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Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain’s functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive DevelopmentSMStudy. Across matched discovery (n=3,525) and replication (n=3,447) samples, the total cortical representation of fronto-parietal PFNs positively correlated with general cognition. Cross-validated ridge regressions trained on PFN topography predicted cognition across domains, with prediction accuracy increasing along the cortex’s sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.

ObjectiveThe authors used multimodal data collected during pre/early-adolescence in research settings to predict self-report of past suicide attempt (SA) by mid-late adolescence in pediatric care settings. The study further aimed to determine types of data that contribute to the prediction; and to test generalizability of the prediction in an independent sample.MethodsThe authors applied machine learning methods on clinical, neurocognitive and geocoded neighborhood environmental data from the Philadelphia Neurodevelopmental Cohort study (PNC, Mean age 11.1, SD=2.2, 52.3% female and 51.4% Black participants) to predict SA reported ∼5 years later in a community pediatric clinic (n=922, 5.3% SA) or emergency department (n=497, 8.2% SA). The authors compared prediction performance when using all data versus individual data types, then used feature selection algorithms (Lasso, Relief and Random Forest) to identify important predictors and compared performance of models relying on feature subsets.ResultsIn the training dataset, SA prediction was good, reaching AUC=0.75, sensitivity/specificity 0.76/0.77 when relying on feature subsets identified using feature selection pipelines. Use of highest-ranking feature subsets from the training dataset yielded similar prediction in the testing dataset with AUC=0.74, sensitivity/specificity 0.66/0.70. Different algorithms showed different high-ranking features, but overall multiple data domains were represented among the highest-ranking predictors selected by each algorithm.ConclusionsThese findings provide evidence for feasibility of predicting youth SA using data collected at a single timepoint early in life in a diverse cohort. Results encourage incorporation of multiple data types including neurocognitive and geocoded environmental measures in machine learning SA prediction pipelines.

BackgroundSuicidal thoughts and behavior (STB) in children are a growing health concern, and more data is needed regarding their biological underpinnings. Immune processes such as inflammation have been associated with STB, primarily in adults. Asthma is a common chronic inflammatory disorder in children and has been associated with STB in adolescent and adult populations, but data in children is lacking. We wished to study associations of asthma with childhood STB given asthma’s potential as a clinically relevant model for childhood chronic immune dysregulation.MethodsUsing data from the Adolescent Brain Cognitive Development (ABCD) Study (N=11,878, 52% males, mean age 9.9 years at baseline assessment and 10.9 years at 1-year follow up), we assessed associations between asthma and STB at both baseline and 1-year follow up.ResultsWe found that asthma at baseline assessment (n=2,214, 18.6%) is associated with STB, controlling for multiple confounders including demographics, socioeconomic factors and environmental confounders such as air pollution (odds ratio (OR)=1.2, 95%CI 1.01-1.42, P=0.039). Indicators of recently active asthma were not significantly associated with suicidality at baseline assessment (currently taking asthma medication: OR=1.22, 95%CI 0.93-1.60, P=0.146), or at 1-year follow up (past year asthma-related clinical visit: OR=1.13, 95%CI 0.87-1.47, P=0.357). Proxy-measures of asthma severity (number of asthma medications or clinical visits) did not reveal a significant dose response relationship with STB.ConclusionsFindings suggest an association between history of asthma and STB in children, which may not be related to asthma disease state. Further research is needed to investigate mechanisms underlying this relationship.

BackgroundThe COVID-19 pandemic is a rapidly evolving stressor with significant mental health consequences. We aimed to delineate distinct anxiety-response trajectories during the early stages of the pandemic and to identify baseline risk and resilience factors as predictors of anxiety responses.MethodsUsing a crowdsourcing website, we enrolled 1,362 participants, primarily from the United States (n = 1064) and Israel (n = 222) over three time-points from April-September 2020. We used latent growth mixture modeling to identify anxiety trajectories over time. Group comparison and multivariate regression models were used to examine demographic and risk and resilience factors associated with class membership.ResultsA four-class model provided the best fit. The resilient trajectory (stable low anxiety) was the most common (n = 961, 75.08%), followed by chronic anxiety (n = 149, 11.64%), recovery (n = 96, 7.50%) and delayed anxiety (n = 74, 5.78%). While COVID-19 stressors did not differ between trajectories, resilient participants were more likely to be older, living with another person and to report higher income, more education, fewer COVID-19 worries, better sleep quality, and more dispositional resilience factors at baseline. Multivariate analyses suggested that baseline emotion regulation capabilities and low conflictual relationships uniquely distinguished participants in distinct trajectories.ConclusionsConsistent with prior resilience research following major adversities, a majority of individuals showed stable low levels of low anxiety in response to the COVID-19 pandemic. Knowledge about dispositional resilience factors may prospectively inform mental health trajectories early in the course of ongoing adversity.

Low socioeconomic status has been shown to have detrimental effects on cognitive performance, including working memory (WM). As executive systems that support WM undergo functional neurodevelopment during adolescence, environmental stressors at both individual and community levels may have a particularly strong impact on cognitive outcomes. Here, we sought to examine how neighborhood socioeconomic status (SES) impacts task-related activation of the executive system during adolescence, and to determine whether this effect mediates the relationship between neighborhood SES and WM performance. To address these questions, we studied 1,158 youths (age 8-22) that completed a fractal n-back WM task during fMRI at 3T as part of the Philadelphia Neurodevelopmental Cohort. We found that higher neighborhood SES was associated with greater activation of the executive system to WM load, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and precuneus. These associations remained significant when controlling for related factors like parental education and exposure to traumatic events. Furthermore, high dimensional multivariate mediation analysis identified two distinct patterns of brain activity within the executive system that significantly mediated the relationship between neighborhood SES and task performance. Together, these findings underscore the importance of the neighborhood environment in shaping executive system function and WM in youth.

Exposures to perinatal, familial, social, and physical environmental stimuli can have substantial effects on human development. Yet the complex network structure of the environment (i.e., exposome) makes it challenging to investigate. Here, we analyze the exposome using data from the Adolescent Brain Cognitive Development Study (ABCD, N = 11,235, mean age = 10.9, 52% male) and replicate key findings in an age and sex matched sample from the Philadelphia Neurodevelopmental Cohort (PNC, N = 4,993). Both these cohorts are large, diverse samples of US adolescents with phenotyping at multiple levels of environmental exposure. In ABCD, applying data-driven iterative factor analyses and bifactor modeling, we reduced dimensionality from n=798 exposures to six exposome subfactors and a general (adverse) exposome factor. These factors revealed quantitative differences among racial and ethnic groups. Exposome factors increased variance explained in mental health by 10-fold (from 38%), over and above other commonly used sociodemographic factors. The general exposome factor was associated with psychopathology (β=0.28, 95%CI 0.26-0.3) and key health-related outcomes: obesity (OR=1.4, 95%CI 1.3-1.5) and advanced pubertal development (OR=1.3, 95%CI 1.2-1.5). In PNC, using substantially fewer available environmental exposures (n=29), analyses yielded consistent associations of the general exposome factor with psychopathology (β =0.15, 95%CI 0.13-0.17), obesity (OR=1.4, 95%CI 1.3-1.6) and advanced pubertal development (OR=1.3, 95%CI 1-1.6). Findings demonstrate how incorporating the exposome framework can be useful to study the role of environment in human development.

Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual patient level when phenotypes are not necessarily already known. Hence, we investigated the stability of PGS in European-American (EUR)- and African-American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort (PNC) and the Adolescent Brain Cognitive Development (ABCD) cohort using different discovery GWAS for post-traumatic stress disorder (PTSD), type-2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations > 0.92. However, PGS calculated from pairs of sameancestry and different-ancestry GWAS had correlations that ranged from th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the level of the individual patient, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.

Suicidal ideation and attempts (i.e., suicidality) are complex behaviors driven by environmental stress, genetic susceptibility, and their interaction. Preadolescent suicidality is a major health problem with rising rates, yet its underlying biology is understudied. Here we studied effects of genetic stress susceptibility, estimated by polygenic risk score (PRS) for post-traumatic-stress-disorder (PTSD), on preadolescent suicidality in participants from the Adolescent Brain Cognitive Development (ABCD) Study®. We further evaluated PTSD-PRS effects on suicidality in the presence of environmental stressors that are established suicide risk factors. Analyses included both European and African ancestry participants using PRS calculated based on summary statistics from ancestry-specific genome-wide association studies. In European ancestry participants (N=4,619, n=378 suicidal), PTSD-PRS was associated with preadolescent suicidality (odds ratio [OR]=1.12, 95%CI 1-1.25, p=0.038). Results in African ancestry participants (N=1,334, n=130 suicidal) showed a similar direction but were not statistically significant (OR=1.21, 95%CI 0.93-1.57, p=0.153). Sensitivity analyses using non-psychiatric polygenic score for height and using cross-ancestry PTSD-PRS did not reveal any association with suicidality, supporting the specificity of the association of ancestry-specific PTSD-PRS with suicidality. Environmental stressors were robustly associated with suicidality across ancestries with moderate effect size for negative life events and family conflict (OR 1.27-1.6); and with large effect size (OR ∼ 4) for sexual-orientation discrimination. When combined with environmental factors, PTSD-PRS showed marginal additive effects in explaining variability in suicidality, with no evidence for G X E interaction. Results support use of cross-phenotype PRS, specifically stress-susceptibility, as a robust genetic marker for suicidality risk early in the lifespan.

BackgroundThe COVID-19 pandemic has major ramifications for global health and the economy, with growing concerns about economic recession and implications for mental health. Here we investigated the associations between COVID-19 pandemic-related income loss with financial strain and mental health trajectories over a 1-month course.MethodsTwo independent studies were conducted in the U.S and in Israel at the beginning of the outbreak (March-April 2020, T1; N = 4 171) and at a 1-month follow-up (T2; N = 1 559). Mixed-effects models were applied to assess associations among COVID-19-related income loss, financial strain, and pandemic-related worries about health, with anxiety and depression, controlling for multiple covariates including pre-COVID-19 income.FindingsIn both studies, income loss and financial strain were associated with greater depressive symptoms at T1, above and beyond T1 anxiety, worries about health, and pre-COVID-19 income. Worsening of income loss was associated with exacerbation of depression at T2 in both studies. Worsening of subjective financial strain was associated with exacerbation of depression at T2 in one study (US).InterpretationIncome loss and financial strain were uniquely associated with depressive symptoms and the exacerbation of symptoms over time, above and beyond pandemic-related anxiety. Considering the painful dilemma of lockdown versus reopening, with the tradeoff between public health and economic wellbeing, our findings provide evidence that the economic impact of COVID-19 has negative implications for mental health.FundingThis study was supported by grants from the National Institute of Mental Health, the US-Israel Binational Science Foundation, Foundation Dora and Kirsh Foundation.