A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics

Clint Mizzi, Eleni Dalabira, Judit Kumuthini, Nduna Dzimiri, Istvan Balogh, Nazli Başak, Ruwen Böhm, Joseph Borg, Paola Borgiani, Nada Bozina, Henrike Bruckmueller, Beata Burzynska, Angel Carracedo, Ingolf Cascorbi, Constantinos Deltas, Vita Dolzan, Anthony Fenech, Godfrey Grech, Vytautas Kasiulevicius, Ľudevít Kádaši, Vaidutis Kučinskas, Elza Khusnutdinova, Yiannis L. Loukas, Milan Macek, Halyna Makukh, Ron Mathijssen, Konstantinos Mitropoulos, Christina Mitropoulou, Giuseppe Novelli, Ioanna Papantoni, Sonja Pavlovic, Giuseppe Saglio, Jadranka Setric, Maja Stojiljkovic, Andrew P. Stubbs, Alessio Squassina, Maria Torres, Marek Turnovec, Ron H. van Schaik, Konstantinos Voskarides, Salma M. Wakil, Anneke Werk, Maria del Zompo, Branka Zukic, Theodora Katsila, Ming Ta Michael Lee, Alison Motsinger-Rief, Howard L. Mc Leod, Peter J. van der Spek, George P. Patrinos

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.