Does coffee consumption impact on heaviness of smoking?

Association between caffeine intake and fat free mass index: a retrospective cohort study

BACKGROUND

Caffeine, identified as a central nervous system stimulant in foods, beverages (coffee, tea, chocolate), and medications, has been focused on its ergogenic properties, enhancing physical performance. The aim of this study was to investigate the association between the caffeine intake (from coffee) and fat-free mass index (FFMI).

MATERIALS AND METHODS

We carried out a cohort study that included 3,466 women and 3,145 men aged ≥20 years who were intaking caffeine. Caffeine intake from coffee were obtained from two 24-hour dietary recall interviews. The FFMI was calculated as FFM (kg) divided by height in m2. The caffeine intake was classified into quartiles and combined into 4 groups. Multiple linear regression model analysis and multiple logistic regression model analysis were used to assess associations between the caffeine and FFMI adjusted for potential confounders.

RESULTS

Among the 2,427 participants, males accounted for 52.4%, and females 47.6%. In multiple linear regression model, Model 1 (unadjusted Model (p = 0.041)) and Model 2 (adjusted for age, race, and BMI (p = 0.006)) in women showed a significant relationship between caffeine intake and FFMI. In multivariable models, caffeine intake and FFMI were significantly different (p < 0.05). In sex subgroups, among females, each quartile of caffeine intake was positively correlated with FFMI levels in the average FFMI group in Model 3 (p < 0.001). In age subgroups, each quartile of caffeine intake was positively correlated with FFMI levels in the average FFMI group in Model 3 for individuals aged 20-40 (p = 0.039) and those aged above 40 (p = 0.016). In drinking status subgroups, if they drunk alcohol, each quartile was positively correlated with FFMI levels in the average FFMI group in Model 3 (p < 0.001).

CONCLUSION

Caffeine intake was mainly positively associated with FFMI, especially in women with above levels of FFMI. Longitudinal studies and randomized controlled trials are needed to establish causality and provide evidence-based recommendations regarding caffeine intake to optimize muscle health.

Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.

Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.

Metabolites Associated with Coffee Consumption and Incident Chronic Kidney Disease

BACKGROUND AND OBJECTIVES

Moderate coffee consumption has been associated with lower risk of CKD; however, the exact biologic mechanisms underlying this association are unknown. Metabolomic profiling may identify metabolic pathways that explain the association between coffee and CKD. The goal of this study was to identify serum metabolites associated with coffee consumption and examine the association between these coffee-associated metabolites and incident CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using multivariable linear regression, we identified coffee-associated metabolites among 372 serum metabolites available in two subsamples of the Atherosclerosis Risk in Communities study (ARIC; n=3811). Fixed effects meta-analysis was used to pool the results from the two ARIC study subsamples. Associations between coffee and metabolites were replicated in the Bogalusa Heart Study (n=1043). Metabolites with significant associations with coffee in both cohorts were then evaluated for their prospective associations with incident CKD in the ARIC study using Cox proportional hazards regression.

RESULTS

In the ARIC study, mean (SD) age was 54 (6) years, 56% were daily coffee drinkers, and 32% drank >2 cups per day. In the Bogalusa Heart Study, mean (SD) age was 48 (5) years, 57% were daily coffee drinkers, and 38% drank >2 cups per day. In a meta-analysis of two subsamples of the ARIC study, 41 metabolites were associated with coffee consumption, of which 20 metabolites replicated in the Bogalusa Heart Study. Three of these 20 coffee-associated metabolites were associated with incident CKD in the ARIC study.

CONCLUSIONS

We detected 20 unique serum metabolites associated with coffee consumption in both the ARIC study and the Bogalusa Heart Study, and three of these 20 candidate biomarkers of coffee consumption were associated with incident CKD. One metabolite (glycochenodeoxycholate), a lipid involved in primary bile acid metabolism, may contribute to the favorable kidney health outcomes associated with coffee consumption. Two metabolites (O-methylcatechol sulfate and 3-methyl catechol sulfate), both of which are xenobiotics involved in benzoate metabolism, may represent potential harmful aspects of coffee on kidney health.

Causal relationship from coffee consumption to diseases and mortality: a review of observational and Mendelian randomization studies including cardiometabolic diseases, cancer, gallstones and other diseases

PURPOSE

High coffee consumption is associated with low risk of mortality and morbidity, but the causality remains unclear. This review aims to discuss findings from observational studies on coffee consumption in context of Mendelian randomization studies.

METHODS

The PubMed database was searched for all Mendelian randomization studies on coffee consumption and corresponding observational studies.

RESULTS

High coffee consumption is associated with low risk of all-cause and cardiovascular mortality in observational studies (HRs of 0.85-0.90 vs. no/low consumers), with no support of causality in Mendelian randomization studies. Moderate/high consumption is associated with low risk of cardiometabolic diseases, including ischemic heart disease (HRs of 0.85-0.90 vs. no/low consumption), stroke (HRs of approximately 0.80 vs. no/low consumption), type 2 diabetes (HRs of approximately 0.70 vs. no/low consumption) and obesity in observational studies, but not in Mendelian randomization studies. High consumption is associated with low risk of endometrial cancer and melanoma and high risk of lung cancer in observational studies, but with high risk of colorectal cancer in Mendelian randomization studies. In observational and Mendelian randomization studies, high coffee consumption is associated with low risk of gallstones (HRs of 0.55-0.70 for high vs. no/low self-reported and 0.81 (0.69-0.96) for highest vs. lowest genetic consumption).

CONCLUSION

High coffee consumption is associated with low risk of mortality, cardiometabolic diseases, some cancers and gallstones in observational studies, with no evidence to support causality from Mendelian randomization studies for most diseases except gallstones.

Metabolites, Nutrients, and Lifestyle Factors in Relation to Coffee Consumption: An Environment-Wide Association Study

Coffee consumption has been inversely associated with various diseases; however, the underlying mechanisms are not entirely clear. We used data of 17,752 Third National Health and Nutrition Examination Survey participants to investigate the association of 245 metabolites, nutrients, and lifestyle factors with coffee consumption. We used data from the first phase (n = 8825) to identify factors with a false discovery rate of <5%. We then replicated our results using data from the second phase (n = 8927). Regular coffee consumption was positively associated with active and passive smoking, serum lead and urinary cadmium concentrations, dietary intake of potassium and magnesium, and aspirin intake. In contrast, regular coffee consumption was inversely associated with serum folate and red blood cell folate levels, serum vitamin E and C, and beta-cryptoxanthin concentrations, Healthy Eating Index score, and total serum bilirubin. Most of the aforementioned associations were also observed for caffeinated beverage intake. In our assessment of the association between coffee consumption and selected metabolites, nutrients, and lifestyle factors, we observed that regular coffee and caffeinated beverage consumption was strongly associated with smoking, serum lead levels, and poorer dietary habits.

Inferring the direction of a causal link and estimating its effect via a Bayesian Mendelian randomization approach

The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or health-related outcome from observational data. Instrumental variables must satisfy strong, often untestable assumptions, which means that finding good genetic instruments among a large list of potential candidates is challenging. This difficulty is compounded by the fact that many genetic variants influence more than one phenotype through different causal pathways, a phenomenon called horizontal pleiotropy. This leads to errors not only in estimating the magnitude of the causal effect but also in inferring the direction of the putative causal link. In this paper, we propose a Bayesian approach called BayesMR that is a generalization of the Mendelian randomization technique in which we allow for pleiotropic effects and, crucially, for the possibility of reverse causation. The output of the method is a posterior distribution over the target causal effect, which provides an immediate and easily interpretable measure of the uncertainty in the estimation. More importantly, we use Bayesian model averaging to determine how much more likely the inferred direction is relative to the reverse direction.

Genetic determinants of beverage consumption: Implications for nutrition and health

Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.

Mendelian Randomization Studies of Coffee and Caffeine Consumption

Habitual coffee and caffeine consumption has been reported to be associated with numerous health outcomes. This perspective focuses on Mendelian Randomization (MR) approaches for determining whether such associations are causal. Genetic instruments for coffee and caffeine consumption are described, along with key concepts of MR and particular challenges when applying this approach to studies of coffee and caffeine. To date, at least fifteen MR studies have investigated the causal role of coffee or caffeine use on risk of type 2 diabetes, cardiovascular disease, Alzheimer's disease, Parkinson's disease, gout, osteoarthritis, cancers, sleep disturbances and other substance use. Most studies provide no consistent support for a causal role of coffee or caffeine on these health outcomes. Common study limitations include low statistical power, potential pleiotropy, and risk of collider bias. As a result, in many cases a causal role cannot confidently be ruled out. Conceptual challenges also arise from the different aspects of coffee and caffeine use captured by current genetic instruments. Nevertheless, with continued genome-wide searches for coffee and caffeine related loci along with advanced statistical methods and MR designs, MR promises to be a valuable approach to understanding the causal impact that coffee and caffeine have in human health.

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study

BACKGROUND AND AIMS

Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use.

METHODS

Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy.

RESULTS

Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing.

CONCLUSIONS

Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use.

Coffee consumption, metabolic syndrome and clinical severity of psoriasis: good or bad stuff?

Despite the wide consumption of coffee, its anti-inflammatory effect on clinical severity of psoriasis is still debatable. The aim of this study was to evaluate the association between the coffee consumption and clinical severity of psoriasis in a sample of patients stratified according to the presence of the metabolic syndrome (MetS) and smoking. This cross-sectional case-control observational study was conducted on 221 treatment-naïve psoriatic patients. Lifestyle habits, anthropometric measures, clinical and biochemical evaluations were obtained. Clinical severity of psoriasis was assessed by Psoriasis Area and Severity Index (PASI) score. Data on energy caloric intake and coffee consumption were collected using a 7-day food diary record. The coffee consumption was analyzed as coffee intake (consumers and non-consumers) and daily servings (range 0-4 servings/day). Coffee consumers have a lower PASI score vs non-consumers (p < 0.001). The lowest PASI score and MetS prevalence were found in patients consuming 3 cups of coffee/day (p < 0.001), which was also the most common daily serving (34.8%), whereas the highest PASI score was found among those drinking ≥ 4 cups/day. Grouping the case patients according to smoking and MetS, the best odds of PASI score was observed in those drinking 3 cups of coffee per day and no smokers, after adjusting for total energy intake (OR 74.8; p < 0.001). As a novel finding, we reported a negative association between coffee intake, MetS prevalence and clinical severity of psoriasis. The evaluation of the anti-inflammatory effect of coffee on clinical severity of psoriasis, whose metabolic risk increases along with its clinical severity, could be of great importance from a public health perspective.

Variation in CYP2A6 Activity and Personalized Medicine

The cytochrome P450 2A6 (CYP2A6) enzyme metabolizes several clinically relevant substrates, including nicotine-the primary psychoactive component in cigarette smoke. The gene that encodes the CYP2A6 enzyme is highly polymorphic, resulting in extensive interindividual variation in CYP2A6 enzyme activity and the rate of metabolism of nicotine and other CYP2A6 substrates including cotinine, tegafur, letrozole, efavirenz, valproic acid, pilocarpine, artemisinin, artesunate, SM-12502, caffeine, and tyrosol. CYP2A6 expression and activity are also impacted by non-genetic factors, including induction or inhibition by pharmacological, endogenous, and dietary substances, as well as age-related changes, or interactions with other hepatic enzymes, co-enzymes, and co-factors. As variation in CYP2A6 activity is associated with smoking behavior, smoking cessation, tobacco-related lung cancer risk, and with altered metabolism and resulting clinical responses for several therapeutics, CYP2A6 expression and enzyme activity is an important clinical consideration. This review will discuss sources of variation in CYP2A6 enzyme activity, with a focus on the impact of CYP2A6 genetic variation on metabolism of the CYP2A6 substrates.

Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis

Background

There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake.

Methods

We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.

Results

Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.

Conclusions

Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

Does coffee consumption impact on heaviness of smoking?

BACKGROUND AND AIMS

Coffee consumption and cigarette smoking are strongly associated, but whether this association is causal remains unclear. We sought to: (1) determine whether coffee consumption influences cigarette smoking causally, (2) estimate the magnitude of any association and (3) explore potential mechanisms.

DESIGN

We used Mendelian randomization (MR) analyses of observational data, using publicly available summarized data from the Tobacco and Genetics (TAG) consortium, individual-level data from the UK Biobank and in-vitro experiments of candidate compounds.

SETTING

The TAG consortium includes data from studies in several countries. The UK Biobank includes data from men and women recruited across England, Wales and Scotland.

PARTICIPANTS

The TAG consortium provided data on n ≤ 38 181 participants. The UK Biobank provided data on 8072 participants.

MEASUREMENTS

In MR analyses, the exposure was coffee consumption (cups/day) and the outcome was heaviness of smoking (cigarettes/day). In our in-vitro experiments we assessed the effect of caffeic acid, quercetin and p-coumaric acid on the rate of nicotine metabolism in human liver microsomes and cDNA-expressed human CYP2A6.

FINDINGS

Two-sample MR analyses of TAG consortium data indicated that heavier coffee consumption might lead to reduced heaviness of smoking [beta = -1.49, 95% confidence interval (CI) = -2.88 to -0.09]. However, in-vitro experiments found that the compounds investigated are unlikely to inhibit significantly the rate of nicotine metabolism following coffee consumption. Further MR analyses in UK Biobank found no evidence of a causal relationship between coffee consumption and heaviness of smoking (beta = 0.20, 95% CI = -1.72 to 2.12).

CONCLUSIONS

Amount of coffee consumption is unlikely to have a major causal impact upon amount of cigarette smoking. If it does influence smoking, this is not likely to operate via effects of caffeic acid, quercetin or p-coumaric acid on nicotine metabolism. The observational association between coffee consumption and cigarette smoking may be due to smoking impacting on coffee consumption or confounding.