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    Exploring the relationship between polygenic risk for cannabis use, peer cannabis use and the longitudinal course of cannabis involvement
    (Wiley, 2019) Johnson, Emma C.; Tillman, Rebecca; Aliev, Fazil; Meyers, Jacquelyn L.; Salvatore, Jessica E.; Anokhin, Andrey P.; Dick, Danielle M.
    Background and aims Few studies have explored how polygenic propensity to cannabis use unfolds across development, and no studies have yet examined this question in the context of environmental contributions such as peer cannabis use. Outlining the factors that contribute to progression from cannabis initiation to problem use over time may ultimately provide insights into mechanisms for targeted interventions. We sought to examine the relationships between polygenic liability for cannabis use, cannabis use trajectories from ages 12-30 years and perceived peer cannabis use at ages 12-17 years. Design Mixed-effect logistic and linear regressions were used to examine associations between polygenic risk scores, cannabis use trajectory membership and perceived peer cannabis use. Setting United States. Participants From the Collaborative Study on the Genetics of Alcoholism (COGA) study, a cohort of 1167 individuals aged 12-26 years at their baseline (i.e. first) interview. Measurements Key measurements included life-time cannabis use (yes/no), frequency of past 12-month cannabis use, maximum life-time frequency of cannabis use, cannabis use disorder (using DSM-5 criteria) and perceived peer cannabis use. Polygenic risk scores (PRS) were created using summary statistics from a large (n = 162 082) genome-wide association study (GWAS) of cannabis use. Findings Three trajectories reflecting no/low (n = 844), moderate (n = 137) and high (n = 186) use were identified. PRS were significantly associated with trajectory membership [P = 0.002-0.006, maximum conditional R-2 = 1.4%, odds ratios (ORs) = 1.40-1.49]. Individuals who reported that most/all of their best friends used cannabis had significantly higher PRS than those who reported that none of their friends were users [OR = 1.35, 95% confidence interval (CI) = 1.04, 1.75, P = 0.023]. Perceived peer use itself explained up to 11.3% of the variance in trajectory class membership (OR = 1.50-4.65). When peer cannabis use and the cannabis use PRS were entered into the model simultaneously, both the PRS and peer use continued to be significantly associated with class membership (P < 0.01). Conclusions Genetic propensity to cannabis use derived from heterogeneous samples appears to correlate with longitudinal increases in cannabis use frequency in young adults.
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    The Genetic Relationship Between Alcohol Consumption and Aspects of Problem Drinking in an Ascertained Sample
    (Wiley, 2019) Johnson, Emma C.; St Pierre, Celine L.; Meyers, Jacquelyn L.; Aliev, Fazil; McCutcheon, Vivia V.; Lai, Dongbing; Dick, Danielle M.
    Background Genomewide association studies (GWAS) have begun to identify loci related to alcohol consumption, but little is known about whether this genetic propensity overlaps with specific indices of problem drinking in ascertained samples. Methods In 6,731 European Americans who had been exposed to alcohol, we examined whether polygenic risk scores (PRS) from a GWAS of weekly alcohol consumption in the UK Biobank predicted variance in 6 alcohol-related phenotypes: alcohol use, maximum drinks within 24 hours (MAXD), total score on the Self-Rating of the Effects of Ethanol Questionnaire (SRE-T), DSM-IV alcohol dependence (DSM4AD), DSM-5 alcohol use disorder symptom counts (DSM5AUDSX), and reduction/cessation of problematic drinking. We also examined the extent to which an single nucleotide polymorphism (rs1229984) in ADH1B, which is strongly associated with both alcohol consumption and dependence, contributed to the polygenic association with these phenotypes and whether PRS interacted with sex, age, or family history of alcoholism to predict alcohol-related outcomes. We performed mixed-effect regression analyses, with family membership and recruitment site included as random effects, as well as survival modeling of age of onset of DSM4AD. Results PRS for alcohol consumption significantly predicted variance in 5 of the 6 outcomes: alcohol use (Delta marginal R-2 = 1.39%, Delta area under the curve [AUC] = 0.011), DSM4AD (Delta marginal R-2 = 0.56%; Delta AUC = 0.003), DSM5AUDSX (Delta marginal R-2 = 0.49%), MAXD (Delta marginal R-2 = 0.31%), and SRE-T (Delta marginal R-2 = 0.22%). PRS were also associated with onset of DSM4AD (hazard ratio = 1.11, p = 2.08e-5). The inclusion of rs1229984 attenuated the effects of the alcohol consumption PRS, particularly for DSM4AD and DSM5AUDSX, but the PRS continued to exert an independent effect for all 5 alcohol measures (Delta marginal R-2 after controlling for ADH1B = 0.14 to 1.22%). Interactions between PRS and sex, age, or family history were nonsignificant. Conclusions Genetic propensity for typical alcohol consumption was associated with alcohol use and was also associated with 4 of the additional 5 outcomes, though the variance explained in this sample was modest. Future GWAS that focus on the multifaceted nature of AUD, which goes beyond consumption, might reveal additional information regarding the polygenic underpinnings of problem drinking.
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    Intergenerational Continuity in Parents' and Adolescents' Externalizing Problems: The Role of Life Events and Their Interaction With GABRA2
    (Amer Psychological Assoc, 2015) Salvatore, Jessica E.; Meyers, Jacquelyn L.; Yan, Jia; Aliev, Fazil; Lansford, Jennifer E.; Pettit, Gregory S.; Bates, John E.
    We examine whether parental externalizing behavior has an indirect effect on adolescent externalizing behavior via elevations in life events, and whether this indirect effect is further qualified by an interaction between life events and adolescents' GABRA2 genotype (rs279871). We use data from 2 samples: the Child Development Project (CDP; n = 324) and FinnTwin12 (n = 802). In CDP, repeated measures of life events, mother-reported adolescent externalizing, and teacher-reported adolescent externalizing were used. In FinnTwin12, life events and externalizing were assessed at age 14. Parental externalizing was indexed by measures of antisocial behavior and alcohol problems or alcohol dependence symptoms in both samples. In CDP, parental externalizing was associated with more life events, and the association between life events and subsequent adolescent externalizing varied as a function of GABRA2 genotype (p <= .05). The association between life events and subsequent adolescent externalizing was stronger for adolescents with 0 copies of the G minor allele compared to those with 1 or 2 copies of the minor allele. Parallel moderation trends were observed in FinnTwin12 (p <= .11). The discussion focuses on how the strength of intergenerational pathways for externalizing psychopathology may differ as a function of adolescent-level individual differences.
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    Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach
    (Springernature, 2021) Kinreich, Sivan; McCutcheon, Vivia V.; Aliev, Fazil; Meyers, Jacquelyn L.; Kamarajan, Chella; Pandey, Ashwini K.; Chorlian, David B.
    Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N=1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.
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    Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples
    (Nature Publishing Group, 2020) Barr, Peter B.; Ksinan, Albert; Su, Jinni; Johnson, Emma C.; Meyers, Jacquelyn L.; Wetherill, Leah; Latvala, Antti
    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 similar to 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.