BACKGROUND:Childhood maltreatment (CM), encompassing abuse and neglect, is highly prevalent and associated with elevated risk for major depressive disorder (MDD), posttraumatic stress disorder (PTSD), and other related conditions. However, the extent to which neuroanatomical alterations in MDD and PTSD are attributable to CM is uncertain. METHODS:Here, we analyzed CM and whole-brain magnetic resonance imaging (MRI) data from 3711 participants in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) MDD and PTSD Working Groups (25 sites; mean age = 33.3 ± 13.0 years; 59.9% female). Normative modeling estimated deviation z scores for 14 subcortical volume, 68 cortical thickness (CT), and 68 surface area (SA) measures. To identify transdiagnostic effects, associations between CM and brain deviation scores were evaluated across all participants (patients and healthy control participants) stratified by sex and 3 age bins (pediatric, young adult, older adult). RESULTS:In young adults (ages 18-35), abuse was associated with larger volumes in the thalamus and pallidum, thinner isthmus cingulate and middle frontal regions, and thicker medial orbitofrontal cortex; there were no significant effects in pediatric (≤18 years) participants. The strongest effects were observed in young female adults (|β| = 0.07-0.22, q < .05): Greater abuse and neglect were correlated with smaller hippocampus and putamen volumes, thinner entorhinal cortex, and smaller SA in fusiform/inferior parietal regions and with larger SA in the orbitofrontal and occipital cortices. In males, abuse had widespread effects on CT and SA (|β| = 0.1-0.18, q < .05); effects for neglect were minimal. CONCLUSIONS:Our findings of age- and sex-specific instantiations of CM on brain morphometry highlight the importance of developmental context in understanding how adverse experiences shape neurobiological vulnerability to MDD and PTSD.

Poor inhibitory control and decision-making are often considered as risks for substance use and other adverse psychiatric outcomes. The Stop-Signal Task (SST) is a widely used protocol, from which inhibitory control is indexed by stop signal reaction time (SSRT). However, heretofore models of SSRT may be too simplistic to capture complex processes underlying task performance. In contrast, the Racing Diffusion Ex-Gaussian ABCD (RDEX-ABCD) model provides a more mechanistic framework, capturing both inhibitory control and task-general decision-making processes during the SST. Here, we applied the RDEX-ABCD model to SST data from the IMAGEN cohort (n > 1000) at ages 19 and 23, and examined model parameters in relation to substance use via Elastic Net regression. Connectome-based predictive modeling was then performed to identify brain networks predicting parameters, and the association between these networks and substance use was examined. We found that parameters indexing inhibitory control had no associations with substance use and were only weakly associated with brain connectivity. In contrast, parameters reflecting general decision-making processes - such as efficiency of evidence accumulation, decision threshold (response caution), probability of go failure - and their associated brain activity were significant predictors of cannabis and cigarette use. These findings suggested that efficiency of evidence accumulation, a neurocognitive mechanism that facilitates adaptive decision making across many contexts, emerged as a robust predictor of substance use vulnerability. Overall, general decision-making mechanisms may act as more reliable indicators of vulnerability to substance use than the conventional inhibitory control measures.

Major depressive disorder (MDD) is common and disabling, yet reported brain structural differences vary across studies. Here we performed a large vertex-wise (point-by-point) meta-analysis of cortical thickness and surface area using harmonized magnetic resonance imaging processing across 64 cohorts from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) MDD and Depression Imaging Research Consortium (DIRECT) consortia (5,736 patients; 6,538 controls). We show significantly lower cortical thickness in patients with MDD in multiple brain regions, including the inferior parietal, lateral occipital, superior parietal, medial and lateral orbitofrontal, anterior and posterior cingulate, and precentral gyri, with cortical surface area showing no significant differences. Effects were most pronounced in adults with acute depression, whereas adolescents showed no significant case-control differences. Antidepressant medication use at scanning was associated with more extensive thinning, although effect sizes remained modest (mostly |Cohen's d| < 0.20). This high-resolution, globally generalizable map can support studies of mechanisms and help evaluate structural markers of the clinical course and treatment response.

ABSTRACT Understanding the dynamics of brain–behaviour relationships during adolescence is critical for elucidating the neurodevelopmental basis of mental health. Leveraging two large-scale longitudinal cohorts—the Adolescent Brain Cognitive Development (ABCD) and IMAGEN studies, comprising over 10,000 participants aged 10 to 22 years with six waves of multimodal neuroimaging and behavioural data, we applied multi-view sparse canonical correlation analysis to investigate evolving associations between structural MRI, resting-state functional connectivity, and multi-domain behavioural measures. Our findings reveal four fundamental patterns of developmental reorganisation in brain-psychopathology relationships. First, symptom profiles evolved from predominantly externalising features (aggression, attention problems) at ages 10-12 toward global psychopathology by age 14, then transitioned toward internalising features (e.g., anxiety, depression) by ages 19-22, reflecting fundamental shifts in vulnerability from behavioural dysregulation to affective disturbance. Second, cortical thickness exhibited negative associations with externalising symptom profiles throughout development. During early adolescence (ages 10-14) this was driven by broadly distributed decreases across sensorimotor, temporal, visual, and cingulate regions alongside overall mean cortical thickness. After 14, this diffuse pattern shifted towards late maturing association cortices, notably the dorsolateral prefrontal and lateral temporal cortices. Third, this was accompanied by subcortical effects that exhibited greater age-specificity: whilst cerebellar volume contributions were evident at most timepoints, basal ganglia volume influence was principally evident in early development (ages 10-12), with thalamic structures and global subcortical grey matter volume becoming dominant at age 14, marking a transition in which subcortical structures mediate psychopathology associations. Fourth, functional connectivity showed a more dynamic developmental trajectory. During early adolescence, symptom associations were driven by positive connectivity between cognitive control and sensorimotor networks, whereas late adolescence exhibited predominantly positive connectivity patterns, transitioning from dense sensorimotor-frontoparietal configurations to more specific patterns involving the central executive and default-mode networks. These findings fundamentally challenge static biomarker models, demonstrating that adolescent psychopathology reflects developmentally contingent brain-behaviour relationships rather than static neural markers. Age 14 emerges as a critical inflection point marked by convergent thalamic reconfiguration, global subcortical grey matter dominance, and symptom profile transitions. This work provides an empirical foundation for precision mental health strategies tailored to specific developmental windows, with implications for reducing psychiatric burden in youth.

Posttraumatic stress disorder (PTSD) is a psychiatric condition that may develop after trauma exposure. PTSD is characterized by considerable clinical heterogeneity. The amygdala's key role in fear conditioning makes it an important focus for investigating the neurobiology of PTSD. However, associations between amygdala volume and PTSD have been inconsistent. The amygdala consists of functionally distinct nuclei. Specific associations between amygdala nuclei volumes and PTSD may account for previous discrepancies between PTSD and whole amygdala volume. This study investigates the associations between amygdala nuclei volumes, PTSD diagnosis, severity, symptom cluster scores, age of onset and childhood trauma. Individuals with a PTSD diagnosis (n = 771) and controls (n = 1 081, 72% trauma-exposed) were sourced from the Enhancing Neuro-Imaging Genetics through Meta-Analysis and Psychiatric Genomics Consortium (mean age = 32.4 years, (SD = 13 years), 60% male). Nine amygdala nuclei volumes were compared to PTSD diagnosis, age of onset, overall severity, symptom cluster scores (re-experiencing, arousal, and avoidance/emotional numbing), and childhood trauma subscales. Analyses were performed using ordinary least-squares regression, corrected for age, sex, intracranial volume, and whole amygdala volume. PTSD diagnosis was not significantly associated with amygdala nuclei volumes. PTSD severity scores were associated with smaller right lateral nucleus volume (β = -0.26, pBON = 0.01). Smaller right lateral nucleus volume was also associated with re-experiencing (β = -1.01, pBON = 0.04) and arousal (β = -0.9, pBON = 0.04), smaller left paralaminar nucleus volume was associated with re-experiencing (β = -0.1, pBON = 0.04), smaller left corticoamygdaloid transition area volume was associated with avoidance (β = -0.31, pBON = 0.02). Larger left and right central nucleus volumes were significantly associated with childhood physical abuse (β = 0.24, pBON = 9 × 10-3) and neglect (β = 0.29, pBON = 0.04), respectively. Differences in select amygdala nuclei volumes among adults are associated with PTSD severity, symptom cluster scores, and childhood physical abuse and neglect. These findings demonstrate nuclei-specific patterns consistent with their functional roles in fear learning and expression.

This study investigated associations between bullying victimization and brain development using longitudinal structural MRI data from the IMAGEN cohort (n = 2,094; 1,009 females) across three time points (~14, ~19, and ~22 years). A data-driven analysis revealed that higher bullying victimization was significantly associated with accelerated volumetric growth in subcortical and limbic regions, including the putamen (β = 0.12, 95% CI: 0.10-0.15), amygdala (β = 0.07, 95% CI: 0.05-0.09), hippocampus (β = 0.06, 95% CI: 0.04-0.08), and anterior cingulate cortex (caudal: β = 0.05, 95% CI: 0.03-0.07; rostral: β = 0.06, 95% CI: 0.04-0.08). In contrast, bullying victimization was also significantly associated with reduced volumetric growth in the cerebellum (β = -0.09, 95% CI: -0.11 to -0.07), entorhinal cortex (β = -0.10, 95% CI: -0.13 to -0.07), and insula (β = -0.08, 95% CI: -0.11 to -0.06). Exploratory analyses indicated that females exhibited more pronounced changes in emotional processing regions, while males showed greater changes in motor and sensory areas. Overall, the findings indicate that bullying victimization is associated with widespread structural differences in brain development from adolescence to early adulthood, with sex-specific trajectories.

Background Patients suffering from alcohol dependence (AD) experience high relapse rates. Prior studies investigating the organization of resting-state functional connectivity networks in AD using graph theory typically focused on alterations of the whole network (macroscale) or on aberrations of single brain regions (microscale). However, little is known about the complex dynamics and interactions among different brain regions and neural systems, i.e. the network organization at mesoscale. Methods To investigate mesoscale network alterations, we applied a data-driven community detection algorithm to identify the modular structure of functional brain networks and assess its association with relapse over a 12-month follow-up period in alcohol-dependent patients (relapsers, REL, n = 59; abstainers, ABS, n = 28) and age-and sex-matched controls (CON, n = 83). Results Our results reveal differences in the modular organization in REL, marked by a fragmentation and reorganization of major functional modules. Across individuals, functional modules of REL exhibited higher modular variability, particularly in brain regions associated with behavioral and emotional regulatory processes. Conversely, prefrontal reward-related brain regions were more central for inter-module communication in REL, emerging as functional brain hubs. Furthermore, higher overall modular variability significantly predicted time to relapse during follow-up. Conclusion Collectively, our results shed light on potential neural substrates of relapse risk in alcohol dependence, which may foster the development of targeted interventions to promote sustained abstinence.

Globally, 60% of the population has experienced at least one type of adversity (e.g., emotional abuse, bullying) across infancy, childhood, and adolescence. Such experiences have been linked to an increased risk for mental health disorders. Changes in brain structure following experiences of childhood adversity have been hypothesised to be a mechanistic pathway explaining later mental health issues. However, to understand how changes in brain structure might mediate the effects of adversity, it is essential to identify which underlying neuronal processes may be affected by different types of adverse experiences. A key open question is whether grey or white matter is more vulnerable to adversity, as these two structures reflect distinct neurobiological mechanisms. This study investigated whether differences in trajectories of grey and white matter development during adolescence can be explained by exposure to different types of adversity. We applied the Adverse Adolescent Experiences Framework (Pollmann et al., 2025) categorising adversity into four levels: Intrapersonal (e.g., accidents), Caregiver (e.g., emotional neglect), Peer (e.g., bullying), and Community (e.g., neighbourhood safety). Exposure to each of the four factors was estimated through principal components analyses. We analysed two large longitudinal datasets: the Adolescent Brain Cognitive Development study (~12,000 adolescents measured at ages 10, 12, and 14) and the IMAGEN study (~1,400 adolescents measured at ages 14, 19, and 22). Using latent growth curve models, we captured individual differences in brain development by estimating baseline levels (intercepts) and rates of change (slopes) for total grey matter volume and mean white matter fractional anisotropy. In both cohorts, we found significant interindividual variability in baseline levels and rates of change for both grey matter volume and fractional anisotropy. Caregiver, Peer, and Community adversities were negatively associated only with the intercepts of grey matter volume and white matter fractional anisotropy. Importantly, associations differed between grey and white matter. In ABCD, Peer and Community adversities were more strongly associated with grey matter volume intercepts. In contrast, in IMAGEN, Caregiver, Peer and Community adversities were more strongly linked to white matter fractional anisotropy intercepts. This suggests that adversity has unique associations with grey and white matter, rather than exerting a uniform influence on brain structure. By demonstrating that different environments generate distinct biological associations with brain maturation, this work underscores the need to consider both grey and white matter when assessing the neurodevelopmental pathways to outcomes across the lifespan.

Inhibitory control matures progressively from childhood to early adulthood, yet the neural mechanisms driving this development and their relevance to psychiatric risk remain poorly understood. Guided by the Dual Cognitive Control model, we leveraged longitudinal fMRI from two independent cohorts in the US (ABCD, ages 9-12) and Europe (IMAGEN, ages 14-22) to map the spatiotemporal dynamics of reactive and proactive control using novel single-trial modeling and representational similarity analysis. We found both reactive and proactive stopping networks stabilize after mid-adolescence, tracking the developmental patterns of inhibitory control and behavioral stability. By decoding trial-by-trial fluctuations along a speedcaution continuum, we demonstrate that brain-behavior coupling to a proactive "Safe state" tightens progressively with age. Furthermore, network-level representational coherence of this Safe state emerged as a scanner-invariant, trait-like biomarker that robustly predicted inhibitory control, behavioral stability, and transdiagnostic psychopathology across multiple developmental windows, providing a validated neural phenotype for precision psychiatry.

Die Geschichte der modernen psychiatrischen Hirnbildgebung („Neuroimaging“) seit den späten 1990er Jahren war allzulang geprägt von zu optimistischen Prognosen. Strukturelle Bildgebung sollte bei Kranken anatomische Narben psychischer Krankheiten aufzeigen, die funktionelle Bildgebung gestörte neuronale Schaltkreise identifizieren. Die Vision reichte bis zu objektiven, bildgebungsbasierten Diagnosen, der Früherkennung psychischer Krankheiten und personalisierten Therapieempfehlungen direkt aus dem Scanner.

Die Biologische Psychiatrie ist heute weit mehr als die Suche nach biochemischen Ungleichgewichten und deren medikamentöse Behandlung. Im 21. Jahrhundert ist sie eine multimodale, systemische Neurowissenschaft, die Neurotransmitter und Netzwerke, Mechanismen und Symptome, Grundlagenforschung und Klinik verbindet. Somit schafft sie ein besseres Verständnis psychischer Störungen und eröffnet neue Wege für deren gezielte Behandlung.

BACKGROUND:Adolescence is a sensitive period when suicidal ideation can peak. Although traumatic life events are a well established risk factor for suicidal ideation, the role of cumulative ordinary life events across multiple dimensions, such as family, autonomy, and sexuality, remains underexplored. Crucially, no evidence is available on how multidimensional trajectories of cumulative exposure to such events relate to suicidal ideation throughout adolescence. We aimed to examine how cumulative and domain-specific trajectories of ordinary life events during adolescence relate to suicidal ideation. METHODS:In this multinational, prospective cohort study, we used longitudinal data from the IMAGEN cohort, gathered from eight centres in Germany, France, Ireland, and the UK between January, 2008, and January, 2010, to model trajectories of exposure to life events during adolescence, and to quantify the association between trajectory group and suicidal ideation. Participants were assessed at ages 14, 16, 19, and 23 years, and key inclusion criteria included having the capacity to provide informed assent or consent, and having parental completion of perinatal and developmental history. Exposure to 39 life events across seven dimensions (family, accidents, distress, autonomy, deviance, sexuality, and relocation) were assessed using the Life Events Questionnaire (LEQ), administered at each of the study timepoints. Childhood maltreatment was also assessed, using the Childhood Trauma Questionnaire, administered once at age 19 years. The primary outcome was the number of participants with suicidal ideation across trajectories, assessed via a dedicated item in the LEQ at the first three timepoints. We also compared self-harm and suicidal ideation responses from the Developmental and Well-Being Assessment at the first three timepoints. Latent trajectory analysis was used to identify classes of cumulative life event exposure across repeated assessments: high, mid-high, mid-low, and low. The association between trajectory group and suicidal ideation was quantified using logistic mixed model regressions, adjusting for childhood maltreatment and demographic covariates. No individuals with lived experience of suicidality or mental health conditions were involved in the design, conduct, or reporting of this research. FINDINGS:At baseline, 2161 adolescents, enrolled between January, 2008, and January, 2010, were included in the cohort (1106 [51·2%] female and 1055 [48·8%] male). Sample sizes at subsequent waves were 1581 at first follow-up (which took place between January, 2011, and January, 2012), 1474 at second follow-up (between January, 2013, and January, 2015), and 1331 at third follow-up (between January, 2016, and January, 2019). At each timepoint, the high trajectory group (1125 [52·1%] of 2161 participants) had the highest proportion of participants with suicidal ideation (90 [8·0%] of 1125 at pre-baseline, 127 [11·3%] of 1125 at age 14 years, 102 [13·4%] of 759 at age 16 years, and 78 [11·0%] of 709 at age 19 years). After controlling for demographics and childhood maltreatment, the high trajectory group had the highest predicted probability of suicidal ideation at each timepoint. Life events in the family dimension predicted adolescent suicidal ideation (marginal R2GLMM=0·078) more than those in all remaining dimensions combined (marginal R2GLMM=0·073). INTERPRETATION:We found that higher cumulative exposure to ordinary life events across multiple dimensions is associated with higher suicidal ideation in adolescence, with life events occurring within the family environment carrying the highest risk. These results point to the importance of evaluating different types of everyday life event exposure, not just childhood trauma or maltreatment, when assessing suicidal risk in adolescents. FUNDING:Abroad Advanced Study Fellowship, Chang Gung Medical Foundation, Taiwan; National Science and Technology Council, Taiwan; Medical Research Council, UK.

Human cognitive processing involves dynamic interactions across brain regions, evolving over time. Traditional neuroimaging analysis often overlooks this temporal aspect, limiting insights into how functional network connectivity (FNC) supports ongoing cognition and behaviour. Using sliding window analysis, we captured FNC changes during tasks, reflecting network reconfiguration in cognitive processes. We further determined behavioural relevance of time-varying FNC by relating network measurements with task performances and psychopathology. We found that several whole-brain FNC patterns, or states, persist across resting and task-based fMRI, with state occurrences fluctuating with the most prominent task stimuli. Regional FNC distinguishes specific task conditions, and time-varying FNC explains more variance in psychopathology symptoms compared to static connectivity. These findings highlight that cognitive tasks reshape regional and whole-brain connectivity. By considering the different FNC states, time-varying connectivity provides a more comprehensive representation of brain interactions and thus may represent a better neural proxy for cognition and behaviour.

ABSTRACT Craving is a hallmark feature of substance use disorders (SUDs) and a major risk factor for relapse, yet reliable biomarkers that enable individual-level prediction remain scarce. Here, we applied connectome-based predictive modeling (CPM) to resting-state functional magnetic resonance imaging (fMRI) data in a transdiagnostic sample of individuals with cannabis, opioid, or tobacco use disorder ( n = 78). Using CPM, we identified a distributed functional brain network that reliably predicted self-reported craving. Computational lesion analyses revealed key contributions from the right medial orbitofrontal cortex, right dorsal posterior cingulate cortex, and left lateral medial frontal gyrus. Importantly, the craving network generalized across two independent datasets. In alcohol-dependent patients ( n = 41 ), the identified craving network, along with its positive and negative subnetworks, predicted distinct cognitive and motivational components of craving. In a second external dataset of smokers ( n = 28), the craving network predicted both nicotine craving after abstinence as well as intra-individual changes in craving between sated and craving states. Together, these findings provide evidence for a robust, transdiagnostic craving signature in SUDs. Future work should assess the network’s predictive utility for longitudinal outcomes such as relapse risk and treatment response.

Introduction Up to 30% of individuals with depression develop persistent depressive disorder (PDD), an often disabling and difficult to treat condition. The Cognitive Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy developed specifically for treating individuals with PDD. While several randomised controlled trials (RCTs) have demonstrated its efficacy in outpatient settings, evidence for its use in inpatient settings remains limited. Pilot studies of CBASP inpatient programmes in Germany have shown promising feasibility and effectiveness; however, no RCTs to date have systematically evaluated their outcomes. This study represents the first RCT to compare the short- and long-term efficacy and safety of CBASP with Behavioural Activation (BA), a first-line psychotherapy for depression, within an intensive multimodal inpatient setting.Methods and analysis In this prospective, multicentre, rater-blinded RCT with an active control group, we aim to recruit 396 adults (aged 18–70 years) with treatment-resistant PDD at eight German university hospitals. Participants will be randomly assigned to receive either (1) CBASP or (2) BA within an intensive treatment programme consisting of 10 weeks acute treatment in an inpatient and/or day clinic setting, followed by 6 weeks of outpatient continuation treatment. Primary and secondary outcome assessments will be conducted at multiple time points: baseline (T0), treatment onset (T1), after 5 and 10 weeks of acute treatment (T2, T3), at the end of continuation treatment (T4, week 16) and every 2 months up to week 64 (T5, naturalistic follow-up).The primary outcome measure will be the change in depression severity, as assessed by the Hamilton Depression Rating Scale (24-item version), after 16 weeks of treatment (from T0 to T4). Secondary outcomes will include response, remission, deterioration and relapse rates, self-reported depression and anxiety symptoms and additional psychological variables. A cost-benefit analysis will evaluate the health-economic benefits of both interventions. Additionally, this RCT will explore personalised treatment selection and mechanisms of change, including potential moderators and mediators of treatment effects. The findings from this trial are expected to provide clinicians with evidence-based guidance on choosing CBASP versus BA for inpatients with treatment-resistant PDD.Ethics and dissemination This study has received ethical approval from the ethics committees of all participating university hospitals. All participants will provide written informed consent before enrolment. Study findings will be published in peer-reviewed journals and presented at national and international conferences. We have involved people with lived experience from the earliest pilots onward, using their feedback to refine our study design. Ongoing consultation at conferences and public events has further ensured that our research remains grounded in patient perspectives.Trial registration number NCT04996433.

KI zeigt in vielen Bereichen der Medizin bereits eine hohe diagnostische Präzision. In der Psychiatrie bleibt sie jedoch hinter den Erwartungen zurück: Es fehlen spezifische Biomarker, die Symptomprofile sind heterogen, und klinische Diagnosen sind nur begrenzt reliabel. Gerade diese Hürden schaffen jedoch den Ausgangspunkt für neue Ansätze – von multimodalen Modellen bis hin zu digitalen Agenten in der therapeutischen Unterstützung.

Psychedelic-assisted therapy has shown promise in the treatment of a range of psychiatric disorders, yet therapeutic responses remain highly variable. Although prior research has focused predominantly on features of the acute psychedelic experience, less attention has been paid to baseline characteristics and preparatory factors. Moreover, therapist-derived insights from real-world practice have not yet been explored. Here we conducted a cross-sectional survey distributed to therapists involved in psychedelic-assisted therapy to assess the perceived impact of baseline, preparation and session parameters on therapeutic outcomes. A total of 158 therapists completed the survey and rated predictors of favorable and unfavorable long-term outcomes. Therapists identified several factors as particularly conducive to positive outcomes, with the highest ratings given to a strong therapeutic alliance, robust social support, personality traits such as openness and capacity to surrender, secure attachment and a belief in an active mode of therapeutic action. By contrast, prior use of nonpsychedelic substances was perceived as the most unfavorable predictor of therapeutic response. Differences also emerged according to therapists' setting of practice and primary substance of experience. Therapists working in unregulated settings rated certain challenging features more favorably. Meanwhile, therapists working with psilocybin placed greater emphasis on preparation and therapeutic presence than therapists working with ketamine. The thematic analysis of open-ended responses further highlighted the importance of preparation, integration, patient mindset and environmental context. These findings provide clinically grounded insights into the key predictors of psychedelic-assisted therapy outcomes and may inform future screening protocols and the optimization of treatment protocols.

Abstract Changes in personality during adolescence may shape future alcohol use, especially in times of societal crisis. The COVID-19 pandemic disrupted social norms and stress regulation, making it a natural experiment to examine how early-life personality trajectories predict later substance use. Using longitudinal data from the European IMAGEN cohort (N = 968), we investigated whether intra-individual personality changes during adolescence predicted alcohol use at three timepoints: pre-pandemic, immediately after COVID-19 onset (T1), and several months into the pandemic (T2). Generalized Additive Mixed Models (GAMMs) were used to model non-linear relationships between adolescent personality change (e.g., in anxiety sensitivity and openness) and alcohol use frequency across time. Participants were drawn from the IMAGEN cohort (N = 968; 54.4% female), assessed longitudinally from early adolescence (BL: M = 13.93, SD = 0.41) through middle (FU1: M = 16.04, SD = 0.60) and late adolescence (FU2: M = 18.41, SD = 0.65) to early adulthood (FU3: M = 22.00, SD = 0.66), with additional follow-ups during the COVID-19 pandemic (COVID-T1: M = 25.00, SD = 0.81; COVID-T2: M = 25.56, SD = 0.75). Assessments were conducted at approximately 2-year intervals during adolescence and at shorter intervals (several months) during the COVID-19 period. Analyses controlled for sex and country-level lockdown stringency. Intra-individual fluctuations in anxiety sensitivity significantly predicted increased alcohol use several months into the pandemic (T2; EDF = 1.86, p < 0.05), but not immediately after lockdown (T1). Pre-pandemic alcohol use was instead associated with changes in openness (EDF = 1.00, p < 0.05). Exploratory analyses suggested gender differences in anxiety-related drinking risk. Our findings suggest that personality dynamics in adolescence shape alcohol use responses during societal crises. Different traits appear to matter depending on the temporal and emotional context of the stressor. These findings have implications for personalized prevention efforts targeting stress-related substance use in youth.

BACKGROUND:Although the initiation of alcohol consumption is common during adolescence, some individuals engage in binge drinking behavior that could lead to harmful consequences such as developing alcohol use disorder later in life. Evidence suggests a relationship between depressive symptoms and harmful alcohol consumption that seems to vary depending on sex. Furthermore, it has been suggested that amygdala activation in response to negative emotional stimuli influences drinking due to depressive mood states. Therefore, we expected a sex-dependent effect of neuronal activation and depressive symptoms on risky drinking. METHODS:Here, we tested our hypothesis using a large dataset of 19-year-old participants (n = 958) in the IMAGEN study. Amygdala activation during an emotional faces task was extracted and entered into sex-moderated mediation models that also included scores from the Alcohol Use Disorders Identification Test and the Adolescent Depression Rating Scale. RESULTS:Moderated mediation models indicated that amygdala activation was associated with hazardous drinking through enhanced depressive symptoms in males, while amygdala reactivity in females was associated with decreased risky drinking. CONCLUSIONS:Taken together, our findings reveal sex differences in negative emotional processing in at-risk adolescents. These associations have the potential to inform the development of sex-specific strategies as well as the detection of early neuronal risk factors to effectively curtail alcohol risk behavior.

Why do individuals respond differently to stress? Since rodent studies indicated that stress regulation relies on limbic and medial prefrontal cortex (mPFC) outputs, we aimed to investigate whether data from these regions could also predict cortisol and affect trajectories following psychosocial stress in humans. In this pre-registered study, 281 healthy adults (145 female) were exposed to ScanSTRESS. Repeated assessments of salivary cortisol and negative affect were used to identify response trajectories (i.e. groups of participants) using latent class mixture modelling (LCMM). LCMMs without brain predictors were compared to LCMMs including structural (volume, thickness) and functional (activation, exposure-time effect) predictors from the amygdala, hippocampus, or mPFC regions, using common fit indices including the Akaike Information Criterion. Results showed that cortisol LCMMs without brain predictors exhibited a single mean trajectory, indicative of homogeneous cortisol responses across the sample. Adding brain predictors resulted in three to four response trajectories, depending on region and outcome. Within identified models, cortisol ‘hyper-response’ trajectories were predicted by larger amygdala and hippocampus volumes. Cortisol ‘non-responses’ were predicted by greater amygdala activation and volume. ‘Elevated baseline’ cortisol was predicted by higher hippocampal activation. mPFC markers did not predict cortisol trajectories, however, medial orbitofrontal cortex parameters identified negative affect response profiles mirroring measures of long-term stress exposure and affect. Together, our findings suggest dissociated roles of limbic and mPFC regions in stress regulation: While limbic structures predicted cortisol responses, the mPFC shaped affective experience.