Adolescent Neurodevelopmental Variance Across Social Strata.

This cohort study explores variability in neurodevelopment across sociodemographic factors among youths.

Lifetime residential history collection and processing for environmental data linkages in the ABCD study.

By using geospatial information such as participants' residential history along with external datasets of environmental exposures, ongoing studies can enrich their cohorts to investigate the role of the environment on brain-behavior health outcomes. However, challenges may arise if clear guidance and key quality control steps are not taken at the outset of data collection of residential information. Here, we detail the protocol development aimed at improving the collection of lifetime residential address information from the Adolescent Brain Cognitive Development (ABCD) Study. This protocol generates a workflow for minimizing gaps in residential information, improving data collection processes, and reducing misclassification error in exposure estimates.

Lifetime residential data collection protocol for the Adolescent Brain Cognitive Development (ABCD) Study.

Understanding the impacts of environmental exposures on health outcomes during development is an important area of research for plenty of reasons. Collecting retrospective and prospective residential history can enrich observational studies through eventual linkages to external sources. Augmenting participant health outcome data with environmental data can better inform on the role of the environment, thereby enhancing prevention and intervention efforts. However, collecting the geospatial information needed for this type of research can be difficult, especially when data are collected directly from participants. Participants' residential histories are unique and often complex. Collecting residential history data often involves capturing precise spatial locations along specific timeframes as well as contending with recall bias and unique, complex living arrangements. When trying to assess lifetime environmental exposures, researchers must consider the many changes in location a person goes through and the timeframes in which these changes occur, ultimately creating a multidimensional and dynamic dataset. Creating data collection protocols that are feasible to administer, result in accurate data, and minimize data missingness is a major challenge to undertake. Here, we provide an overview of the protocol developed to collect the lifetime residential address information of participants in the Adolescent Brain Cognitive Development (ABCD) Study.

Sex, gender diversity, and brain structure in early adolescence.

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

High Resolution Multi-delay Arterial Spin Labeling with Transformer based Denoising for Pediatric Perfusion MRI.

Multi-delay arterial spin labeling (MDASL) can quantitatively measure cerebral blood flow (CBF) and arterial transit time (ATT), which is particularly suitable for pediatric perfusion imaging. Here we present a high resolution (iso-2mm) MDASL protocol and performed test-retest scans on 21 typically developing children aged 8 to 17 years. We further proposed a Transformer-based deep learning (DL) model with k-space weighted image average (KWIA) denoised images as reference for training the model. The performance of the model was evaluated by the SNR of perfusion images, as well as the SNR, bias and repeatability of the fitted CBF and ATT maps. The proposed method was compared to several benchmark methods including KWIA, joint denoising and reconstruction with total generalized variation (TGV) regularization, as well as directly applying a pretrained Transformer model on a larger dataset. The results show that the proposed Transformer model with KWIA reference can effectively denoise multi-delay ASL images, not only improving the SNR for perfusion images of each delay, but also improving the SNR for the fitted CBF and ATT maps. The proposed method also improved test-retest repeatability of whole-brain perfusion measurements. This may facilitate the use of MDASL in neurodevelopmental studies to characterize typical and aberrant brain development.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves.

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Neural Correlates of Obesity and Inflammation in Children and Adolescents with Congenital Adrenal Hyperplasia.

INTRODUCTION: Patients with classical congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency exhibit an increased prevalence of obesity from childhood including central adiposity and inflammation. There is also an emerging affected brain phenotype in CAH, with decreased cortico-limbic gray matter volumes and white matter abnormalities. We aimed to study the relationship between brain structure, obesity, and inflammation in children and adolescents with CAH compared to controls. METHODS: 27 CAH (12.6±3.4y, 16 females) and 35 controls (13.0±2.8y, 20 females) had MRI of gray matter regions of interest [prefrontal cortex (PFC), amygdala, hippocampus] and white matter microstructure [fornix, stria terminalis (ST)]. Anthropometric measures and lab analytes were obtained. Relaimpo analyses (relative importance for linear regression; percent variance) identified which brain structures were most different between groups. Subsequent regressions further quantified the magnitude and direction of these relationships. Correlations analyzed relationships between brain structure, obesity, and inflammation in the context of CAH status. RESULTS: PFC (13.3% variance) and its superior frontal (SF) subregion (14%) were most different between CAH and controls for gray matter; ST (16%) for white matter. Patients with CAH had lower caudal middle frontal [ß = -0.56, (-0.96, -0.15)] and superior frontal [ß = -0.58 (-0.92, -0.25)] subregion volumes, increased orientation dispersion index in the fornix [ß = 0.56 (0.01, 1.10)] and ST [ß = 0.85 (0.34, 1.36)], and decreased fractional anisotropy in the fornix [ß = -0.91 (-1.42, -0.42)] and ST [ß = -0.83 (-1.34, -0.33)] (all p's <0.05) indicating axonal disorganization, reduced myelin content, and/or higher microglial density within the affected white matter tracts. For the full cohort, SF was correlated with MCP-1 (r=-0.41), visceral adipose tissue (r=-0.25), and waist-to-height ratio (r=-0.27, all p's <0.05); ST was correlated with MCP-1 (r=0.31) and TNF-α (r= 0.29, all p's <0.05); however, after adjusting for CAH status, almost all correlations were attenuated for significance. CONCLUSIONS: Relationships among key brain structures, body composition and inflammatory markers in pediatric patients with CAH could be largely driven by having CAH, with implications for obesity and neuroinflammation in this high-risk population.

Age-Related Decline in BBB Function is More Pronounced in Males than Females.

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8 to 92 years old, using a novel non-invasive diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our novel DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60s, which was more pronounced in males. In addition, we observed sex differences in parietotemporal and hippocampal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders.

Building towards an adolescent neural urbanome: Expanding environmental measures using linked external data (LED) in the ABCD study.

Many recent studies have demonstrated that environmental contexts, both social and physical, have an important impact on child and adolescent neural and behavioral development. The adoption of geospatial methods, such as in the Adolescent Brain Cognitive Development (ABCD) Study, has facilitated the exploration of many environmental contexts surrounding participants' residential locations without creating additional burdens for research participants (i.e., youth and families) in neuroscience studies. However, as the number of linked databases increases, developing a framework that considers the various domains related to child and adolescent environments external to their home becomes crucial. Such a framework needs to identify structural contextual factors that may yield inequalities in children's built and natural environments; these differences may, in turn, result in downstream negative effects on children from historically minoritized groups. In this paper, we develop such a framework - which we describe as the "adolescent neural urbanome" - and use it to categorize newly geocoded information incorporated into the ABCD Study by the Linked External Data (LED) Environment & Policy Working Group. We also highlight important relationships between the linked measures and describe possible applications of the Adolescent Neural Urbanome. Finally, we provide a number of recommendations and considerations regarding the responsible use and communication of these data, highlighting the potential harm to historically minoritized groups through their misuse.

"Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors.

While numerous studies over the last decade have highlighted the important influence of environmental factors on mental health, globally applicable data on physical surroundings are still limited. Access to such data and the possibility to link them to epidemiological studies is critical to unlocking the relationship of environment, brain and behaviour and promoting positive future mental health outcomes. The Adolescent Brain Cognitive Development (ABCD) Study is the largest ongoing longitudinal and observational study exploring brain development and child health among children from 21 sites across the United States. Here we describe the linking of the ABCD study data with satellite-based "Urban-Satellite" (UrbanSat) variables consisting of 11 satellite-data derived environmental indicators associated with each subject's residential address at their baseline visit, including land cover and land use, nighttime lights, and population characteristics. We present these UrbanSat variables and provide a review of the current literature that links environmental indicators with mental health, as well as key aspects that must be considered when using satellite data for mental health research. We also highlight and discuss significant links of the satellite data variables to the default mode network clustering coefficient and cognition. This comprehensive dataset provides the foundation for large-scale environmental epidemiology research.

Air pollution and age-dependent changes in emotional behavior across early adolescence in the U.S.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9-10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.

Associations among prenatal exposure to gestational diabetes mellitus, brain structure, and child adiposity markers.

OBJECTIVE: The aim of this study was to investigate the mediating role of child brain structure in the relationship between prenatal gestational diabetes mellitus (GDM) exposure and child adiposity. METHODS: This was a cross-sectional study of 9- to 10-year-old participants and siblings across the US. Data were obtained from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study®. Brain structure was evaluated by magnetic resonance imaging. GDM exposure was self-reported, and discordance for GDM exposure within biological siblings was identified. Mixed effects and mediation models were used to examine associations among prenatal GDM exposure, brain structure, and adiposity markers with sociodemographic covariates. RESULTS: The sample included 8521 children (7% GDM-exposed), among whom there were 28 sibling pairs discordant for GDM exposure. Across the entire study sample, prenatal exposure to GDM was associated with lower global and regional cortical gray matter volume (GMV) in the bilateral rostral middle frontal gyrus and superior temporal gyrus. GDM-exposed siblings also demonstrated lower global cortical GMV than unexposed siblings. Global cortical GMV partially mediated the associations between prenatal GDM exposure and child adiposity markers. CONCLUSIONS: The results identify brain markers of prenatal GDM exposure and suggest that low cortical GMV may explain increased obesity risk for offspring prenatally exposed to GDM.

Joint polygenic and environmental risks for childhood attention-deficit/hyperactivity disorder (ADHD) and ADHD symptom dimensions.

Background: attention-deficit/hyperactivity disorder (ADHD) is associated with both polygenic liability and environmental exposures, both intrinsic to the family, such as family conflict, and extrinsic, such as air pollution. However, much less is known about the interplay between environmental and genetic risks relevant to ADHD-a better understanding of which could inform both mechanistic models and clinical prediction algorithms. Methods: Two independent data sets, the population-based Adolescent Brain Cognitive Development Study (ABCD) (N = 11,876) and the case-control Oregon-ADHD-1000 (N = 1449), were used to examine additive (G + E) and interactive (GxE) effects of selected polygenic risk scores (PRS) and environmental factors in a cross-sectional design. Genetic risk was measured using PRS for nine mental health disorders/traits. Exposures included family income, family conflict/negative sentiment, and geocoded measures of area deprivation, lead exposure risk, and air pollution exposure (nitrogen dioxide and fine particulate matter). Results: ADHD PRS and family conflict jointly predicted concurrent ADHD symptoms in both cohorts. Additive-effects models, including both genetic and environmental factors, explained significantly more variation in symptoms than any individual factor alone (joint R 2 = .091 for total symptoms in ABCD; joint R 2 = .173 in Oregon-ADHD-1000; all delta-R 2 p-values <2e-7). Significant effect size heterogeneity across ancestry groups was observed for genetic and environmental factors (e.g., Q = 9.01, p = .011 for major depressive disorder PRS; Q = 13.34, p = .001 for area deprivation). GxE interactions observed in the full ABCD cohort suggested stronger environmental effects when genetic risk is low, though they did not replicate. Conclusions: Reproducible additive effects of PRS and family environment on ADHD symptoms were found, but GxE interaction effects were not replicated and appeared confounded by ancestry. Results highlight the potential value of combining exposures and PRS in clinical prediction algorithms. The observed differences in risks across ancestry groups warrant further study to avoid health care disparities.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old.

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Profiling intra- and inter-individual differences in brain development across early adolescence.

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

Sex-specific effects in how childhood exposures to multiple ambient air pollutants affect white matter microstructure development across early adolescence.

Ambient air pollution is ubiquitous, yet questions remain as to how it might impact the developing brain. Large changes occur in the brain's white matter (WM) microstructure across adolescence, with noticeable differences in WM integrity in male and female youth. Here we report sex-stratified effects of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) on longitudinal patterns of WM microstructure from 9-13 years-old in 8,182 (49% female) participants using restriction spectrum imaging. After adjusting for key sociodemographic factors, multi-pollutant, sex-stratified models showed that one-year annual exposure to PM2.5 and NO2 was associated with higher, while O3 was associated with lower, intracellular diffusion at age 9. All three pollutants also affected trajectories of WM maturation from 9-13 years-old, with some sex-specific differences in the number and anatomical locations of tracts showing altered trajectories of intracellular diffusion. Concentrations were well-below current U.S. standards, suggesting exposure to these criteria pollutants during adolescence may have long-term consequences on brain development.

Effects of ambient fine particulates, nitrogen dioxide, and ozone on maturation of functional brain networks across early adolescence.

BACKGROUND: Air pollution is linked to neurodevelopmental delays, but its association with longitudinal changes in brain network development has yet to be investigated. We aimed to characterize the effect of PM2.5, O3, and NO2 exposure at ages 9-10 years on changes in functional connectivity (FC) over a 2-year follow-up period, with a focus on the salience (SN), frontoparietal (FPN), and default-mode (DMN) brain networks as well as the amygdala and hippocampus given their importance in emotional and cognitive functioning. METHODS: A sample of children (N = 9,497; with 1-2 scans each for a total of 13,824 scans; 45.6% with two brain scans) from the Adolescent Brain Cognitive Development (ABCD) Study® were included. Annual averages of pollutant concentrations were assigned to the child's primary residential address using an ensemble-based exposure modeling approach. Resting-state functional MRI was collected on 3T MRI scanners. First, developmental linear mixed-effect models were performed to characterize typical FC development within our sample. Next, single- and multi-pollutant linear mixed-effect models were constructed to examine the association between exposure and intra-network, inter-network, and subcortical-to-network FC change over time, adjusting for sex, race/ethnicity, income, parental education, handedness, scanner type, and motion. RESULTS: Developmental profiles of FC over the 2-year follow-up included intra-network integration within the DMN and FPN as well as inter-network integration between the SN-FPN; along with intra-network segregation in the SN as well as subcortical-to-network segregation more broadly. Higher PM2.5 exposure resulted in greater inter-network and subcortical-to-network FC over time. In contrast, higher O3 concentrations resulted in greater intra-network, but less subcortical-to-network FC over time. Lastly, higher NO2 exposure led to less inter-network and subcortical-to-network FC over the 2-year follow-up period. CONCLUSION: Taken together, PM2.5, O3, and NO2 exposure in childhood relate to distinct changes in patterns of network maturation over time. This is the first study to show outdoor ambient air pollution during childhood is linked to longitudinal changes in brain network connectivity development.

Air pollution and emotional behavior in adolescents across the U.S.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study examines how annual average PM2.5 and NO2 exposure at ages 9-10 years relates to internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at baseline and annually for two follow-up sessions for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Overall, the pollution effects moderated the main effects of age with higher levels of PM2.5 and NO2 leading to an even greater likelihood of having no behavioral problems (i.e., score of zero) with age over time, as well as fewer problems when problems are present as the child ages. Albeit this was on the order equal to or less than a 1-point change. Thus, one year of annual exposure at 9-10 years is linked with very small change in emotional behaviors in early adolescence, which may be of little clinical relevance.

Ambient fine particulate exposure and subcortical gray matter microarchitecture in 9- and 10-year-old children across the United States.

Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM2.5), daily nitrogen dioxide (NO2), and 8-h maximum ozone (O3) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Study℠. Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.