Decomposing complex links between the childhood environment and brain structure in school-aged youth

Abstract

Childhood experiences play a profound role in conferring risk and resilience for brain and behavioral development. However, how different facets of the environment shape neurodevelopment remains largely unknown. Here we sought to decompose heterogeneous relationships between environmental factors and brain structure in 989 school-aged children from the Adolescent Brain Cognitive Development Study. We applied a cross-modal integration and clustering approach called ‘Similarity Network Fusion’, which combined two brain morphometrics ( i.e., cortical thickness and myelin-surrogate markers), and key environmental factors ( i.e., trauma exposure, neighborhood safety, school environment, and family environment) to identify homogeneous subtypes. Depending on the subtyping resolution, results identified two or five subgroups, each characterized by distinct brain structure–environment profiles. Notably, more supportive caregiving and school environments were associated with greater myelination, whereas less supportive caregiving, higher family conflict and psychopathology, and higher perceived neighborhood safety were observed with greater cortical thickness. These subtypes were highly reproducible and predicted externalizing symptoms and overall mental health problems. Our findings support the theory that distinct environmental exposures are differentially associated with alterations in structural neurodevelopment. Delineating more precise associations between risk factors, protective factors, and brain development may inform approaches to enhance risk identification and optimize interventions targeting specific experiences.

Brain-Based Biotypes of Psychiatric Vulnerability in the Acute Aftermath of Trauma

“…We used very simple and transparent tools for clustering, uninformed by psychiatric symptoms or diagnoses, and found strong evidence for overlap (65%) in the cluster solutions arising from two fully independent hierarchical clustering solutions in different subcohorts. This level of overlap is consistent with cluster replication levels seen in larger brain-based clustering efforts, such as in the Adolescent Brain Cognitive Development study (41), and suggests that multivariate task-based fMRI data contain consistent information about individual differences. In fact, a major value of this study is its demonstration of taskbased fMRI as a useful tool for mapping psychiatric heterogeneity.…”

Association between Neighborhood Socioeconomic Status and Executive System Activation in Youth

“…Given these considerations, it is possible that children in low-income neighborhoods are not receiving the level of stimulation needed in order to develop higher levels of WM, which may explain the relationship presented in the current work. This hypothesis is consistent with recent work showing that protective measures, like cognitively enriched care or positive parenting, may alter the effects of early life adversity on neural measures such as brain volume (Farah et al 2021), patterns of myelination and cortical thickness (Hong et al 2021) or altered brain development in the temporal lobes (Whittle et al 2017).…”

Measurement matters: An individual differences examination of family socioeconomic factors, latent dimensions of children’s experiences, and resting state functional brain connectivity in the ABCD sample

“…Linking the above findings to our first aim, the absence of many of our predicted associations highlight the importance of testing and adjusting for potential measurement biases. Indeed, prior work in the ABCD study has shown relations between the environmental measures used in the current study and various neurodevelopmental metrics (e.g., Thijssen et al, 2020 ; Modabbernia et al, 2021 ; Hong et al, 2021 ; Rakesh et al, 2021b ). We may not have come to similar conclusions due to the way in which MNLFA creates person-specific scores that empirically adjust for sociodemographic heterogeneity in item responses.…”

“…Although studies using the ABCD sample have begun uncovering associations between aspects of children’s environments and rsFC ( Thijssen et al, 2020 , Modabbernia et al, 2021 , Ellwood-Lowe et al, 2020 , Hong et al, 2021 , Rakesh et al, 2021b ), approaches that aim to disentangle the effects of broader socioeconomic context (e.g., SES, parental education) from youths’ downstream experiences of these broader contexts (e.g., their home environment) remain to be explored. Based on prior work mentioned above (e.g., Brody et al, 2019 ), it is likely that the magnitude of SES effects on brain connectivity will be stronger in the context of proximal environmental factors.…”