A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics
2016
Authors
Mizzi, ClintDalabira, Eleni
Kumuthini, Judit
Dzimiri, Nduna
Balogh, Istvan
Basak, Nazli
Boehm, Ruwen
Borg, Joseph
Borgiani, Paola
Bozina, Nada
Bruckmueller, Henrike
Burzynska, Beata
Carracedo, Angel
Cascorbi, Ingolf
Deltas, Constantinos
Dolzan, Vita
Fenech, Anthony
Grech, Godfrey
Kasiulevicius, Vytautas
Kadasi, L'udevit
Kucinskas, Vaidutis
Khusnutdinova, Elza
Loukas, Yiannis L.
Macek, Milan, Jr.
Makukh, Halyna
Mathijssen, Ron
Mitropoulos, Konstantinos
Mitropoulou, Christina
Novelli, Giuseppe
Papantoni, Ioanna
Pavlović, Sonja
Saglio, Giuseppe
Setrić, Jadranka
Stojiljković, Maja
Stubbs, Andrew P.
Squassina, Alessio
Torres, Maria
Turnovec, Marek
van Schaik, Ron H.
Voskarides, Konstantinos
Wakil, Salma M.
Werk, Anneke
del Zompo, Maria
Zukić, Branka
Katsila, Theodora
Lee, Ming Ta Michael
Motsinger-Rief, Alison
Mc Leod, Howard L.
van der Spek, Peter J.
Patrinos, George P.
Article (Published version)
Metadata
Show full item recordAbstract
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 interpopulation 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 prevale...nce 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.
Source:
PLoS One, 2016, 11, 9Publisher:
- Public Library Science, San Francisco
Funding / projects:
- European grant (RD-Connect) [FP7-305444]
- Golden Helix Foundation
- LITGEN project - European Social Fund under the Global Grant Measure [VP1-3.1-SMM-07-K-01-013]
- National Institutes of Health Common Fund Award NHGRI Grant [U41HG006941]
- [00064203]
- [LN14073]
- [LM2015091]
- [NF-CZ11-PDP-3-003-2014]
- [CZ.2.16/3.1.00/24022OPPK]
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [U41HG006941] Funding Source: NIH RePORTER
DOI: 10.1371/journal.pone.0162866
ISSN: 1932-6203
PubMed: 27636550
WoS: 000383723700018
Scopus: 2-s2.0-84992409620
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Institution/Community
Institut za molekularnu genetiku i genetičko inženjerstvoTY - JOUR AU - Mizzi, Clint AU - Dalabira, Eleni AU - Kumuthini, Judit AU - Dzimiri, Nduna AU - Balogh, Istvan AU - Basak, Nazli AU - Boehm, Ruwen AU - Borg, Joseph AU - Borgiani, Paola AU - Bozina, Nada AU - Bruckmueller, Henrike AU - Burzynska, Beata AU - Carracedo, Angel AU - Cascorbi, Ingolf AU - Deltas, Constantinos AU - Dolzan, Vita AU - Fenech, Anthony AU - Grech, Godfrey AU - Kasiulevicius, Vytautas AU - Kadasi, L'udevit AU - Kucinskas, Vaidutis AU - Khusnutdinova, Elza AU - Loukas, Yiannis L. AU - Macek, Milan, Jr. AU - Makukh, Halyna AU - Mathijssen, Ron AU - Mitropoulos, Konstantinos AU - Mitropoulou, Christina AU - Novelli, Giuseppe AU - Papantoni, Ioanna AU - Pavlović, Sonja AU - Saglio, Giuseppe AU - Setrić, Jadranka AU - Stojiljković, Maja AU - Stubbs, Andrew P. AU - Squassina, Alessio AU - Torres, Maria AU - Turnovec, Marek AU - van Schaik, Ron H. AU - Voskarides, Konstantinos AU - Wakil, Salma M. AU - Werk, Anneke AU - del Zompo, Maria AU - Zukić, Branka AU - Katsila, Theodora AU - Lee, Ming Ta Michael AU - Motsinger-Rief, Alison AU - Mc Leod, Howard L. AU - van der Spek, Peter J. AU - Patrinos, George P. PY - 2016 UR - https://imagine.imgge.bg.ac.rs/handle/123456789/909 AB - 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 interpopulation 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. PB - Public Library Science, San Francisco T2 - PLoS One T1 - A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics IS - 9 VL - 11 DO - 10.1371/journal.pone.0162866 ER -
@article{ author = "Mizzi, Clint and Dalabira, Eleni and Kumuthini, Judit and Dzimiri, Nduna and Balogh, Istvan and Basak, Nazli and Boehm, Ruwen and Borg, Joseph and Borgiani, Paola and Bozina, Nada and Bruckmueller, Henrike and Burzynska, Beata and Carracedo, Angel and Cascorbi, Ingolf and Deltas, Constantinos and Dolzan, Vita and Fenech, Anthony and Grech, Godfrey and Kasiulevicius, Vytautas and Kadasi, L'udevit and Kucinskas, Vaidutis and Khusnutdinova, Elza and Loukas, Yiannis L. and Macek, Milan, Jr. and Makukh, Halyna and Mathijssen, Ron and Mitropoulos, Konstantinos and Mitropoulou, Christina and Novelli, Giuseppe and Papantoni, Ioanna and Pavlović, Sonja and Saglio, Giuseppe and Setrić, Jadranka and Stojiljković, Maja and Stubbs, Andrew P. and Squassina, Alessio and Torres, Maria and Turnovec, Marek and van Schaik, Ron H. and Voskarides, Konstantinos and Wakil, Salma M. and Werk, Anneke and del Zompo, Maria and Zukić, Branka and Katsila, Theodora and Lee, Ming Ta Michael and Motsinger-Rief, Alison and Mc Leod, Howard L. and van der Spek, Peter J. and Patrinos, George P.", year = "2016", abstract = "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 interpopulation 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.", publisher = "Public Library Science, San Francisco", journal = "PLoS One", title = "A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics", number = "9", volume = "11", doi = "10.1371/journal.pone.0162866" }
Mizzi, C., Dalabira, E., Kumuthini, J., Dzimiri, N., Balogh, I., Basak, N., Boehm, R., Borg, J., Borgiani, P., Bozina, N., Bruckmueller, H., Burzynska, B., Carracedo, A., Cascorbi, I., Deltas, C., Dolzan, V., Fenech, A., Grech, G., Kasiulevicius, V., Kadasi, L., Kucinskas, V., Khusnutdinova, E., Loukas, Y. L., Macek, M. Jr., Makukh, H., Mathijssen, R., Mitropoulos, K., Mitropoulou, C., Novelli, G., Papantoni, I., Pavlović, S., Saglio, G., Setrić, J., Stojiljković, M., Stubbs, A. P., Squassina, A., Torres, M., Turnovec, M., van Schaik, R. H., Voskarides, K., Wakil, S. M., Werk, A., del Zompo, M., Zukić, B., Katsila, T., Lee, M. T. M., Motsinger-Rief, A., Mc Leod, H. L., van der Spek, P. J.,& Patrinos, G. P.. (2016). A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics. in PLoS One Public Library Science, San Francisco., 11(9). https://doi.org/10.1371/journal.pone.0162866
Mizzi C, Dalabira E, Kumuthini J, Dzimiri N, Balogh I, Basak N, Boehm R, Borg J, Borgiani P, Bozina N, Bruckmueller H, Burzynska B, Carracedo A, Cascorbi I, Deltas C, Dolzan V, Fenech A, Grech G, Kasiulevicius V, Kadasi L, Kucinskas V, Khusnutdinova E, Loukas YL, Macek MJ, Makukh H, Mathijssen R, Mitropoulos K, Mitropoulou C, Novelli G, Papantoni I, Pavlović S, Saglio G, Setrić J, Stojiljković M, Stubbs AP, Squassina A, Torres M, Turnovec M, van Schaik RH, Voskarides K, Wakil SM, Werk A, del Zompo M, Zukić B, Katsila T, Lee MTM, Motsinger-Rief A, Mc Leod HL, van der Spek PJ, Patrinos GP. A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics. in PLoS One. 2016;11(9). doi:10.1371/journal.pone.0162866 .
Mizzi, Clint, Dalabira, Eleni, Kumuthini, Judit, Dzimiri, Nduna, Balogh, Istvan, Basak, Nazli, Boehm, Ruwen, Borg, Joseph, Borgiani, Paola, Bozina, Nada, Bruckmueller, Henrike, Burzynska, Beata, Carracedo, Angel, Cascorbi, Ingolf, Deltas, Constantinos, Dolzan, Vita, Fenech, Anthony, Grech, Godfrey, Kasiulevicius, Vytautas, Kadasi, L'udevit, Kucinskas, Vaidutis, Khusnutdinova, Elza, Loukas, Yiannis L., Macek, Milan, Jr., Makukh, Halyna, Mathijssen, Ron, Mitropoulos, Konstantinos, Mitropoulou, Christina, Novelli, Giuseppe, Papantoni, Ioanna, Pavlović, Sonja, Saglio, Giuseppe, Setrić, Jadranka, Stojiljković, Maja, Stubbs, Andrew P., Squassina, Alessio, Torres, Maria, Turnovec, Marek, van Schaik, Ron H., Voskarides, Konstantinos, Wakil, Salma M., Werk, Anneke, del Zompo, Maria, Zukić, Branka, Katsila, Theodora, Lee, Ming Ta Michael, Motsinger-Rief, Alison, Mc Leod, Howard L., van der Spek, Peter J., Patrinos, George P., "A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics" in PLoS One, 11, no. 9 (2016), https://doi.org/10.1371/journal.pone.0162866 . .