Eugenia Giampetruzzi

Childhood adversity has enduring consequences for health and development across the lifespan, yet the organizing structure linking diverse environmental experiences to the developing brain remains poorly understood. We jointly modeled 104 measures of children’s environments, spanning interpersonal, household, and neighborhood contexts, with 7 neuroimaging modalities of brain structure and function in 5,976 youth. Despite this breadth, only a single adversity-brain dimension emerged and replicated in held-out data. This dimension was defined primarily by socioeconomic and neighborhood deprivation and selectively expressed in lower cortical surface area and distributed functional connectivity concentrated in sensorimotor systems. Total cortical surface area reproduced 96% of the regional association, indicating a global rather than regionally specific structural signature. This dimension predicted poorer cognition and cardiometabolic health six years later. These findings reveal a strikingly selective, low-dimensional relation between children’s environments and neurodevelopment, with socioeconomic deprivation emerging as the principal environmental axis associated with the developing brain.

Objective: Mental disorders are the leading cause of disability in youth. Identifying which youth have, or will develop, mental illness relies increasingly on large, shared cohorts whose diagnostic data are analyzed by hundreds of investigators. Deriving psychiatric diagnoses from these data, however, requires analytic decisions that are rarely reported or standardized. Here, we tested whether these largely invisible decisions can change, or even reverse, conclusions about youth mental illness in the largest and most frequently analyzed cohort, the Adolescent Brain Cognitive Development (ABCD) Study.Method: We first reviewed the ABCD literature to document current practices. Then, using KSADS-COMP diagnoses from ABCD Release 7.0 (N=11,858 at baseline), we held the data fixed and, for every combination of timeframe, threshold, and informant, we recomputed prevalence for 13 DSM-5 categories and re-estimated associations of six categories with demographic, psychosocial, and neuroimaging variables.Results: In the same children, these choices changed the prevalence of a single disorder from 1.9% to 56.8%. Caregiver and youth reports agreed barely above chance and identified nearly independent sets of children; the choice of informant alone thus substantially determined who was classified as a case. Across demographic (sex, income, race/ethnicity), psychosocial (screen time, family conflict), and neuroimaging (resting-state functional connectivity) correlates, only 26% of associations held under every decision, with brain-diagnosis relations the least stable.Conclusions: These findings suggest caution in interpreting existing results and underscore the need to report diagnostic choices and their influence on findings. We provide a harmonized dataset and reporting standards to support these efforts.

The neighborhoods children grow up in are associated with cognitive and mental health outcomes across the lifespan. Yet how neighborhood-level factors are quantified, and how they relate to large-scale functional brain connectivity, remains an emerging area of investigation. This scoping review synthesizes empirical evidence on associations between area-level factors and resting-state functional brain connectivity and network organization. We included studies assessing resting-state fMRI functional connectivity or rs-fMRI-derived intrinsic activity in relation to validated area-level deprivation indices guided by Trinidad et al.’s (2022) inventory, the Opportunity Atlas, or geocoded crime exposure from the Uniform Crime Reporting program. Of the 28 studies meeting inclusion criteria, the evidence base was unevenly distributed across the lifespan; 25 of 28 (89.3%) examined perinatal, childhood, or adolescent samples, while only one examined adults exclusively. The literature was also methodologically non-independent, over half drew on the Adolescent Brain and Cognitive Development (ABCD) Study, and the Area Deprivation Index was the most commonly used measure (k = 16, 57.1%). Therefore, apparent convergence partly reflects shared data and instruments rather than independent replication. Where directions could be compared, higher area-level disadvantage was associated predominantly with lower within-network connectivity in association and control systems and higher connectivity in somatomotor systems, with several findings attenuating once area-level exposure was isolated from household socioeconomic status. Geographic resolution varied but was rarely justified. Progress will require greater theoretical intentionality in selecting area-level measures, transparent justification of geographic resolution, treatment of dataset and measure non-independence, and investment in understudied developmental periods and non-US contexts.

Early adversity is among the most potent environmental influences on the developing brain; yet whether it remodels the areal layout of cortical networks, and along which dimensions, is unknown. In a longitudinal sample of 4,525 youth aged 9-18, we derived individualized cortical parcellations and related the topography of 15 networks to 10 data-driven dimensions of adversity. Greater exposure to threat, but not deprivation or unpredictability, predicted dose-dependent expansion of the somato-cognitive action network (SCAN), an effect nearly seven times larger than for any other network. The SCAN expanded toward the sensorimotor pole, encroached on neighbors, and shifted functional connectivity toward sensorimotor and away from control systems. Expansion mediated the association between threat and poorer cognition, replicating across waves, within children, and out-of-sample. Rather than diffusing across many systems, the imprint of adversity on the developing cortex converges on the territory of a single integrative network that couples brain to body.

Objective: The autonomic nervous system, which regulates cardiac rhythm, undergoes pronounced maturation across adolescence. How cardiac rhythm develops over this period, however, and whether individual differences in its development forecast mental and physical illness, remain open questions. We used three waves of Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study to characterize the developmental trajectory of the cardiac rhythm and to test whether variation in that trajectory predicts onset of psychopathology and cardiometabolic disease. Methods: 8,301 adolescents contributed 242,811 valid Fitbit wear days across Waves 2 (Mage=12), 4 (Mage=14), and 6 (Mage=16). Cosinor mixed-effects models yielded three rhythm parameters per session: mesor (24-hour mean), amplitude (diurnal swing), and acrophase (peak timing). We first characterized age- and sex-specific trajectories, cross-wave stability, and factors shaping the rhythm. We then used parallel-process latent growth models to test whether within-person changes in rhythm tracked symptom trajectories, and hierarchical logistic models to test whether rhythm parameters predicted the first clinical onset of psychopathology and of obesity and hypertension. Results: The cardiac rhythm changed substantially across adolescence: mesor decreased, amplitude flattened, and acrophase shifted later. Within-person change in the rhythm tracked change in blood pressure, BMI, and trajectories of depression and ADHD symptoms. Higher mesor predicted incident onset of all five outcomes controlling for demographics, baseline symptoms, and behavior (ORs 1.36-1.54); amplitude, acrophase, and rhythm instability conferred additional risk. Conclusions: The 24-hour cardiac rhythm is a passively measurable substrate of adolescent autonomic development that indexes transdiagnostic risk for psychiatric and cardiometabolic illness.