Literature DB >> 28217400

Novel plasma biomarker of atenolol-induced hyperglycemia identified through a metabolomics-genomics integrative approach.

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.   

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.

Entities:  

Keywords:  Atenolol; Hyperglycemia; Pharmacogenomics; Pharmacometabolomics; β-alanine; β-blockers

Year:  2016        PMID: 28217400      PMCID: PMC5310671          DOI: 10.1007/s11306-016-1076-8

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  29 in total

1.  Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients.

Authors:  S Yusuf; P Sleight; J Pogue; J Bosch; R Davies; G Dagenais
Journal:  N Engl J Med       Date:  2000-01-20       Impact factor: 91.245

2.  Normal fasting plasma glucose and risk of type 2 diabetes diagnosis.

Authors:  Gregory A Nichols; Teresa A Hillier; Jonathan B Brown
Journal:  Am J Med       Date:  2008-06       Impact factor: 4.965

3.  Mutations in the hepatocyte nuclear factor-1alpha gene in MODY and early-onset NIDDM: evidence for a mutational hotspot in exon 4.

Authors:  P J Kaisaki; S Menzel; T Lindner; N Oda; I Rjasanowski; J Sahm; G Meincke; J Schulze; H Schmechel; C Petzold; H M Ledermann; G Sachse; V V Boriraj; R Menzel; W Kerner; R C Turner; K Yamagata; G I Bell
Journal:  Diabetes       Date:  1997-03       Impact factor: 9.461

4.  Global burden of hypertension: analysis of worldwide data.

Authors:  Patricia M Kearney; Megan Whelton; Kristi Reynolds; Paul Muntner; Paul K Whelton; Jiang He
Journal:  Lancet       Date:  2005 Jan 15-21       Impact factor: 79.321

5.  Reduced muscle carnosine content in type 2, but not in type 1 diabetic patients.

Authors:  Bruno Gualano; Inge Everaert; Sanne Stegen; Guilherme Giannini Artioli; Youri Taes; Hamilton Roschel; Eric Achten; Maria Concepción Otaduy; Antonio Herbert Lancha Junior; Roger Harris; Wim Derave
Journal:  Amino Acids       Date:  2011-11-27       Impact factor: 3.520

Review 6.  Beta-alanine supplementation, muscle carnosine and exercise performance.

Authors:  Laura Blancquaert; Inge Everaert; Wim Derave
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2015-01       Impact factor: 4.294

7.  Contribution of dihydropyrimidinase gene alterations to the development of serious toxicity in fluoropyrimidine-treated cancer patients.

Authors:  Julie Fidlerova; Petra Kleiblova; Matej Bilek; Stanislav Kormunda; Zuzana Formankova; Jan Novotny; Zdenek Kleibl
Journal:  Cancer Chemother Pharmacol       Date:  2009-08-01       Impact factor: 3.333

8.  Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.

Authors: 
Journal:  Lancet       Date:  1998-09-12       Impact factor: 79.321

9.  Obesity and diabetes related plasma amino acid alterations.

Authors:  Yong Zhou; Ling Qiu; Qian Xiao; Yi Wang; Xiangying Meng; Rong Xu; Siyang Wang; Risu Na
Journal:  Clin Biochem       Date:  2013-05-19       Impact factor: 3.281

10.  Pharmacogenomics of antihypertensive drugs: rationale and design of the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) study.

Authors:  Julie A Johnson; Eric Boerwinkle; Issam Zineh; Arlene B Chapman; Kent Bailey; Rhonda M Cooper-DeHoff; John Gums; R Whit Curry; Yan Gong; Amber L Beitelshees; Gary Schwartz; Stephen T Turner
Journal:  Am Heart J       Date:  2009-03       Impact factor: 4.749

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  3 in total

1.  Sphingolipid Metabolic Pathway Impacts Thiazide Diuretics Blood Pressure Response: Insights From Genomics, Metabolomics, and Lipidomics.

Authors:  Mohamed H Shahin; Yan Gong; Reginald F Frye; Daniel M Rotroff; Amber L Beitelshees; Rebecca A Baillie; Arlene B Chapman; John G Gums; Stephen T Turner; Eric Boerwinkle; Alison Motsinger-Reif; Oliver Fiehn; Rhonda M Cooper-DeHoff; Xianlin Han; Rima Kaddurah-Daouk; Julie A Johnson
Journal:  J Am Heart Assoc       Date:  2017-12-29       Impact factor: 5.501

2.  Metabolomic profiling of metoprolol hypertension treatment reveals altered gut microbiota-derived urinary metabolites.

Authors:  Chad N Brocker; Thomas Velenosi; Hania K Flaten; Glenn McWilliams; Kyle McDaniel; Shelby K Shelton; Jessica Saben; Kristopher W Krausz; Frank J Gonzalez; Andrew A Monte
Journal:  Hum Genomics       Date:  2020-03-11       Impact factor: 4.639

Review 3.  Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine.

Authors:  Richard D Beger; Michael A Schmidt; Rima Kaddurah-Daouk
Journal:  Metabolites       Date:  2020-03-27
  3 in total

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