Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior
Open accessAbstract
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.
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The two SNPs used as instrumental variables for caffeine consumption explained about 1.31% of the variance in caffeine consumption.
“The two SNPs explained about 1.31% of the variance in caffeine consumption.”
From Association between caffeine consumption and bone mineral density in children and adolescent: Observational and Mendelian randomization study (2023) · cites this paper as [28]
Cites
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
Fredholm, B. B., Bättig, K., Holmén, J., Nehlig, A., & Zvartau, E. E. (1999) · Pharmacological Reviews · doi:10.1016/s0031-6997(24)01396-6 · Cited by 2,624 · see citing works
Fast and accurate genotype imputation in genome-wide association studies through pre-phasing
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012) · Nature Genetics · doi:10.1038/ng.2354 · Cited by 1,737 · see citing works
Human metabolic individuality in biomedical and pharmaceutical research
CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., et al. (2011) · Nature · doi:10.1038/nature10354 · Cited by 1,017 · see citing works
Self-citationThe Aryl Hydrocarbon Receptor Complex and the Control of Gene Expression
Beischlag, T. V., Morales, J. L., Hollingshead, B. D., & Perdew, G. H. (2008) · Critical Reviews™ in Eukaryotic Gene Expression · doi:10.1615/critreveukargeneexpr.v18.i3.20 · Cited by 727 · see citing works
Sequence variants at CHRNB3–CHRNA6 and CYP2A6 affect smoking behavior
The ENGAGE Consortium, Thorgeirsson, T. E., Gudbjartsson, D. F., Surakka, I., Vink, J. M., Amin, N., Geller, F., Sulem, P., Rafnar, T., Esko, T., et al. (2010) · Nature Genetics · doi:10.1038/ng.573 · Cited by 689 · see citing works
Self-citationPharmacokinetics and metabolism of natural methylxanthines in animal and man
Arnaud, M. J. (2011) · Handbook of experimental pharmacology · doi:10.1007/978-3-642-13443-2_3 · Cited by 259 · see citing works
Cornelis, M. C., Monda, K. L., Yu, K., Paynter, N., Azzato, E. M., Bennett, S. N., Berndt, S. I., Boerwinkle, E., Chanock, S., Chatterjee, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002033 · Cited by 228 · see citing works
Self-citationCYP2A6 genotype and the metabolism and disposition kinetics of nicotine
BENOWITZ, N., SWAN, G., JACOBIII, P., LESSOVSCHLAGGAR, C., & TYNDALE, R. (2006) · Clinical Pharmacology & Therapeutics · doi:10.1016/j.clpt.2006.08.011 · Cited by 217 · see citing works
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Interindividual Differences in Caffeine Metabolism and Factors Driving Caffeine Consumption
Nehlig, A. (2018) · Pharmacological Reviews · doi:10.1124/pr.117.014407 · Cited by 632 · see citing works
van Dam, R. M., Hu, F. B., & Willett, W. C. (2020) · New England Journal of Medicine · doi:10.1056/nejmra1816604 · Cited by 508 · see citing works
Finger sweat analysis enables short interval metabolic biomonitoring in humans
Brunmair, J., Gotsmy, M., Niederstaetter, L., Neuditschko, B., Bileck, A., Slany, A., Feuerstein, M. L., Langbauer, C., Janker, L., Zanghellini, J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26245-4 · Cited by 96 · see citing works
The Role of Genetics in Moderating the Inter-Individual Differences in the Ergogenicity of Caffeine
Southward, K., Rutherfurd-Markwick, K., Badenhorst, C., & Ali, A. (2018) · Nutrients · doi:10.3390/nu10101352 · Cited by 81 · see citing works
Ferré, S., Díaz-Ríos, M., Salamone, J. D., & Prediger, R. D. (2018) · Journal of Caffeine and Adenosine Research · doi:10.1089/caff.2018.0017 · Cited by 52 · see citing works
Leviton, A. (2018) · Nutrients · doi:10.3390/nu10091152 · Cited by 27 · see citing works
Du, Y., Li, P., Wen, Y., Liang, X., Liu, L., Cheng, B., Ding, M., Zhao, Y., Ma, M., Zhang, L., et al. (2020) · Calcified Tissue International · doi:10.1007/s00223-019-00640-y · Cited by 14 · see citing works
Cui, A., Xiao, P., He, J., Fan, Z., Xie, M., Chen, L., Zhuang, Y., & Wang, H. (2023) · PLoS ONE · doi:10.1371/journal.pone.0287756 · Cited by 6 · see citing works
- Authors
- Cornelis, M. C., Kacprowski, T., Menni, C., Gustafsson, S., Pivin, E., Adamski, J., Artati, A., Eap, C. B., Ehret, G., Friedrich, N., Ganna, A., Guessous, I., Homuth, G., Lind, L., Magnusson, P. K., Mangino, M., Pedersen, N. L., Pietzner, M., Suhre, K., Völzke, H., Swiss Kidney Project on Genes in Hypertension (SKIPOGH) team, Bochud, M., Spector, T. D., Grabe, H. J., & Ingelsson, E.
- Affiliations
- Northwestern University (US)
- Universität Greifswald (DE)
- St Thomas' Hospital (GB)
- Uppsala University (SE)
- Centre Hospitalier Universitaire Vaudois (CH)
- Helmholtz Munich (DE)
- University of Geneva (CH)
- Johns Hopkins University (US)
- Universitätsmedizin Greifswald (DE)
- Broad Institute (US)
- Emory University (US)
- Karolinska Institutet (SE)
- Corresponding author
- Cornelis, Marilyn C.
- ORCID
- Cornelis, Marilyn C.
- Kacprowski, Tim
- Menni, Cristina
- Gustafsson, Stefan
- Adamski, Jerzy
- Eap, Chin B.
- Ehret, Georg
- Friedrich, Nele
- Ganna, Andrea
- Guessous, Idris
- Homuth, Georg
- Lind, Lars
- Magnusson, Patrik K.
- Mangino, Massimo
- Pedersen, Nancy L.
- Pietzner, Maik
- Suhre, Karsten
- Völzke, Henry
- Bochud, Murielle
- Spector, Tim D.
- Grabe, Hans J.
- Ingelsson, Erik
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-10-03
- Volume
- 25
- Issue
- 24
- Pages
- ddw334
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- OpenAlex
- W2527978307
- Cited by
- 175
- References
- 10
- Citations by year
- 2026: 2 · 2025: 20 · 2024: 29 · 2023: 31 · 2022: 19 · 2021: 18 · 2020: 16 · 2019: 10 · 2018: 22 · 2017: 8
- FWCI
- 10.79
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Human Molecular Genetics (publishedVersion)
- PubMed (publishedVersion)
- Archive ouverte UNIGE (University of Geneva) (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- BORIS (University Library Bern) (submittedVersion, other-oa)
- IRIS (submittedVersion)
- Site cant be reached (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Open Access CRIS of the University of Bern
- Funders
- National Science Foundation
- American Diabetes Association (7–13‐JF‐15)
- Northwestern University
- Qatar Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (124087)
- Bundesministerium für Bildung und Forschung (03ZIK012, 01ZZ0403, 01ZZ0103, 01ZZ9603)
- Universität Greifswald
- Weill Cornell Medical College
- Quest High Performance Computing
- Weill Cornell Medicine - Qatar
- Topics
- Health Sciences › Medicine › Pharmacology › Coffee research and impacts
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Keywords
- caffeine metabolism, caffeine metabolites, paraxanthine, theophylline, theobromine, genetic variants, CYP1A2, CYP2A6, AHR, CD83, coffee consumption, GCKR, ABCG2, POR, European ancestry
- MeSH terms
- CD83 Antigen, Caffeine, Coffee, Female, Humans, Immunoglobulins, Male, Membrane Glycoproteins, Theobromine, Theophylline, Antigens, CD, Receptors, Aryl Hydrocarbon, Cytochrome P-450 CYP1A2, Polymorphism, Single Nucleotide, White People, Basic Helix-Loop-Helix Transcription Factors, Basic Helix-Loop-Helix Proteins, Genome-Wide Association Study, Cytochrome P-450 CYP2A6
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