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.

Boğaziçi University Istanbul Turkey

Center for Molecular Medicine Slovak Academy of Sciences Bratislava Slovakia

Center for Proteomic and Genomic Research Observatory Cape Town South Africa

Charles University 2nd Faculty of Medicine and University Hospital Motol Prague Czech Republic

Comenius University Faculty of Natural Sciences Bratislava Slovakia

Department of Genetics and Fundamental Medicine Bashkir State University Ufa Russia

Department of Human and Medical Genetics Faculty of Medicine Vilnius University Vilnius Lithuania

Erasmus University Medical Center Department of Clinical Chemistry Rotterdam the Netherlands

Erasmus University Medical Center Faculty of Medicine Department of Bioinformatics Rotterdam the Netherlands

Institute of Biochemistry and Biophysics Polish Academy of Sciences Warsaw Poland

Institute of Biochemistry and Genetics Ufa Scientific Center Russian Academy of Sciences Ufa Russia

Institute of Hereditary Pathology Ukrainian National Academy of Medical Sciences Lviv Ukraine

Institute of Molecular Genetics and Genetic Engineering University of Belgrade Laboratory of Molecular Biomedicine Belgrade Serbia

King Faisal Specialist Hospital and Research Centre Riyadh Saudi Arabia

Moffitt Cancer Center Tampa FL United States of America

North Carolina State University Department of Statistics Raleigh NC United States of America

RIKEN Institute Center for Genomic Medicine Laboratory for International Alliance Yokohama Japan

The Golden Helix Foundation London United Kingdom

University Hospital Centre Zagreb Croatia

University of Athens Faculty of Pharmacy Department of Pharmaceutical Chemistry Athens Greece

University of Cagliari Department of Biomedical Sciences Cagliari Italy

University of Cyprus Molecular Medicine Research Center Department of Biological Sciences Nicosia Cyprus

University of Debrecen Debrecen Hungary

University of Kiel Institute for Experimental and Clinical Pharmacology Kiel Germany

University of Ljubljana Faculty of Medicine Ljubljana Slovenia

University of Malta Department of Applied Biomedical Science Faculty of Health Sciences Msida Malta

University of Malta Faculty of Medicine and Surgery Department of Physiology and Biochemistry Msida Malta

University of Malta Faculty of Medicine Department of Surgery Msida Malta

University of Patras School of Health Sciences Department of Pharmacy Patras Greece

University of Rome Tor Vergata Department of Biomedicine and Prevention Rome Italy

University of Santiago de Compostela Santiago Spain

University of Turin School of Medicine Turin Italy

University of Zagreb School of Medicine Zagreb Croatia

PLoS One. 2017 Feb 16;12(2):e0172595. doi: 10.1371/journal.pone.0172595. PubMed

Zobrazit více v PubMed

Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, et al. Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice. Pharmacogenomics. 2010;11(8):1149–1167 10.2217/pgs.10.97 PubMed DOI

Davies EC, Green CF, Mottram DR, Pirmohamed M. Interpreting adverse drug reaction (ADR) reports as hospital patient safety incidents. Br J Clin Pharmacol. 2010;70(1):102–108. 10.1111/j.1365-2125.2010.03671.x PubMed DOI PMC

Zineh I, Pacanowski MA. Pharmacogenomics in the assessment of therapeutic risks versus benefits: inside the United States Food and Drug Administration. Pharmacotherapy, 2011;31(8):729–735. 10.1592/phco.31.8.729 PubMed DOI

Ehmann F, Caneva L, Prasad K, Paulmichl M, Maliepaard M, Llerena A, et al. Pharmacogenomic information in drug labels: European Medicines Agency perspective. Pharmacogenomics J. 2015;15(3):201–210. 10.1038/tpj.2014.86 PubMed DOI

Arnold FL, Fukunaga S, Kusama M, Matsuki N, Ono S. Assessment of factors associated with dose differences between Japan and the United States. Clin Pharmacol Ther. 2014;95(5):542–549. 10.1038/clpt.2013.231 PubMed DOI

Wilson JF, Weale ME, Smith AC, Gratrix F, Fletcher B, Thomas MG, et al. Population genetic structure of variable drug response. Nat Genet. 2001;29(3):265–269 PubMed

Ge D, Fellay J, Thompson AJ, Simon JS, Shianna KV, Urban TJ, et al. Genetic variation in IL28B predicts hepatitis C treatment-induced viral clearance. Nature. 2009;461(7262):399–401. 10.1038/nature08309 PubMed DOI

Roewer L, Croucher PJ, Willuweit S, Lu TT, Kayser M, Lessig R, et al. Signature of recent historical events in the European Y-chromosomal STR haplotype distribution. Hum Genet. 2005;116:279–291. PubMed

Giardine B, Borg J, Higgs DR, Peterson KR, Philipsen S, Maglott D, et al. Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach. Nat Genet. 2011;43(4):295–301. 10.1038/ng.785 PubMed DOI PMC

Patrinos GP, Cooper DN, van Mulligen E, Gkantouna V, Tzimas G, Tatum Z, et al. Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain. Hum Mutat. 2012;33(11): 1503–1512. 10.1002/humu.22144 PubMed DOI

Weale ME. Quality control for genome-wide association studies. Methods Mol Biol, 2010;628:341–72. 10.1007/978-1-60327-367-1_19 PubMed DOI

Papadopoulos P, Viennas E, Gkantouna V, Pavlidis C, Bartsakoulia M, Ioannou ZM, et al. Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies. Nucleic Acids Res. 2014;42(Database issue):D1020–D1026. 10.1093/nar/gkt1125 PubMed DOI PMC

International Warfarin Pharmacogenetics Consortium, Klein TE, Altman RB, Eriksson N, Gage BF, Kimmel SE, Lee MT, et al. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med. 2009;360(8):753–764 10.1056/NEJMoa0809329 PubMed DOI PMC

International HapMap Consortium. The International HapMap Project. Nature. 2003;426(6968):789–796. PubMed

Ramsey LB, Johnson SG, Caudle KE, Haidar CE, Voora D, Wilke RA, et al. The clinical pharmacogenetics implementation consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update. Clin Pharmacol Ther. 2014;96(4):423–428. 10.1038/clpt.2014.125 PubMed DOI PMC

Wilke RA, Ramsey LB, Johnson SG, Maxwell WD, McLeod HL, Voora D, et al. The clinical pharmacogenomics implementation consortium: CPIC guideline for SLCO1B1 and simvastatin-induced myopathy. Clin Pharmacol Ther. 2012;92(1):112–117. 10.1038/clpt.2012.57 PubMed DOI PMC

Van Driest SL, Shi Y, Bowton EA, Schildcrout JS, Peterson JF, Pulley J, et al. Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing. Clin Pharmacol Ther. 2014;95(4):423–431. 10.1038/clpt.2013.229 PubMed DOI PMC

Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics, 2000;155(2):945–959. PubMed PMC

Limdi NA. Warfarin pharmacogenetics: challenges and opportunities for clinical translation. Front Pharmacol, 2012;3:183 10.3389/fphar.2012.00183 PubMed DOI PMC

Sosnay PR, Siklosi KR, Van Goor F, Kaniecki K, Yu H, Sharma N, et al. Defining the disease liability of variants in the cystic fibrosis transmembrane conductance regulator gene. Nat Genet. 2013;45(10):1160–1167 10.1038/ng.2745 PubMed DOI PMC

Bonifaz-Peña V, Contreras AV, Struchiner CJ, Roela RA, Furuya-Mazzotti TK, Chammas R, et al. Exploring the distribution of genetic markers of pharmacogenomics relevance in Brazilian and Mexican populations. PLoS One. 2014;9(11):e112640 10.1371/journal.pone.0112640 PubMed DOI PMC

Jittikoon J, Mahasirimongkol S, Charoenyingwattana A, Chaikledkaew U, Tragulpiankit P, Mangmool S, et al. Comparison of genetic variation in drug ADME-related genes in Thais with Caucasian, African and Asian HapMap populations. J Hum Genet. 2016;61(2):119–127. 10.1038/jhg.2015.115 PubMed DOI

Maisano Delser P, Fuselli S. Human loci involved in drug biotransformation: worldwide genetic variation, population structure, and pharmacogenetic implications. Hum Genet. 2013;132(5):563–577. 10.1007/s00439-013-1268-5 PubMed DOI

Ramos E, Doumatey A, Elkahloun AG, Shriner D, Huang H, Chen G, et al. Pharmacogenomics, ancestry and clinical decision making for global populations. Pharmacogenomics J. 2014;14(3):217–222. 10.1038/tpj.2013.24 PubMed DOI

Chen J, Teo YY, Toh DS, Sung C. Interethnic comparisons of important pharmacology genes using SNP databases: potential application to drug regulatory assessments. Pharmacogenomics. 2010;11(8):1077–1094. 10.2217/pgs.10.79 PubMed DOI

Jackson JN, Long KM, He Y, Motsinger-Reif AA, McLeod HL, Jack J. A comparison of DMET Plus microarray and genome-wide technologies by assessing population substructure. Pharmacogenetics Genomics. 2016; in press. PubMed PMC

Snyder SR, Mitropoulou C, Patrinos GP, Williams MS. Economic evaluation of pharmacogenomics: a value-based approach to pragmatic decision making in the face of complexity. Public Health Genomics. 2014;17(5–6):256–264 10.1159/000366177 PubMed DOI

Potamias G, Lakiotaki K, Katsila T, Lee MT, Topouzis S, Cooper DN, et al. Deciphering next-generation pharmacogenomics: An information technology perspective. Open Biol. 2014;4(7). pii:140071. PubMed PMC

Kampourakis K, Vayena E, Mitropoulou C, Borg J, van Schaik RH, Cooper DN, et al. Key challenges for next generation pharmacogenomics. EMBO Rep 2014;15(5):472–476. PubMed PMC

Mitropoulou C, Mai Y, van Schaik RH, Vozikis A, Patrinos GP. Documentation and analysis of the policy environment and key stakeholders in pharmacogenomics and genomic medicine in Greece. Public Health Genomics 2014;17(5–6):280–286. PubMed

Mizzi C, Peters B, Mitropoulou C, Mitropoulos K, Katsila T, Agarwal MR, et al. Personalized pharmacogenomics profiling using whole-genome sequencing. Pharmacogenomics. 2014;15(9):1223–1234. 10.2217/pgs.14.102 PubMed DOI

Schildcrout JS, Denny JC, Bowton E, Gregg W, Pulley JM, Basford MA, et al. Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping. Clin Pharmacol Ther. 2012;92(2):235–242. 10.1038/clpt.2012.66 PubMed DOI PMC

Pharmacogenomic profile of a central European urban random population-Czech population