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Background Longitudinal studies enhance understanding of the complex reciprocal relationship between smoking and depression from adolescence to young adulthood. Examining bi-directional associations between cigarette smoking and depressive symptoms in a genetically informative twin design can help to understand whether the associations are independent of shared genetic and environmental factors. Methods We analyzed longitudinal data on smoking and depressive symptoms in twins participating in the adolescent (mean age 17.5) and young adult (mean age 21.9) surveys of the FinnTwin12 study (maximum N = 2,954 individuals; 1,154 twin pairs). At both waves, self-reported depressive symptoms, assessed with the 10-item version of the General Behavior Inventory (GBI), and smoking status were analyzed. The bi-directional associations were first studied among individuals and then within monozygotic and dizygotic twin pairs. Results When adjusted for multiple covariates and baseline depressive symptoms, daily smokers at age 17 had higher depressive symptom scores at age 22 than never smokers (Incidence Rate Ratio = 1.17, 95% CI: 1.03–1.33). Similarly, when adjusted for covariates and baseline smoking, higher score in GBI at age 17 was associated with an increased likelihood of being a non-daily (Relative Risk Ratio (RRR) = 1.06, 95% CI: 1.01–1.11) or daily (RRR = 1.05, 95% CI: 1.00–1.10) smoker at age 22. No associations were found in within-pair analyses, suggesting that the individual-level association is explained by shared familial liabilities. Conclusion During the developmental period from adolescence to adulthood, cigarette smoking and depressive symptoms are reciprocally associated. However, these associations are confounded by shared genetic and other familial liabilities.

Longitudinal, genetically informative studies of the association between cigarette smoking and depressive symptoms among adolescents are limited. We examined the longitudinal association of cigarette smoking with subsequent depressive symptoms during adolescence in a Finnish twin cohort. We used prospective data from the population-based FinnTwin12 study (maximum N = 4152 individuals, 1910 twin pairs). Current smoking status and a number of lifetime cigarettes smoked were assessed at the age of 14 and depressive symptoms at the age of 17. Negative binomial regression was conducted to model the association between smoking behavior and subsequent depressive symptoms among individuals, and within-pair analyses were conducted to control for unmeasured familial confounding. Analyses were adjusted for age, sex, school grades, drinking alcohol to intoxication, health status, family structure, parental education, and smoking, as well as for pre-existing depressiveness. The results of the individual-level analyses showed that cigarette smoking at the age of 14 predicted depressive symptoms at the age of 17. Compared to never smokers, those who had smoked over 50 cigarettes (incidence rate ratio, IRR = 1.43, 95% CI 1.28–1.60) and regular smokers (IRR = 1.46, 95% CI 1.32–1.62) had higher depression scores. The associations were attenuated when adjusted for measured covariates and further reduced in within-pair analyses. In the within-pair results, the estimates were lower within monozygotic (MZ) pairs compared to dizygotic (DZ) pairs, suggesting that shared genetic factors contribute to the associations observed in individual-based analyses. Thus, we conclude that cigarette smoking is associated with subsequent depressive symptoms during adolescence, but the association is not independent of measured confounding factors and shared genetic influences. Electronic supplementary material The online version of this article (10.1007/s11121-019-01020-6) contains supplementary material, which is available to authorized users.

The older Finnish Twin Cohort (FTC) was established in 1974. The baseline survey was in 1975, with two follow-up health surveys in 1981 and 1990. The fourth wave of assessments was done in three parts, with a questionnaire study of twins born during 1945–1957 in 2011–2012, while older twins were interviewed and screened for dementia in two time periods, between 1999 and 2007 for twins born before 1938 and between 2013 and 2017 for twins born in 1938–1944. The content of these wave 4 assessments is described and some initial results are described. In addition, we have invited twin-pairs, based on response to the cohortwide surveys, to participate in detailed in-person studies; these are described briefly together with key results. We also review other projects based on the older FTC and provide information on the biobanking of biosamples and related phenotypes.

The heritability of nicotine dependence based on family studies is substantial. Nevertheless, knowledge of the underlying genetic architecture remains meager. Our aim was to identify novel genetic variants responsible for interindividual differences in smoking behavior. We performed a genome-wide association study on 1715 ever smokers ascertained from the population-based Finnish Twin Cohort enriched for heavy smoking. Data imputation used the 1000 Genomes Phase I reference panel together with a whole genome sequence-based Finnish reference panel. We analyzed three measures of nicotine addiction-smoking quantity, nicotine dependence and nicotine withdrawal. We annotated all genome-wide significant SNPs for their functional potential. First, we detected genome-wide significant association on 16p12 with smoking quantity (P = 8.5 x 10(-9)), near CLEC19A. The lead-SNP stands 22 kb from a binding site for NF-kappa B transcription factors, which play a role in the neurotrophin signaling pathway. However, the signal was not replicated in an independent Finnish population-based sample, FINRISK (n = 6763). Second, nicotine withdrawal showed association on 2q21 in an intron of TMEM163 (P = 2.1 x 10(-9)), and on 11p15 (P = 6.6 x 10(-8)) in an intron of AP2A2, and P = 4.2 x 10(-7) for a missense variant in MUC6, both involved in the neurotrophin signaling pathway). Third, association was detected on 3p22.3 for maximum number of cigarettes smoked per day (P = 3.1 x 10(-8)) near STAC. Associating CLEC19A and TMEM163 SNPs were annotated to influence gene expression or methylation. The neurotrophin signaling pathway has previously been associated with smoking behavior. Our findings further support the role in nicotine addiction.

Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on the rate of nicotine metabolism. Our objective was to use nicotine metabolite ratio (NMR), an established biomarker of nicotine metabolism rate, in a genome-wide association study (GWAS) to identify novel genetic variants influencing nicotine metabolism. A heritability estimate of 0.81 (95% CI 0.70–0.88) was obtained for NMR using monozygotic and dizygotic twins of the FinnTwin cohort. We performed a GWAS in cotinine-verified current smokers of three Finnish cohorts (FinnTwin, Young Finns Study, FINRISK2007), followed by a meta-analysis of 1518 subjects, and annotated the genome-wide significant SNPs with methylation quantitative loci (meQTL) analyses. We detected association on 19q13 with 719 SNPs exceeding genome-wide significance within a 4.2 Mb region. The strongest evidence for association emerged for CYP2A6 (min p = 5.77E-86, in intron 4), the main metabolic enzyme for nicotine. Other interesting genes with genome-wide significant signals included CYP2B6, CYP2A7, EGLN2, and NUMBL. Conditional analyses revealed three independent signals on 19q13, all located within or in the immediate vicinity of CYP2A6. A genetic risk score constructed using the independent signals showed association with smoking quantity (p = 0.0019) in two independent Finnish samples. Our meQTL results showed that methylation values of 16 CpG sites within the region are affected by genotypes of the genome-wide significant SNPs, and according to causal inference test, for some of the SNPs the effect on NMR is mediated through methylation. To our knowledge, this is the first GWAS on NMR. Our results enclose three independent novel signals on 19q13.2. The detected CYP2A6 variants explain a strikingly large fraction of variance (up to 31%) in NMR in these study samples. Further, we provide evidence for plausible epigenetic mechanisms influencing NMR., Author Summary Nicotine metabolism rate significantly varies between individuals and affects smoking behavior. Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on nicotine metabolism rate. Twin and family studies have shown that genes influence nicotine metabolism; however, only a minor fraction of variance in inter-individual differences in nicotine metabolism is accounted for by known reduced activity variants in CYP2A6, the main metabolic enzyme for nicotine. Here we utilized a biomarker of nicotine metabolism (nicotine metabolite ratio, NMR) in a genome-wide association study of three Finnish cohorts to identify novel genetic variants influencing nicotine metabolism rate. Our results enclose three independent novel signals in CYP2A6. The detected variants explain a strikingly large fraction of variance (up to 31%) in NMR in the study samples. A genetic risk score constructed using the independent signals predicts smoking quantity in two independent Finnish samples. Further, we enclose evidence for plausible epigenetic mechanisms influencing NMR. With the advent of other nicotine delivery devices than tobacco, such as e-cigarettes, the need to understand the long-term consequences and action mechanisms of nicotine and its metabolism are of high public health relevance.