influence drug metabolism. A specific single nucleotide polymorphism (SNP), rs5758550, within an enhancer region significantly impacts CYP2D6 expression, aiding phenotype prediction.

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Area of Science:

  • Pharmacogenomics
  • Molecular Biology
  • Genetics

Background:

  • CYP2D6 is crucial for metabolizing approximately 25% of clinical drugs.
  • Genetic variations in CYP2D6 lead to significant inter-individual differences in enzyme activity.
  • Predicting CYP2D6 metabolizer phenotype is vital for personalized medicine.

Purpose of the Study:

  • To elucidate the functional impact of a previously identified CYP2D6 enhancer region.
  • To pinpoint the specific single nucleotide polymorphism (SNP) responsible for regulating CYP2D6 expression.
  • To validate the role of the enhancer and its variants in controlling CYP2D6 gene activity.

Main Methods:

  • Chromatin conformation capture combined with next-generation sequencing (4C assays).
  • Chromatin immunoprecipitation with P300 antibody in HepG2 cells and primary hepatocytes.
  • Reporter gene assays and clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genome editing.

Main Results:

  • The study confirmed the enhancer region's role in regulating CYP2D6 expression.
  • Three highly linked SNPs (rs133333, rs5758550, rs4822082) were identified as candidates.
  • Only SNP rs5758550 demonstrated significant regulatory activity in reporter assays and CRISPR-mediated deletion reduced CYP2D6 mRNA by 70%.

Conclusions:

  • The identified enhancer element and specifically SNP rs5758550 robustly influence CYP2D6 expression.
  • SNP rs5758550 is a key determinant of CYP2D6 activity.
  • Incorporating rs5758550 into CYP2D6 genotyping panels can improve phenotype prediction accuracy.