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Characterizing reward system neural trajectories from adolescence to young adulthood.

ABSTRACT: Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant's alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

SUBMITTER: Cao Z

PROVIDER: S-EPMC8668439 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceLittle is known about cannabis vaping trajectories across adolescence and young adulthood or the co-occurrence with nicotine vaping.ObjectiveTo evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to young adulthood (≥18 years of age) and the extent of polysubstance vaping.Design, setting, and participantsIn this prospective cohort study, 5 surveys (including information on substance vaped) were completed at 10 high schools in the Los Angeles, California, metro area. Students were surveyed at 6-month intervals from fall of 11th grade (October to December 2015; wave 5) through spring of 12th grade (March to June 2017; wave 8) and again approximately 1 to 2 years after high school (October 2018 to October 2019; wave 9).ExposuresPast 30-day nicotine and cannabis vaping frequency across 5 waves.Main outcomes and measuresSelf-reported frequency of nicotine vaping and cannabis vaping within the past 30 days across 5 time points from late adolescence to young adulthood. Trajectories were measured with these past 30-day use frequencies at each wave. Parallel growth mixture modeling estimated conditional probabilities of polysubstance vaping.ResultsThe analytic sample included 3322 participants with at least 1 time point of data (mean [SD] age, 16.50 [0.42] years at baseline; 1777 [53.5%] female; 1573 [47.4%] Hispanic or Latino). Growth mixture modeling identified the 5-trajectory model as optimal for both nicotine vaping and cannabis vaping. Trajectories for nicotine and cannabis vaping were similar (nonusers: 2246 [67.6%] nicotine, 2157 [64.9%] cannabis; infrequent users: 566 [17.0%] nicotine, 608 [18.3%] cannabis; moderate users: 167 [5.0%] nicotine, 233 [7.0%] cannabis; young adult-onset frequent users: 213 [6.4%] nicotine, 190 [5.7%] cannabis; adolescent-onset escalating frequent users: 131 [3.9%] nicotine, 134 [4.0%] cannabis). Males had greater odds of belonging to the adolescent-onset escalating frequent users nicotine (adjusted odds ratio, 2.88; 95% CI, 1.58-5.23; P < .01) and cannabis (adjusted odds ratio, 1.95; 95% CI,1.03-3.66; P < .05) vaping trajectories compared with nonusers. Polysubstance vaping was common, with those in trajectories reflecting more frequent nicotine vaping (adolescent-onset escalating frequent users and young adult-onset frequent users) having a high probability of membership (85% and 93%, respectively) in a cannabis-use trajectory.Conclusions and relevanceIn this cohort study, the prevalence and type of nicotine vaping and cannabis vaping developmental trajectories from late adolescence to young adulthood were similar. Polysubstance vaping was common from late adolescence to young adulthood, particularly among those reporting more frequent vaping use. The findings suggest that public health policy and clinical interventions should address polysubstance vaping in both adolescence and young adulthood.

Project description:ImportanceCharacterizing patterns of handgun carrying among adolescents and young adults can inform programs to reduce firearm-related harm. Longitudinal patterns of handgun carrying among rural adolescents have not been identified.ObjectivesTo assess specific points of intervention by characterizing patterns of handgun carrying by youths in rural communities from early adolescence to young adulthood and to quantify how age at initiation, duration, and frequency of carrying differ across identified patterns.Design, setting, and participantsThis cohort study uses the control group of the community-randomized trial of the Communities That Care prevention system, conducted among public school students in 12 rural communities across 7 states. Participants self-reported their handgun carrying at 10 data collection points from 12 to 26 years of age (2005-2019). Data were analyzed from January to July 2021.Main outcomes and measuresHandgun carrying in the past 12 months. Latent class growth analysis was used to estimate handgun carrying trajectories.ResultsIn this longitudinal rural sample of 2002 students, 1040 (51.9%) were male; 532 (26.6%) were Hispanic, Latino, Latina, or Latinx; 1310 (65.4%) were White; and the highest level of educational attainment of either parent was a high school degree or less for 649 students (32.4%). The prevalence of handgun carrying in the last 12 months ranged from 5.3% (95 of 1795) to 7.4% (146 of 1969) in adolescence and increased during the mid-20s (range, 8.9% [154 of 1722] to 10.9% [185 of 1704] from 23 to 26 years of age). Among the participants who reported handgun carrying at least once between 12 and 26 years of age (n = 601 [30.0%]), 320 (53.2%) reported carrying a handgun in only 1 wave. Latent class growth analysis indicated 6 longitudinal trajectories: never or low probability of carrying (1590 [79.4%]), emerging adulthood carrying (166 [8.3%]), steadily increasing carrying (163 [8.1%]), adolescent carrying (53 [2.6%]), declining carrying (24 [1.2%]), and high probability and persistent carrying (6 [0.3%]). The earliest mean (SD) age at initiation of handgun carrying occurred in both the adolescent and declining carrying groups at the ages of 12.6 (0.9) and 12.5 (0.7) years, respectively. More than 20% of some groups (emerging adulthood [age 26 years: 49 of 154 (31.8%)], steadily increasing [age 26 years: 37 of 131 (28.2%)], declining [age 13 years: 7 of 23 (30.4%)], and high probability and persistent carrying [age 15 years: 3 of 6 (50.0%)]) reported carrying 40 times or more in the past year by the age of 26 years.Conclusions and relevanceThis study found distinct patterns of handgun carrying from adolescence to young adulthood in rural settings. Findings suggest that promoting handgun safety in rural areas should start early. Potential high-risk trajectories, including carrying at high frequencies, should be the focus of future work to explore the antecedents and consequences of handgun carrying in rural areas.

Project description:BackgroundAdolescence is a critical period for the development of eating disorders, but data is lacking on the heterogeneity of their evolution during that time-period. Group-based trajectories can be used to understand how eating disorders emerge and evolve over time. The aim of this study was to identify groups of individuals with distinct levels of eating disorder symptoms between 12 and 20 years and the onset of different types of symptoms. We also studied sex differences in the evolution and course of eating disorder symptoms from early adolescence to adulthood.MethodsUsing archival data from the QLSCD cohort, trajectories of eating disorder symptomatology were estimated from ages 12 to 20 years using semiparametric models. These trajectories included overall eating disorder symptomatology as measured by the SCOFF (Sick, Control, One Stone, Fat, Food), sex, and symptom-specific trajectories.ResultsTwo groups of adolescents following distinct trajectories of eating disorder symptoms were identified. The first trajectory group included 30.9% of youth with sharply rising levels between 12 and 15 years, followed by high levels of symptoms between 15 and 20 years. The second trajectory group included 69.1% of youth with low and stable levels of symptoms between 12 and 20 years. Sex-specific models indicated that the proportion of girls in the high trajectory group was 1.3 times higher than the proportion of boys (42.8% girls vs. 32.3% boys). Trajectories of SCOFF items were similar for loss-of-control eating, feeling overweight, and attributing importance to food. The weight loss item had a different developmental pattern, increasing between 12 and 15 years and then decreasing between 17 and 20 years.ConclusionsThe largest increase in eating disorder symptoms in adolescence is between the ages of 12 and 15 . Yet, most prevention programs start after 15 years of age. Our findings suggest that, unlike common practices, eating disorder prevention programs should aim to start before puberty.

Project description:BackgroundReports on body mass index (BMI) trajectories from childhood into late adolescence, their determinants, and subsequent cardiometabolic risk markers, particularly among European populations have been few. Moreover, sex-specific investigation is necessary considering the sex difference in BMI, and the sex-specific association between BMI and some cardiometabolic risk markers.MethodsUsing a sample from the DOrtmund Nutritional and Anthropometric Longitudinally Designed study, we explored sex-specific trajectories of the BMI standard deviation score (SDS) from 4 to 18 years of age in 354 males and 335 females by latent (class) growth models. The determinants of trajectory were assessed by logistic regression. We identified cardiometabolic risk markers that were highly associated with BMI SDS trajectory by random forest regression, and finally we used generalized linear models to investigate differences in the identified cardiometabolic risk markers between pairs of trajectories.ResultsWe observed four: 'low-normal weight', 'mid-normal weight', 'high-normal weight', and 'overweight', and three: ''low-normal weight', 'mid-normal weight', and 'high-normal weight' trajectories in males and females, respectively. Higher maternal prepregnancy BMI was associated with the 'overweight' trajectory, and with 'high-normal weight' trajectory in both sexes. In addition, employed mothers and first-born status were associated with 'high-normal weight' trajectory in females. BMI SDS trajectory was associated with high-density lipoprotein-cholesterol and interleukin-18 (IL-18) in males, and diastolic blood pressure and interleukin-6 (IL-6) in females. However, only males following the 'overweight' trajectory had significantly higher IL-18 when compared to their 'low-normal weight' counterpart.ConclusionsWe identified sex-specific distinct trajectories of BMI SDS from childhood into late adolescence, higher maternal prepregnancy BMI as a common determinant of the 'high-normal weight' and 'overweight' trajectories, and 'overweight' trajectory being associated with elevated IL-18 in late adolescence-young adulthood. This study emphasizes the role of maternal prepregnancy BMI in overweight, and highlights IL-18 as a cardiometabolic signature of overweight across life.

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Characterizing reward system neural trajectories from adolescence to young adulthood.

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