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Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study.

ABSTRACT: Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all P_FDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

SUBMITTER: Modabbernia A

PROVIDER: S-EPMC7981783 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Binge drinking and age at first full drink (AFD) of alcohol prior to 21 years (AFD < 21) have been linked to neuroanatomical differences in cortical and subcortical grey matter (GM) volume, cortical thickness, and surface area. Despite the importance of understanding network-level relationships, structural covariation patterns among these morphological measures have yet to be examined in relation to binge drinking and AFD < 21. Here, we used the Joint and Individual Variance Explained (JIVE) method to characterize structural covariation patterns common across and specific to morphological measures in 293 participants (149 individuals with past-12-month binge drinking and 144 healthy controls) from the Human Connectome Project (HCP). An independent dataset (Nathan Kline Institute Rockland Sample; NKI-RS) was used to examine reproducibility/generalizability. We identified a reproducible joint component dominated by structural covariation between GM volume in the brainstem and thalamus proper, and GM volume and surface area in prefrontal cortical regions. Using linear mixed regression models, we found that participants with AFD < 21 showed lower joint component scores in both the HCP (beta = 0.059, p-value = 0.016; Cohen's d = 0.441) and NKI-RS (beta = 0.023, p-value = 0.040, Cohen's d = 0.216) datasets, whereas the individual thickness component associated with binge drinking (p-value = 0.02) and AFD < 21 (p-value < 0.001) in the HCP dataset was not statistically significant in the NKI-RS sample. Our findings were also generalizable to the HCP full sample (n = 880 participants). Taken together, our results show that use of JIVE analysis in high-dimensional, large-scale, psychiatry-related datasets led to discovery of a reproducible cortical and subcortical structural covariation pattern involving brain regions relevant to thalamic-PFC-brainstem neural circuitry which is related to AFD < 21 and suggests a possible extension of existing addiction neurocircuitry in humans.

Project description:ObjectiveWe aimed to assess the trends in body mass index (BMI) and body fat percentage (BF%) from the age of 13 to 17 years and to evaluate how sociodemographic and behavioural characteristics at the age of 13 impact changes in BMI and BF%.SettingPorto, Portugal.ParticipantsWe evaluated 1451 adolescents in a community-based cohort.Outcome measuresBMI z-scores were calculated according to CDC references. BF% was assessed by bioelectrical impedance. Variables with a significant effect in adiposity changes were identified through linear regression models. In girls, estimates were controlled for duration of follow-up, parental education, baseline BMI z-score, age at menarche and the interaction term baseline BMI z-score×age at menarche; in boys, adjustments were performed for duration of follow-up, parental education, baseline BMI z-score and the interaction term baseline BMI z-score×duration of follow-up.ResultsOn average, BMI z-score decreased from the age of 13 to 17 years (mean difference -0.20, 95% CI -0.23 to -0.16 among girls and -0.15, 95% CI -0.19 to -0.11 among boys). Accordingly, 12.4% of girls and 13% of boys moved to a lower BMI category and 2.2% of girls and 5.5% of boys to a higher category. There were sex differences in the significant determinants of adiposity trends. Among girls, BMI z-score significantly decreased with baseline BMI z-score (β=-0.163, 95% CI -0.204 to -0.122) and significantly increased with age at menarche (β=0.078, 95% CI 0.050 to 0.107). Results were similar for BF%. Among boys, BMI z-score significantly increased with higher parental BMI, and BF% decreased among those who wished to look larger at the age of 13 (β=-1.367, 95% CI -2.174 to -0.560), compared with those who were satisfied with their image.ConclusionsIn adolescents, ageing resulted in a decrease in BMI z-scores and BF%. BMI and BF% at the age of 13 were the major determinants of the observed trends. Our results suggest that adolescence is a possible specific time window for intervention.

Project description:ObjectiveAutistic traits are associated with alterations in brain morphology. However, the anatomic location of these differences and their developmental trajectories are unclear. The primary objective of this longitudinal study was to explore the bidirectional relationship between autistic traits and brain morphology from childhood to adolescence.MethodParticipants were drawn from a population-based cohort. Cross-sectional and longitudinal analyses included 1950 (mean age 13.5) and 304 participants (mean ages 6.2 and 13.5), respectively. Autistic traits were measured with the Social Responsiveness Scale. Global brain measures and surface-based measures of gyrification, cortical thickness and surface area were obtained from T1-weighted MRI scans. Cross-sectional associations were assessed using linear regression analyses. Cross-lagged panel models were used to determine the longitudinal bidirectional relationship between autistic traits and brain morphology.ResultsCross-sectionally, higher levels of autistic traits in adolescents are associated with lower gyrification in the pars opercularis, insula and superior temporal cortex; smaller surface area in the middle temporal and postcentral cortex; larger cortical thickness in the superior frontal cortex; and smaller cerebellum cortex volume. Longitudinally, both autistic traits and brain measures were quite stable, with neither brain measures predicting changes in autistic traits, nor vice-versa.LimitationsAutistic traits were assessed at only two time points, and thus we could not distinguish within- versus between-person effects. Furthermore, two different MRI scanners were used between baseline and follow-up for imaging data acquisition.ConclusionsOur findings point to early changes in brain morphology in children with autistic symptoms that remain quite stable over time. The observed relationship did not change substantially after excluding children with high levels of autistic traits, bolstering the evidence for the extension of the neurobiology of autistic traits to the general population.

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Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study.

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