Investigating the genetic and causal relationship between initiation or use of alcohol, caffeine, cannabis and nicotine

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

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.

The impact of cannabis use on erectile dysfunction and sex hormones: a Mendelian randomization analysis

Previous study has highlighted an association between cannabis use (CU) and an increased risk of erectile dysfunction (ED), potentially due to indirect effects on sex hormonal balance. However, the evidence remains controversial, and the causal relationship is unclear. This study utilized genome-wide association study (GWAS) data to investigate the causal relationships between cannabis use disorder (CUD), lifetime cannabis use (LCU), and ED, as well as levels of sex hormones including estradiol (E2), bioavailable testosterone (BT), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) through Mendelian randomization (MR) analysis. The primary method of analysis was the inverse variance weighted (IVW) method. Data from the FinnGen and UK Biobank were used for replication and meta-analysis. The results indicated no causal relationship between genetically predicted CUD (OR = 0.97, 95% CI 0.87-1.10, P = 0.66) and LCU (OR = 1.13, 95% CI 0.84-1.50, P = 0.42) with the risk of ED. The meta-analysis provided consistent evidence (P > 0.05). No causal relationships were found between CUD and LCU with E2(CUD: β = 0.00, 95% CI 0.00-0.01, P = 0.37; LCU: β = 0.00, 95% CI -0.02-0.01, P = 0.62), BT (CUD: β = 0.00, 95% CI -0.03-0.02, P = 0.90; LCU: β = 0.02, 95% CI -0.04-0.09, P = 0.46), FSH (CUD: β = 0.01, 95% CI -0.18-0.20, P = 0.92; LCU: β = 0.01, 95% CI -0.44-0.47, P = 0.95), and LH (CUD: β = 0.01, 95% CI -0.18-0.21, P = 0.90; LCU: β = 0.13, 95% CI -0.22-0.49, P = 0.46). Sensitivity analyses detected no evidence of horizontal pleiotropy or heterogeneity, ensuring the robustness of the results. In conclusion, this MR analysis did not provide evidence supporting a causal relationship between CU and ED or sex hormone levels.

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.

The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond

Cannabis is among the most widely consumed psychoactive substances worldwide. Individual differences in cannabis use phenotypes can partly be explained by genetic differences. Technical and methodological advances have increased our understanding of the genetic aetiology of cannabis use. This narrative review discusses the genetic literature on cannabis use, covering twin, linkage, and candidate-gene studies, and the more recent genome-wide association studies (GWASs), as well as the interplay between genetic and environmental factors. Not only do we focus on the insights that these methods have provided on the genetic aetiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders. Twin studies have shown that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified, located in genes such as CADM2, FOXP2, and CHRNA2. Studies that applied multivariate methods (twin models, genetic correlation analysis, polygenic score analysis, genomic structural equation modelling, Mendelian randomisation) indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships (most convincingly for schizophrenia). We end our review by discussing implications of these findings and suggestions for future work.

Prevalence of caffeine consumers, daily caffeine consumption, and factors associated with caffeine use among active duty United States military personnel

Background

Although representative data on caffeine intake in Americans are available, these data do not include US service members (SMs). The few previous investigations in military personnel largely involve convenience samples. This cross-sectional study examined prevalence of caffeine consumers, daily caffeine consumption, and factors associated with caffeine use among United States active duty military service members (SMs).

Methods

A stratified random sample of SMs were asked to complete an on-line questionnaire on their personal characteristics and consumption of caffeinated products (exclusive of dietary supplements). Eighteen percent (n = 26,680) of successfully contacted SMs (n = 146,365) completed the questionnaire.

Results

Overall, 87% reported consuming caffeinated products ≥1 time/week. Mean ± standard error per-capita consumption (all participants) was 218 ± 2 and 167 ± 3 mg/day for men and women, respectively. Caffeine consumers ingested 243 ± 2 mg/day (251 ± 2 mg/day men, 195 ± 3 mg/day women). On a body-weight basis, men and women consumed respectively similar caffeine amounts (2.93 vs 2.85 mg/day/kg; p = 0.12). Among individual caffeinated products, coffee had the highest use (68%), followed by sodas (42%), teas (29%), energy drinks (29%) and gums/candy/medications (4%). In multivariable logistic regression, characteristics independently associated with caffeine use (≥1 time/week) included female gender, older age, white race/ethnicity, higher body mass index, tobacco use or former use, greater alcohol intake, and higher enlisted or officer rank.

Conclusion

Compared to National Health and Nutrition Examination Survey data, daily caffeine consumption (mg/day) by SMs was higher, perhaps reflecting higher mental and physical occupational demands on SMs.

Using Mendelian randomization to explore the gateway hypothesis: possible causal effects of smoking initiation and alcohol consumption on substance use outcomes

BACKGROUND AND AIMS

Initial use of drugs such as tobacco and alcohol may lead to subsequent more problematic drug use-the 'gateway' hypothesis. However, observed associations may be due to a shared underlying risk factor, such as trait impulsivity. We used bidirectional Mendelian randomization (MR) to test the gateway hypothesis.

DESIGN

Our main method was inverse-variance weighted (IVW) MR, with other methods included as sensitivity analyses (where consistent results across methods would raise confidence in our primary results). MR is a genetic instrumental variable approach used to support stronger causal inference in observational studies.

SETTING AND PARTICIPANTS

Genome-wide association summary data among European ancestry individuals for smoking initiation, alcoholic drinks per week, cannabis use and dependence, cocaine and opioid dependence (n = 1749-1 232 091).

MEASUREMENTS

Genetic variants for exposure.

FINDINGS

We found evidence of causal effects from smoking initiation to increased drinks per week [(IVW): β = 0.06; 95% confidence interval (CI) = 0.03-0.09; P = 9.44 × 10-06 ], cannabis use [IVW: odds ratio (OR) = 1.34; 95% CI = 1.24-1.44; P = 1.95 × 10-14 ] and cannabis dependence (IVW: OR = 1.68; 95% CI = 1.12-2.51; P = 0.01). We also found evidence of an effect of cannabis use on the increased likelihood of smoking initiation (IVW: OR = 1.39; 95% CI = 1.08-1.80; P = 0.01). We did not find evidence of an effect of drinks per week on other substance use outcomes, except weak evidence of an effect on cannabis use (IVW: OR = 0.55; 95% CI = 0.16-1.93; P-value = 0.35). We found weak evidence of an effect of opioid dependence on increased drinks per week (IVW: β = 0.002; 95% CI = 0.0005-0.003; P = 8.61 × 10-03 ).

CONCLUSIONS

Bidirectional Mendelian randomization testing of the gateway hypothesis reveals that smoking initiation may lead to increased alcohol consumption, cannabis use and cannabis dependence. Cannabis use may also lead to smoking initiation and opioid dependence to alcohol consumption. However, given that tobacco and alcohol use typically begin before other drug use, these results may reflect a shared risk factor or a bidirectional effect for cannabis use and opioid dependence.

Heritability of tea drinking and its relationship with cigarette smoking in the Chinese male adult twins

The aims of this study are to estimate the contributions of genetic factors to the variation of tea drinking and cigarette smoking, to examine the roles of genetic factors in their correlation and further to investigate underlying causation between them. We included 11 625 male twin pairs from the Chinese National Twin Registry (CNTR). Bivariate genetic modelling was fitted to explore the genetic influences on tea drinking, cigarette smoking and their correlation. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was further used to explore the causal relationship between them. We found that genetic factors explained 17% and 23% of the variation in tea drinking and cigarette smoking, respectively. A low phenotypic association between them was reported (r_ph  = 0.21, 95% confidence interval [CI]: [0.19, 0.24]), which was partly attributed to common genetic factors (r_A  = 0.45, 95% CI [0.19, 1.00]). In the ICE FALCON analysis with current smoking as the exposure, tea drinking was associated with his own (βself = 0.39, 95% CI [0.23, 0.55]) and his co-twin's smoking status (βco-twin = 0.25, 95% CI [0.10, 0.41]). Their association attenuated with borderline significance conditioning on his own smoking status (p = 0.045), indicating a suggestive causal effect of smoking status on tea drinking. On the contrary, when we used tea drinking as the predictor, we found familial confounding between them only. In conclusion, both tea drinking and cigarette smoking were influenced by genetic factors, and their correlation was partly explained by common genetic factors. In addition, our finding suggests that familial confounders account for the relationship between tea drinking and cigarette smoking. And current smoking might have a causal effect on weekly tea drinking, but not vice versa.

Shared Genetics and Causality Between Decaffeinated Coffee Consumption and Neuropsychiatric Diseases: A Large-Scale Genome-Wide Cross-Trait Analysis and Mendelian Randomization Analysis

Coffee or caffeine consumption has been associated with neuropsychiatric disorders, implying a shared etiology. However, whether these associations reflect causality remains largely unknown. To understand the genetic structure of the association between decaffeinated coffee consumption (DCC) and neuropsychiatric traits, we examined the genetic correlation, causality, and shared genetic structure between DCC and neuropsychiatric traits using linkage disequilibrium score regression, bidirectional Mendelian randomization (MR), and genome-wide cross-trait meta-analysis in large GWAS Consortia for coffee consumption (N = 329,671) and 13 neuropsychiatric traits (sample size ranges from 36,052 to 500,199). We found strong positive genetic correlations between DCC and lifetime cannabis use (LCU; Rg = 0.48, P = 8.40 × 10^-19), alcohol use disorder identification test (AUDIT) total score (AUDIT_T; Rg = 0.40, P = 4.63 × 10^-13), AUDIT_C score (alcohol consumption component of the AUDIT; Rg = 0.40, P = 5.26 × 10^-11), AUDIT_P score (dependence and hazardous-use component of the AUDIT; Rg = 0.28, P = 1.36 × 10^-05), and strong negative genetic correlations between DCC and neuroticism (Rg = -0.15, P = 7.27 × 10^-05), major depressed diseases (MDD; Rg = -0.15, P = 0.0010), and insomnia (Rg= -0.15, P = 0.0007). In the cross-trait meta-analysis, we identified 6, 5, 1, 1, 2, 31, and 27 shared loci between DCC and Insomnia, LCU, AUDIT_T, AUDIT_C, AUDIT_P, neuroticism, and MDD, respectively, which were mainly enriched in bone marrow, lymph node, cervix, uterine, lung, and thyroid gland tissues, T cell receptor signaling pathway, antigen receptor-mediated signaling pathway, and epigenetic pathways. A large of TWAS-significant associations were identified in tissues that are part of the nervous system, digestive system, and exo-/endocrine system. Our findings further indicated a causal influence of liability to DCC on LCU and low risk of MDD (odds ratio: 0.90, P = 9.06 × 10^-5 and 1.27, P = 7.63 × 10^-4 respectively). We also observed that AUDIT_T and AUDIT_C were causally related to DCC (odds ratio: 1.83 per 1-SD increase in AUDIT_T, P = 1.67 × 10^-05, 1.80 per 1-SD increase in AUDIT_C, P = 5.09 × 10^-04). Meanwhile, insomnia and MDD had a causal negative influence on DCC (OR: 0.91, 95% CI: 0.86-0.95, P = 1.51 × 10^-04 for Insomnia; OR: 0.93, 95% CI: 0.89-0.99, P = 6.02 × 10^-04 for MDD). These findings provided evidence for the shared genetic basis and causality between DCC and neuropsychiatric diseases, and advance our understanding of the shared genetic mechanisms underlying their associations, as well as assisting with making recommendations for clinical works or health education.

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.

Genome-Wide Association Study of Smoking Behavior Traits in a Chinese Han Population

Tobacco use is one of the leading causes of preventable disease worldwide. Genetic studies have elucidated numerous smoking-associated risk loci in American and European populations. However, genetic determinants for cigarette smoking in Chinese populations are under investigated. In this study, a whole-genome sequencing (WGS)-based genome-wide association study (GWAS) was performed in a Chinese Han population comprising 620 smokers and 564 nonsmokers. Thirteen single-nucleotide polymorphisms (SNPs) of the raftlin lipid linker 1 (RFTN1) gene achieved genome-wide significance levels (P < 5 x 10^-8) for smoking initiation. The rs139753473 from RFTN1 and six other suggestively significant loci from CUB and sushi multiple domains 1 (CSMD1) gene were also associated with cigarettes per day (CPD) in an independent Chinese sample consisting of 1,329 subjects (805 smokers and 524 nonsmokers). When treating males separately, associations between smoking initiation and PCAT5/ANKRD30A, two genes involved in cancer development, were identified and replicated. Within RFTN1, two haplotypes (i.e., C-A-C-G and A-G-T-C) formed by rs796812630-rs796584733-rs796349027-rs879511366 and three haplotypes (i.e., T-T-C-C-C, T-T-A-T-T, and C-A-A-T-T) formed by rs879401109-rs879453873-rs75180423-rs541378415-rs796757175 were strongly associated with smoking initiation. In addition, we also revealed two haplotypes (i.e., C-A-G-G and T-C-T-T derived from rs4875371-rs4875372-rs17070935-rs11991366) in the CSMD1 gene showing a significant association with smoking initiation. Further bioinformatics functional assessment suggested that RFTN1 may participate in smoking behavior through modulating immune responses or interactions with the glucocorticoid receptor alpha and the androgen receptor. Together, our results may help understand the mechanisms underlying smoking behavior in the Chinese Han population.