The ABCD study: understanding the development of risk for mental and physical health outcomes

Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Function and Psychopathology in Preadolescents

BACKGROUND

Cognitive function and general psychopathology are two important classes of human behavior dimensions that are individually related to mental disorders across diagnostic categories. However, whether these two transdiagnostic dimensions are linked to common or distinct brain networks that convey resilience or risk for the development of psychiatric disorders remains unclear.

METHODS

The current study is a longitudinal investigation with 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study at ages 9 to 10 years at the onset of the study. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of the resting-state functional connectome with multidomain behavioral assessments including cognitive functions and psychopathological measures. For the latent resting-state functional connectivity factor showing a robust behavioral association, its ability to predict psychiatric disorders was assessed using 2-year follow-up data, and its genetic association was evaluated using twin data from the same cohort.

RESULTS

A latent functional connectome pattern was identified that showed a strong and generalizable association with the multidomain behavioral assessments (5-fold cross-validation: ρ = 0.68-0.73 for the training set [n = 5096]; ρ = 0.56-0.58 for the test set [n = 1476]). This functional connectome pattern was highly heritable (h2 = 74.42%, 95% CI: 56.76%-85.42%), exhibited a dose-response relationship with the cumulative number of psychiatric disorders assessed concurrently and at 2 years post-magnetic resonance imaging scan, and predicted the transition of diagnosis across disorders over the 2-year follow-up period.

CONCLUSIONS

These findings provide preliminary evidence for a transdiagnostic connectome-based measure that underlies individual differences in the development of psychiatric disorders during early adolescence.

Data-driven, generalizable prediction of adolescent sleep disturbances in the multisite Adolescent Brain Cognitive Development Study

STUDY OBJECTIVES

Sleep disturbances are common in adolescence and associated with a host of negative outcomes. Here, we assess associations between multifaceted sleep disturbances and a broad set of psychological, cognitive, and demographic variables using a data-driven approach, canonical correlation analysis (CCA).

METHODS

Baseline data from 9093 participants from the Adolescent Brain Cognitive Development (ABCD) Study were examined using CCA, a multivariate statistical approach that identifies many-to-many associations between two sets of variables by finding combinations for each set of variables that maximize their correlation. We combined CCA with leave-one-site-out cross-validation across ABCD sites to examine the robustness of results and generalizability to new participants. The statistical significance of canonical correlations was determined by non-parametric permutation tests that accounted for twin, family, and site structure. To assess the stability of the associations identified at baseline, CCA was repeated using 2-year follow-up data from 4247 ABCD Study participants.

RESULTS

Two significant sets of associations were identified: (1) difficulty initiating and maintaining sleep and excessive daytime somnolence were strongly linked to nearly all domains of psychopathology (r2 = 0.36, p < .0001); (2) sleep breathing disorders were linked to BMI and African American/black race (r2 = 0.08, p < .0001). These associations generalized to unseen participants at all 22 ABCD sites and were replicated using 2-year follow-up data.

CONCLUSIONS

These findings underscore interwoven links between sleep disturbances in early adolescence and psychological, social, and demographic factors.

Long-term impact of digital media on brain development in children

Digital media (DM) takes an increasingly large part of children's time, yet the long-term effect on brain development remains unclear. We investigated how individual effects of DM use (i.e., using social media, playing video games, or watching television/videos) on the development of the cortex (i.e., global cortical surface area), striatum, and cerebellum in children over 4 years, accounting for both socioeconomic status and genetic predisposition. We used a prospective, multicentre, longitudinal cohort of children from the Adolescent Brain and Cognitive Development Study, aged 9.9 years when entering the study, and who were followed for 4 years. Annually, children reported their DM usage through the Youth Screen Time Survey and underwent brain magnetic resonance imaging scans every 2 years. Quadratic-mixed effect modelling was used to investigate the relationship between individual DM usage and brain development. We found that individual DM usage did not alter the development of cortex or striatum volumes. However, high social media usage was associated with a statistically significant change in the developmental trajectory of cerebellum volumes, and the accumulated effect of high-vs-low social media users on cerebellum volumes over 4 years was only β = - 0.03, which was considered insignificant. Nevertheless, the developmental trend for heavy social media users was accelerated at later time points. This calls for further studies and longer follow-ups on the impact of social media on brain development.

The future of intergenerational transmission research: A prospective, three-generation approach

Dr. Dante Cicchetti's pioneering theory and research on developmental psychopathology have been fundamental to the proliferation of research on intergenerational transmission over the last 40 years. In part due to this foundation, much has been learned about continuities and discontinuities in child maltreatment, attachment, parenting, and psychopathology across generations. Looking towards the future, we propose that this field stands to benefit from a prospective, three-generation approach. Specifically, following established prospective, longitudinal cohorts of children over their transition to parenting the next generation will afford the opportunity to investigate the developmental origins of intergenerational transmission. This approach also can address key outstanding questions and methodological limitations in the extant literature related to the confounding of retrospective and prospective measures; examination of mediators and moderators; and investigation of the roles of biology, environment, and their interplay. After considering these advantages, we offer several considerations and recommendations for future research, many of which are broadly applicable to the study of two or more generations. We hope that this discussion will inspire the leveraging of existing prospective cohorts to carry forward Dr. Cicchetti's remarkable contributions, with the ultimate aim to inform the development of preventions and interventions that disrupt deleterious intergenerational cycles.

Familial risk for depression moderates neural circuitry in healthy preadolescents to predict adolescent depression symptoms in the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

There is an imminent need to identify neural markers during preadolescence that are linked to developing depression during adolescence, especially among youth at elevated familial risk. However, longitudinal studies remain scarce and exhibit mixed findings. Here we aimed to elucidate functional connectivity (FC) patterns among preadolescents that interact with familial depression risk to predict depression two years later.

METHODS

9-10 year-olds in the Adolescent Brain Cognitive Development (ABCD) Study were classified as healthy (i.e., no lifetime psychiatric diagnoses) at high familial risk for depression (HR; n=559) or at low familial risk for psychopathology (LR; n=1203). Whole-brain seed-to-voxel resting-state FC patterns with the amygdala, putamen, nucleus accumbens, and caudate were calculated. Multi-level, mixed-effects regression analyses were conducted to test whether FC at ages 9-10 interacted with familial risk to predict depression symptoms at ages 11-12.

RESULTS

HR youth demonstrated stronger associations between preadolescent FC and adolescent depression symptoms (ps<0.001) as compared to LR youth (ps>0.001), primarily among amygdala/striatal FC with visual and sensory/somatomotor networks.

CONCLUSIONS

Preadolescent amygdala and striatal FC may be useful biomarkers of adolescent-onset depression, particularly for youth with family histories of depression. This research may point to neurobiologically-informed approaches to prevention and intervention for depression in adolescents.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

The copy number variant architecture of psychopathology and cognitive development in the ABCD® study

Importance

Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored.

Objective

Investigating CNV associations with dimensions of child psychopathology and cognitive functions.

Design Setting and Participants

ABCD® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024.

Main Outcomes and Measures

In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes.

Results

In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains.

Conclusions and Relevance

In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

Perceptual Dysfunction in Eating Disorders

Eating disorders (EDs) are characterized by abnormal responses to food and weight-related stimuli and are associated with significant distress, impairment, and poor outcomes. Because many of the cardinal symptoms of EDs involve disturbances in perception of one's body or abnormal affective or cognitive reactions to food intake and how that affects one's size, there has been longstanding interest in characterizing alterations in sensory perception among differing ED diagnostic groups. Within the current review, we aimed to critically assess the existing research on exteroceptive and interoceptive perception and how sensory perception may influence ED behavior. Overall, existing research is most consistent regarding alterations in taste, visual, tactile, and gastric-specific interoceptive processing in EDs, with emerging work indicating elevated respiratory and cardiovascular sensitivity. However, this work is far from conclusive, with most studies unable to speak to the precise etiology of observed perceptual differences in these domains and disentangle these effects from affective and cognitive processes observed within EDs. Further, existing knowledge regarding perceptual disturbances in EDs is limited by heterogeneity in methodology, lack of multimodal assessment protocols, and inconsistent attention to different ED diagnoses. We propose several new avenues for improving neurobiology-informed research on sensory processing to generate actionable knowledge that can inform the development of innovative interventions for these serious disorders.

Racial-Ethnic Discrimination and Early Adolescents' Behavioral Problems: The Protective Role of Parental Warmth

OBJECTIVE

The purpose of the study was to investigate the association between discrimination by multiple sources (ie, teachers, students, and other adults) and early adolescents' behavioral problems (ie, internalizing, externalizing, and attention problems), also considering the protective role of parental warmth in the association.

METHOD

Cross-sectional analyses were conducted with 3,245 early adolescents of color obtained from the Adolescent Brain Cognitive Development Study (ABCD Study) at year 1 follow-up (Y1), a large and diverse sample of children (mean age = 9.48 years) in the United States. Racially-ethnically minoritized adolescents reported sources of discrimination, parental warmth, and symptoms of psychopathology. Regression with interaction terms was conducted to investigate the associations among sources of discrimination, parental warmth, and behavioral problems among racially-ethnically minority adolescents. Sensitivity analyses were conducted to examine (1) race/ethnicity and sex/gender variations; (2) whether the associations between different sources of discrimination and behavioral problems were reliably different; and (3) effects of discrimination, parental warmth, and their interplay at Y1 in predicting adolescents' behavioral problems at year 2 follow-up.

RESULTS

Early adolescents experiencing interpersonal racial-ethnic discrimination by multiple sources, including teachers, students, and other adults, reported higher levels of attention, internalizing, and externalizing problems. Parental warmth was protective for the association between interpersonal racial-ethnic discrimination and early adolescents' behavioral problems.

CONCLUSION

Experiencing interpersonal racial-ethnic discrimination from teachers, peers, and other adults is related to heightened attention, internalizing, and externalizing problems among racially-ethnically minoritized early adolescents. Parental warmth may reduce the risk of developing behavioral problems among early adolescents who experience interpersonal racial-ethnic discrimination from students, teachers, and other adults outside of school.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. We actively worked to promote sex and gender balance in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals

BACKGROUND

Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes.

METHODS

We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses.

FINDINGS

The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort.

INTERPRETATION

Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine.

FUNDING

MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

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.

The impact of menarche on hippocampal mechanisms of severity of psychotic-like experiences in the ABCD study

Accumulating evidence suggests that estrogens play an important modulatory role in the pathogenesis of psychosis. Estrogens come online within a dynamic developmental context of emerging psychopathology and neurodevelopment. As a result, estradiol (the primary form of estrogen) may influence psychosis lability directly or indirectly through its neurodevelopmental influence on estrogens-sensitive areas like the hippocampus. Understanding this influence may provide novel insight into mechanisms of psychosis lability. This study included baseline and year 2 timepoints from 4422 female participants from the Adolescent Brain Cognitive Development (ABCD) study (age 8-13), who varied in estradiol availability (pre-menarche, post-menarche, pre- and post-menarche timepoints). Estradiol availability was related to psychotic-like experiences (PLE) severity both directly and as an interactive effect with hippocampal connectivity using menarche status (pre/post) in a multilevel model. PLE severity was highest in individuals with early menarche emphasizing the importance of the developmental timing. Although PLE severity decreased over time in the sample, it stayed clinically-relevant over 2 years. Lower hippocampal connectivity was related to elevated PLE severity. This effect was moderated by estradiol; before the availability of estradiol (pre-menarche), lower hippocampal connectivity significantly contributed to the PLE severity, but when estradiol was available (post-menarche) hippocampal dysconnectivity did not account for PLE severity. This moderation suggests that the estrodiol's influence on hippocampal plasticity also reduced the mechanistic role of the hippocampus on PLE severity. Further, the lack of a significant direct reduction of PLE severity post-menarche, may suggest an increased role for other interacting psychosis lability factors during this critical developmental period.

Associations between somatomotor-putamen resting state connectivity and obsessive-compulsive symptoms vary as a function of stress during early adolescence: Data from the ABCD study

Obsessive-compulsive symptoms (OCS) are relatively common during adolescence although most individuals do not meet diagnostic criteria for obsessive-compulsive disorder (OCD). Nonetheless, OCS during adolescence are associated with comorbid psychopathologies and behavioral problems. Heightened levels of environmental stress and greater functional connectivity between the somatomotor network and putamen have been previously associated with elevated OCS in OCD patients relative to healthy controls. However, the interaction of these factors within the same sample of individuals has been understudied. This study examined somatomotor-putamen resting state connectivity, stress, and their interaction on OCS in adolescents from 9-12 years of age. Participants (n = 6386) were drawn from the ABCD Study 4.0 release. Multilevel modeling was used to account for nesting in the data and to assess changes in OCS in this age range. Stress moderated the association between somatomotor-putamen connectivity and OCS (β = 0.35, S.E. = 0.13, p = 0.006). Participants who reported more stress than their average and had greater somatomotor-left putamen connectivity reported more OCS, whereas participants who reported less stress than their average and had greater somatomotor-left putamen connectivity reported less OCS. These data suggest that stress differentially affects the direction of association between somatomotor-putamen connectivity and OCS. Individual differences in the experience or perception of stress may contribute to more OCS in adolescents with greater somatomotor-putamen connectivity.

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Childhood maltreatment influences adult brain structure through its effects on immune, metabolic, and psychosocial factors

Childhood maltreatment (CM) leads to a lifelong susceptibility to mental ill-health which might be reflected by its effects on adult brain structure, perhaps indirectly mediated by its effects on adult metabolic, immune, and psychosocial systems. Indexing these systemic factors via body mass index (BMI), C-reactive protein (CRP), and rates of adult trauma (AT), respectively, we tested three hypotheses: (H1) CM has direct or indirect effects on adult trauma, BMI, and CRP; (H2) adult trauma, BMI, and CRP are all independently related to adult brain structure; and (H3) childhood maltreatment has indirect effects on adult brain structure mediated in parallel by BMI, CRP, and AT. Using path analysis and data from N = 116,887 participants in UK Biobank, we find that CM is related to greater BMI and AT levels, and that these two variables mediate CM's effects on CRP [H1]. Regression analyses on the UKB MRI subsample (N = 21,738) revealed that greater CRP and BMI were both independently related to a spatially convergent pattern of cortical effects (Spearman's ρ = 0.87) characterized by fronto-occipital increases and temporo-parietal reductions in thickness. Subcortically, BMI was associated with greater volume, AT with lower volume and CPR with effects in both directions [H2]. Finally, path models indicated that CM has indirect effects in a subset of brain regions mediated through its direct effects on BMI and AT and indirect effects on CRP [H3]. Results provide evidence that childhood maltreatment can influence brain structure decades after exposure by increasing individual risk toward adult trauma, obesity, and inflammation.

A Brainwide Risk Score for Psychiatric Disorder Evaluated in a Large Adolescent Population Reveals Increased Divergence Among Higher-Risk Groups Relative to Control Participants

BACKGROUND

Accurate psychiatric risk assessment requires biomarkers that are both stable and adaptable to development. Functional network connectivity (FNC), which steadily reconfigures over time, potentially contains abundant information to assess psychiatric risks. However, the absence of suitable analytical methodologies has constrained this area of investigation.

METHODS

We investigated the brainwide risk score (BRS), a novel FNC-based metric that contrasts the relative distances of an individual's FNC to that of psychiatric disorders versus healthy control references. To generate group-level disorder and healthy control references, we utilized a large brain imaging dataset containing 5231 total individuals diagnosed with schizophrenia, autism spectrum disorder, major depressive disorder, and bipolar disorder and their corresponding healthy control individuals. The BRS metric was employed to assess the psychiatric risk in 2 new datasets: Adolescent Brain Cognitive Development (ABCD) Study (n = 8191) and Human Connectome Project Early Psychosis (n = 170).

RESULTS

The BRS revealed a clear, reproducible gradient of FNC patterns from low to high risk for each psychiatric disorder in unaffected adolescents. We found that low-risk ABCD Study adolescent FNC patterns for each disorder were strongly present in over 25% of the ABCD Study participants and homogeneous, whereas high-risk patterns of each psychiatric disorder were strongly present in about 1% of ABCD Study participants and heterogeneous. The BRS also showed its effectiveness in predicting psychosis scores and distinguishing individuals with early psychosis from healthy control individuals.

CONCLUSIONS

The BRS could be a new image-based tool for assessing psychiatric vulnerability over time and in unaffected individuals, and it could also serve as a potential biomarker, facilitating early screening and monitoring interventions.

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.

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline

Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that requires many software packages with complex dependencies and high computational costs. We developed MaPPeRTrac, an edge-centric tractography pipeline that simplifies and accelerates this process in a wide range of high-performance computing (HPC) environments. It fully automates either probabilistic or deterministic tractography, starting from a subject's magnetic resonance imaging (MRI) data, including structural and diffusion MRI images, to the edge density image (EDI) of their structural connectomes. Dependencies are containerized with Singularity (now called Apptainer) and decoupled from code to enable rapid prototyping and modification. Data derivatives are organized with the Brain Imaging Data Structure (BIDS) to ensure that they are findable, accessible, interoperable, and reusable following FAIR principles. The pipeline takes full advantage of HPC resources using the Parsl parallel programming framework, resulting in the creation of connectome datasets of unprecedented size. MaPPeRTrac is publicly available and tested on commercial and scientific hardware, so it can accelerate brain connectome research for a broader user community. MaPPeRTrac is available at: https://github.com/LLNL/mappertrac .

Neurodevelopmental Subtypes of Functional Brain Organization in the ABCD Study Using a Rigorous Analytic Framework

The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9-11, we identified four distinct RSFC subtypes We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

Distinct Topological Properties of the Reward Anticipation Network in Preadolescent Children With Binge Eating Disorder Symptoms

OBJECTIVE

Few studies have considered the neural underpinnings of binge eating disorder (BED) in children, despite clinical and subclinical symptom presentation occurring in this age group. Symptom presentation at this age is of clinical relevance, as early onset of binge eating is linked to negative health outcomes. Studies in adults have highlighted dysfunction in the frontostriatal reward system as a potential candidate for binge eating pathophysiology, although the exact nature of such dysfunction is currently unclear.

METHOD

Data from 83 children (mean age 9.9 years, SD = 0.60) with symptoms of BED (57% girls) and 123 control participants (mean age 10.0 years, SD = 0.60) (52% girls) were acquired from the 4.0 baseline release of the Adolescent Brain Cognitive Development Study. Task-based graph theoretic techniques were used to analyze data from anticipation trials of the monetary incentive delay task. Network and nodal properties were compared between groups.

RESULTS

The BED-S group showed alterations in topological properties associated with the frontostriatal subnetwork, such as reduced nodal efficiency in the superior frontal gyrus, nucleus accumbens, putamen, and in normal sex-difference patterns of these properties, such as diminished girls-greater-than-boys pattern of betweenness-centrality in nucleus accumbens observed in controls.

CONCLUSION

Distinct network properties and sex-difference patterns in preadolescent children with BED-S suggest dysregulation in the reward system compared to those of matched controls. For the first time, these results quantify this dysregulation in terms of systems-level properties during anticipation of monetary reward and significantly inform the early and sex-related brain markers of BED symptoms.

Causal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents

The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule-breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

The Developmental Timing but Not Magnitude of Adolescent Risk-Taking Propensity Is Consistent Across Social, Environmental, and Psychological Factors

PURPOSE

Risk-taking is thought to peak during adolescence, but most prior studies have relied on small convenience samples lacking participant diversity. This study tested the generalizability of adolescent self-reported risk-taking propensity across a comprehensive set of participant-level social, environmental, and psychological factors.

METHODS

Data (N = 1,005,421) from the National Survey on Drug Use and Health were used to test the developmental timing and magnitude of risk-taking propensity and its link to alcohol and cannabis use across 19 subgroups defined via sex, race/ethnicity, socioeconomic status, population density, religious affiliation, and mental health.

RESULTS

The developmental timing of a lifespan peak in risk-taking propensity during adolescence (15-18 years old) generalized across nearly all levels of social, environmental, and psychological factors, whereas the magnitude of this peak widely varied. Nearly all adolescents with regular substance use reported higher levels of risk-taking propensity.

DISCUSSION

Results support a broad generalizability of adolescence as the peak lifespan period of self-reported risk-taking but emphasize the importance of participant-level factors in determining the specific magnitude of reported risk-taking.

Making Connections: Neurodevelopmental Changes in Brain Connectivity After Adverse Experiences in Early Adolescence

Adverse childhood experiences have been linked to detrimental mental health outcomes in adulthood. This study investigates a potential neurodevelopmental pathway between adversity and mental health outcomes: brain connectivity. We used data from the prospective, longitudinal Adolescent Brain Cognitive Development (ABCD) study (N ≍ 12.000, participants aged 9-13 years, male and female) and assessed structural brain connectivity using fractional anisotropy (FA) of white matter tracts. The adverse experiences modeled included family conflict and traumatic experiences. K-means clustering and latent basis growth models were used to determine subgroups based on total levels and trajectories of brain connectivity. Multinomial regression was used to determine associations between cluster membership and adverse experiences. The results showed that higher family conflict was associated with higher FA levels across brain tracts (e.g., t (3) = -3.81, β = -0.09, p bonf = 0.003) and within the corpus callosum (CC), fornix, and anterior thalamic radiations (ATR). A decreasing FA trajectory across two brain imaging timepoints was linked to lower socioeconomic status and neighborhood safety. Socioeconomic status was related to FA across brain tracts (e.g., t (3) = 3.44, β = 0.10, p bonf = 0.01), the CC and the ATR. Neighborhood safety was associated with FA in the Fornix and ATR (e.g., t (1) = 3.48, β = 0.09, p bonf = 0.01). There is a complex and multifaceted relationship between adverse experiences and brain development, where adverse experiences during early adolescence are related to brain connectivity. These findings underscore the importance of studying adverse experiences beyond early childhood to understand lifespan developmental outcomes.

Leveraging big data for causal understanding in mental health: a research framework

Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause.

Longitudinal study of peer victimization, social support, and mental health during early adolescence

BACKGROUND

Peer victimization predicts the development of mental health symptoms in the transition to adolescence, but it is unclear whether and how parents and school environments can buffer this link.

METHODS

We analyzed two-year longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study, involving a diverse sample of 11 844 children across the United States (average at baseline = 9.91 years; standard deviation = 0.63; range = 8.92-11.08; complete case sample = 8385). Longitudinal associations between peer victimization and two-year changes in mental health symptoms of major depression disorder (MDD), separation anxiety (SA), prodromal psychosis (PP), and attention-deficit/hyperactivity disorder (ADHD) were examined including a wide range of covariates. Mixed linear models were used to test for the moderating effects of parental warmth and prosocial school environment.

RESULTS

20% of children experienced peer victimization. Higher exposure to peer victimization was associated with increases in MDD, SA, and ADHD symptoms. Parental warmth was associated with decreases in MDD symptoms but did not robustly buffer the link between peer victimization and mental health symptoms. Prosocial school environment predicted decreases in PP symptoms and buffered the link between peer victimization and MDD symptoms but amplified the link between peer victimization and SA and ADHD symptoms.

CONCLUSIONS

Peer victimization is associated with increases in mental health symptoms during the transition to adolescence. Parental warmth and prosocial school environments might not be enough to counter the negative consequences of peer victimization on all mental health outcomes.

Physical and mental health in adolescence: novel insights from a transdiagnostic examination of FitBit data in the ABCD study

Adolescence is among the most vulnerable period for the emergence of serious mental illnesses. Addressing this vulnerability has generated interest in identifying markers of risk for symptoms and opportunities for early intervention. Physical fitness has been linked to psychopathology and may be a useful risk marker and target for early intervention. New wearable technology has made assessing fitness behavior more practical while avoiding recall and self-report bias. Still, questions remain regarding the clinical utility of physical fitness metrics for mental health, both transdiagnostically and along specific symptom dimensions. The current study includes 5007 adolescents (ages 10-13) who participated in the Adolescent Brain Cognitive Development (ABCD) study and additional sub-study that collected fitness data from wearable technology and clinical symptom measures. Physical fitness metrics included resting heart rate (RHR- an index of cardiovascular health), time spent sedentary (associated with increased inflammation and cardiovascular disease), and time spent in moderate physical activity (associated with increased neurogenesis, neuroplasticity, and healthy neurodevelopment). Self-report clinical symptoms included measures of psychosis-like experiences (PLE), internalizing symptoms, and externalizing symptoms. Increased RHR- lower cardiovascular fitness- related only to greater internalizing symptoms (t = 3.63). More sedentary behavior related to elevated PLE severity (t = 5.49). More moderate activity related to lower PLE (t = -2.69) and internalizing (t = -6.29) symptom severity. Wearable technology fitness metrics linked physical health to specific mental health dimensions, which emphasizes the utility of detailed digital health data as a marker for risk and the need for precision in targeting physical health behaviors to benefit symptoms of psychopathology.

Understanding divergence: Placing developmental neuroscience in its dynamic context

Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique to each individual and to the environments we co-create. However, our theoretical and methodological toolkits often ignore this reality. There is growing awareness that a shift is needed that allows us to study divergence of brain and behaviour across conventional categorical boundaries. However, we argue that in future our study of divergence must also incorporate the developmental dynamics that capture the emergence of those neurodevelopmental differences. This crucial step will require adjustments in study design and methodology. If our ultimate aim is to incorporate the developmental dynamics that capture how, and ultimately when, divergence takes place then we will need an analytic toolkit equal to these ambitions. We argue that the over reliance on group averages has been a conceptual dead-end with regard to the neurodevelopmental differences. This is in part because any individual differences and developmental dynamics are inevitably lost within the group average. Instead, analytic approaches which are themselves new, or simply newly applied within this context, may allow us to shift our theoretical and methodological frameworks from groups to individuals. Likewise, methods capable of modelling complex dynamic systems may allow us to understand the emergent dynamics only possible at the level of an interacting neural system.

Sexual orientation and mental health in a US cohort of children: a longitudinal mediation study

BACKGROUND

Sexual minorities, including children, are at increased risk for adverse mental health outcomes compared to their heterosexual peers, but longitudinal studies are needed to determine the factors that explain the associations between sexual minority identification and adverse mental health outcomes during this developmental period. We examined longitudinal associations between sexual orientation and mental health over 2 years in a US cohort of children (aged 9-10 at baseline) and two explanatory factors (increased social problems such as getting teased and decreased perceived school safety). We hypothesized that beginning to identify as gay/bisexual and consistently identifying as gay/bisexual would be associated with increases in internalizing (e.g. depression, anxiety) and externalizing (e.g. aggression) problems compared to consistently identifying as heterosexual, and these associations would be partially explained by increased social problems and decreased perceived school safety.

METHODS

We used data from Waves 1-3 of the Adolescent Brain Cognitive Development study. The analytic sample included 5,574 children (46.0% female; 55.1% non-Hispanic White).

RESULTS

Beginning to identify as gay/bisexual was associated with increased internalizing/externalizing problems, and consistently identifying as gay/bisexual was associated with increased internalizing problems, compared to consistently identifying as heterosexual. For those who consistently identified as gay/bisexual, increased disparities in internalizing problems were partially explained by increased social problems and decreased perceived school safety, and increased disparities in externalizing problems were partially explained by increased social problems.

CONCLUSIONS

These findings suggest the health disparities affecting sexual minority children include both internalizing and externalizing problems, and social problems and feeling unsafe at school may be contributing factors.

Neural Circuit Markers of Familial Risk for Depression Among Healthy Youths in the Adolescent Brain Cognitive Development Study

BACKGROUND

Family history of depression is a robust predictor of early-onset depression, which may confer risk through alterations in neural circuits that have been implicated in reward and emotional processing. These alterations may be evident in youths who are at familial risk for depression but who do not currently have depression. However, the identification of robust and replicable findings has been hindered by few studies and small sample sizes. In the current study, we sought to identify functional connectivity (FC) patterns associated with familial risk for depression.

METHODS

Participants included healthy (i.e., no lifetime psychiatric diagnoses) youths at high familial risk for depression (HR) (n = 754; at least one parent with a history of depression) and healthy youths at low familial risk for psychiatric problems (LR) (n = 1745; no parental history of psychopathology) who were 9 to 10 years of age and from the Adolescent Brain Cognitive Development (ABCD) Study sample. We conducted whole-brain seed-to-voxel analyses to examine group differences in resting-state FC with the amygdala, caudate, nucleus accumbens, and putamen. We hypothesized that HR youths would exhibit global amygdala hyperconnectivity and striatal hypoconnectivity patterns primarily driven by maternal risk.

RESULTS

HR youths exhibited weaker caudate-angular gyrus FC than LR youths (α = 0.04, Cohen's d = 0.17). HR youths with a history of maternal depression specifically exhibited weaker caudate-angular gyrus FC (α = 0.03, Cohen's d = 0.19) as well as weaker caudate-dorsolateral prefrontal cortex FC (α = 0.04, Cohen's d = 0.21) than LR youths.

CONCLUSIONS

Weaker striatal connectivity may be related to heightened familial risk for depression, primarily driven by maternal history. Identifying brain-based markers of depression risk in youths can inform approaches to improving early detection, diagnosis, and treatment.

"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.

The Role of Individual Discrimination and Structural Stigma in the Mental Health of Sexual Minority Youth

OBJECTIVE

Sexual minority (SM) youth experience a greater mental health burden compared with their heterosexual peers. This study aimed to characterize mental health disparities among SM compared with non-SM youth, test main and interactive associations of SM identity and stressors targeting SM youth at the individual level (interpersonal SM discrimination) and structural level (state-level structural SM stigma) with youth mental health, and explore the contribution of interpersonal SM discrimination to the mental health burden of SM youth.

METHOD

Participants included 11,622 youth (ages 9-13; 47.6% assigned female at birth) from the Adolescent Brain Cognitive Development (ABCD) Study. Linear mixed-effects models tested main and interactive associations of SM identity, interpersonal SM discrimination, and structural SM stigma with mental health measures (self-reported overall psychopathology, suicidal ideation, and suicide attempts), adjusting for demographics and other interpersonal stressors not specific to SM (other discrimination types, peer victimization, and cyberbullying). Longitudinal mediation models tested whether interpersonal SM discrimination mediated the associations between SM identity and mental health measures.

RESULTS

SM youth (n = 1,051) experienced more interpersonal SM discrimination and overall psychopathology compared with their non-SM peers (n = 10,571). Adjusting for demographics, there were significant associations (main effects) of interpersonal SM discrimination and structural SM stigma with overall psychopathology. When further adjusting for other non-SM-related stressors, the main effect of structural SM stigma was no longer significant. Interpersonal SM discrimination was also significantly associated with suicidal ideation and attempt, accounting for demographics, while structural SM stigma was not. Accounting for both demographics and other non-SM stressors, there was a significant interaction between SM identity and structural SM stigma in association with psychopathology (p = .02), such that, compared with their peers, SM youth showed a greater association between structural SM stigma and psychopathology. Longitudinal mediation revealed that interpersonal SM discrimination was a significant mediator explaining approximately 10% to 15% of the variance of the pathways between SM identity and all mental health outcomes.

CONCLUSION

Results delineate contributions of interpersonal discrimination and structural stigma targeting SM youth to their heightened mental health burden in early adolescence. These findings underscore the need to address microlevel and macrolevel SM discrimination and structural stigma when caring for this population.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list.

Evidence for the biopsychosocial model of suicide: a review of whole person modeling studies using machine learning

Background

Traditional approaches to modeling suicide-related thoughts and behaviors focus on few data types from often-siloed disciplines. While psychosocial aspects of risk for these phenotypes are frequently studied, there is a lack of research assessing their impact in the context of biological factors, which are important in determining an individual's fulsome risk profile. To directly test this biopsychosocial model of suicide and identify the relative importance of predictive measures when considered together, a transdisciplinary, multivariate approach is needed. Here, we systematically review the emerging literature on large-scale studies using machine learning to integrate measures of psychological, social, and biological factors simultaneously in the study of suicide.

Methods

We conducted a systematic review of studies that used machine learning to model suicide-related outcomes in human populations including at least one predictor from each of biological, psychological, and sociological data domains. Electronic databases MEDLINE, EMBASE, PsychINFO, PubMed, and Web of Science were searched for reports published between August 2013 and August 30, 2023. We evaluated populations studied, features emerging most consistently as risk or resilience factors, methods used, and strength of evidence for or against the biopsychosocial model of suicide.

Results

Out of 518 full-text articles screened, we identified a total of 20 studies meeting our inclusion criteria, including eight studies conducted in general population samples and 12 in clinical populations. Common important features identified included depressive and anxious symptoms, comorbid psychiatric disorders, social behaviors, lifestyle factors such as exercise, alcohol intake, smoking exposure, and marital and vocational status, and biological factors such as hypothalamic-pituitary-thyroid axis activity markers, sleep-related measures, and selected genetic markers. A minority of studies conducted iterative modeling testing each data type for contribution to model performance, instead of reporting basic measures of relative feature importance.

Conclusion

Studies combining biopsychosocial measures to predict suicide-related phenotypes are beginning to proliferate. This literature provides some early empirical evidence for the biopsychosocial model of suicide, though it is marred by harmonization challenges. For future studies, more specific definitions of suicide-related outcomes, inclusion of a greater breadth of biological data, and more diversity in study populations will be needed.

Engaging Adolescents in Contemporary Longitudinal Health Research: Strategies for Promoting Participation and Retention

PURPOSE

High (and nonselective) recruitment and retention rates in longitudinal studies of adolescence are essential for illuminating health trajectories and determinants during this critical period. Knowledge of optimal recruitment and retention strategies must keep pace with emerging challenges and opportunities, such as the shifts towards digitally-based data collection.

METHODS

We used a narrative review approach to synthesize research on promising recruitment and retention strategies for optimizing engagement in the next generation of longitudinal adolescent health studies.

RESULTS

We identified a small number of well-evidenced strategies, emerging challenges and opportunities for recruitment and retention in contemporary studies, and key evidence gaps. Core recommendations include the use of well-evidenced strategies (e.g., incentivizing participation, reducing barriers and burden, and investing in building positive relationships with participants) and coproducing recruitment and retention strategies with adolescents and parents of adolescents.

DISCUSSION

More research is needed into successful recruitment/retention strategies for digital/remote data collection methods, but initial evidence suggests that adopting principles and adapting well-evidenced strategies from traditional longitudinal studies is promising.

Selectively predicting the onset of ADHD, oppositional defiant disorder, and conduct disorder in early adolescence with high accuracy

Introduction

The externalizing disorders of attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD) are common in adolescence and are strong predictors of adult psychopathology. While treatable, substantial diagnostic overlap complicates intervention planning. Understanding which factors predict the onset of each disorder and disambiguating their different predictors is of substantial translational interest.

Materials and methods

We analyzed 5,777 multimodal candidate predictors from children aged 9-10 years and their parents in the ABCD cohort to predict the future onset of ADHD, ODD, and CD at 2-year follow-up. We used deep learning optimized with an innovative AI algorithm to jointly optimize model training, perform automated feature selection, and construct individual-level predictions of illness onset and all prevailing cases at 11-12 years and examined relative predictive performance when candidate predictors were restricted to only neural metrics.

Results

Multimodal models achieved ~86-97% accuracy, 0.919-0.996 AUROC, and ~82-97% precision and recall in testing in held-out, unseen data. In neural-only models, predictive performance dropped substantially but nonetheless achieved accuracy and AUROC of ~80%. Parent aggressive and externalizing traits uniquely differentiated the onset of ODD, while structural MRI metrics in the limbic system were specific to CD. Psychosocial measures of sleep disorders, parent mental health and behavioral traits, and school performance proved valuable across all disorders. In neural-only models, structural and functional MRI metrics in subcortical regions and cortical-subcortical connectivity were emphasized. Overall, we identified a strong correlation between accuracy and final predictor importance.

Conclusion

Deep learning optimized with AI can generate highly accurate individual-level predictions of the onset of early adolescent externalizing disorders using multimodal features. While externalizing disorders are frequently co-morbid in adolescents, certain predictors were specific to the onset of ODD or CD vs. ADHD. To our knowledge, this is the first machine learning study to predict the onset of all three major adolescent externalizing disorders with the same design and participant cohort to enable direct comparisons, analyze >200 multimodal features, and include many types of neuroimaging metrics. Future study to test our observations in external validation data will help further test the generalizability of these findings.

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Importance

Social determinants of health (SDOH) influence child health. However, most previous studies have used individual, small-set, or cherry-picked SDOH variables without examining unbiased computed SDOH patterns from high-dimensional SDOH factors to investigate associations with child mental health, cognition, and physical health.

Objective

To identify SDOH patterns and estimate their associations with children's mental, cognitive, and physical developmental outcomes.

Design, Setting, and Participants

This population-based cohort study included children aged 9 to 10 years at baseline and their caregivers enrolled in the Adolescent Brain Cognitive Development (ABCD) Study between 2016 and 2021. The ABCD Study includes 21 sites across 17 states.

Exposures

Eighty-four neighborhood-level, geocoded variables spanning 7 domains of SDOH, including bias, education, physical and health infrastructure, natural environment, socioeconomic status, social context, and crime and drugs, were studied. Hierarchical agglomerative clustering was used to identify SDOH patterns.

Main Outcomes and Measures

Associations of SDOH and child mental health (internalizing and externalizing behaviors) and suicidal behaviors, cognitive function (performance, reading skills), and physical health (body mass index, exercise, sleep disorder) were estimated using mixed-effects linear and logistic regression models.

Results

Among 10 504 children (baseline median [SD] age, 9.9 [0.6] years; 5510 boys [52.5%] and 4994 girls [47.5%]; 229 Asian [2.2%], 1468 Black [14.0%], 2128 Hispanic [20.3%], 5565 White [53.0%], and 1108 multiracial [10.5%]), 4 SDOH patterns were identified: pattern 1, affluence (4078 children [38.8%]); pattern 2, high-stigma environment (2661 children [25.3%]); pattern 3, high socioeconomic deprivation (2653 children [25.3%]); and pattern 4, high crime and drug sales, low education, and high population density (1112 children [10.6%]). The SDOH patterns were distinctly associated with child health outcomes. Children exposed to socioeconomic deprivation (SDOH pattern 3) showed the worst health profiles, manifesting more internalizing (β = 0.75; 95% CI, 0.14-1.37) and externalizing (β = 1.43; 95% CI, 0.83-2.02) mental health problems, lower cognitive performance, and adverse physical health.

Conclusions

This study shows that an unbiased quantitative analysis of multidimensional SDOH can permit the determination of how SDOH patterns are associated with child developmental outcomes. Children exposed to socioeconomic deprivation showed the worst outcomes relative to other SDOH categories. These findings suggest the need to determine whether improvement in socioeconomic conditions can enhance child developmental outcomes.

Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject's connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale.

Can we diagnose mental disorders in children? A large-scale assessment of machine learning on structural neuroimaging of 6916 children in the adolescent brain cognitive development study

Background

Prediction of mental disorders based on neuroimaging is an emerging area of research with promising first results in adults. However, research on the unique demographic of children is underrepresented and it is doubtful whether findings obtained on adults can be transferred to children.

Methods

Using data from 6916 children aged 9-10 in the multicenter Adolescent Brain Cognitive Development study, we extracted 136 regional volume and thickness measures from structural magnetic resonance images to rigorously evaluate the capabilities of machine learning to predict 10 different psychiatric disorders: major depressive disorder, bipolar disorder (BD), psychotic symptoms, attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, post-traumatic stress disorder, obsessive-compulsive disorder, generalized anxiety disorder, and social anxiety disorder. For each disorder, we performed cross-validation and assessed whether models discovered a true pattern in the data via permutation testing.

Results

Two of 10 disorders can be detected with statistical significance when using advanced models that (i) allow for non-linear relationships between neuroanatomy and disorder, (ii) model interdependencies between disorders, and (iii) avoid confounding due to sociodemographic factors: ADHD (AUROC = 0.567, p = 0.002) and BD (AUROC = 0.551, p = 0.002). In contrast, traditional models perform consistently worse and predict only ADHD with statistical significance (AUROC = 0.529, p = 0.002).

Conclusion

While the modest absolute classification performance does not warrant application in the clinic, our results provide empirical evidence that embracing and explicitly accounting for the complexities of mental disorders via advanced machine learning models can discover patterns that would remain hidden with traditional models.

The Association between Family Environment and Subsequent Risk of Cyberbullying Victimization in Adolescents

BACKGROUND

Family environment and parental monitoring have long been recognized as two important factors associated with adolescents' psychological development. Studies have suggested a potential link between parenting style/parental engagement and the likelihood of bullying victimization among adolescents. Nonetheless, no studies to date have investigated the association between family environment and the subsequent risk of cyberbullying victimization among adolescents. In this study, we assessed the association between family environment (eg, parental monitoring and family conflict) and subsequent risk of cyberbullying victimization using data from the Adolescent Brain Cognitive Development (ABCD).

METHODS

We used multivariable logistic regressions to assess the association between parental monitoring and family conflict at year 1 and the subsequent risk of cyberbullying victimization at year 2 in 10,410 eligible ABCD study participants.

RESULTS

Adjusting for sociodemographic characteristics, study sampling weights and study site, higher levels of parental monitoring at year 1 were associated with a lower reported past 12-month (OR: 0.61, 95% CI: 0.50-0.75) history of cyberbullying victimization at year 2. Higher levels of family conflict at year 1 were associated with a higher risk of reported past 12-month history (OR: 1.10, 95% CI: 1.04-1.16) of cyberbullying victimization one year later.

CONCLUSION

Higher levels of parental monitoring and lower levels of family conflict are associated with a subsequent lower risk of cyberbullying victimization among adolescents. Cyberbullying victimization preventive programs should advocate for increased parental monitoring and minimize family conflict at home to reduce the risks of cyberbullying victimization among adolescents.

Socioeconomic resources in youth are linked to divergent patterns of network integration and segregation across the brain's transmodal axis

Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully influence intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neurobiological meaning of these widespread alterations remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform. In the present study, we leverage the resources of graph theory to precisely characterize multivariate and univariate associations between household SER and the functional integration and segregation (i.e., participation coefficient, within-module degree) of brain regions across major cognitive, affective, and sensorimotor systems during the resting state in 5,821 youth (ages 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. First, we establish that decomposing the brain into profiles of integration and segregation captures more than half of the multivariate association between SER and functional connectivity with greater parsimony (100-fold reduction in number of features) and interpretability. Second, we show that the topological effects of SER are not uniform across the brain; rather, higher SER levels are related to greater integration of somatomotor and subcortical systems, but greater segregation of default mode, orbitofrontal, and cerebellar systems. Finally, we demonstrate that the effects of SER are spatially patterned along the unimodal-transmodal gradient of brain organization. These findings provide critical interpretive context for the established and widespread effects of SER on brain organization, indicating that SER levels differentially configure the intrinsic functional architecture of developing unimodal and transmodal systems. This study highlights both sensorimotor and higher-order networks that may serve as neural markers of environmental stress and opportunity, and which may guide efforts to scaffold healthy neurobehavioral development among disadvantaged communities of youth.

Associations Between Structural Stigma and Psychopathology Among Early Adolescents

OBJECTIVE

Ample evidence demonstrates that structural stigma - defined as societal-level conditions, cultural norms, and institutional policies and practices that constrain opportunities, resources, and well-being of stigmatized populations - is associated with psychopathology in adults from marginalized groups. Yet there is limited research on whether structural stigma is similarly associated with internalizing and externalizing symptoms among youth.

METHOD

Structural stigma related to sex, sexual orientation, race, and Latinx ethnicity was measured using indicators of state-level policy and aggregated attitudes. Using data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,414; M age = 12 years, SD = 0.66; 48% female, 6.8% lesbian, gay, and bisexual (LGB), 13.4% Black, 20% Latinx), we examined associations of structural stigma with internalizing and externalizing symptoms among female, LGB, Black, and Latinx youth.

RESULTS

LGB youth living in higher (vs. lower) structural stigma states had elevated levels of internalizing and externalizing symptoms. In lower structural stigma states, there were no differences in externalizing symptoms between LGB and heterosexual youth. Similarly, Latinx youth and females living in higher (vs. lower) structural stigma states had elevated levels of externalizing symptoms. In lower structural stigma states, there were no differences in externalizing symptoms between Latinx youth and non-Latinx White youth. Structural stigma related to race was unrelated to internalizing or externalizing symptoms for Black youth.

CONCLUSIONS

This study provides novel evidence that macro-level social environments, in the form of structural stigma, contribute to adverse mental health outcomes for marginalized youth and partly explain disparities in externalizing symptoms.

Functional neuroimaging as a catalyst for integrated neuroscience

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.

Regional Vulnerability Indices in Youth With Persistent and Distressing Psychoticlike Experiences

Importance

Distressing and persistent psychoticlike experiences (PLEs) in youth are associated with greater odds of developing psychiatric conditions in adulthood. Despite this risk, it is unclear whether early PLEs show similar brain patterns compared with adults with psychiatric and neurologic conditions.

Objective

To examine the degree to which persistent and distressing PLEs exhibit neural metrics that show similarity to adults with chronic psychiatric and neurologic conditions.

Design, Setting, and Participants

This cohort study used Adolescent Brain Cognitive Development (ABCD) Study examining the persistence and distress associated with PLEs across the first 3 waves of data with baseline structural magnetic resonance imaging data. Analyzed data were collected between September 1, 2016, and September 27, 2021. Children were recruited from 21 research sites across the US.

Exposures

Psychoticlike experiences were assessed using the Prodromal Questionnaire-Brief Child Version, and participants were categorized into groups based on the persistence and distress associated with PLEs.

Main Outcomes and Measures

Cortical and subcortical regional vulnerability indices (RVIs) were created by quantifying the similarity of participants' baseline neuroimaging measures to the expected patterns found in adult neuropsychiatric samples. The PLE groups were compared on the following RVI cortical and subcortical metrics: schizophrenia spectrum disorders, bipolar disorder, major depressive disorder, Parkinson disease, Alzheimer disease, and metabolic diseases.

Results

Analyses examined PLE groups created from 8242 children in the ABCD sample (52.5% male; mean [SD] age, 9.93 [0.63] years; and 56.3% White), including persistent distressing PLEs (n = 329), transient distressing PLEs (n = 396), persistent nondistressing PLEs (n = 234), transient nondistressing PLEs (n = 390), and low distressing PLEs (n = 6893) groups. Participants with persistent or transient distressing PLEs broadly showed increased subcortical RVI scores across most RVI metrics, with persistent distressing PLEs additionally showing increased scores for cortical RVI metrics. The greatest effect sizes were found for persistent distressing PLEs with cortical RVI-schizophrenia spectrum disorders (β estimate, 1.055; 95% CI, 0.326-1.786) and RVI-Alzheimer disease (β estimate, 2.473; 95% CI, 0.930-4.018).

Conclusions and Relevance

In this cohort study of ABCD participants, the findings suggest that especially the persistent distressing PLEs in children were associated with neural metrics resembling those observed in adults with severe psychiatric and neurologic conditions. These findings support the potential use of brain-based risk scores for early identification and precision medicine approaches in the assessment of PLEs.

Risk Factors for the Development of Multisite Pain in Children

OBJECTIVE

Chronic pain has economic costs on par with cardiovascular disease, diabetes, and cancer. Despite this impact on the health care system and increasing awareness of the relationship between pain and mortality, efforts to identify simple symptom-based risk factors for the development of pain, particularly in children, have fallen short. This is critically important as pain that manifests during childhood often persists into adulthood. To date, no longitudinal studies have examined symptoms in pain-free children that presage a new, multisite manifestation of pain in the future. We hypothesized that female sex, sleep problems, and heightened somatic symptoms complaints at baseline would be associated with the risk of developing new multisite pain 1 year later.

METHODS

Symptom assessments were completed by parents of youth (ages 9 to 10) enrolled in the Adolescent Brain Cognitive Development study. Multivariate logistic regression models focused on children who developed multisite pain 1 year later (n=331) and children who remained pain free (n=3335).

RESULTS

Female sex (odds ratio [OR]=1.35; 95% CI, 1.07, 1.71; P =0.01), elevated nonpainful somatic symptoms (OR=1.17; 95% CI, 1.06, 1.29; P <0.01), total sleep problems (OR=1.20; 95% CI, 1.07, 1.34; P <0.01), and attentional issues (OR=1.22; 95% CI, 1.10, 1.35; P <0.001) at baseline were associated with new multisite pain 1 year later. Baseline negative affect was not associated with new multisite pain.

DISCUSSION

Identifying symptom-based risk factors for multisite pain in children is critical for early prevention. Somatic awareness, sleep and attention problems represent actionable targets for early detection, treatment, and possible prevention of multisite pain in youth.

Longitudinal Associations Between Perceived Discrimination and Suicidality in Youth

Research among adults reveals robust associations between discrimination and suicidality. However, the relationship between discrimination and suicidality is understudied in youth. Participants in the Adolescent Brain Cognitive Development study (n = 10  312) completed a measure of discrimination based on multiple attributes. The Kiddie Schedule for Affective Disorders and Schizophrenia was administered 1 year later to assess depressive disorders and suicidality (ideation and behavior). Logistic regressions, adjusting for age, sex, race/ethnicity, family income, lifetime depressive disorders, and body composition were conducted. Adjusting for covariates, discrimination based on weight (OR: 2.19), race/ethnicity/color (OR: 3.21), and sexual orientation (OR: 3.83) were associated with greater odds of reporting suicidality 1 year later (ps < 0.025). Nationality-based discrimination was not significantly associated with suicidality. Compared with those reporting no discrimination, youths reporting discrimination based on 2 or more attributes had nearly 5 times greater odds of recent suicidality (OR: 4.72; P < .001). The current study highlights the deleterious impacts of discrimination on mental health among youths reporting multiple forms of discrimination.

Associations Between Polygenic Scores for Cognitive and Non-cognitive Factors of Educational Attainment and Measures of Behavior, Psychopathology, and Neuroimaging in the Adolescent Brain Cognitive Development Study

Background

Both cognitive and non-cognitive (e.g., traits like curiosity) factors are critical for social and emotional functioning and independently predict educational attainment. These factors are heritable and genetically correlated with a range of health-relevant traits and behaviors in adulthood (e.g., risk-taking, psychopathology). However, whether these associations are present during adolescence, and to what extent these relationships diverge, could have implications for adolescent health and well-being.

Methods

Using data from 5,517 youth of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and outcomes related to cognition, socioeconomic status, risk tolerance and decision-making, substance initiation, psychopathology, and brain structure.

Results

Cognitive and non-cognitive PGSs were both positively associated with cognitive performance and family income, and negatively associated with ADHD and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk-taking, delayed discounting, and anorexia, as well as lower likelihood of nicotine initiation. The cognitive PGS was further associated with cognition scores and anorexia in within-sibling analyses, suggesting these results do not solely reflect the effects of assortative mating or passive gene-environment correlations. The cognitive PGS showed significantly stronger associations with cortical volumes than the non-cognitive PGS and was associated with right hemisphere caudal anterior cingulate and pars-orbitalis in within-sibling analyses, while the non-cognitive PGS showed stronger associations with white matter fractional anisotropy and a significant within-sibling association for right superior corticostriate-frontal cortex.

Conclusions

Our findings suggest that PGSs for cognitive and non-cognitive factors show similar associations with cognition and socioeconomic status as well as other psychosocial outcomes, but distinct associations with regional neural phenotypes in this adolescent sample.

Working Memory-Related Neurofunctional Correlates Associated with the Frontal Lobe in Children with Familial vs. Non-Familial Attention Deficit/Hyperactivity Disorder

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with high prevalence, heritability, and heterogeneity. Children with a positive family history of ADHD have a heightened risk of ADHD emergence, persistence, and executive function deficits, with the neural mechanisms having been under investigated. The objective of this study was to investigate working memory-related functional brain activation patterns in children with ADHD (with vs. without positive family histories (ADHD-F vs. ADHD-NF)) and matched typically developing children (TDC). Voxel-based and region of interest analyses were conducted on two-back task-based fMRI data of 362 subjects, including 186, 96, and 80 children in groups of TDC, ADHD-NF, and ADHD-F, respectively. Relative to TDC, both ADHD groups had significantly reduced activation in the left inferior frontal gyrus (IFG). And the ADHD-F group demonstrated a significant positive association of left IFG activation with task reaction time, a negative association of the right IFG with ADHD symptomatology, and a negative association of the IFG activation laterality index with the inattention symptom score. These results suggest that working memory-related functional alterations in bilateral IFGs may play distinct roles in ADHD-F, with the functional underdevelopment of the left IFG significantly informing the onset of ADHD symptoms. Our findings have the potential to assist in tailored diagnoses and targeted interventions in children with ADHD-F.

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence

Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known about how to robustly identify youth at risk to target intervention efforts known to improve outcomes. Barriers to knowledge have included obtaining robust predictions while simultaneously analyzing large numbers of different types of candidate predictors. In a new, large, transdiagnostic youth sample and multidomain high-dimension data, we used 160 candidate predictors encompassing neural, prenatal, developmental, physiologic, sociocultural, environmental, emotional and cognitive features and leveraged three different machine learning algorithms optimized with a novel artificial intelligence meta-learning technique to predict individual cases of anxiety, depression, attention deficit, disruptive behaviors and post-traumatic stress. Our models tested well in unseen, held-out data (AUC ≥ 0.94). By utilizing a large-scale design and advanced computational approaches, we were able to compare the relative predictive ability of neural versus psychosocial features in a principled manner and found that psychosocial features consistently outperformed neural metrics in their relative ability to deliver robust predictions of individual cases. We found that deep learning with artificial neural networks and tree-based learning with XGBoost outperformed logistic regression with ElasticNet, supporting the conceptualization of mental illnesses as multifactorial disease processes with non-linear relationships among predictors that can be robustly modeled with computational psychiatry techniques. To our knowledge, this is the first study to test the relative predictive ability of these gold-standard algorithms from different classes across multiple mental health conditions in youth within the same study design in multidomain data utilizing >100 candidate predictors. Further research is suggested to explore these findings in longitudinal data and validate results in an external dataset.

Effects of family income on brain functional connectivity in US children: associations with cognition

Higher family income (FI) is associated with larger cortical gray matter volume and improved cognitive performance in children. However, little is known about the effects of FI on brain functional and structural connectivity. This cross-sectional study investigates the effects of FI on brain connectivity and cognitive performance in 9- to 11-years old children (n = 8739) from the Adolescent Brain Cognitive Development (ABCD) study. Lower FI was associated with decreased global functional connectivity density (gFCD) in the default-mode network (DMN), inferior and superior parietal cortices and in posterior cerebellum, and increased gFCD in motor, auditory, and extrastriate visual areas, and in subcortical regions both for girls and boys. Findings demonstrated high reproducibility in Discovery and Reproducibility samples. Cognitive performance partially mediated the association between FI and DMN connectivity, whereas DMN connectivity did not mediate the association between FI and cognitive performance. In contrast, there was no significant association between FI and structural connectivity. Findings suggest that poor cognitive performance, which likely reflects multiple factors (genetic, nutritional, the level and quality of parental interactions, and educational exposure [1]), contributes to reduced DMN functional connectivity in children from low-income families. Follow-up studies are needed to help clarify if this leads to reductions in structural connectivity as these children age.

Transmit Radiant Individuality to Offspring (TRIO) study: investigating intergenerational transmission effects on brain development

Intergenerational transmission is a crucial aspect of human development. Although prior studies have demonstrated the continuity of psychopathology and maladaptive upbringing environments between parents and offspring, the underlying neurobiological mechanisms remain unclear. We have begun a novel neuroimaging research project, the Transmit Radiant Individuality to Offspring (TRIO) study, which focuses on biological parent-offspring trios. The participants of the TRIO study were Japanese parent-offspring trios consisting of offspring aged 10-40 and their biological mother and father. Structural and functional brain images of all participants were acquired using magnetic resonance imaging (MRI). Saliva samples were collected for DNA analysis. We obtained psychosocial information, such as intelligence, mental health problems, personality traits, and experiences during the developmental period from each parent and offspring in the same manner as much as possible. By April 2023, we completed data acquisition from 174 trios consisting of fathers, mothers, and offspring. The target sample size was 310 trios. However, we plan to conduct genetic and epigenetic analyses, and the sample size is expected to be expanded further while developing this project into a multi-site collaborative study in the future. The TRIO study can challenge the elucidation of the mechanism of intergenerational transmission effects on human development by collecting diverse information from parents and offspring at the molecular, neural, and behavioral levels. Our study provides interdisciplinary insights into how individuals' lives are involved in the construction of the lives of their descendants in the subsequent generation.