Motivation and Cognitive Abilities as Mediators Between Polygenic Scores and Psychopathology in Children

Polygenic risks for depression and neural responses to reward and punishment in young adults

BACKGROUND

Extensive research has shown aberrant reward and punishment processing in people with depression. Genetic risks contribute to depression, but whether or how these risks of depression may impact behavioral and neural responses to reward and punishment remains unclear.

METHODS

We curated the data of 879 young adults performing a gambling task during brain imaging from the Human Connectome Project. Depression severity was assessed with the Achenbach Adult Self Report. Polygenic risk scores (PRS) for depression were computed for all subjects. With published routines and at a corrected threshold, we evaluated how brain responses to reward and punishment associated with depression scores and PRS in a linear regression in all, male, and female subjects, with age, sex (for all), race, and drinking severity as covariates.

RESULTS

The results showed broad frontal, parietal, and occipital cortical activation in negative correlation with PRS during both reward and punishment processing. Notably, posterior cingulate cortical activation was specifically associated with PRS-related punishment processing. Additionally, men and women displayed both shared and distinct neural responses to PRS-related reward and punishment processing.

CONCLUSIONS

These findings highlight the influence of genetic risks for depression on neural responses to reward and punishment and provide insights into genetically informed markers of depression.

Gene-environment pathways to cognitive intelligence and psychotic-like experiences in children

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning, influenced by genetic and environmental factors, is hypothesized to mediate the relationship between these factors and childhood PLEs. Using large-scale 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. We leveraged large-scale multimodal data of 6,602 children from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows estimation of both components and factors were used to estimate the joint effects of cognitive phenotypes 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). Our findings indicate that lower cognitive intelligence and higher PLEs are significantly associated with lower PGSs for cognitive phenotypes, lower familial SES, lower neighborhood SES, and less supportive environments. Specifically, cognitive intelligence mediates the effects of these factors on PLEs, with supportive parenting and positive school environments showing the strongest impact on reducing PLEs. This study underscores the influence of genetic and environmental factors on PLEs through their effects on cognitive intelligence. Our findings have policy implications in that improving school and family environments and promoting local economic development may enhance cognitive and mental health in children.

Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population

This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.

Longitudinally stable, brain-based predictive models mediate the relationships between childhood cognition and socio-demographic, psychological and genetic factors

Cognitive abilities are one of the major transdiagnostic domains in the National Institute of Mental Health's Research Domain Criteria (RDoC). Following RDoC's integrative approach, we aimed to develop brain-based predictive models for cognitive abilities that (a) are developmentally stable over years during adolescence and (b) account for the relationships between cognitive abilities and socio-demographic, psychological and genetic factors. For this, we leveraged the unique power of the large-scale, longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (n ~ 11 k) and combined MRI data across modalities (task-fMRI from three tasks: resting-state fMRI, structural MRI and DTI) using machine-learning. Our brain-based, predictive models for cognitive abilities were stable across 2 years during young adolescence and generalisable to different sites, partially predicting childhood cognition at around 20% of the variance. Moreover, our use of 'opportunistic stacking' allowed the model to handle missing values, reducing the exclusion from around 80% to around 5% of the data. We found fronto-parietal networks during a working-memory task to drive childhood-cognition prediction. The brain-based, predictive models significantly, albeit partially, accounted for variance in childhood cognition due to (1) key socio-demographic and psychological factors (proportion mediated = 18.65% [17.29%-20.12%]) and (2) genetic variation, as reflected by the polygenic score of cognition (proportion mediated = 15.6% [11%-20.7%]). Thus, our brain-based predictive models for cognitive abilities facilitate the development of a robust, transdiagnostic research tool for cognition at the neural level in keeping with the RDoC's integrative framework.

Editorial: Polygenic Risk Scores in Child Psychiatry, Research Promise, and Potential Clinical Pitfalls

Polygenic risk scores (PRSs) for mental disorders have become a major player in child psychiatry research. PRSs quantify a child's risk for childhood psychiatric disorders by summing the effects of a multitude of common risk genetic variants across the entire genome. Each genetic variant in isolation contributes a minuscule amount to the disorder, but their combined effect can be substantial. The study by Pat et al.¹ illustrates how PRSs can be used as a starting point to examine the mechanisms that might link common genetic variant risk with symptoms. In their exploration of how genes, cognition, and psychopathology may be tied together, the authors apply meticulous analytic techniques to a rich, open dataset (the Adolescent Brain Cognitive Development [ABCD] cohort) and report fascinating results.