Genetics and the environment determine your need for coffee

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Why do some people feel like they need three cups of coffee just to get through the day when others are happy with only one?

Why do some people abstain entirely?

New research suggests that our intake of coffee – the most popular beverage in America, above bottled water, sodas, tea, and beer – is affected by a positive feedback loop between genetics and the environment

This phenomenon, known as “quantile-specific heritability,” is also associated with cholesterol levels and body weight, and is thought to play a role in other human physiological and behavioral traits that defy simple explanation.

“It appears that environmental factors sort of set the groundwork in which your genes start to have an effect,” said Paul Williams, a statistician at Lawrence Berkeley National Laboratory (Berkeley Lab).

“So, if your surroundings predispose you to drinking more coffee – like your coworkers or spouse drink a lot, or you live in an area with a lot of cafes – then the genes you possess that predispose you to like coffee will have a bigger impact. These two effects are synergistic.”

Williams’ findings, published in the journal Behavioral Genetics, came from an analysis of 4,788 child-parent pairs and 2,380 siblings from the Framingham Study – a famous, ongoing study launched by the National Institutes of Health in 1948 to investigate how lifestyle and genetics affect rates of cardiovascular disease.

Participants, who are all related to an original group from Framingham, Massachusetts, submit detailed information about diet, exercise, medication use, and medical history every three to five years. Data from the study have been used in thousands of investigations into many facets of human health.

Williams used a statistical approach called quantile regression to calculate what proportion of participants’ coffee drinking could be explained by genetics – as the study follows families – and what must be influenced by external factors.

Past research shows that the most significant environmental factors influencing coffee drinking are culture and geographic location, age, sex, and whether or not one smokes tobacco; with older male smokers of European ancestry drinking the most, overall.

The analysis indicated that between 36% and 58% of coffee intake is genetically determined (although the exact causative genes remain unknown).

However, confirming Williams’ hypothesis that coffee drinking is a quantile-specific trait, the correlation between a parent’s coffee drinking and an offspring’s coffee-drinking got increasingly stronger for each offspring’s coffee consumption quantile, or bracket (for example, zero cups per day, one to two cups, two to four cups, and five or more cups).

“When we started to decode the human genome, we thought we’d be able to read the DNA and understand how genes translate into behavior, medical conditions, and such.

But that’s not the way it’s worked out,” said Williams, who is a staff scientist in Berkeley Lab’s Molecular Biophysics & Integrated Bioimaging (MBIB) Division.

“For many traits, like coffee drinking, we know that they have a strong genetic component – we’ve known coffee drinking runs in families since the 1960s.

But, when we actually start looking at the DNA itself, we usually find a very small percentage of the traits’ variation can be attributed to genes alone.”

The analysis indicated that between 36% and 58% of coffee intake is genetically determined (although the exact causative genes remain unknown).

The traditional assumption in genetic research has been that one’s surroundings and lifestyle alter gene expression levels in consistent and measurable ways, ultimately creating the outward manifestation – called a phenotype – of a trait.

Williams’ statistics work shows that the situation is more complex, which helps explain the diversity of traits we see in the real world.

MBIB Division Director Paul Adams commented, “Paul’s statistical studies complement the genomics research that Berkeley Lab bioscientists conduct to learn more about the relationship between genes and the environment.”

Next, Williams plans to assess whether quantile-specific heritability plays a role in alcohol consumption and pulmonary function.

“This is a whole new area of exploration that is just now opening up,” he said. “I think it will change, in a very fundamental way, how we think genes influence a person’s traits.”

Funding: This research was funded by a grant from the National Institute of Environmental Health Sciences and a gift from HOKA ONE ONE. The Framingham Study Data were made available through the Biologic Specimen and Data Repository Information Coordinating Center of the National Heart, Lung, and Blood Institute.


Coffee is the most widely consumed beverage in the world with known health benefits [1]. Besides caffeine (0.5–1.0% of green coffee beans) [2], a well-known CNS stimulant, coffee contains a very complex mixture of organic compounds, such as chlorogenic acids, caffeic acid, kahweol, trigonelline, and minerals. However, roasting coffee gives rise to more healthy compounds, known as quinolactones, as well as some other polycyclic aromatic hydrocarbons with carcinogenic effects [3].

Caffeine is primarily metabolized by human hepatic microsomal reaction of 3-demethylation, catalyzed by CYP1A2, which is responsible for approximately 95% of caffeine metabolism [4]. CYP1A2 DNA code is located at 15 q24 and exhibits polymorphism that can determine a decrease in the enzyme’s inducibility.

Individuals presenting with homozygous variant CYP1A2 (rs762551-C allele) are slow caffeine metabolizers, whereas individuals who are carriers of CYP1A2 (rs762551-A allele) are fast metabolizers [5,6].

In a previous pilot study, we aimed to determine if the genetic variability of caffeine metabolism could influence coffee consumption. The study showed that 8 out of 11 healthy volunteers (two samples were mishandled and were not tested) presented a fast metabolizer phenotype and displayed a large variability in their caffeine levels (0–0.67 mg/L).

One volunteer presented a slow metabolizer phenotype and the highest caffeine blood levels (1.1 mg/mL) [7]. The study confirmed the relationship between genotype/phenotype and blood levels of caffeine, as well as the prevalence of the fast metabolizer phenotype in the population (see column 1 for caffeine plasma levels and SNP # 9 for caffeine metabolism genotype on Figure 1). However, the study could not reach any conclusion about the relationship between genotype and coffee consumption due to the small sample size.

Figure 1. Genotypogram of coffee and caffeine consumption and related traits: 16 SNPs localized at five chromosomes, genotyped from 13 healthy volunteers.

Linked disequilibrium (LD) was first used in 1960 signifying the presence of non-random association of alleles at two or more loci in the same chromosome [8]. There are 3 possible genotypes: homozygote, homozygote-variant, and heterozygote, according with the predefined major and minor allele.

The ancestral allele is normally considered the major allele and the variant allele is considered the minor allele. The discovery of haplotype blocks, non-overlapping sets of loci in strong LD, led to a worldwide effort to identify SNPs in haplotype blocks in the human genome—the International HapMap Project.

The first trial identified over a million SNPs and the second generation characterized 3.1 millions of SNPs in the same original group of individuals [9]. Genomic Wide Association Studies (GWAS) test sets of SNPs associated with a specific condition comparing allele frequencies on affected and non-affected individuals [10].

Coffee Consumption is a very complex trait as it involves many sets of SNPs’ loci, in different chromosomes displaying increased or decreased inducibility in the phenotypic expression of various traits.Recently, The Coffee and Caffeine Genetics Consortium was created with the purpose of using genome-wide association studies (GWAS) to identify specific loci in the genome associated with coffee and caffeine consumption.

Their first results point to eight loci that show genome-wide significance. Six of these are located in or near genes potentially involved in the pharmacokinetics (ABCG2, AHR, POR, and CYP1A2) and pharmacodynamics of caffeine (BDNF and SLC6A4) [11]. Therefore, genetic factors could be a valuable tool to study the potential health effects of coffee by means of gene–environment interaction [12].

Another GWAS on coffee and caffeine consumption [7,11,13,14] identified SNPs at the aryl hydrocarbon receptor region (AHR) and between the CYP1A1 and CYP1A2 gene regions that present significant association with habitual caffeine and coffee consumption. According to Josse et al. [14,15], the 23-kbp segment between CYP1A1/CYP1A2 displays a SNP (rs2472297-T-allele) associated with increased caffeine intake.

They also found that this intergenic locus at 7 p21, which corresponds to the aryl hydrocarbon receptor (AHR), has a regulatory role in basal and substrate-induced expression of CYP1A1 and CYP1A2.

They concluded that it is possible that genotypes associated with increased CYP1A2 enzyme activity resulted in increased caffeine metabolism and possibly increased caffeine/coffee consumption.In addition, other studies [14,16] found significant evidence of association with coffee and caffeine consumption at NRCAM gene, which is implicated with addictive behavior and other independent hits such as CPLX3-ULK3 (caffeine and blood pressure), CSK-NCALD (addictive behavior), and CHRNA3 (lung cancer and smoking traits) regions.

The objective of the present study is to examine the relationship between 16 SNPs found to be significantly associated with coffee and caffeine consumption through GWAS within a small sample of volunteers.

Our hypothesis is that regular coffee consumers might display similar genotype patterns (positive or negative allele effect) for those sixteen SNPs and this could lead us to potential new targets to treat/prevent the various chronic disorders for which regular coffee consumption has preventive effects.


Source:
DOE/Lawrence Berkeley National Laboratory

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