Estonian study reveals critical gaps in pharmacogenetic testing
Researchers identified clinically relevant CYP2C19 and CYP2D6 variants that significantly affect drug metabolism, which could improve current pharmacogenetic testing.
According to current clinical practice, pharmacogenetic testing relies on a limited set of “star alleles” to predict drug metabolism, yet this approach may miss up to 35–40% of clinically relevant genetic variants that affect how patients process several common medications.
In a study recently published in npj Genomic Medicine, researchers from the University of Tartu (Estonia), Tartu University Hospital (Estonia), and North Estonia Medical Centre (Tallinn, Estonia) have identified and validated previously uncharacterized genetic variants that traditional testing methods overlook. These findings offer a promising solution to improve precision medicine by predicting patients’ drug metabolic phenotype.
The researchers began by conducting an in vivo phenotyping study encompassing 114 Estonian Biobank participants with rare or novel variants in the CYP2C19 and CYP2D6 genes. CYP2C19 and CYP2D6 enzymes are responsible for metabolizing approximately 35–40% of clinical drugs.
The participants were administered with probe drugs omeprazole (a CYP2C19 substrate) and metoprolol (a CYP2D6 substrate). Blood plasma levels of these drugs and their metabolites were measured using ultra high-performance liquid chromatography and high-resolution mass spectrometry at ten different time-points. The researchers then calculated the ratio between the original drug and its metabolite to determine how well the enzymes were working.
You may also be interested in:
- Identifying blood metabolites for type 2 diabetes risk
- Metabolomics and microbiomics: dietary and environmental factors in cancer
- LC–MS/MS for quantitation of protein biomarkers
The team combined long-read sequencing for high-resolution variant detection with precise plasma drug monitoring, generating direct evidence of enzymatic activity rather than genetic inference alone. Collaborating with Oslo University (Norway) and Karolinska Institutet (Stockholm, Sweden), they confirmed variants in CYP2C19 (alleles CYP2C19*37 and CYP2C19*42) and CYP2D6 (alleles CYP2D6*124 and c.940C>A) could alter drug metabolism significantly and correlated with a poor metabolizer phenotype, highlighting the importance of rare and structural variants testing that are often missed in the current approach.
“The new data suggest that incorporating broader variant discovery by long-read HiFi sequencing and phenotyping strategies accounting for drug-drug interactions can improve metabolic phenotype assignment and support more precise drug dosing recommendations,” said Lili Milani, Professor and Head of the Estonian Biobank at University of Tartu.
Future pharmacogenetic testing could incorporate pharmacokinetic studies with probe drugs to better define metabolic phenotypes and optimize personalized therapy.
