Cross-Cultural Comparison of Genetic and Cultural Transmission of Smoking Initiation Using an Extended Twin Kinship Model

Evidence of correlations between human partners based on systematic reviews and meta-analyses of 22 traits and UK Biobank analysis of 133 traits

Positive correlations between mates can increase trait variation and prevalence, as well as bias estimates from genetically informed study designs. While past studies of similarity between human mating partners have largely found evidence of positive correlations, to our knowledge, no formal meta-analysis has examined human partner correlations across multiple categories of traits. Thus, we conducted systematic reviews and random-effects meta-analyses of human male-female partner correlations across 22 traits commonly studied by psychologists, economists, sociologists, anthropologists, epidemiologists and geneticists. Using ScienceDirect, PubMed and Google Scholar, we incorporated 480 partner correlations from 199 peer-reviewed studies of co-parents, engaged pairs, married pairs and/or cohabitating pairs that were published on or before 16 August 2022. We also calculated 133 trait correlations using up to 79,074 male-female couples in the UK Biobank (UKB). Estimates of the 22 mean meta-analysed correlations ranged from rmeta = 0.08 (adjusted 95% CI = 0.03, 0.13) for extraversion to rmeta = 0.58 (adjusted 95% CI = 0.50, 0.64) for political values, with funnel plots showing little evidence of publication bias across traits. The 133 UKB correlations ranged from rUKB = -0.18 (adjusted 95% CI = -0.20, -0.16) for chronotype (being a 'morning' or 'evening' person) to rUKB = 0.87 (adjusted 95% CI = 0.86, 0.87) for birth year. Across analyses, political and religious attitudes, educational attainment and some substance use traits showed the highest correlations, while psychological (that is, psychiatric/personality) and anthropometric traits generally yielded lower but positive correlations. We observed high levels of between-sample heterogeneity for most meta-analysed traits, probably because of both systematic differences between samples and true differences in partner correlations across populations.

Genetic and Cultural Transmission of Alcohol Use Disorder in Swedish Twin Pedigrees

OBJECTIVE

Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of alcohol use disorder (AUD) by extended twin pedigree modeling.

METHOD

AUD was defined using public inpatient, outpatient, prescription, and criminal records. Three-generational pedigrees were selected for index individuals born between 1980 and 1990, obtained from the national twin and genealogical registers, whose parents were twins. Relatives of the twins included in the pedigrees were their parents, siblings, spouses, and children. Genetic structural equation modeling was applied to the population-based data on AUD, using OpenMx, with age used as a covariate.

RESULTS

Analyses including up to 162,469 individuals in 18,971 pedigrees estimated AUD prevalence at 5%-12% in men and 2%-5% in women. Results indicated substantial heritability (about 50%-60%), of which a portion upwards of 5% was attributable to the consequences of assortative mating. Contributions of shared environmental factors to AUD, which represent a mix of within- and cross-generational effects, appeared to be moderate (about 10%-20%). Unique environment accounted for the remaining variance (about 20%-30%). Sex differences in the magnitude of the variance components suggested higher heritability in men and correspondingly higher shared environmental contributions in women.

CONCLUSIONS

Using objective registry data, we found that AUD is highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of AUD in both men and women.

The Genetically Informed Neurobiology of Addiction (GINA) model

Addictions are heritable and unfold dynamically across the lifespan. One prominent neurobiological theory proposes that substance-induced changes in neural circuitry promote the progression of addiction. Genome-wide association studies have begun to characterize the polygenic architecture undergirding addiction liability and revealed that genetic loci associated with risk can be divided into those associated with a general broad-spectrum liability to addiction and those associated with drug-specific addiction risk. In this Perspective, we integrate these genomic findings with our current understanding of the neurobiology of addiction to propose a new Genetically Informed Neurobiology of Addiction (GINA) model.

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 (h²_SNP ). 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 h²_SNP 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 [h²_SNP = 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 (h²_SNP  = 0.05, SE = 0.01) and binned CPD (h²_SNP  = 0.1, SE = 0.01) were substantially below published twin-based h² of 50%. CPD encoding influenced estimates, with dichotomized CPD h²_SNP  = 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.

Estimating causal and time-varying effects of maternal smoking on youth smoking

INTRODUCTION

Maternal smoking is a well-known risk factor for youth smoking, yet whether this relationship is causal remains unresolved. This study utilizes propensity score methods for causal inference to robustly account for shared risk factors between maternal and offspring smoking.

METHODS

An 8-year longitudinal cohort of 900 adolescents in the Chicago area were followed starting from approximately age 15.6. The effects of maternal lifetime smoking (MLS) and prenatal tobacco exposure (PTE) (among participants reporting MLS) on offspring's past 30-day smoking, daily smoking status and smoking frequency were examined using logistic regression and Poisson regression after nearest-neighbor propensity matching. Age dependency of this relationship was then examined across the age range of 15-25 using time-varying effect modeling.

RESULTS

Propensity matching yielded 438 and 132 pairs for MLS and PTE study samples, respectively. MLS demonstrated significant associations with past 30-day smoking (RR 1.09; 95% CI 1.04-1.14), daily smoking (RR 1.08; 95% CI 1.05-1.12), and smoking frequency of offspring (RR 1.32; 95% CI 1.15-1.52), with stable effects across age. Among participants reporting MLS, having PTE showed significant additional effects on daily smoking (RR 1.09; 95% CI 1.02-1.17) and age-dependency that showed significance during young adulthood but not adolescence.

CONCLUSION

The relationship between maternal and offspring smoking was not fully accounted for by shared risk factors, suggesting possible causation with PTE having a delayed effect across age. Targeted prevention efforts should be made on maternal smoking-exposed adolescents to mitigate their risks of developing heavy smoking habits in adulthood.

Parental characteristics and offspring mental health and related outcomes: a systematic review of genetically informative literature

Various parental characteristics, including psychiatric disorders and parenting behaviours, are associated with offspring mental health and related outcomes in observational studies. The application of genetically informative designs is crucial to disentangle the role of genetic and environmental factors (as well as gene-environment correlation) underlying these observations, as parents provide not only the rearing environment but also transmit 50% of their genes to their offspring. This article first provides an overview of behavioural genetics, matched-pair, and molecular genetics designs that can be applied to investigate parent-offspring associations, whilst modelling or accounting for genetic effects. We then present a systematic literature review of genetically informative studies investigating associations between parental characteristics and offspring mental health and related outcomes, published since 2014. The reviewed studies provide reliable evidence of genetic transmission of depression, criminal behaviour, educational attainment, and substance use. These results highlight that studies that do not use genetically informative designs are likely to misinterpret the mechanisms underlying these parent-offspring associations. After accounting for genetic effects, several parental characteristics, including parental psychiatric traits and parenting behaviours, were associated with offspring internalising problems, externalising problems, educational attainment, substance use, and personality through environmental pathways. Overall, genetically informative designs to study intergenerational transmission prove valuable for the understanding of individual differences in offspring mental health and related outcomes, and mechanisms of transmission within families.

Smoking and drinking among patients with mental disorders: Evidence from a nationally representative Japanese survey

BACKGROUND

No studies to date have addressed the association of mental disorder with smoking and drinking behaviors independent of anxiety and depressive symptoms. We therefore examined this association, stratified by age and sex, to determine the target population for behavioral modification in Japan.

METHODS

We analyzed data from participants aged 20-79 years without hospitalized or institutionalized status who participated in the nationwide Comprehensive Survey of Living Conditions conducted in 2016. Prevalence ratios (PRs) for current smoking, heavy daily smoking (>20 cigarettes per day), at-risk drinking (>100 g alcohol per week), and heavy drinking (>350 g) were calculated with adjustment for potential confounders. After stratification by age (20-39, 40-64, and 65-79 years) and sex, prevalence and PRs were calculated using propensity scores.

RESULTS

From among 340,194 participants, 8275 (2.4%) had mental disorder. Presence of mental disorder was significantly associated with current smoking (PR=1.18, 95%CI=1.12-1.23) and heavy daily smoking (PR=1.35, 95%CI=1.21-1.50) and inversely associated with at-risk drinking (PR=0.70, 95%CI=0.66-0.75). PRs for smoking behavior were higher in women than in men and in younger adults than in the other age groups. They were particularly high in younger women (PR=1.67 for current smokers and PR=2.17 for heavy daily smokers).

LIMITATIONS

Our findings were obtained from a cross-sectional study.

CONCLUSION

This is the first evidence that the association of mental disorder with smoking behavior is independent of anxiety and depressive symptoms. Our results indicate the need for tailored behavioral modification interventions for young people with mental disorders in Japan, particularly young women.

Modeling Etiology of Smoking During Pregnancy in Swedish Twins, Full-, and Half-Siblings, Reared Together and Apart

INTRODUCTION

Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of smoking status across stages of pregnancy with increasing degrees of social and psychological pressure to reduce or quit smoking, by twin and sibling modeling.

AIMS AND METHODS

Smoking status was available before, and during early and late pregnancy from the Medical Birth Register. Twin, full-, and half-sibling pairs, both reared together and apart, born between 1960 and 1990 were obtained from national twin and genealogical registers. Genetic structural equation modeling in OpenMx was applied to the population-based data to estimate shared genetic and/or environmental covariance across stages of pregnancy, accounting for maternal birth cohort and age at pregnancy.

RESULTS

Analyses of paired data on 258 749 individuals suggested that risk factors for smoking status changed across stages of pregnancy. Results predicted substantial heritability (60-70%) and moderate contributions of shared environmental factors (10-15%) for smoking status. Whilst the same shared environmental factors were amplified from before pregnancy to late pregnancy, new primarily unique environmental factors explained ~10% of the variance during early pregnancy which was carried forward to late pregnancy.

CONCLUSIONS

Using registry data on women across pregnancy, we replicated that smoking status is highly heritable. Furthermore, we found support for increased impact of shared environmental factors during pregnancy of factors already present prior to pregnancy, and an independent set of mostly new unique environmental factors that may be triggered by increased social pressure to reduce or quit smoking during pregnancy.

IMPLICATIONS

As new factors partially explain smoking status during pregnancy and the effects of familial factors increase across pregnancy, efforts to prevent or reduce smoking during pregnancy should receive continued attention, with a focus on both the individual and the family unit.

Nicholas (Nick) G. Martin and the Extended Twin Model

The extended twin model is a unique design in the genetic epidemiology toolbox that allows to simultaneously estimate multiple causes of variation such as genetic and cultural transmission, genotype-environment covariance and assortative mating, among others. Nick Martin has played a key role in the conception of the model, the collection of substantially large data sets to test the model, the application of the model to a range of phenotypes, the publication of the results including cross-cultural comparisons, the evaluation of bias and power of the design and the further elaborations of the model, such as the children-of-twins design.

The Mid-Atlantic Twin Registry of Virginia Commonwealth University

The Mid-Atlantic Twin Registry (MATR) is a population-based registry of more than 60,000 twins primarily born or living in Virginia, North Carolina and South Carolina. Researchers may utilize the MATR for administration of research services, including study recruitment, data or sample (e.g., DNA) collection, archival dataset creation, as well as data collection through mailed, phone or online surveys. In addition, the MATR houses the MATR Repository, with over 1700 DNA samples primarily from whole blood available for researchers interested in DNA genotyping. For over 40 years MATR twins have participated in research studies with investigators from a range of scientific disciplines and institutions. These studies, which have resulted in numerous publications, explored diverse topics, including substance use, smoking behaviors, developmental psychopathology, bullying, children's health, cardiovascular disease, cancer, the human microbiome, epigenetics of aging, children of twins and sleep homeostasis. Researchers interested in utilizing twins are encouraged to contact the MATR to discuss potential research opportunities.