News Release

Is coffee good for you or bad for you?

When it comes to your genetics, the answer is complicated

Peer-Reviewed Publication

University of California - San Diego

Coffee drinking is a heritable habit, and one that carries a certain amount of genetic baggage.

Caffeinated coffee is a psychoactive substance, notes Sandra Sanchez-Roige, Ph.D., an associate professor in the University of California San Diego School of Medicine Department of Psychiatry. She is one of an international group of researchers that compared coffee-consumption characteristics from a 23andMe database with an even larger set of records in the United Kingdom. She is the corresponding author of a study recently published in the journal Neuropsychopharmacology.

Hayley H. A. Thorpe, Ph.D., is the lead author on the paper. Thorpe, of the Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry at Western University in Ontario, explained that the team collected genetic data as well as self-reported coffee-consumption numbers to assemble a genome-wide association study (GWAS). The idea was to make connections between the genes that were known to be associated with coffee consumption and the traits or conditions related to health.

“We used this data to identify regions on the genome associated with whether somebody is more or less likely to consume coffee,” Thorpe explained. “And then identify the genes and biology that could underlie coffee intake.”

Abraham Palmer, Ph.D., is also a lead researcher on the paper and a professor in the UC San Diego School of Medicine Department of Psychiatry. He said that most people are surprised that there is a genetic influence on coffee consumption. “We had good reason to suspect from earlier papers that there were genes that influence how much coffee someone consumes,” he said. “And so, we weren't surprised to find that in both of the cohorts we examined there was statistical evidence that this is a heritable trait. In other words, the particular gene variants that you inherit from your parents influence how much coffee you're likely to consume.”

Sanchez-Roige said the genetic influence on coffee consumption was the first of two questions the researchers wanted to address.

“The second is something that coffee lovers are really keen on learning,” Sanchez-Roige said. “Is drinking coffee good or bad? Is it associated with positive health outcomes or not?”

The answer is not definitive. The group’s genome-wide association study of 130,153 U.S.-based 23andMe research participants was compared with a similar UK Biobank database of 334,649 Britons, revealing consistent positive genetic associations between coffee and harmful health outcomes such as obesity and substance use. A positive genetic association is a connection between a specific gene variant (the genotype) and a specific condition (the phenotype). Conversely, a negative genetic association is an apparent protective quality discouraging the development of a condition. The findings get more complicated when it comes to psychiatric conditions.

“Look at the genetics of anxiety, for instance, or bipolar and depression: In the 23andMe data set, they tend to be positively genetically correlated with coffee intake genetics,” Thorpe said. “But then, in the UK Biobank, you see the opposite pattern, where they're negatively genetically correlated. This is not what we expected.”

She said there were other instances in which the 23andMe set didn’t align with the UK Biobank, but the greatest disagreement was in psychiatric conditions.

“It’s common to combine similar datasets in this field to increase study power. This information paints a fairly clear picture that combining these two datasets was really not a wise idea. And we didn't end up doing that,” Thorpe said. She explained that melding the databases might mask effects, leading researchers toward incorrect conclusions — or even cancelling each other out.

Sanchez-Roige says the researchers have some ideas about how the differences in results arose. To begin with, there was an apples-and-oranges aspect to the surveys. For instance, the 23andMe survey asked, “How many 5-ounce (cup-sized) servings of caffeinated coffee do you consume each day?” Compare it to the UK Biobank’s “How many cups of coffee do you drink each day? (Include decaffeinated coffee)”

Beyond serving size and the caffeinated/decaf divide, the surveys made no accommodation for the various ways coffee is served. “We know that in the U.K., they have generally higher preference for instant coffee, whereas ground coffee is more preferred in the U.S.,” Thorpe said.

“And then there’s the frappuccinos,” Sanchez-Roige added, citing the American trend of taking coffee loaded with sugary additives. Palmer mentioned other caffeinated drinks and especially in the context of the UK Biobank, tea, none of which were included in the GWAS, which addressed only coffee. Palmer added that the GWAS demonstrates the relationship between genotype and phenotype is more different than the relationship between coffee and tea.

“Genetics influences lots of things. For instance, it influences how tall you might be,” he said. “And those kinds of things probably would play out very similarly, whether you lived in the U.S. or the U.K. But coffee is a decision that people make.”

Sanchez-Roige pointed out that coffee comes in a variety of forms, from instant to frappuccino, and is consumed amid cultural norms that differ from place to place. A person with a given genotype might end up having quite a different phenotype living in the U.K. versus the U.S.

“And that's really what the data are telling us,” she said. “Because unlike height, where your behavior doesn't really have much to do with it, your behavior and the choices you're making in your environment play out in various ways. So the interaction between genotype and environment complicates the picture.”

The collaborators stressed the need for more investigation to unravel the relationships between genetics and the environment, focusing not only on coffee/caffeine intake but also other substance-use issues.

In addition to the researchers noted above, co-authors on the paper from UC San Diego are: Benjamin K. Pham, John J. Meredith, Mariela V. Jennings, Natasia S. Courchesne-Krak and Sevim B. Bianchi, all of the Department of Psychiatry. Other co-authors are Pierre Fontanillas, of 23andMe, Inc.; Laura Vilar-Ribó, of the Universitat Autònoma de Barcelona, Spain; Julian Mutz, of King's College London, U.K.; Sarah L. Elson and Jibran Y. Khokhar, of the University of Guelph, Canada; Abdel Abdellaoui, of the University of Amsterdam, The Netherlands; Lea K. Davis, of Vanderbilt University Medical Center; and the 23andMe Research Team.

Mariela V. Jennings, Sevim B. Bianchi and Sandra Sanchez-Roige are supported by funds from the California Tobacco-Related Disease Research Program (TRDRP; Grant Number T29KT0526 and T32IR5226). Sevim B. Bianchi and Abraham Palmer were also supported by P50DA037844. BKP, Julian Mutz, and Sandra Sanchez-Roige are supported by NIH/NIDA DP1DA054394. Hayley H. A .Thorpe is funded through a Natural Science and Engineering Research Council PGS-D scholarship and Canadian Institutes of Health Research (CIHR) Fellowship. Jibran Y. Khokhar is supported by a CIHR Canada Research Chair in Translational Neuropsychopharmacology. Lea K. Davis is supported by R01 MH113362. Natasia S. Courchesne-Krak is funded through an Interdisciplinary Research Fellowship in NeuroAIDs (Grant Number R25MH081482). Julian Mutz is funded by the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London.

The datasets used for the PheWAS and LabWAS analyses described were obtained from Vanderbilt University Medical Center’s BioVU which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH funded Shared Instrumentation Grant S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/. PheWAS and LabWAS analyses used CTSA (SD, Vanderbilt Resources). This project was supported by the National Center for Research Resources, Grant UL1 RR024975-01, and is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06.

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