Leveraging Diverse Longitudinal Data to Map Neurobiological and Environmental Predictors of Disorder

Introduction: Adolescence is a period of heightened vulnerability to internalising symptoms, such as depression and anxiety, especially in girls (Dahl et al., 2018). Developmental models suggest that significant reorganisation of neural systems involved in emotion regulation may contribute to this vulnerability (Casey et al., 2008). At the same time, the adolescent brain is sensitive to environmental inputs, with evidence suggesting that parenting behaviours influence the neural correlates of emotion regulation and the development of internalising outcomes in young people (Kerr et al., 2019; Yap et al., 2014). However, no study has yet examined whether a causal relationship exists between parenting and brain function, and whether brain function acts as a mediating mechanism through which parenting influences adolescent internalising outcomes. Methods: Female adolescents with elevated internalising symptoms (N = 70, mean age, 11.46 [SD = 0.77]) and their mothers were randomly assigned to an emotion-focused parenting intervention (Tuning in to Teens [TINT; Havighurst et al., 2019], N = 34) or a waitlist control group (N = 36). At baseline and 6-month follow-up, adolescents underwent fMRI scans during implicit and explicit emotion regulation (i.e., affect labelling task, cognitive reappraisal task). We used voxel-wise repeated measures ANOVA implemented in SPM to examine the interaction effect of a between-subject factor of group (intervention vs control) and a within-subject factor of time (baseline vs 6-month follow-up) on adolescent brain activation and functional connectivity during emotion regulation tasks. For brain activation, we conducted both amygdala and prefrontal cortex region of interest (ROI) analysis and exploratory whole-brain analysis. Whole brain functional connectivity was assessed with generalised psychophysiological interaction analysis, including the amygdala, insula, and hippocampus as seed regions. The BOLD signal from significant clusters from the repeated measure ANOVA (mean of signal from a 5mm radius sphere around peak values) was extracted for causal mediation analysis. Adolescent internalising symptoms were assessed using the Revised Children’s Anxiety and Depressions Scale at baseline and 8-month follow-up. We used a model-based inference approach with the ‘mediation’ package (Tingley et al., 2014) implemented in R to examine causal effects of the TINT intervention on adolescent internalising symptoms through brain function (controlling for baseline adolescent symptoms and brain function). Point estimates for the average causal mediation effect (ACME) with 95% CI using 1000 bootstrapped Monte Carlo simulations were calculated. Results: Adolescent girls whose mothers received the TINT intervention (as compared to the control condition) showed increased activation in the superior frontal gyrus (SFG) during affect labelling and decreased activation in the inferior frontal gyrus (IFG) during cognitive reappraisal. Additionally, adolescents from the intervention group relative to the control group showed greater insula-supplementary motor area and insula-precuneus functional connectivity during cognitive reappraisal. Causal mediation analysis showed that the IFG activity at 6-month follow-up partly explained the effect of TINT on adolescent self-reported internalising symptoms at 8-month follow-up (ACME = -6.71, 95% CI = [-15.96, -0.63]). Conclusions: This study provides the first causal evidence that an emotion-focused parenting intervention altered neural correlates of emotion regulation in adolescent girls. Importantly, our findings identify neural mechanisms through which improvements in parenting lead to reductions in adolescent internalising symptoms, in a sample of early adolescent girls with elevated internalising symptoms. These findings suggest early adolescence may be a key window of intervention and highlight the importance of intervening with modifiable parenting behaviours to promote adaptive neural function and improve mental health in youth. 

Introduction: Adolescence is a dynamic period of brain development, with important influences from a range of environmental factors, with combined impacts on trajectories of mental health and wellbeing. Various brain regions that process cognitive and social information develop throughout adolescence, and the way these regions interact is critical, as young people learn to navigate their increasingly social and independent lives. Described as ‘structural connectivity’, white matter (WM) projections play a vital role in linking neural elements within brain regions and serve to optimise the efficiency of information processing. Since 2018, the Longitudinal Adolescent Brain Study (LABS) has frequently assessed numerous measures of mental health & wellbeing, as well as a range of lifestyle and environmental factors, in conjunction with neuroimaging, as participants progress through adolescence. LABS researchers have been investigating the relationships between changes in WM integrity (as measured via diffusion tensor imaging; DTI) and a range of environmental factors. Methods: Data is collected from LABS participants, from 12 years-of-age, at 4-month intervals, over a 5-year period. At each time-point, data collection involves self-report questionnaires, cognitive assessments, neuropsychiatric interview, electroencephalography and neuroimaging (including DTI). To date, 180 adolescents have commenced LABS, with 1000+ assessments completed (up to 15 timepoints for some individuals). Structural connectivity from DTI, is indexed by WM integrity measures (fractional anisotropy [FA], axial diffusivity [AD], radial diffusivity [RD]) from projection, commissural and association fibre pathways (tracts). Across our studies, cohort-specific templates are utilised as the target of the tract-based spatial statistics analysis (TBSS). Environmental/lifestyle factors such as sleep quality, social connectedness and screen time/social media use is recorded via self-report, whereas childhood adversity is recorded via interview with a clinical psychologist, when participants reach 16 years of age; they are asked about any early life stress or traumatic events that they may have experienced. Results: A series of papers/analyses that involve the tracking of WM profiles (FA, AD, RD) during adolescent development, and their associations with mental health and well-being outcomes, as well as environmental factors (sleep quality, social connectedness or early life stress/childhood adversity) will be presented. More specially, development trajectories of WM diffusion metrics utilise generalised estimated equations or generalised additive mixed modelling and incorporate potentially differentiating factors such as biological sex and socio-economic status. Conclusions: LABS has great scope to identify the links between structural brain changes and environmental factors as young people progress through adolescence, with potential fluctuations in their mental health and wellbeing. It is important to understand the mechanisms involved in the maturation of structural connectivity, particularly between functional brain regions implicated in the processing of complex cognitive and social information, and how these impact or influence adolescents’ mental health and wellbeing. 

Introduction: Mental health problems often emerge or intensify during adolescence, a critical developmental period marked by rapid biological, psychological, and social changes. Numerous studies have been conducted to investigate mental health issues during this stage, offering valuable insights into the prevalence and potential causes of these challenges. However, most existing research relies on cross-sectional designs, which, while useful for identifying associations at specific time points, fail to capture the dynamic and evolving nature of mental health trajectories during adolescence. In addition, much of the current research tends to focus on single biomarkers in isolation when studying their associations with mental health problems. This narrow approach overlooks the complexity and multifactorial nature of adolescent mental health, which is influenced by a combination of genetic, environmental, and neurobiological factors. To address these gaps, longitudinal studies that integrate diverse biomarkers and consider their interplay over time are essential. Method: Buckova et al. (2024) developed a method to calculate brain metrics, such as cortical thickness, within a normative longitudinal framework (bayesian linear regression(blr)), enabling the investigation of the rate of change in variables of interest and their deviations from typical developmental trajectories. Building on this approach, we extended the method to assess longitudinal deviations of various biomarkers relative to normative trajectories in longitudinal Adolescent Brain Cognitive Development (ABCD) cohort (age range 9-16 years old, N= 11000 years old). We used biological measures, such as hormonal levels and physical growth; neuroimaging metrics, including brain networks, diffusion-weighted imaging (e.g., fractional anisotropy in tracts), and T1-weighted imaging (e.g., cortical thickness, surface area, and subcortical volume); as well as social factors like parent and peer relationships and lifestyle factors such as physical activity, sleep disturbances, and screen time. By constructing normative trajectories that capture the rate of change for these measures in a healthy population, we developed a reference framework to identify deviations in individuals with emotion regulation difficulties and depression disorder, as determined by the KSADS questionnaire. Using a k-nearest neighbors (KNN) classification model, we identified specific biomarker profiles in this patient group, highlighting patterns of divergence across biological, neuroimaging, social, and lifestyle domains. This comprehensive framework offers critical insights into the multifaceted factors underlying mental health challenges during adolescence. Results: Our results revealed that individuals with emotion dysregulation and depressive disorders exhibit distinct deviations across multiple domains when compared to healthy populations with cross-validated accuracy: 85.64%. Specifically, these individuals showed signs of accelerated brain maturation, characterized by lower specific pattern of cortical and subcortical volumes, higher fractional anisotropy (FA) in the fornix tracts, and reduced connectivity within corticolimbic regions as well as between the salience and sensorimotor networks aligned with higher rate of pubertal changes and a lower overall quality of lifestyle, marked by reduced physical activity, increased screen time, and disrupted sleep patterns. These deviations highlight the multifaceted interplay of neurobiological, biological, and lifestyle factors in individuals with mental health challenges, emphasizing the need for holistic approaches to understanding and addressing these conditions. Discussion: The findings of this study highlight critical deviations in brain maturation, biological development, and lifestyle factors among individuals with emotion dysregulation and depressive disorders compared to their healthy peers. These deviations underscore the multifaceted nature of mental health challenges in adolescence and provide insights into potential mechanisms underlying these conditions. 

Introduction: Early life adversity (ELA), encompassing abuse and neglect, affects more than two-thirds of the general population and substantially increases risk for stress-related psychopathology, including major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). While neuroanatomical abnormalities are frequently observed in both MDD and PTSD, the extent to which these alterations are attributable to ELA exposure remains uncertain. Methods: We analyzed ELA and structural MRI data from 3,711 participants (1,389 patients [872 MDD, 517 PTSD] and 2,322 healthy controls) across 25 international cohorts from the ENIGMA MDD and PTSD Working Groups (mean age 33±12.98 years; 59.82% female). Using the Childhood Trauma Questionnaire, we calculated separate composite scores for abuse (emotional, physical, and sexual) and neglect (emotional and physical) subscales. Leveraging normative modeling based on an independent reference population of 37,407 healthy individuals, we quantified deviation scores in subcortical volumes, cortical thickness, and surface area, evaluating transdiagnostic associations between ELA and brain deviation scores separately within each sex across three age groups: pediatric (≤18 years), young adult (>18 and <35 years), and older adult (≥35 years). Results: We observed heterogeneous effects of ELA on brain deviation scores that varied by exposure type, age, and sex, with the strongest effects emerging in young adult females. In this group, childhood abuse was associated with widespread alterations in volumes of the hippocampus and pallidum and cortical thickness of medial temporal and frontal regions (|r |= 0.12-0.18, q < 0.01), while childhood neglect was associated with larger surface area of frontal and temporal pole regions (r = 0.19-0.21, q < 0.01). Notably, no significant associations were observed in the pediatric cohort, and effects were most pronounced in association cortices showing protracted developmental trajectories. These patterns remained robust after controlling for diagnosis, site effects, and clinical variables. Conclusions: Our findings support incubation models of ELA, suggesting that the neurobiological consequences of early adversity may not manifest immediately but rather emerge more prominently during young adulthood, particularly in females. This work highlights the importance of considering age- and sex-specific effects when studying the impact of early adversity on brain development and emphasizes the potential value of targeted interventions during young adulthood, especially for females with histories of childhood trauma.