Limited psychological and social effects of lifetime cannabis use frequency: Evidence from a 30-year community study of 4,078 twins.

BACKGROUND: Cannabis use is associated with outcomes like income, legal problems, and psychopathology. This finding rests largely on correlational research designs, which rely at best on statistical controls for confounding. Here, we control for unmeasured confounders using a longitudinal study of twins. METHOD: In a sample of 4,078 American adult twins first assessed decades ago, we used cotwin control mixed effects models to evaluate the effect of lifetime average frequency of cannabis consumption measured on substance use, psychiatric, and psychosocial outcomes. RESULTS: On average, participants had a lifetime cannabis frequency of about one to two times per month, across adolescence and adulthood. As expected, in individual-level analyses, cannabis use was significantly associated with almost all outcomes in the expected directions. However, when comparing each twin to their cotwin, which inherently controls for shared genes and environments, we observed within-pair differences consistent with possible causality in three of the 22 assessed outcomes: cannabis use disorder symptoms (ßW-Pooled = .15, SE = .02, p = 1.7 × 10-22), frequency of tobacco use (ßW-Pooled = .06, SE = .01, p = 1.2 × 10-5), and illicit drug involvement (ßW-Pooled = .06, SE = .02, p = 1.2 × 10-4). Covariate specification curve analyses indicated that within-pair effects on tobacco and illicit drug use, but not cannabis use disorder, attenuated substantially when covarying for lifetime alcohol and tobacco use. CONCLUSIONS: The cotwin control results suggest that more frequent cannabis use causes small increases in cannabis use disorder symptoms, approximately 1.3 symptoms when going from a once-a-year use to daily use. For other outcomes, our results are more consistent with familial confounding, at least in this community population of twins. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating substance use outcomes of recreational cannabis legalization using a unique co-twin control design.

Background: As more states pass recreational cannabis legalization (RCL), we must understand how RCL affects substance use.Objectives: The current study aims to examine the effect of RCL on lifetime and past-year use of cannabis, alcohol, tobacco, and other drugs, frequency of cannabis, alcohol, and tobacco use, co-use of cannabis with alcohol and tobacco, and consequences from cannabis and alcohol use.Methods: We used a unique, co-twin control design of twin pairs who were discordant for living in a state with RCL between 2018 and 2021. The sample consisted of 3,830 adult twins (41% male), including 232 twin pairs discordant for RCL. Problems from alcohol and cannabis use were assessed via the Brief Marijuana Consequences Questionnaire and the Brief Young Adult Alcohol Consequences Questionnaire.Results: Results indicated that the twin living in an RCL state was more likely to endorse past-year cannabis use (OR = 1.56, p = .009), greater number of cannabis use days in the past 6 months (ß = 0.47, p = .019), but not more negative consequences from cannabis use (ß = 0.21, p = .456) compared to their co-twin in a non-RCL state. There were no differences within-twin pairs in frequency of alcohol use (ß=-0.05, p = .601), but the RCL twin reported fewer negative consequences from alcohol use (ß=-0.29, p = .016) compared to their co-twin in a non-RCL state. We did not observe any other differences within-twin pairs on other outcomes.Conclusion: These results suggest that living in an RCL state is associated with greater cannabis frequency but not more negative consequences from cannabis use than living in a non-RCL state.

Associations between polygenic risk of substance use and use disorder and alcohol, cannabis, and nicotine use in adolescence and young adulthood in a longitudinal twin study.

BACKGROUND: Recent well-powered genome-wide association studies have enhanced prediction of substance use outcomes via polygenic scores (PGSs). Here, we test (1) whether these scores contribute to prediction over-and-above family history, (2) the extent to which PGS prediction reflects inherited genetic variation v. demography (population stratification and assortative mating) and indirect genetic effects of parents (genetic nurture), and (3) whether PGS prediction is mediated by behavioral disinhibition prior to substance use onset. METHODS: PGSs for alcohol, cannabis, and nicotine use/use disorder were calculated for Minnesota Twin Family Study participants (N = 2483, 1565 monozygotic/918 dizygotic). Twins' parents were assessed for histories of substance use disorder. Twins were assessed for behavioral disinhibition at age 11 and substance use from ages 14 to 24. PGS prediction of substance use was examined using linear mixed-effects, within-twin pair, and structural equation models. RESULTS: Nearly all PGS measures were associated with multiple types of substance use independently of family history. However, most within-pair PGS prediction estimates were substantially smaller than the corresponding between-pair estimates, suggesting that prediction is driven in part by demography and indirect genetic effects of parents. Path analyses indicated the effects of both PGSs and family history on substance use were mediated via disinhibition in preadolescence. CONCLUSIONS: PGSs capturing risk of substance use and use disorder can be combined with family history measures to augment prediction of substance use outcomes. Results highlight indirect sources of genetic associations and preadolescent elevations in behavioral disinhibition as two routes through which these scores may relate to substance use.

Impacts of recreational cannabis legalization on cannabis use: a longitudinal discordant twin study.

AIMS: To estimate the effect of recreational legalization on cannabis use frequency and sources of variance across legal environments. DESIGN: Longitudinal discordant twin and gene-environment interaction models in twins recruited from birth records and assessed prospectively. SETTING: The United States, including states with different recreational cannabis policies before and after 2014, when recreational cannabis was first legalized. PARTICIPANTS: Two longitudinal, prospectively assessed samples of American twins aged 24-47 (n = 1425 in legal states, n = 1996 in illegal states), including 111 monozygotic pairs discordant for residence. MEASUREMENTS: Current cannabis use frequency (measured continuously and ordinally) was the primary outcome, and the predictor was recreational status of cannabis (legal/illegal) in the participant's state of residence at the time of assessment. Covariates include age, sex and cannabis use frequency prior to 2014. FINDINGS: Accounting for pre-2014 use, residents of legal states used cannabis more frequently than residents of illegal states (b = 0.21, P = 8.08 × 10-5 ). Comparing 111 pairs of monozygotic twins discordant for residence confirmed the effect (b = 0.18, P = 0.014). There was inconclusive evidence for genetic influences on cannabis use frequency that were specific to the legal environment [χ2  = 2.9 × 10-9 , degrees of freedom (d.f.) = 1, P > 0.999]. Existing genetic influences were moderated by the legal environment, as the genetic correlation between marijuana use before and after legalization was lower in states that legalized (rgenetic  = 0.24) compared with states that did not (rgenetic  = 0.78, Pdifference  = 0.016). CONCLUSIONS: In the United States, there appears to be a ~ 20% average increase in cannabis use frequency attributable to recreational legalization, consistent across increasingly rigorous designs. In addition, the heritability of cannabis use frequency appears to be moderated by legalization.

Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection.

The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies. The broader scientific community was invited to review and provide feedback on the preliminary recommendation of the Working Group. Fourteen selected protocols for measuring smoking cessation, harm reduction, and biomarkers research associated with smoking cessation were released in the PhenX Toolkit ( https://www.phenxtoolkit.org) in February 2021. These protocols complement existing PhenX Toolkit content related to tobacco regulatory research, substance use and addiction research, and other measures of smoking-related health outcomes. Adopting well-established protocols enables consistent data collection and facilitates comparing and combining data across studies, potentially increasing the scientific impact of individual studies.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Longitudinal effects and environmental moderation of ALDH2 and ADH1B gene variants on substance use from age 14 to 40.

Alcohol use and dependence are strongly affected by variation in aldehyde dehydrogenase (ALDH2) and, to a lesser extent, alcohol dehydrogenase (ADH1B) genes. We use this genetic variation with an adoption design to test the causal role of alcohol use on other drug use, as well as the moderating role of adoptive parent, sibling, and peer alcohol use. Longitudinal models were run on 412 genotyped adopted individuals of East Asian ancestry with multiple assessments between ages 14 and 40. We found robust associations between alcohol frequency, quantity, and maximum drinks and ALDH2, but not ADH1B, status. The magnitude of the ALDH2 protective effect increased with age, particularly for maximum drinks, though estimates were smaller than previously reported in ancestrally similar individuals in East/North-East Asian countries. These results suggest that sociocultural factors in Minnesota may reduce the protective effects of ALDH2. We found that peer alcohol use, but not parent or sibling use, predicted adopted offspring's use, and that these environmental influences did not vary by ALDH2 status. Finally, we did not find strong evidence of associations between ALDH2 status and tobacco, marijuana, or illegal drug use, contrary to expectation if alcohol serves as a gateway to use of other drugs.

Developmental and etiological patterns of substance use from adolescence to middle age: A longitudinal twin study.

BACKGROUND: The common liability to addiction framework suggests the tendency to use substances is largely a general heritable liability, but little is known about how expression of liability varies across development. We evaluated average developmental trajectories and covariation underlying commonly used substances using a genetically informative prospective design spanning three decades. METHODS: Using a sample of 3762 twins across seven waves of assessment spanning ages 14-40, we modeled these relationships using two complementary approaches: piecewise latent growth and common factor modeling on four measures of alcohol, tobacco, and marijuana use RESULTS: Average use increased across adolescence and either stabilized (alcohol frequency) or declined (all others) in adulthood. Trajectories were heritable (~.35-.75), and genetically correlated with one another (~.40-.80). The random intercepts, centered at age 16, exhibited shared environmental correlations across substances. We found moderate to large phenotypic (rp~.3-.9) and genetic correlations (rg~.3-1) among the longitudinally varying common factors loading on use of each substance at each age. The factor loadings declined with age, reflecting waning influence of common etiology in substance use. CONCLUSIONS: Trajectories of substance use were strongly correlated with each other and influenced primarily by genetic and non-shared environment. A heritable common factor accounted for co-occurring substance use from mid-adolescence to mid-adulthood, and greater substance specificity emerged with maturation. These results extend and reinforce prior work examining consumption and problem use, providing new evidence over a broad age range showing that substance use behaviors are influenced by a more general liability in adolescence and specificity increases across development.

Genetic correlation, pleiotropy, and causal associations between substance use and psychiatric disorder.

BACKGROUND: Substance use occurs at a high rate in persons with a psychiatric disorder. Genetically informative studies have the potential to elucidate the etiology of these phenomena. Recent developments in genome-wide association studies (GWAS) allow new avenues of investigation. METHOD: Using results of GWAS meta-analyses, we performed a factor analysis of the genetic correlation structure, a genome-wide search of shared loci, and causally informative tests for six substance use phenotypes (four smoking, one alcohol, and one cannabis use) and five psychiatric disorders (ADHD, anorexia, depression, bipolar disorder, and schizophrenia). RESULTS: Two correlated externalizing and internalizing/psychosis factor were found, although model fit was beneath conventional standards. Of 458 loci reported in previous univariate GWAS of substance use and psychiatric disorders, about 50% (230 loci) were pleiotropic with additional 111 pleiotropic loci not reported from past GWAS. Of the 341 pleiotropic loci, 152 were associated with both substance use and psychiatric disorders, implicating neurodevelopment, cell morphogenesis, biological adhesion pathways, and enrichment in 13 different brain tissues. Seventy-five and 114 pleiotropic loci were specific to either psychiatric disorders or substance use phenotypes, implicating neuronal signaling pathway and clathrin-binding functions/structures, respectively. No consistent evidence for phenotypic causation was found across different Mendelian randomization methods. CONCLUSIONS: Genetic etiology of substance use and psychiatric disorders is highly pleiotropic and involves shared neurodevelopmental path, neurotransmission, and intracellular trafficking. In aggregate, the patterns are not consistent with vertical pleiotropy, more likely reflecting horizontal pleiotropy or more complex forms of phenotypic causation.

Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood.

BACKGROUND AND AIMS: Molecular genetic studies of alcohol and nicotine use have identified many genome-wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance-specific versus broader-liability PGS effects, and if PGS performance varied for consumption versus problematic substance use. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: We fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date. FINDINGS: Each PGS was associated with trajectories of use for their respective substances [i.e. DPW (ßmean = 0.08; ßrange = 0.02-0.12) and PAU (ßmean = 0.12; ßrange = -0.02 to 0.31) for alcohol; CPD (ßmean = 0.08; ßrange = 0.04-0.14) and SMK (ßmean = 0.18; ßrange = 0.05-0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross-substance associations (i.e. PAU for nicotine-specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (ßmean = 0.15; ßrange = 0.02-0.33), even after adjusting for the respective effects of all other PGSs. CONCLUSIONS: Substance use-related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine-specific and non-specific genetic liability for substance use, and potentially externalizing problems in general.

Polygenic scores for smoking and educational attainment have independent influences on academic success and adjustment in adolescence and educational attainment in adulthood.

Educational success is associated with greater quality of life and depends, in part, on heritable cognitive and non-cognitive traits. We used polygenic scores (PGS) for smoking and educational attainment to examine different genetic influences on facets of academic adjustment in adolescence and educational attainment in adulthood. PGSs were calculated for participants of the Minnesota Twin Family Study (N = 3225) and included as predictors of grades, academic motivation, and discipline problems at ages 11, 14, and 17 years-old, cigarettes per day from ages 14 to 24 years old, and educational attainment in adulthood (mean age 29.4 years). Smoking and educational attainment PGSs had significant incremental associations with each academic variable and cigarettes per day. About half of the adjusted effects of the smoking and education PGSs on educational attainment in adulthood were mediated by the academic variables in adolescence. Cigarettes per day from ages 14 to 24 years old did not account for the effect of the smoking PGS on educational attainment, suggesting the smoking PGS indexes genetic influences related to general behavioral disinhibition. In sum, distinct genetic influences measured by the smoking and educational attainment PGSs contribute to academic adjustment in adolescence and educational attainment in adulthood.

Mechanisms of parent-child transmission of tobacco and alcohol use with polygenic risk scores: Evidence for a genetic nurture effect.

Parent-child similarity is a function of genetic and environmental transmission. In addition, genetic effects not transmitted to offspring may drive parental behavior, thereby affecting the rearing environment of the child. Measuring genetic proclivity directly, through polygenic risk scores (PRSs), provides a way to test for the effect of nontransmitted parental genotype, on offspring outcome, termed a genetic nurture effect-in other words, if and how parental genomes might affect their children through the environment. The current study used polygenic risk scores for smoking initiation, cigarettes per day, and drinks per week to predict substance use in a sample of 3,008 twins, assessed prospectively from age 17-29, and their parents, from the Minnesota Center for Twin and Family Research. Mixed-effects models were used to test for a genetic nurture effect whereby parental PRSs predict offspring tobacco and alcohol use after statistically adjusting for offspring's own PRS. Parental smoking initiation PRS predicted offspring cigarettes per day at age 24 (ß = .103, 95% CI [.03, .17]) and alcohol use at age 17 (ß = .091, 95% CI [.04, .14]) independent of shared genetics. There was also a suggestive independent association between the parent PRS and offspring smoking at age 17 (ß = .096; 95% CI [.02, .17]). Mediation analyses provided some evidence for environmental effects of parental smoking, alcohol use, and family socioeconomic status. These findings, and more broadly the molecular genetic method used, have implications on the identification of environmental effects on developmental outcomes such as substance use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment.

BACKGROUND: To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. METHOD: A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. RESULTS: Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [ß = -0.032, nonparametric bootstrap 95% confidence interval (CI) -0.059 to -0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (ß = -0.034, 95% CI -0.063 to -0.006) and regular smoking PGSs (ß = -0.032, 95% CI -0.061 to -0.005) and positively associated with educational attainment PGS (ß = 0.031, 95% CI 0.003-0.058). CONCLUSIONS: Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.

Genetic architecture of four smoking behaviors using partitioned SNP heritability.

BACKGROUND AND AIMS: Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance remains unexplained. We characterized the genetic architecture of four smoking behaviors using single nucleotide polymorphism (SNP) heritability (h2SNP ). This is an estimate of narrow-sense heritability specifically estimating the proportion of phenotypic variation due to causal variants (CVs) tagged by SNPs. DESIGN: Partitioned h2SNP analysis of smoking behavior traits. SETTING: UK Biobank. PARTICIPANTS: UK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54 792 to 323 068. MEASUREMENTS: Smoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned and dichotomized into heavy versus light) and smoking cessation with imputed genome-wide SNPs. FINDINGS: We estimated that, in aggregate, approximately 18% of the phenotypic variance in smoking initiation was captured by imputed SNPs [h2SNP = 0.18, standard error (SE) = 0.01] and 12% [SE = 0.02] for smoking cessation, both of which were more than twice the previously reported estimates. Estimated age of initiation (h2SNP  = 0.05, SE = 0.01) and binned CPD (h2SNP  = 0.1, SE = 0.01) were substantially below published twin-based h2 of 50%. CPD encoding influenced estimates, with dichotomized CPD h2SNP  = 0.28. There was no evidence of dominance genetic variance for any trait. CONCLUSION: A biobank study of smoking behavior traits suggested that the phenotypic variance explained by SNPs of smoking initiation, age of initiation, cigarettes per day and smoking cessation is modest overall.

Polygenic Score for Smoking is associated with Externalizing Psychopathology and Disinhibited Personality Traits but not Internalizing Psychopathology in Adolescence.

We examined whether a polygenic score (PGS) for smoking measured genetic risk for general behavioral disinhibition by estimating its associations with externalizing and internalizing psychopathology and related personality traits at multiple time points in adolescence (ages 11, 14, and 17 years; N = 3225). The smoking PGS had strong associations with the stable variance across time for all the externalizing measures (mean standardized ß = .27), agreeableness (ß = -.22, 95% CI: -.28, -.16), and conscientiousness (ß = -.19, 95% CI: -.24, -.13), but was not significantly associated with internalizing measures (mean ß = .06) or extraversion (ß = .01, 95% CI: -.05, .07). After controlling for smoking at age 17, the associations with externalizing, low agreeableness, and low conscientiousness remained statistically significant. The smoking PGS measures genetic influences that contribute to a spectrum of phenotypes related to behavioral disinhibition including externalizing psychopathology and normal-range personality traits related to behavioral control, but not internalizing psychopathology.

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (rg = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.

Dissecting the genetic overlap of smoking behaviors, lung cancer, and chronic obstructive pulmonary disease: A focus on nicotinic receptors and nicotine metabolizing enzyme.

Smoking is a major contributor to lung cancer and chronic obstructive pulmonary disease (COPD). Two of the strongest genetic associations of smoking-related phenotypes are the chromosomal regions 15q25.1, encompassing the nicotinic acetylcholine receptor subunit genes CHRNA5-CHRNA3-CHRNB4, and 19q13.2, encompassing the nicotine metabolizing gene CYP2A6. In this study, we examined genetic relations between cigarettes smoked per day, smoking cessation, lung cancer, and COPD. Data consisted of genome-wide association study summary results. Genetic correlations were estimated using linkage disequilibrium score regression software. For each pair of outcomes, z-score-z-score (ZZ) plots were generated. Overall, heavier smoking and decreased smoking cessation showed positive genetic associations with increased lung cancer and COPD risk. The chromosomal region 19q13.2, however, showed a different correlational pattern. For example, the effect allele-C of the sentinel SNP (rs56113850) within CYP2A6 was associated with an increased risk of heavier smoking (z-score = 19.2; p = 1.10 × 10-81 ), lung cancer (z-score = 8.91; p = 5.02 × 10-19 ), and COPD (z-score = 4.04; p = 5.40 × 10-5 ). Surprisingly, this allele-C (rs56113850) was associated with increased smoking cessation (z-score = -8.17; p = 2.52 × 10-26 ). This inverse relationship highlights the need for additional investigation to determine how CYP2A6 variation could increase smoking cessation while also increasing the risk of lung cancer and COPD likely through increased cigarettes smoked per day.

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

Behavioral impact of return of genetic test results for complex disease: Systematic review and meta-analysis.

OBJECTIVE: Advances in genomewide association studies have made possible the return of genetic risk results for complex diseases. Two concerns about these results are (a) negative psychological consequences and (b) viewing probabilistic results as deterministic, leading to misinterpretation and inappropriate decisions. The present study evaluates these concerns through a meta-analytic review of existing literature. METHOD: Seventeen genetic testing studies of complex disease, including 1,171 participants and reporting 195 effects, 104 of which were unadjusted for covariates, were meta-analyzed under a random effects model. Diseases included Alzheimer's, cardiovascular and coronary heart disease, lung cancer, melanoma, thrombophilia, and type II diabetes. Six domains of behavioral-psychological reactions were examined. RESULTS: Carriers showed significantly increased self-reported behavior change compared to noncarriers when assessed 6 months or later after results return (Hedges's g = .36, p = .019). CONCLUSIONS: Return of genetic testing results for complex disease does not strongly impact self-reported negative behavior or psychological function of at-risk individuals. Return of results does appear to moderately increase self-reported healthy behavior in carriers, although research on objectively observed behavior change is needed. This is a growing area of research, with preliminary results suggesting potential positive implications of genetic testing for complex disease on behavior change. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes.

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.