Felipe A de Oliveira1, Mohamed H Shahin1, Yan Gong1, Caitrin W McDonough1, Amber L Beitelshees2, John G Gums3, Arlene B Chapman4, Eric Boerwinkle5, Stephen T Turner6, Reginald F Frye1, Oliver Fiehn7, Rima Kaddurah-Daouk8, Julie A Johnson1, Rhonda M Cooper-DeHoff1. 1. Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, PO Box 100486, Gainesville, FL 32610-0486, USA. 2. Department of Medicine, University of Maryland, Baltimore, MD, USA. 3. Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, PO Box 100486, Gainesville, FL 32610-0486, USA; Department of Community Health and Family Medicine, College of Medicine, University of Florida, Gainesville, FL, USA. 4. Department of Medicine, University of Chicago, Chicago, IL, USA. 5. Human Genetics Center and Institute for Molecular Medicine, University of Texas Health Science Center, Houston, TX, USA. 6. College of Medicine, Mayo Clinic, Rochester, MN, USA. 7. Genome Center, University of California at Davis, Davis, CA, USA; Biochemistry Department, King Abdullah University, Jeddah, Saudi Arabia. 8. Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
Abstract
INTRODUCTION: While atenolol is an effective antihypertensive agent, its use is also associated with adverse events including hyperglycemia and incident diabetes that may offset the benefits of blood pressure lowering. By combining metabolomic and genomic data acquired from hypertensive individuals treated with atenolol, it may be possible to better understand the pathways that most impact the development of an adverse glycemic state. OBJECTIVE: To identify biomarkers that can help predict susceptibility to blood glucose excursions during exposure to atenolol. METHODS: Plasma samples acquired from 234 Caucasian participants treated with atenolol in the Pharmacogenomic Evaluation of Antihypertensive Responses trial were analyzed by gas chromatography Time-Of-Flight Mass Spectroscopy. Metabolomics and genomics data were integrated by first correlating participant's metabolomic profiles to change in glucose after treatment with atenolol, and then incorporating genotype information from genes involved in metabolite pathways associated with glucose response. RESULTS: Our findings indicate that the baseline level of β-alanine was associated with glucose change after treatment with atenolol (Q = 0.007, β = 2.97 mg/dL). Analysis of genomic data revealed that carriers of the G allele for SNP rs2669429 in gene DPYS, which codes for dihydropyrimidinase, an enzyme involved in β-alanine formation, had significantly higher glucose levels after treatment with atenolol when compared with non-carriers (Q = 0.05, β = 2.76 mg/dL). This finding was replicated in participants who received atenolol as an add-on therapy (P = 0.04, β = 1.86 mg/dL). CONCLUSION: These results suggest that β-alanine and rs2669429 may be predictors of atenolol-induced hyperglycemia in Caucasian individuals and further investigation is warranted.
INTRODUCTION: While atenolol is an effective antihypertensive agent, its use is also associated with adverse events including hyperglycemia and incident diabetes that may offset the benefits of blood pressure lowering. By combining metabolomic and genomic data acquired from hypertensive individuals treated with atenolol, it may be possible to better understand the pathways that most impact the development of an adverse glycemic state. OBJECTIVE: To identify biomarkers that can help predict susceptibility to blood glucose excursions during exposure to atenolol. METHODS: Plasma samples acquired from 234 Caucasian participants treated with atenolol in the Pharmacogenomic Evaluation of Antihypertensive Responses trial were analyzed by gas chromatography Time-Of-Flight Mass Spectroscopy. Metabolomics and genomics data were integrated by first correlating participant's metabolomic profiles to change in glucose after treatment with atenolol, and then incorporating genotype information from genes involved in metabolite pathways associated with glucose response. RESULTS: Our findings indicate that the baseline level of β-alanine was associated with glucose change after treatment with atenolol (Q = 0.007, β = 2.97 mg/dL). Analysis of genomic data revealed that carriers of the G allele for SNP rs2669429 in gene DPYS, which codes for dihydropyrimidinase, an enzyme involved in β-alanine formation, had significantly higher glucose levels after treatment with atenolol when compared with non-carriers (Q = 0.05, β = 2.76 mg/dL). This finding was replicated in participants who received atenolol as an add-on therapy (P = 0.04, β = 1.86 mg/dL). CONCLUSION: These results suggest that β-alanine and rs2669429 may be predictors of atenolol-induced hyperglycemia in Caucasian individuals and further investigation is warranted.
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