Potential Impact of Pharmacogenomic Single Nucleotide Variants in a Rural Caucasian Population

Abstract

Background: In the US adverse drug reactions (ADRs) are estimated to cause 100 000 fatalities and cost over $136 billion annually. A patient's genes play a significant role in their response to a drug. Pharmacogenomics aims to optimize drug choice and dose for individual patients by characterizing patients' pharmacologically relevant genes to identify variants of known impact.

Methods: DNA was extracted from randomly selected remnant whole blood samples from Caucasian patients with previously performed complete blood counts. Samples were genotyped by mass spectrometry using a customized pharmacogenomics panel. A third-party result interpretation service used genotypic results to predict likely individual responses to frequently prescribed drugs.

Results: Complete genotypic and phenotypic calls for all tested Cytochrome P450 isoenzymes and other genes were obtained from 152 DNA samples. Of these 152 unique genomic DNA samples, 140 had genetic variants suggesting dose adjustment for at least one drug. Cardiovascular and psychiatry drugs had the highest number of recommendations, which included United States Food and Drug Administration warnings for highly prescribed drugs metabolized by CYP2C19, CYP2C9, CYP2D6, HLA-A, and VKORC1.

Conclusions: Risk for each drug:gene pairing primarily depends upon the degree of predicted enzyme impairment or activation, width of the therapeutic window, and whether parent compound or metabolite is pharmacologically active. The resulting metabolic variations range from risk of toxicity to therapeutic failure. Pharmacogenomic profiling likely reduces ADR potential by allowing up front drug/dose selection to fit a patient's unique drug-response profile.

Fig. 1.

Summary of sample drug recommendations defined as “actionable” in TS report and also having a strong recommendation from either CPIC, PharmGKB, or the FDA. Each pie piece contains the number of samples corresponding with the category in the legend. (A), Number of drug recommendations per sample out of 152 samples; (B), Total recommendations for all samples divided by drug class; (C), 178 cardiovascular category drug recommendations divided by class of medication; (D), 423 psychotropic drug recommendations divided by class.