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Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18–65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.
Researchers have identified genetic and neural risk factors for externalizing behaviors. However, it has not yet been determined if genetic liability is conferred in part through associations with more proximal neurophysiological risk markers.
Participants from the Collaborative Study on the Genetics of Alcoholism, a large, family-based study of alcohol use disorders were genotyped and polygenic scores for externalizing (EXT PGS) were calculated. Associations with target P3 amplitude from a visual oddball task (P3) and broad endorsement of externalizing behaviors (indexed via self-report of alcohol and cannabis use, and antisocial behavior) were assessed in participants of European (EA; N = 2851) and African ancestry (AA; N = 1402). Analyses were also stratified by age (adolescents, age 12–17 and young adults, age 18–32).
The EXT PGS was significantly associated with higher levels of externalizing behaviors among EA adolescents and young adults as well as AA young adults. P3 was inversely associated with externalizing behaviors among EA young adults. EXT PGS was not significantly associated with P3 amplitude and therefore, there was no evidence that P3 amplitude indirectly accounted for the association between EXT PGS and externalizing behaviors.
Both the EXT PGS and P3 amplitude were significantly associated with externalizing behaviors among EA young adults. However, these associations with externalizing behaviors appear to be independent of each other, suggesting that they may index different facets of externalizing.
Genetic factors contribute to the intergenerational transmission of alcohol misuse, but not all individuals at high genetic risk develop problems. The present study examined adolescent relationships with parents, peers, and romantic partners as predictors of realized resistance, defined as high biological risk for disorder combined with a healthy outcome, to alcohol initiation, heavy episodic drinking, and alcohol use disorder (AUD). Data were from the Collaborative Study on the Genetics of Alcoholism (N = 1,858; 49.9% female; mean age at baseline = 13.91 years). Genetic risk, indexed using family history density and polygenic risk scores for alcohol problems and AUD, was used to define alcohol resistance. Adolescent predictors included parent-child relationship quality, parental monitoring, peer drinking, romantic partner drinking, and social competence. There was little support for the hypothesis that social relationship factors would promote alcohol resistance, with the exception that higher father-child relationship quality was associated with higher resistance to alcohol initiation (
$$\hat \beta $$
= −0.19, 95% CI = −0.35, −0.03). Unexpectedly, social competence was associated with lower resistance to heavy episodic drinking (
$$\hat \beta $$
= 0.10, 95% CI = 0.01, 0.20). This pattern of largely null effects underscores how little is known about resistance processes among those at high genetic risk for AUD.
Despite the simplicity of Kurzban et al.'s framework, we argue that important information is lost in their simplification. We discuss research on delay of gratification and self-regulation that identifies key situational and psychological factors affecting how people represent rewards and costs. These factors affect the expected utilities of behavioral options and thus dramatically influence whether individuals persist on a difficult task.
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