Polygenic risk for alcohol misuse is moderated by romantic partnerships

Marital status and genetic liability independently predict coronary heart disease incidence

AIMS

Married individuals have a lower coronary heart disease (CHD) risk than non-married, but the mechanisms behind this are not fully understood. We analyzed whether genetic liability to CHD may affect these associations.

METHODS

Marital status, a polygenic score of CHD (PGS-CHD), and other risk factors for CHD were measured from 35,444 participants (53% female) in Finnish population-based surveys conducted between 1992 and 2012. During the register-based follow-up until 2020, there were 2439 fatal and non-fatal incident CHD cases. The data were analyzed using linear and Cox regression models.

RESULTS

Divorced and cohabiting men and women had a higher genetic risk of CHD than married individuals, but the difference was very small (0.023-0.058 standard deviation of PGS-CHD, p-values 0.011-0.429). Both marital status and PGS-CHD were associated with CHD incidence, but the associations were largely independent. Adjusting for behavioral and metabolic risk factors for CHD explained part of these associations (11-20%). No interaction was found between marital status and PGS-CHD for CHD incidence.

CONCLUSIONS

We showed minor differences between the marital status categories in PGS-CHD and demonstrated that marital status and genetic liability predicted CHD incidence largely independently. This emphasizes the need to measure multiple risk factors when predicting CHD risk.

Examining interactions between polygenic scores and interpersonal trauma exposure on alcohol consumption and use disorder in an ancestrally diverse college cohort

Introduction: Genetic factors impact alcohol consumption and use disorder (AUD), with large-scale genome-wide association studies (GWAS) identifying numerous associated variants. Aggregate genetic methods in combination with important environmental factors (e.g., interpersonal trauma [IPT]) can be applied to expand our understanding of the ways by which genetic and environmental variables work together to influence alcohol consumption and disordered use. The present study aimed to detail the relationships between genome-wide polygenic scores (PGS) for alcohol phenotypes (i.e., alcohol consumption and AUD status) and IPT exposure as well as the interaction between them across ancestry. Methods: Data were drawn from the Spit for Science (S4S) study, a US college student population, where participants reported on IPT exposure prior to college and alcohol consumption and problems during college (N = 9,006; ancestry: 21.3% African [AFR], 12.5% Admixed Americas [AMR], 9.6% East Asian [EAS], 48.1% European [EUR], 8.6% South Asian [SAS]). Two trans-ancestry PGS were constructed, one for alcohol consumption and another for AUD, using large-scale GWAS summary statistics from multiple ancestries weighted using PRS-CSx. Regression models were applied to test for the presence of associations between alcohol-PGS and IPT main and interaction effects. Results: In the meta-analysis across ancestry groups, IPT exposure and PGS were significantly associated with alcohol consumption (βIPT = 0.31, P IPT = 0.0002; βPGS = 0.09, P PGS = 0.004) and AUD (ORIPT = 1.12, P IPT = 3.5 × 10-8; ORPGS = 1.02, P PGS = 0.002). No statistically significant interactions were detected between IPT and sex nor between IPT and PGS. When inspecting ancestry specific results, the alcohol consumption-PGS and AUD-PGS were only statistically significant in the EUR ancestry group (βPGS = 0.09, P PGS = 0.04; ORPGS = 1.02, P PGS = 0.022, respectively). Discussion: IPT exposure prior to college was strongly associated with alcohol outcomes in this college-age sample, which could be used as a preventative measure to identify students at high risk for problematic alcohol use. Additionally, results add to developing evidence of polygenic score association in meta-analyzed samples, highlighting the importance of continued efforts to increase ancestral representation in genetic studies and inclusive analytic approaches to increase the generalizability of results from genetic association studies.

The Collaborative Study on the Genetics of Alcoholism: Overview

Alcohol use disorders (AUD) are commonly occurring, heritable and polygenic disorders with etiological origins in the brain and the environment. To outline the causes and consequences of alcohol-related milestones, including AUD, and their related psychiatric comorbidities, the Collaborative Study on the Genetics of Alcoholism (COGA) was launched in 1989 with a gene-brain-behavior framework. COGA is a family based, diverse (~25% self-identified African American, ~52% female) sample, including data on 17,878 individuals, ages 7-97 years, in 2246 families of which a proportion are densely affected for AUD. All participants responded to questionnaires (e.g., personality) and the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) which gathers information on psychiatric diagnoses, conditions and related behaviors (e.g., parental monitoring). In addition, 9871 individuals have brain function data from electroencephalogram (EEG) recordings while 12,009 individuals have been genotyped on genome-wide association study (GWAS) arrays. A series of functional genomics studies examine the specific cellular and molecular mechanisms underlying AUD. This overview provides the framework for the development of COGA as a scientific resource in the past three decades, with individual reviews providing in-depth descriptions of data on and discoveries from behavioral and clinical, brain function, genetic and functional genomics data. The value of COGA also resides in its data sharing policies, its efforts to communicate scientific findings to the broader community via a project website and its potential to nurture early career investigators and to generate independent research that has broadened the impact of gene-brain-behavior research into AUD.

Association between genetic risk of alcohol consumption and alcohol-related morbidity and mortality under different alcohol policy conditions: Evidence from the Finnish alcohol price reduction of 2004

AIMS

Harmful alcohol consumption is influenced by both genetic susceptibility and the price of alcohol. Many previous studies have observed that genetic susceptibility to consumption of alcohol is more predictive in less restrictive drinking conditions. We assess whether such a pattern applies when the prices of alcoholic beverages are decreased.

DESIGN

Data consist of genetically informed population-representative surveys (FINRISK 1992, 1997, 2002 and Health 2000) linked to administrative registers. We analysed the interaction between a polygenic score (PGS) for alcoholic drinks per week consumed and price reduction in predicting the incidence of alcohol-related hospitalizations and deaths in difference-in-difference and interrupted time-series frameworks.

SETTING

Individuals in Finland were followed quarter-yearly from 1 March 2000 to 31 May 2008.

PARTICIPANTS

A total of 22 152 individuals (607 132-person quarter-years, 1399 outcome events) aged 30-79 years.

INTERVENTION

A natural experiment stemming from the alcohol tax reduction in March 2004 and import deregulation in May 2004.

MEASUREMENTS

Outcome was quarter-yearly-measured alcohol-related death or hospitalization. The independent variables of main interest were PGS and a price reform indicator. We adjusted for gender, age, age squared, season, 10 first principal components of the genome, data collection round and genotyping batch.

FINDINGS

Both alcohol price reduction and one standard deviation change in PGS were associated with alcohol-related health outcomes; odds ratios (ORs) were 1.32, 95% confidence interval (CI) = 1.13, 1.53 and 1.26, 95% CI = 1.12, 1.42 in the 8-year follow-up, respectively. The association between PGS and alcohol-related morbidity was similar before and after the alcohol price reform (PGS × price reform interaction OR = 0.96, 95% CI = 0.81, 1.14). These results were robust across different follow-up periods and measurement and analysis strategies.

CONCLUSIONS

Although the decrease of alcohol price in Finland in 2004 substantially increased overall alcohol-related morbidity and mortality, the genetic susceptibility to alcohol consumption did not become more manifest in predicting them.

Changing associations of coronary heart disease incidence with current partnership status and marital history over three decades

Married men and women have better health than non-married, but little is known about how cohabitation and marital history are associated with coronary heart disease (CHD) incidence and how these associations have changed over time. We analyzed these associations by fitting Cox regression models to register data covering the whole Finnish population aged 35 years or older (N = 4,415,590), who experienced 530,560 first time non-fatal or fatal CHD events during the years 1990–2018. Further, we used stratified Cox regression models to analyze CHD incidence within same-sex sibling pairs (N = 377,730 pairs). Married men and women without previous divorce had the lowest CHD incidence whereas cohabitation and a history of divorce were associated with higher CHD incidence. The associations were stronger in younger (35–64 years old) than older participants (65 years or older). These associations remained after adjusting for several indicators of social position, and the lower CHD incidence among those married without previous divorce was also observed within sibling pairs with a shared family background. The differences in CHD incidence between the categories generally widened over time; the largest and most systematic widening was observed among women in the younger age category. The long standing negative effect of divorce suggests that selection may partly explain the association between partnership status and CHD incidence. Partnership status is an increasingly important factor contributing to social inequalities in health.

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Married men and women without previous divorce history have the lowest CHD risk.

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Cohabitation is associated with higher CHD risk than marriage.

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The associations between partnership and CHD risk are not explained by social factors.

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These associations generally widened over time, especially among women.

Predicting Alcohol Use From Genome-Wide Polygenic Scores, Environmental Factors, and Their Interactions in Young Adulthood

OBJECTIVE

Alcohol use during emerging adulthood is associated with adverse life outcomes, but its risk factors are not well known. Here, we predicted alcohol use in 3153 young adults aged 22 years from a) genome-wide polygenic scores (GPS) based on genome-wide association studies for the target phenotypes number of drinks per week and Alcohol Use Disorders Identification Test scores, b) 30 environmental factors, and c) their interactions (i.e., G × E effects).

METHODS

Data were collected from 1994 to 2018 as a part of the UK Twins Early Development Study.

RESULTS

GPS accounted for up to 1.9% of the variance in alcohol use (i.e., Alcohol Use Disorders Identification Test score), whereas the 30 measures of environmental factors together accounted for 21.1%. The 30 GPS by environment interactions did not explain any additional variance, and none of the interaction terms exceeded the significance threshold after correcting for multiple testing.

CONCLUSIONS

GPS and some environmental factors significantly predicted alcohol use in young adulthood, but we observed no GPS by environment interactions in our study.

A systematic review of gene-by-intervention studies of alcohol and other substance use

Alcohol and other substance use problems are common, and the efficacy of current prevention and intervention programs is limited. Genetics may contribute to differential effectiveness of psychosocial prevention and intervention programs. This paper reviews gene-by-intervention (G×I) studies of alcohol and other substance use, and implications for integrating genetics into prevention science. Systematic review yielded 17 studies for inclusion. Most studies focused on youth substance prevention, alcohol was the most common outcome, and measures of genotype were heterogeneous. All studies reported at least one significant G×I interaction. We discuss these findings in the context of the history and current state of genetics, and provide recommendations for future G×I research. These include the integration of genome-wide polygenic scores into prevention studies, broad outcome measurement, recruitment of underrepresented populations, testing mediators of G×I effects, and addressing ethical implications. Integrating genetic research into prevention science, and training researchers to work fluidly across these fields, will enhance our ability to determine the best intervention for each individual across development. With growing public interest in obtaining personalized genetic information, we anticipate that the integration of genetics and prevention science will become increasingly important as we move into the era of precision medicine.

Gene-environment dependencies lead to collider bias in models with polygenic scores

The application of polygenic scores has transformed our ability to investigate whether and how genetic and environmental factors jointly contribute to the variation of complex traits. Modelling the complex interplay between genes and environment, however, raises serious methodological challenges. Here we illustrate the largely unrecognised impact of gene-environment dependencies on the identification of the effects of genes and their variation across environments. We show that controlling for heritable covariates in regression models that include polygenic scores as independent variables introduces endogenous selection bias when one or more of these covariates depends on unmeasured factors that also affect the outcome. This results in the problem of conditioning on a collider, which in turn leads to spurious associations and effect sizes. Using graphical and simulation methods we demonstrate that the degree of bias depends on the strength of the gene-covariate correlation and of hidden heterogeneity linking covariates with outcomes, regardless of whether the main analytic focus is mediation, confounding, or gene × covariate (commonly gene × environment) interactions. We offer potential solutions, highlighting the importance of causal inference. We also urge further caution when fitting and interpreting models with polygenic scores and non-exogenous environments or phenotypes and demonstrate how spurious associations are likely to arise, advancing our understanding of such results.

Characterization of alcohol polygenic risk scores in the context of mental health outcomes: Within-individual and intergenerational analyses in the Avon Longitudinal Study of Parents and Children

BACKGROUND

Heavy alcohol consumption often co-occurs with mental health problems; this could be due to confounding, shared biological mechanisms, or causal effects. Polygenic risk scores (PRS) for alcohol use can be used to explore this association at critical life stages.

DESIGN

We characterized a PRS reliably associated with patterns of adult alcohol consumption by 1) validating whether it predicts own alcohol use at different life-stages (pregnancy, adolescence) of interest for mental health impact. Additionally, we explored associations of alcohol PRS on mental health phenotypes 2) within-individuals (using own alcohol PRS on own phenotypes) and 3) intergenerationally (using maternal alcohol PRS on offspring phenotypes). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 960-7841). Additional substance abuse behaviors and mental health/behavioral outcomes were investigated (alcohol phenotypes n = 22; health phenotypes n = 91).

FINDINGS

Maternal alcohol PRS was associated with consumption during pregnancy (strongest signal: alcohol frequency at 18 weeks' gestation: β = 0.041, 95%CI = 0.0.02-0.06), p = 1.01 × 10-5, adjusted R2 = 1.6 %), offspring alcohol PRS did not predict offspring alcohol consumption. We found evidence for an association of maternal alcohol PRS with own perinatal depression (OR  = 1.10, 95% CI = 1.02 to 1.18, p = 0.022) and decreased offspring intellectual ability (β=-0.209, 95% CI -0.38 to -0.04, p= 0.016).

CONCLUSIONS

These alcohol PRS are a valid proxy for maternal alcohol use in pregnancy. Offspring alcohol PRS was not associated with drinking in adolescence. Consistently with results from different study designs, we found evidence that maternal alcohol PRS are associated with both prenatal depression and decreased offspring intellectual ability.

Predictive validity of genome-wide polygenic scores for alcohol use from adolescence to young adulthood

BACKGROUND

Adolescence is a critical period for experimenting with alcohol, and these early experiences have long-term influences on alcohol-related behaviours throughout adulthood. This study examined the utility of genome-wide polygenic scores (GPS) for predicting alcohol use during adolescence and young adulthood.

METHODS

We used GPS based on the Genome-wide association study and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) study on drinks per week to predict alcohol use in a longitudinal, UK-representative sample of unrelated adolescents aged 16 through to 22 years (N_max = 3390).

RESULTS

At age 16, the GSCAN GPS predicted variance in alcohol consumption on a typical day (0.58 %), intake frequency (0.89 %), and hazardous drinking (i.e. ≥6 units at one occasion) (1.07 %). At age 22, the predictive power of the GPS had increased, explaining variance in alcohol consumption (0.61 %), intake frequency (1.69 %), and hazardous drinking (1.19 %).

CONCLUSIONS

The predictive validity of GPS for phenotypic alcohol use was evident in adolescence and increased in young adulthood. The findings suggest that GPS, which are available from birth, may be potentially useful for identifying individuals at risk for harmful and hazardous alcohol use. However, because the overall effect sizes were small, the utility of the GPS that are currently available is limited for the prediction of individual-level alcohol use.

Multivariable G-E interplay in the prediction of educational achievement

Polygenic scores are increasingly powerful predictors of educational achievement. It is unclear, however, how sets of polygenic scores, which partly capture environmental effects, perform jointly with sets of environmental measures, which are themselves heritable, in prediction models of educational achievement. Here, for the first time, we systematically investigate gene-environment correlation (rGE) and interaction (GxE) in the joint analysis of multiple genome-wide polygenic scores (GPS) and multiple environmental measures as they predict tested educational achievement (EA). We predict EA in a representative sample of 7,026 16-year-olds, with 20 GPS for psychiatric, cognitive and anthropometric traits, and 13 environments (including life events, home environment, and SES) measured earlier in life. Environmental and GPS predictors were modelled, separately and jointly, in penalized regression models with out-of-sample comparisons of prediction accuracy, considering the implications that their interplay had on model performance. Jointly modelling multiple GPS and environmental factors significantly improved prediction of EA, with cognitive-related GPS adding unique independent information beyond SES, home environment and life events. We found evidence for rGE underlying variation in EA (rGE = .38; 95% CIs = .30, .45). We estimated that 40% (95% CIs = 31%, 50%) of the polygenic scores effects on EA were mediated by environmental effects, and in turn that 18% (95% CIs = 12%, 25%) of environmental effects were accounted for by the polygenic model, indicating genetic confounding. Lastly, we did not find evidence that GxE effects significantly contributed to multivariable prediction. Our multivariable polygenic and environmental prediction model suggests widespread rGE and unsystematic GxE contributions to EA in adolescence.

Our study investigates the complex interplay between genetic and environmental contributions underlying educational achievement (EA). Polygenic scores are becoming increasingly powerful predictors of EA. While emerging evidence indicates that polygenic scores are not pure measures of genetic predisposition, previous quantitative genetics findings indicate that measures of the environment are themselves heritable. In this regard it is unclear how such measures of individual predisposition jointly combine to predict EA. We investigate this question in a representative UK sample of 7,026 16-year-olds where we provide substantive results on gene-environment correlation and interaction underlying variation in EA. We show that polygenic score and environmental prediction models of EA overlap substantially. Polygenic scores effects on EA are partly accounted for by their correlation with environmental effects; similarly, environmental effects on EA are linked to polygenic scores effects. Nonetheless, jointly considering polygenic scores and measured environments significantly improves prediction of EA. We also find that, although correlation between polygenic scores and measured environments is substantial, interactions between them do not play a significant role in the prediction of EA. Our findings have relevance for genomic and environmental prediction models alike, as they show the way in which individuals’ genetic predispositions and environmental effects are intertwined. This suggests that both genetic and environmental effects must be taken into account in prediction models of complex behavioral traits such as EA.

Sex differences in the relative influence of marital status and parenthood on alcohol use disorder symptoms: A multilevel discordant twin design

Marriage and parenthood are associated with alcohol use and use disorder (AUD), although they are confounded such that many studies struggle to identify their unique and/or causal effects. The present study utilized a genetically informed discordant twin design that strengthens the putative causal role of marital and parental status in the presentation of AUD symptoms by using each individual's cotwin as their own control while simultaneously modeling both predictors among men and women. Participants were 980 complete same-sex twin pairs from the Australian Twin Registry (M_age = 31.70 [SD = 2.48]; 71% women). Marital status, parental status, and past year AUD symptoms were assessed via semistructured interview. Three random-intercept generalized linear mixed models were fit in men and women including (a) marital status only, (b) parental status only, and (c) both marital and parental status; demographics, past year pregnancy, age of first drink, age of regular drinking, personality traits, and antisociality were included as covariates. Models tested for quasi-causal and familial effects. The sole-predictor marital status model (Model 1) provided the best fit among men, while the simultaneous-predictor marital and parental status model (Model 3) provided the best fit among women. Sole-predictor models showed familial effects of both predictors among men and quasi-causal and familial effects of both predictors among women; the simultaneous-predictor model revealed familial effects of marital status only among men and quasi-causal effects of parental status only among women. The present study elucidates important sex differences in the presentation of AUD among midlife adults in the context of notable developmental milestones. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain ~2.5-3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

FinnTwin12 Cohort: An Updated Review

This review offers an update on research conducted with FinnTwin12 (FT12), the youngest of the three Finnish Twin Cohorts. FT12 was designed as a two-stage study. In the first stage, we conducted multiwave questionnaire research enrolling all eligible twins born in Finland during 1983-1987 along with their biological parents. In stage 2, we intensively studied a subset of these twins with in-school assessments at age 12 and semistructured poly-diagnostic interviews at age 14. At baseline, parents of intensively studied twins were administered the adult version of the interview. Laboratory studies with repeat interviews, neuropsychological tests, and collection of DNA were made of intensively studied twins during follow-up in early adulthood. The basic aim of the FT12 study design was to obtain information on individual, familial and school/neighborhood risks for substance use/abuse prior to the onset of regular tobacco and alcohol use and then track trajectories of use and abuse and their consequences into adulthood. But the longitudinal assessments were not narrowly limited to this basic aim, and with multiwave, multirater assessments from ages 11 to 12, the study has created a richly informative data set for analyses of gene-environment interactions of both candidate genes and genomewide measures with measured risk-relevant environments. Because 25 years have elapsed since the start of the study, we are planning a fifth-wave follow-up assessment.

The Genetics of Externalizing Problems

Externalizing problems generally refer to a constellation of behaviors and/or disorders characterized by impulsive action and behavioral disinhibition. Phenotypes on the externalizing spectrum include psychiatric disorders, nonclinical behaviors, and personality characteristics (e.g. alcohol use disorders, other illicit substance use, antisocial behaviors, risky sex, sensation seeking, among others). Research using genetic designs including latent designs from twin and family data and more recent designs using genome-wide data reveal that these behaviors and problems are genetically influenced and largely share a common genetic etiology. Large-scale gene-identification efforts have started to identify robust associations between genetic variants and these phenotypes. However, there is still considerable work to be done. This chapter provides an overview of the current state of research into the genetics of behaviors and disorders on the externalizing spectrum.