Risk profiles for heavy drinking in adolescence: differential effects of gender

Abstract

Abnormalities across different domains of neuropsychological functioning may constitute a risk factor for heavy drinking during adolescence and for developing alcohol use disorders later in life. However, the exact nature of such multi-domain risk profiles is unclear, and it is further unclear whether these risk profiles differ between genders. We combined longitudinal and cross-sectional analyses on the large IMAGEN sample (N ≈ 1000) to predict heavy drinking at age 19 from gray matter volume as well as from psychosocial data at age 14 and 19-for males and females separately. Heavy drinking was associated with reduced gray matter volume in 19-year-olds' bilateral ACC, MPFC, thalamus, middle, medial and superior OFC as well as left amygdala and anterior insula and right inferior OFC. Notably, this lower gray matter volume associated with heavy drinking was stronger in females than in males. In both genders, we observed that impulsivity and facets of novelty seeking at the age of 14 and 19, as well as hopelessness at the age of 14, are risk factors for heavy drinking at the age of 19. Stressful life events with internal (but not external) locus of control were associated with heavy drinking only at age 19. Personality and stress assessment in adolescents may help to better target counseling and prevention programs. This might reduce heavy drinking in adolescents and hence reduce the risk of early brain atrophy, especially in females. In turn, this could additionally reduce the risk of developing alcohol use disorders later in adulthood.

Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls

“…Our results support our first hypothesis, showing that neural PIT signatures based on fMRI data gathered from the affective mixed-gambles task may successfully classify out-of-sample subjects into GD and HC, with a cross-validated mean AUC-ROC of 70.0% (p = 0.013). This performance on out-of sample data is similar to other studies using MRI data for classification in the field of addictive disorders (Guggenmos et al, 2018;Pariyadath, Stein, & Ross, 2014;Seo et al, 2018Seo et al, , 2015Whelan et al, 2014). To our knowledge, however, the present study is Alexander Genauck 32 the first one to use fMRI classification for investigating a behavioral addiction, namely GD, and the neural basis of increased PIT.…”

“…We therefore compiled a feature vector comprised of cue reactivity and PIT-related contrasts in amygdala and NAcc, and of functional connectivity parameters in a network of NAcc, amygdala and OFC. Hence the feature vector represented each subject's neural PIT signature, in the form of multiple functional magnetic resonance imaging (fMRI) aggregates (Seo et al, 2018(Seo et al, , 2015Whelan et al, 2014). We used all subjects' neural PIT signatures to estimate a classifier which would Alexander Genauck 11 distinguish GD from HC subjects.…”

Sex/gender differences in brain function and structure in alcohol use: A narrative review of neuroimaging findings over the last 10 years

“…et al, 2008). This is consistent with gray matter atrophy in PFC being more strongly associated with heavy drinking in females compared to males (Seo et al, 2019). Adolescent female binge drinkers also exhibited ~8% thicker frontal cortices compared to same-sex controls, which was associated with worse cognitive performances, while male binge drinkers had ~7% thinner cortices compared to same-sex controls (Squeglia et al, 2012).…”

“…Although, Seo and colleagues (2019) found that atrophy of gray matter in thalamus and other regions was more strongly associated with heavy drinking in females compared to males (Seo et al, 2019).…”

Predicting future drinking among young adults: using ensemble machine-learning to combine MRI with psychometrics and behaviour

“…We further found that reduced grey matter volume in the OFC and anterior PFC predicted future drinking only. Previous studies have found lower OFC volumes in heavy drinkers (54) and relapsers (55). Whether OFC volumetric changes are a pre-existing risk factor for alcohol use thus remains to be examined.…”