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Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior.
Hum Mol Genet 2016; 25(24):5472-5482HM

Abstract

Caffeine is the most widely consumed psychoactive substance in the world and presents with wide interindividual variation in metabolism. This variation may modify potential adverse or beneficial effects of caffeine on health. We conducted a genome-wide association study (GWAS) of plasma caffeine, paraxanthine, theophylline, theobromine and paraxanthine/caffeine ratio among up to 9,876 individuals of European ancestry from six population-based studies. A single SNP at 6p23 (near CD83) and several SNPs at 7p21 (near AHR), 15q24 (near CYP1A2) and 19q13.2 (near CYP2A6) met GW-significance (P < 5 × 10-8) and were associated with one or more metabolites. Variants at 7p21 and 15q24 associated with higher plasma caffeine and lower plasma paraxanthine/caffeine (slow caffeine metabolism) were previously associated with lower coffee and caffeine consumption behavior in GWAS. Variants at 19q13.2 associated with higher plasma paraxanthine/caffeine (slow paraxanthine metabolism) were also associated with lower coffee consumption in the UK Biobank (n = 94 343, P < 1.0 × 10-6). Variants at 2p24 (in GCKR), 4q22 (in ABCG2) and 7q11.23 (near POR) that were previously associated with coffee consumption in GWAS were nominally associated with plasma caffeine or its metabolites. Taken together, we have identified genetic factors contributing to variation in caffeine metabolism and confirm an important modulating role of systemic caffeine levels in dietary caffeine consumption behavior. Moreover, candidate genes identified encode proteins with important clinical functions that extend beyond caffeine metabolism.

Authors+Show Affiliations

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, USA.Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany. DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas Hospital, London, UK.Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.Division of Chronic Diseases, University Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne (CHUV), Lausanne, Switzerland.Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany. German Center for Diabetes Research (DZD), Neuherberg, Germany.Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.Department of Psychiatry, Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Lausanne, Switzerland. School of Pharmaceutical Sciences, University of Geneve, University of Lausanne, Geneva, Switzerland.Cardiology, Department of Specialties of Internal Medicine, Geneva University Hospitals, Geneva, Switzerland. Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, USA.DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Germany.Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, USA. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, USA.Division of Chronic Diseases, University Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne (CHUV), Lausanne, Switzerland. Department of Community Medicine and Primary Care and Emergency Medicine, Unit of Population Epidemiology, Geneva University Hospitals, Geneva, Switzerland. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany.Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas Hospital, London, UK.Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Germany.Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.No affiliation info availableDivision of Chronic Diseases, University Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne (CHUV), Lausanne, Switzerland.Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas Hospital, London, UK.Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, USA.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

27702941

Citation

Cornelis, Marilyn C., et al. "Genome-wide Association Study of Caffeine Metabolites Provides New Insights to Caffeine Metabolism and Dietary Caffeine-consumption Behavior." Human Molecular Genetics, vol. 25, no. 24, 2016, pp. 5472-5482.
Cornelis MC, Kacprowski T, Menni C, et al. Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior. Hum Mol Genet. 2016;25(24):5472-5482.
Cornelis, M. C., Kacprowski, T., Menni, C., Gustafsson, S., Pivin, E., Adamski, J., ... Ingelsson, E. (2016). Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior. Human Molecular Genetics, 25(24), pp. 5472-5482. doi:10.1093/hmg/ddw334.
Cornelis MC, et al. Genome-wide Association Study of Caffeine Metabolites Provides New Insights to Caffeine Metabolism and Dietary Caffeine-consumption Behavior. Hum Mol Genet. 2016 12 15;25(24):5472-5482. PubMed PMID: 27702941.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior. AU - Cornelis,Marilyn C, AU - Kacprowski,Tim, AU - Menni,Cristina, AU - Gustafsson,Stefan, AU - Pivin,Edward, AU - Adamski,Jerzy, AU - Artati,Anna, AU - Eap,Chin B, AU - Ehret,Georg, AU - Friedrich,Nele, AU - Ganna,Andrea, AU - Guessous,Idris, AU - Homuth,Georg, AU - Lind,Lars, AU - Magnusson,Patrik K, AU - Mangino,Massimo, AU - Pedersen,Nancy L, AU - Pietzner,Maik, AU - Suhre,Karsten, AU - Völzke,Henry, AU - ,, AU - Bochud,Murielle, AU - Spector,Tim D, AU - Grabe,Hans J, AU - Ingelsson,Erik, PY - 2016/06/04/received PY - 2016/09/28/accepted PY - 2016/10/6/pubmed PY - 2017/6/10/medline PY - 2016/10/6/entrez SP - 5472 EP - 5482 JF - Human molecular genetics JO - Hum. Mol. Genet. VL - 25 IS - 24 N2 - Caffeine is the most widely consumed psychoactive substance in the world and presents with wide interindividual variation in metabolism. This variation may modify potential adverse or beneficial effects of caffeine on health. We conducted a genome-wide association study (GWAS) of plasma caffeine, paraxanthine, theophylline, theobromine and paraxanthine/caffeine ratio among up to 9,876 individuals of European ancestry from six population-based studies. A single SNP at 6p23 (near CD83) and several SNPs at 7p21 (near AHR), 15q24 (near CYP1A2) and 19q13.2 (near CYP2A6) met GW-significance (P < 5 × 10-8) and were associated with one or more metabolites. Variants at 7p21 and 15q24 associated with higher plasma caffeine and lower plasma paraxanthine/caffeine (slow caffeine metabolism) were previously associated with lower coffee and caffeine consumption behavior in GWAS. Variants at 19q13.2 associated with higher plasma paraxanthine/caffeine (slow paraxanthine metabolism) were also associated with lower coffee consumption in the UK Biobank (n = 94 343, P < 1.0 × 10-6). Variants at 2p24 (in GCKR), 4q22 (in ABCG2) and 7q11.23 (near POR) that were previously associated with coffee consumption in GWAS were nominally associated with plasma caffeine or its metabolites. Taken together, we have identified genetic factors contributing to variation in caffeine metabolism and confirm an important modulating role of systemic caffeine levels in dietary caffeine consumption behavior. Moreover, candidate genes identified encode proteins with important clinical functions that extend beyond caffeine metabolism. SN - 1460-2083 UR - https://www.unboundmedicine.com/medline/citation/27702941/Genome_wide_association_study_of_caffeine_metabolites_provides_new_insights_to_caffeine_metabolism_and_dietary_caffeine_consumption_behavior_ L2 - https://academic.oup.com/hmg/article-lookup/doi/10.1093/hmg/ddw334 DB - PRIME DP - Unbound Medicine ER -