Identifying the social and biological mechanisms of cognitive and psychological development of children is essential for optimizing preventive and educational efforts. However, the causal pathways by which genetic and environmental factors affect cognitive and psychiatric outcomes remain unknown, especially in early childhood. We examined the causal relationships among genes, the environment, intelligence, and psychotic-like experiences in 7,632 multiethnic (5,905 with European ancestry) children aged 9-10 years old from the Adolescent Brain Cognitive Development (ABCD) Study. Using up-to-date computational causal analysis and rigorous path modeling, we found a significant causal influence of residential, family, and school environments and genome-wide polygenic scores of cognitive capacities on preadolescents' psychotic-like experiences mediated by intelligence. Mitigation of good parenting behavior and positive school environments on psychotic-like experiences dominated the pernicious effects of genetic and residential adversities. Our findings support that intelligence may be a biological resilience factor for psychosis. To the best of our knowledge, this is the first study to identify casual trajectories of neurocognitive development in early childhood and the first to provide empirical evidence that positive parenting behavior and school environment can impose a considerable degree of causal impact on children's cognitive and psychiatric outcomes. We suggest the implementation of socioeconomic policies to improve family and school environments and promote local economic development to enhance children's cognitive ability and mental health.

Background: Causal explanations for the association of young motherhood with increased risk for child attentiondeficit hyperactivity disorder (ADHD) remain unclear. Methods: The ABCD Study recruited 11,878 youth from 22 sites across the United States between June 1, 2016 and October 15, 2018. This cross-sectional analysis of 8,514 children aged 8-11 years excluded 2,260 twins/triplets, 265 adopted children, and 839 younger siblings. We examined associations of maternal age with ADHD clinical range diagnoses based on the Child Behavior Checklist and NIH Toolbox Flanker Attention Scores using mixed logistic and linear regression models, respectively. We conducted confounding and causal mediation analyses using genotype array, demographic, socioeconomic, and prenatal environment data to investigate which genetic and environmental variables may explain the association between young maternal age and child ADHD. Results: In crude models, each 10-year increase in maternal age was associated with 32% decreased odds of ADHD clinical range diagnosis (OR = 0.68; 95% CI [0.59, 0.78]) and 1.09points increased NIH Flanker Attention Scores (b = 1.09; 95% CI [0.76, 1.41]), indicating better child visual selective attention. However, adjustment for confounders weakened these associations. The strongest confounders were family income, caregiver education, and ADHD polygenic risk score for ADHD clinical range diagnoses, and family income, caregiver education, and race/ethnicity for NIH Flanker Attention Scores. Breastfeeding duration, prenatal alcohol exposure, and prenatal tobacco exposure were responsible for up to 18%, 6%, and 4% mediation, respectively. Conclusions: Socioeconomic disadvantages were likely the primary explanation for the association of young maternal age with child ADHD, although genetics and modifiable environmental factors also played a role. Public policies aimed at reducing the burden of ADHD associated with young motherhood should target socioeconomic inequalities and support young pregnant women by advocating for reduced prenatal tobacco exposure and healthy breastfeeding practices after childbirth.

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning is a well-known risk factor and early marker for psychosis, schizophrenia, and other mental disorders. Since cognitive functioning is linked to various genetic and environmental factors during development, we hypothesize that it mediates the effects of those factors on childhood PLEs. Using large, representative, longitudinal data, we tested the relationships of genetic and environmental factors (such as familial and neighborhood environment) with cognitive intelligence and their relationships with current and future PLEs in children. To estimate unbiased associations against potential confounding variables, we leveraged large-scale, representative, multimodal data of 6,602 children (aged 9-10 years old; 47.15% females; 5,211 European-ancestry) from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows unbiased estimation of both components and factors were used to estimate the joint effects of cognitive capacity polygenic scores (PGSs), familial and neighborhood socioeconomic status (SES), and supportive environment on NIH Toolbox cognitive intelligence and PLEs. We adjusted for ethnicity (genetically defined), schizophrenia PGS, and additionally unobserved confounders (using computational confound modeling). We identified that lower cognitive intelligence and higher PLEs correlated significantly with several genetic and environmental variables: i.e., lower PGSs for cognitive capacity, lower familial SES, lower neighborhood SES, lower supportive parenting behavior, and lower positive school environment. In SEM, lower cognitive intelligence significantly mediated the genetic and environmental influences on higher PLEs (Indirect effects of PGS: β range=-0.0355∼ -0.0274; Family SES: β range=-0.0429∼ -0.0331; Neighborhood SES: β range=0.0126∼ 0.0164; Positive Environment: β range=-0.0039∼ -0.003). Supportive parenting and a positive school environment had the largest total impact on PLEs (β range=-0.152∼ -0.1316) than genetic or environmental factors. Our results reveal the role of genetic and environmental factors on children’s risk for psychosis via its negative impact on cognitive intelligence. Our findings have policy implications in that improving the school and family environment and promoting local economic development might be a way to enhance cognitive and mental health in children. While existing research shows the association between cognitive decline and the onset of psychosis, the genetic and environmental pathways to cognitive intelligence and psychotic risk in children remain unclear. We identified the significant role of genetic and environmental factors (family, neighborhood, and school) on children’s risk for psychosis via a negative impact on cognitive intelligence. Obtaining unbiased estimation by leveraging large, representative samples with multimodal data and advanced computational modeling for confounders, our results underscore the importance of incorporating socioeconomic policies into children’s cognitive and mental health programs.

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning is a well-known risk factor and early marker for psychosis, schizophrenia, and other mental disorders. Since cognitive functioning is linked to various genetic and environmental factors during development, we hypothesize that it mediates the effects of those factors on childhood PLEs. Using large, representative, longitudinal data, we tested the relationships of genetic and environmental factors (such as familial and neighborhood environment) with cognitive intelligence and their relationships with current and future PLEs in children. To estimate unbiased associations against potential confounding variables, we leveraged large-scale, representative, multimodal data of 6,602 children (aged 9-10 years old; 47.15% females; 5,211 European-ancestry) from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows unbiased estimation of both components and factors were used to estimate the joint effects of cognitive capacity polygenic scores (PGSs), familial and neighborhood socioeconomic status (SES), and supportive environment on NIH Toolbox cognitive intelligence and PLEs. We adjusted for ethnicity (genetically defined), schizophrenia PGS, and additionally unobserved confounders (using computational confound modeling). We identified that lower cognitive intelligence and higher PLEs correlated significantly with several genetic and environmental variables: i.e., lower PGSs for cognitive capacity, lower familial SES, lower neighborhood SES, lower supportive parenting behavior, and lower positive school environment. In SEM, lower cognitive intelligence significantly mediated the genetic and environmental influences on higher PLEs (Indirect effects of PGS: β range=-0.0355∼ -0.0274; Family SES: β range=-0.0429∼ -0.0331; Neighborhood SES: β range=0.0126∼ 0.0164; Positive Environment: β range=-0.0039∼ -0.003). Supportive parenting and a positive school environment had the largest total impact on PLEs (β range=-0.152∼ -0.1316) than genetic or environmental factors. Our results reveal the role of genetic and environmental factors on children’s risk for psychosis via its negative impact on cognitive intelligence. Our findings have policy implications in that improving the school and family environment and promoting local economic development might be a way to enhance cognitive and mental health in children. While existing research shows the association between cognitive decline and the onset of psychosis, the genetic and environmental pathways to cognitive intelligence and psychotic risk in children remain unclear. We identified the significant role of genetic and environmental factors (family, neighborhood, and school) on children’s risk for psychosis via a negative impact on cognitive intelligence. Obtaining unbiased estimation by leveraging large, representative samples with multimodal data and advanced computational modeling for confounders, our results underscore the importance of incorporating socioeconomic policies into children’s cognitive and mental health programs.

Delay discounting is linked to developmental trajectories of cognition and the brain, as well as psychopathology, such as psychosis. Although childhood socioeconomic deprivation is associated with both increased delay discounting and a higher incidence of psychotic disorders, the genetic and neural basis of these associations remains unclear. This study examined the causal relationships between neighborhood socioeconomic deprivation, delay discounting, and psychotic-like experiences (PLEs) in 2,135 preadolescent children using machine learning-based causal inference methods. We found that neighborhood deprivation, as measured by the Area Deprivation Index, had significant causal effects on delay discounting (β= -1.7297, p-FDR= 0.0258) and 1-year and 2-year follow-up PLEs (β= 1.3425~1.8721, p-FDR≤ 0.0291). Furthermore, our analysis revealed significant heterogeneous causal effects of neighborhood deprivation on PLEs (p-FDR<0.005). The subgroups most vulnerable to these causal effects exhibited steeper discounting of future rewards, higher polygenic scores for educational attainment, reduced structural volume/area/white matter in the parahippocampal, right temporal pole, and right pars opercularis, and greater functional activation in the limbic system during Monetary Incentives Delay tasks. Our findings highlight the importance of a bioecological framework and the involvement of the mesocorticolimbic system in the causal relationship between socioeconomic deprivation and the risk of psychosis during childhood. Overall, our results support that enhancing the residential socioeconomic environment could positively influence child development.