Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40–48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13–20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10−8) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.
AimsTo investigate the relationship between cannabis and tobacco use by age 15 and subsequent educational outcomes.DesignBirth cohort study.SettingEngland.ParticipantsThe sample was drawn from the Avon Longitudinal Study of Parents and Children; a core sample of 1155 individuals had complete information on all the variables.MeasurementsThe main exposures were cannabis and tobacco use at age 15 assessed in clinic by computer‐assisted questionnaire and serum cotinine. The main outcomes were performance in standardized assessments at 16 [Key Stage 4, General Certificate of Secondary Education (GCSE)] in English and mathematics (mean scores), completion of five or more assessments at grade C level or higher and leaving school having achieved no qualifications. Analyses were sequentially adjusted for multiple covariates using a hierarchical approach. Covariates considered were: maternal substance use (ever tobacco or cannabis use, alcohol use above recommended limits); life course socio‐economic position (family occupational class, maternal education, family income); child sex; month and year of birth; child educational attainment prior to age 11 (Key Stage 2); child substance use (tobacco, alcohol and cannabis) prior to age 15 and child conduct disorder.FindingsIn fully adjusted models both cannabis and tobacco use at age 15 were associated with subsequent adverse educational outcomes. In general, the dose–response effect seen was consistent across all educational outcomes assessed. Weekly cannabis use was associated negatively with English GCSE results [grade point difference (GPD), –5.93, 95% confidence interval (CI) = –8.34, –3.53] and with mathematics GCSE results (GPD, –6.91, 95% CI = –9.92, –3.89). Daily tobacco smoking was associated negatively with English GCSE (GPD, –11.90, 95% CI = –13.47, –10.33) and with mathematics GCSE (GPD, –16.72, 95% CI = –18.57, –14.86). The greatest attenuation of these effects was seen on adjustment for other substance use and conduct disorder. Following adjustment, tobacco appeared to have a consistently stronger effect than cannabis.ConclusionsBoth cannabis and tobacco use in adolescence are associated strongly with subsequent adverse educational outcomes. Given the non‐specific patterns of association seen and the attenuation of estimates on adjustment, it is possible that these effects arise through non‐causal mechanisms, although a causal explanation cannot be discounted. © 2015 Society for the Study of Addiction
Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10−10 for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.
Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD dependent on diabetic or smoking status. Results: We identified 5 genome-wide significant ( P association ≤5×10 −8 ) associations with PAD in 449 548 (N cases =12 086) individuals of European ancestry near LPA , CDKN2BAS1 , SH2B3-PTPN11 , HDAC9 , and CHRNA5 loci (which overlapped previously reported associations). Meta-analysis with variants previously association with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32–1.74], P diabetes =2.5×10 −9 , P interactionwithdiabetes =5.3×10 −7 ). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11–1.19], P smokers =9.3×10 −10 , P interactionwithsmoking =3.9×10 −5 ). Conclusions: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.
Introduction:Our aim was to understand the strength of association between parental smoking and child environmental tobacco smoke (ETS) exposure in order to inform the development of future tobacco control policies. ETS was measured using child cotinine levels below the active smoking threshold. Methods:Participants were drawn from the Avon Longitudinal Study of Parents and Children and included 3,128 participants at age 7 years and 1,868 participants at age 15 years. The primary outcome was cotinine levels of nonsmoking children, to investigate the relationship between maternal smoking and child cotinine levels. The secondary outcome was cotinine levels of all individuals to investigate the relationship between child smoking and child cotinine levels. Maternal and child smoking behavior was assessed by self-report questionnaire. We adjusted for several sociodemographic variables.Results:We found an association between maternal smoking and child cotinine at age 7 years (mean cotinine = 1.16ng/ml serum, ratio of geometric means = 3.94, 95% CI = 2.86–5.42) and at age 15 years (mean cotinine = 0.94ng/ml serum, ratio of geometric means = 5.26, 95% CI = 3.06–9.03), after adjustment for potential confounders. Conclusions:The magnitude of this association for children whose mothers were heavy smokers was comparable with the quantity of half the levels of cotinine observed among children who were irregular (i.e., nonweekly) active smokers, and it was greater than five times higher than that seen in nonsmoking children whose mothers didn’t smoke. This provides further evidence for the importance of public health interventions to reduce smoking exposure in the home.
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