Symposium
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.