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Funder: Cambridge Trust (University of Cambridge); Id: http://dx.doi.org/10.13039/501100000735, Funder: National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Funder: Maudsley NHS Foundation Trust and King's College London, Funder: Medical Research Foundation; Id: http://dx.doi.org/10.13039/501100009187, Funder: Mission Interministérielle de Lutte‐contre‐les‐Drogues‐et‐les‐Conduites‐Addictives (MILDECA), Funder: Assistance‐Publique‐Hôpitaux‐de‐Paris and INSERM, Funder: Paris Sud University IDEX 2012, Funder: Fédération pour la Recherche sur le Cerveau; Id: http://dx.doi.org/10.13039/501100006424, BACKGROUND: Stress exposure in childhood and adolescence has been linked to reductions in cortical structures and cognitive functioning. However, to date, most of these studies have been cross-sectional, limiting the ability to make long-term inferences, given that most cortical structures continue to develop through adolescence. METHODS: Here, we used a subset of the IMAGEN population cohort sample (N = 502; assessment ages: 14, 19, and 22 years; mean age: 21.945 years; SD = 0.610) to understand longitudinally the long-term interrelations between stress, cortical development, and cognitive functioning. To these ends, we first used a latent change score model to examine four bivariate relations - assessing individual differences in change in the relations between adolescent stress exposure and volume, surface area, and cortical thickness of cortical structures, as well as cognitive outcomes. Second, we probed for indirect neurocognitive effects linking stress to cortical brain structures and cognitive functions using rich longitudinal mediation modeling. RESULTS: Latent change score modeling showed that greater baseline adolescence stress at age 14 predicted a small reduction in the right anterior cingulate volume (Std. β = -.327, p = .042, 95% CI [-0.643, -0.012]) and right anterior cingulate surface area (Std. β = -.274, p = .038, 95% CI [-0.533, -0.015]) across ages 14-22. These effects were very modest in nature and became nonsignificant after correcting for multiple comparisons. Our longitudinal analyses found no evidence of indirect effects in the two neurocognitive pathways linking adolescent stress to brain and cognitive outcomes. CONCLUSION: Findings shed light on the impact of stress on brain reductions, particularly in the prefrontal cortex that have consistently been implicated in the previous cross-sectional studies. However, the magnitude of effects observed in our study is smaller than that has been reported in past cross-sectional work. This suggests that the potential impact of stress during adolescence on brain structures may likely be more modest than previously noted.

IMPORTANCE: Arsenic, a contaminant of groundwater and irrigated crops, is a global public health hazard. Exposure to low levels of arsenic through food extends well beyond the areas with high arsenic content in water.OBJECTIVE: To identify cognitive impairments following commonly prevalent low-level arsenic exposure and characterize their underlying brain mechanisms.DESIGN, SETTING, AND PARTICIPANTS: This multicenter population-based cohort study analyzed cross-sectional data of the Indian Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, recruited between November 4, 2016, and May 4, 2019. Participants aged 6 to 23 years were characterized using deep phenotyping measures of behavior, neuropsychology, psychopathology, brain neuroimaging, and exposure to developmental adversities and environmental neurotoxins. All analyses were performed between June 1, 2020, and December 31, 2021.EXPOSURE: Arsenic levels were measured in urine as an index of exposure.MAIN OUTCOMES AND MEASURES: Executive function measured using the cVEDA neuropsychological battery, gray matter volume (GMV) from T1-weighted magnetic resonance imaging, and functional network connectivity measures from resting state functional magnetic resonance imaging.RESULTS: A total of 1014 participants aged 6 to 23 years (589 male [58.1%]; mean [SD] age, 14.86 [4.79] years) were included from 5 geographic locations. Sparse-partial least squares analysis was used to describe a negative association of arsenic exposure with executive function (r = -0.12 [P = 5.4 × 10-4]), brain structure (r = -0.20 [P = 1.8 × 10-8]), and functional connectivity (within network, r = -0.12 [P = 7.5 × 10-4]; between network, r = -0.23 [P = 1.8 × 10-10]). Alterations in executive function were partially mediated by GMV (b = -0.004 [95% CI, -0.007 to -0.002]) and within-network functional connectivity (b = -0.004 [95% CI, -0.008 to -0.002]). Socioeconomic status and body mass index moderated the association between arsenic and GMV, such that the association was strongest in participants with lower socioeconomic status and body mass index.CONCLUSIONS AND RELEVANCE: The findings of this cross-sectional study suggest that low-level arsenic exposure was associated with alterations in executive functioning and underlying brain correlates. These results indicate potential detrimental consequences of arsenic exposure that are below the currently recommended guidelines and may extend beyond endemic risk areas. Precision medicine approaches to study global mental health vulnerabilities highlight widespread but potentially modifiable risk factors and a mechanistic understanding of the impact of low-level arsenic exposure on brain development.

et al., Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging., The ENIGMA-Plasticity Working Group is part of the ENIGMA World Aging Center, funded by NIA grants R56 AG058854 and R01 AG058854. The ENIGMA Consortium core funding was supported by NIH Consortium Grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centers of Excellence. 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported, in part, by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 785907 (Human Brain Project SGA2; Svenja Caspers, Sven Cichon and Katrin Amunts). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A; Sven Cichon) and by the Swiss National Science Foundation (SNSF, grant 156791; Sven Cichon). The authors acknowledge grants supporting their work from the European Union’s Horizon 2020 Research and Innovation Programme (H2020/2014–2020) under grant agreements 667302 (CoCA), 728018 (Eat2beNICE), 785907 (HBP SGA2) and 772376 (EScORIAL) and the Netherlands ALS Foundation.Additional support is received from the European Community’s Seventh Framework Programme (FP7/2007—2013) under grant agreements n° 602805 (Aggressotype), n° 603016 (MATRICS), n° 602450 (IMAGEMEND) and n° 278948 (TACTICS) and from the European Community’s Horizon 2020 Programme (H2020/2014—2020) under grant agreements n° 643051 (MiND) and n° 667302 (CoCA). FP7 Ideas: the European Research Council (ERC-230374 to D.B.). This work was supported by Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012 and PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7- HEALTH-2013-2.2.1-2-603196 (Project PSYSCAN) and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement 115916, Project PRISM and grant agreement 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. The Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313). The FP7 project MATRICS (603016). The research leading to these results also received support from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement 278948 (TACTICS), 602805 (Aggressotype), 603016 (MATRICS) and 602450 (Imagemend) and the Innovation Medicine Initiative grants 115300 (EU-AIMS) and 777394 (AIMS-2-TRIALS).PAFIP: PAFIP was supported by the Instituto de Salud Carlos III (PI14/00639, PI14/00918 and PI17/01056) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT025KG Jebsen Stiftelsen and H2020 CoMorMent (847776).34363). European Union Marie Curie Research Training Network (MRTN-CT-2006-035987).

BACKGROUND AND AIMS: Graph theoretic analysis of structural covariance networks (SCN) provides an assessment of brain organization that has not yet been applied to alcohol dependence (AD). We estimated whether SCN differences are present in adults with AD and heavy-drinking adolescents at age 19 and age 14, prior to substantial exposure to alcohol. DESIGN: Cross-sectional sample of adults and a cohort of adolescents. Correlation matrices for cortical thicknesses across 68 regions were summarized with graph theoretic metrics. SETTING AND PARTICIPANTS: A total of 745 adults with AD and 979 non-dependent controls from 24 sites curated by the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA)-Addiction consortium, and 297 hazardous drinking adolescents and 594 controls at ages 19 and 14 from the IMAGEN study, all from Europe. MEASUREMENTS: Metrics of network segregation (modularity, clustering coefficient and local efficiency) and integration (average shortest path length and global efficiency). FINDINGS: The younger AD adults had lower network segregation and higher integration relative to non-dependent controls. Compared with controls, the hazardous drinkers at age 19 showed lower modularity [area-under-the-curve (AUC) difference?=?-0.0142, 95% confidence interval (CI)?=?-0.1333, 0.0092; P-value?=?0.017], clustering coefficient (AUC difference?=?-0.0164, 95% CI?=?-0.1456, 0.0043; P-value?=?0.008) and local efficiency (AUC difference?=?-0.0141, 95% CI?=?-0.0097, 0.0034; P-value?=?0.010), as well as lower average shortest path length (AUC difference?=?-0.0405, 95% CI?=?-0.0392, 0.0096; P-value?=?0.021) and higher global efficiency (AUC difference?=?0.0044, 95% CI?=?-0.0011, 0.0043; P-value?=?0.023). The same pattern was present at age 14 with lower clustering coefficient (AUC difference?=?-0.0131, 95% CI?=?-0.1304, 0.0033; P-value?=?0.024), lower average shortest path length (AUC difference?=?-0.0362, 95% CI?=?-0.0334, 0.0118; P-value?=?0.019) and higher global efficiency (AUC difference?=?0.0035, 95% CI?=?-0.0011, 0.0038; P-value?=?0.048). CONCLUSIONS: Cross-sectional analyses indicate that a specific structural covariance network profile is an early marker of alcohol dependence in adults. Similar effects in a cohort of heavy-drinking adolescents, observed at age 19 and prior to substantial alcohol exposure at age 14, suggest that this pattern may be a pre-existing risk factor for problematic drinking.

It has been suggested that autistic traits are associated with less frequent alcohol use in adolescence. Our study seeks to examine the relationship between autistic traits and alcohol use in a large adolescent population. Leveraging data from the IMAGEN cohort, including 2045 14-year-old adolescents that were followed-up to age 18, we selected items on social preference/skills and rigidity from different questionnaires. We used linear regression models to (1) test the effect of the sum scores on the prevalence of alcohol use (AUDIT-C) over time, (2) explore the relationship between autistic traits and alcohol use patterns, and (3) explore the specific effect of each autistic trait on alcohol use. Higher scores on the selected items were associated with trajectories of less alcohol use from the ages between 14 and 18 (b = ? 0.030; CI 95% = ? 0.042, ? 0.017; p < 0.001). Among adolescents who used alcohol, those who reported more autistic traits were also drinking less per occasion than their peers and were less likely to engage in binge drinking. We found significant associations between alcohol use and social preference (p < 0.001), nervousness for new situations (p = 0.001), and detail orientation (p < 0.001). Autistic traits (social impairment, detail orientation, and anxiety) may buffer against alcohol use in adolescence.

Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions.

Adolescence is a period of vulnerability for the maturation of gray matter (GM) and also for the onset of psychiatric disorders such as major depressive disorder (MDD), bipolar disorder and schizophrenia. Chronic neuroinflammation is considered to play a role in the etiology of these illnesses. However, the involvement of neuroinflammation in the observed link between regional GM volume reductions and psychiatric symptoms is not established yet. Here, we investigated a possible common immune-related genetic link between these two phenomena in european adolescents recruited from the community. Hippocampal and medial prefrontal cortex (mPFC) were defined a priori as regions of interest (ROIs). Their GM volumes were extracted in 1,563 14-year-olds from the IMAGEN database. We found a set of 26 SNPs that correlated with the hippocampal volumes and 29 with the mPFC volumes at age 14. We formed two ROI-Related Immune-gene scores (RRI) with the inflammation SNPs that correlated to hippocampal GM volume and to mPFC GM volume. The predictive ability of both RRIs with regards to the presence of psychiatric symptoms at age 18 was investigated by correlating the RRIs with psychometric questionnaires obtained at age 18. The RRIs (but not control scores constructed with random SNPs) correlated with the presence of depressive symptoms, positive psychotic symptoms, and externalizing symptoms in later adolescence. In addition, the effect of childhood maltreatment, one of the major environmental risk factors for depression and other mental disorders, interacted with the RRI effect. We next sought to validate this finding by investigating our set of inflammatory genes in a translational animal model of early life adversity. Mice were subjected to a protocol of maternal separation at an early post-natal age. We evaluated depressive behaviors in separated and non-separated mice at adolescence and their correlations with the concomitant expression of our genes in whole blood samples. We show that in mice, early life adversity affected the expression of our set of genes in peripheral blood, and that levels of expression correlated with symptoms of negative affect in adolescence. Overall, our translational findings in adolescent mice and humans provide a novel validated gene-set of immune-related genes for further research in the early stages of mood disorders.

IMPORTANCE Animal studies have shown that the adolescent brain is sensitive to disruptions in endocannabinoid signaling, resulting in altered neurodevelopment and lasting behavioral effects. However, few studies have investigated ties between cannabis use and adolescent brain development in humans.OBJECTIVE To examine the degree to which magnetic resonance (MR) imaging–assessed cerebral cortical thickness development is associated with cannabis use in a longitudinal sample of adolescents.DESIGN, SETTING, AND PARTICIPANTS Data were obtained from the community-based IMAGEN cohort study, conducted across 8 European sites. Baseline data used in the present study were acquired from March 1, 2008, to December 31, 2011, and follow-up data were acquired from January 1, 2013, to December 31, 2016. A total of 799 IMAGEN participants were identified who reported being cannabis naive at study baseline and had behavioral and neuroimaging data available at baseline and 5-year follow-up. Statistical analysis was performed from October 1, 2019, to August 31, 2020.MAIN OUTCOMES AND MEASURES Cannabis use was assessed at baseline and 5-year follow-up with the European School Survey Project on Alcohol and Other Drugs. Anatomical MR images were acquired with a 3-dimensional T1-weighted magnetization prepared gradient echo sequence. Quality-controlled nativeMR images were processed through the CIVET pipeline, version 2.1.0.RESULTS The study evaluated 1598 MR images from 799 participants (450 female participants [56.3%]; mean [SD] age, 14.4 [0.4] years at baseline and 19.0 [0.7] years at follow-up). At 5-year follow-up, cannabis use (from 0 to >40 uses) was negatively associated with thickness in left prefrontal (peak: t785 = –4.87, cluster size = 1558 vertices; P = 1.10 × 10−6, random field theory cluster corrected) and right prefrontal (peak: t785 = –4.27, cluster size = 1551 vertices; P = 2.81 × 10−5, random field theory cluster corrected) cortices. There were no significant associations between lifetime cannabis use at 5- year follow-up and baseline cortical thickness, suggesting that the observed neuroanatomical differences did not precede initiation of cannabis use. Longitudinal analysis revealed that age-related cortical thinning was qualified by cannabis use in a dose-dependent fashion such that greater use, from baseline to follow-up, was associated with increased thinning in left prefrontal (peak: t815.27 = –4.24, cluster size = 3643 vertices; P = 2.28 × 10−8, random field theory cluster corrected) and right prefrontal (peak: t813.30 = –4.71, cluster size = 2675 vertices; P = 3.72 × 10−8, random field theory cluster corrected) cortices. The spatial pattern of cannabis-related thinning was associated with age-related thinning in this sample (r = 0.540; P less than< .001), and a positron emission tomography–assessed cannabinoid 1 receptor–binding map derived from a separate sample of participants (r = −0.189; P less than .001). Analysis revealed that thinning in right prefrontal cortices, from baseline to follow-up, was associated with attentional impulsiveness at follow-up.CONCLUSIONS AND RELEVANCE Results suggest that cannabis use during adolescence is associated with altered neurodevelopment, particularly in cortices rich in cannabinoid 1 receptors and undergoing the greatest age-related thickness change in middle to late adolescence.

Changing sleep rhythms in adolescents often lead to sleep deficits and a delay in sleep timing between weekdays and weekends. The adolescent brain, and in particular the rapidly developing structures involved in emotional control, are vulnerable to external and internal factors. In our previous study in adolescents at age 14, we observed a strong relationship between weekend sleep schedules and regional medial prefrontal cortex grey matter volumes. Here, we aimed to assess whether this relationship remained in this group of adolescents of the general population at the age of 16 (n = 101; mean age 16.8 years; 55% girls). We further examined grey matter volumes in the hippocampi and the amygdalae, calculated with voxel-based morphometry. In addition, we investigated the relationships between sleep habits, assessed with self-reports, and regional grey matter volumes, and psychological functioning, assessed with the Strengths and Difficulties Questionnaire and tests on working memory and impulsivity. Later weekend wake-up times were associated with smaller grey matter volumes in the medial prefrontal cortex and the amygdalae, and greater weekend delays in wake-up time were associated with smaller grey matter volumes in the right hippocampus and amygdala. The medial prefrontal cortex region mediated the correlation between weekend wake up time and externalising symptoms. Paying attention to regular sleep habits during adolescence could act as a protective factor against the emergence of psychopathology via enabling favourable brain development. publishedVersion

Contemporary theories propose that dysregulation of emotional perception is involved in the aetiology of psychosis. 298 healthy adolescents were assessed at age 14- and 19-years using fMRI while performing a facial emotion task. Psychotic-like experiences (PLEs) were assessed with the CAPE-42 questionnaire at age 19. The high PLEs group at age 19 years exhibited an enhanced response in right insular cortex and decreased response in right prefrontal, right parahippocampal and left striatal regions; also, a gradient of decreasing response to emotional faces with age, from 14 to 19 years, in the right parahippocampal region and left insular cortical area. The right insula demonstrated an increasing response to emotional faces with increasing age in the low PLEs group, and a decreasing response over time in the high PLEs group. The change in parahippocampal / amygdala and insula responses during the perception of emotional faces in adolescents with high PLEs between the ages of 14 and 19 suggests a potential ‘aberrant’ neurodevelopmental trajectory for critical limbic areas. Our findings emphasize the role of the frontal and limbic areas in the aetiology of psychotic symptoms, in subjects without the illness phenotype and the confounds introduced by antipsychotic medication.

Genetic and environmental factors both contribute to cognitive test performance. A substantial increase in average intelligence test results in the second half of the previous century within one generation is unlikely to be explained by genetic changes. One possible explanation for the strong malleability of cognitive performance measure is that environmental factors modify gene expression via epigenetic mechanisms. Epigenetic factors may help to understand the recent observations of an association between dopamine-dependent encoding of reward prediction errors and cognitive capacity, which was modulated by adverse life events. The possible manifestation of malleable biomarkers contributing to variance in cognitive test performance, and thus possibly contributing to the "missing heritability" between estimates from twin studies and variance explained by genetic markers, is still unclear. Here we show in 1475 healthy adolescents from the IMaging and GENetics (IMAGEN) sample that general IQ (gIQ) is associated with (1) polygenic scores for intelligence, (2) epigenetic modification of DRD2 gene, (3) gray matter density in striatum, and (4) functional striatal activation elicited by temporarily surprising reward-predicting cues. Comparing the relative importance for the prediction of gIQ in an overlapping subsample, our results demonstrate neurobiological correlates of the malleability of gIQ and point to equal importance of genetic variance, epigenetic modification of DRD2 receptor gene, as well as functional striatal activation, known to influence dopamine neurotransmission. Peripheral epigenetic markers are in need of confirmation in the central nervous system and should be tested in longitudinal settings specifically assessing individual and environmental factors that modify epigenetic structure., Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe, 950

Objective: To characterize the structural and functional neurobiology of a large group of adolescents exhibiting a behaviorally and emotionally dysregulated phenotype.Methods: Age 14 adolescents from the IMAGEN study were investigated. Latent class analysis (LCA) on the Strengths and Difficulties Questionnaire (SDQ) was used to identify a class of individuals with elevated behavioral and emotional difficulties (“dysregulated”; N=233) who were compared to a matched sample from a low symptom class (controls, N=233). Whole-brain gray matter volume (GMV) images were compared using a general linear model with 10,000 random label permutations. Regional GMV findings were then probed for functional differences from three fMRI tasks. Significant brain features then informed mediation path models linking the likelihood of psychiatric disorders (DSM-IV) with dysregulation.Results: Whole-brain differences were found in the right orbitofrontal cortex (R.OFC; p less than .05; k=48), with dysregulated individuals exhibiting lower GMV. The dysregulated group also exhibited higher activity in this region during successful inhibitory control (F1,429=7.53, p less than .05). Path analyses indicated significant direct effects between the likelihood of psychopathologies and dysregulation. Modeling the R.OFC as a mediator returned modest partial effects, suggesting the path linking the likelihood of an anxiety or conduct disorder diagnoses to dysregulation is partially explained by this anatomical feature.Conclusion: A large sample of dysregulated adolescents exhibited lower GMV in the R.OFC relative to controls. Dysregulated individuals also exhibited higher regional activations when exercising inhibitory control at performance levels comparable to controls. These findings suggest a neurobiological marker of dysregulation, and highlight the role of the R.OFC in impaired emotional and behavioral control.