14 research outputs found

    Reconstructing Roma History from Genome-Wide Data

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    The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000–1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs). We estimate that the Roma harbor about 80% West Eurasian ancestry–derived from a combination of European and South Asian sources–and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe.Országos Tudományos Kutatási Alapprogramok (OTKA K 103983)Országos Tudományos Kutatási Alapprogramok (OTKA 73430)National Science Foundation (U.S.) (HOMINID grant 1032255)National Institutes of Health (U.S.) (grant GM100233

    A European spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics

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    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

    A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics

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    Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicitywith the underlying genetic composition, particularly in genes encoding for protein factorsand enzymes involved in drug metabolism and transport. In several Europeanpopulations, particularly in countries with lower income, information related to the prevalenceof pharmacogenomic biomarkers is incomplete or lacking. Here, we have implementedthe microattribution approach to assess the pharmacogenomic biomarkers allelicspectrum in 18 European populations, mostly from developing European countries, by analyzing1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant interpopulationpharmacogenomic biomarker allele frequency differences, particularly in 7 clinicallyactionable pharmacogenomic biomarkers in 7 European populations, affecting drugefficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on thedifferences observed in the prevalence of high-risk genotypes in these populations, as faras common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMTpharmacogenes are concerned. Also, our data demonstrate notable differences in predictedgenotype-based warfarin dosing among these populations. Our findings can beexploited not only to develop guidelines for medical prioritization, but most importantly tofacilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomictesting. This may subsequently contribute towards significant cost-savings in the overallhealthcare expenditure in the participating countries, where pharmacogenomics implementationproves to be cost-effective.Introductio

    A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics.

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    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

    Outline of the predicted average warfarin dosage calculation for all populations.

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    <p>This table suggests the weekly average dosage along with the standard deviation, confidence interval (95%) and the respective upper bound and lower bound for each population.</p

    Comparison of the frequencies (vertical axis; %) of the 36 actionable PGx biomarkers (depicted at the horizontal axis) among European, Saudi Arabian and South African populations.

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    <p>Comparison of the frequencies (vertical axis; %) of the 36 actionable PGx biomarkers (depicted at the horizontal axis) among European, Saudi Arabian and South African populations.</p
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