| Environmental Risk Factors and Psychotic-like Symptoms in Children Aged 9-11 | Objective: Research implicates environmental risk factors, including correlates of urbanicity, deprivation, and environmental toxins, in psychotic-like experiences (PLEs). The current study examined associations between several types of environmental risk factors and PLEs in school-age children, whether these associations were specific to PLEs or generalized to other psychopathology, and examined possible neural mechanisms for significant associations.
Method: The current study used data from 10,328 9-11-year-olds from the Adolescent Brain Cognitive Development (ABCD) study. Hierarchical linear models examined associations between PLEs and geocoded environmental risk factors, and whether associations generalized to internalizing/externalizing symptoms. Mediation models examined whether structural MRI abnormalities (e.g., intracranial volume) mediated associations between PLEs and environmental risk factors.
Results: The results found specific types of environmental risk factors, namely measures of urbanicity (i.e., drug offense exposure, less perception of neighborhood safety), deprivation (including overall deprivation, rate of poverty, fewer years at residence), and lead exposure risk, were associated with PLEs. These associations showed evidence of stronger associations with PLEs than internalizing/externalizing symptoms (especially overall deprivation, poverty, drug offense exposure, and lead exposure risk). There was evidence that brain volume mediated between 11-25% of the associations between poverty, perception of neighborhood safety, and lead exposure risk with PLEs.
Conclusions: These results are the first to find support for neural measures partially mediating the association between PLEs and environmental exposures. Furthermore, the current study replicated and extended recent findings of the association between PLEs and environmental exposures, finding evidence for specific associations with correlates of urbanicity, deprivation, and lead exposure risk.
| 8669/11898 | Secondary Analysis | Private |
| Longitudinally stable, brain-based predictive models mediate the relationships between childhood cognition and socio-demographic, psychological and genetic factors. | Cognitive abilities are one of the major transdiagnostic domains in the National Institute of Mental Health's Research Domain Criteria (RDoC). Following RDoC's integrative approach, we aimed to develop brain-based predictive models for cognitive abilities that (a) are developmentally stable over years during adolescence and (b) account for the relationships between cognitive abilities and socio-demographic, psychological and genetic factors. For this, we leveraged the unique power of the large-scale, longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (n ~ 11 k) and combined MRI data across modalities (task-fMRI from three tasks: resting-state fMRI, structural MRI and DTI) using machine-learning. Our brain-based, predictive models for cognitive abilities were stable across 2 years during young adolescence and generalisable to different sites, partially predicting childhood cognition at around 20% of the variance. Moreover, our use of ‘opportunistic stacking’ allowed the model to handle missing values, reducing the exclusion from around 80% to around 5% of the data. We found fronto-parietal networks during a working-memory task to drive childhood-cognition prediction. The brain-based, predictive models significantly, albeit partially, accounted for variance in childhood cognition due to (1) key socio-demographic and psychological factors (proportion mediated = 18.65% [17.29%–20.12%]) and (2) genetic variation, as reflected by the polygenic score of cognition (proportion mediated = 15.6% [11%–20.7%]). Thus, our brain-based predictive models for cognitive abilities facilitate the development of a robust, transdiagnostic research tool for cognition at the neural level in keeping with the RDoC's integrative framework. | 8662/11878 | Secondary Analysis | Shared |
| P Factor Resting State | BACKGROUND Convergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. However, brain functional connectivity patterns that underpin the P factor remain poorly understood, especially at the transition to adolescence when many serious mental disorders have their onset.
OBJECTIVE: Identify a distributed connectome-wide neurosignature of the P factor and assess the generalizability of this neurosignature in held out samples.
DESIGN, SETTING, AND PARTICIPANTS This study used data from the full baseline wave of the Adolescent Brain and Cognitive Development (ABCD) national consortium study, a prospective, population-based study of 11,875 9- and 10-year olds. Data for this study were collected from September 1, 2016 to November 15, 2018 at 21 research sites across the United States.
MAIN OUTCOMES AND MEASURES We produced whole brain functional connectomes for 5,880 youth with high quality resting state scans. We then constructed a low rank basis set of 250 components that captures interindividual connectomic differences. Multi-level regression modeling was used to link these components to the P factor, and leave-one-site-out cross-validation was used to assess generalizability of P factor neurosignatures to held out subjects across 19 ABCD sites.
RESULTS The set of 250 connectomic components was highly statistically significantly related to the P factor, over and above nuisance covariates alone (ANOVA nested model comparison, incremental R-squared 6.05%, χ2(250) = 412.1, p<4.6x10-10). In addition, two individual connectomic components were statistically significantly related to the P factor after Bonferroni correction for multiple comparisons (t(5511)= 4.8, p<1.4x10-06; t(5121)= 3.9, p<9.7x10-05). Functional connections linking control networks and default mode network were prominent in the P factor neurosignature. In leave-one-site-out cross-validation, the P factor neurosignature generalized to held out subjects (average correlation between actual and predicted P factor scores across 19 held out sites=0.13; pPERMUTATION<0.0001). Additionally, results remained significant after a number of robustness checks.
CONCLUSIONS AND RELEVANCE: The general factor of psychopathology is associated with connectomic alterations involving control networks and default mode network. Brain imaging combined with network neuroscience can identify distributed and generalizable signatures of transdiagnostic risk for psychopathology during emerging adolescence.
| 4799/11878 | Secondary Analysis | Private |
| Prenatal development has stable and consistent effects on the human brain throughout the lifespan | Human fetal development has been associated with brain health at later stages. It is unknown whether and how consistently growth in utero, as indexed by birth weight (BW), relates to lifespan brain characteristics and changes, and to what extent these influences are of a genetic and/or environmental nature. We hypothesized that associations of BW and structural brain characteristics persist through the lifespan, with topographically consistent effects across samples of varying age and origin, that BW is not protective against atrophy in aging, and that effects are partly environmental. The associations of BW and cortical surface, thickness, volume and their change were investigated vertex-wise in one developmental (ABCD), one older adult and aging (UKB) and one lifespan (LCBC) sample. In total, 5794 persons (4-82 years, w/ 386 monozygotic twins), were followed for up to 8.3 years, yielding 12,088 brain MRIs. Positive associations between BW and cortical surface area and volume were remarkably stable through the lifespan and across samples of different origin, with spatial correlations in the range r = .51- .79. In contrast, there was modest and no consistent effect of BW on brain changes. Effects of BW discordance in the monozygotic twin subsample showed that the effects were partly non-genetic. In conclusion, the influence of prenatal growth on cortical topography is stable through the lifespan, and is reliably seen in development, adulthood, and aging. These findings support early life influence on the brain through the lifespan according to a threshold model of brain reserve, rather than a maintenance model. | 8662/11878 | Primary Analysis | Private |
| ABCD Dissertation Study | Assessing longitudinal trajectories of resting state functional connectivity and psychopathology, as they relate to social support. | 8661/11876 | Secondary Analysis | Private |
| ARCHIVED Association between mild traumatic brain injury, brain structure, and mental health outcomes in the Adolescent Brain Cognitive Development Study | This private NDA Study was archived on 06/24/2022 and was never shared. Background: Children that experience a mild traumatic brain injury (mTBI) are at an increased risk of neural alterations that can deteriorate mental health. We test the hypothesis that mTBI is associated with behavioral and emotional problems and that structural brain metrics (e.g., volume, area) meaningfully mediate the relation in an adolescent population.
Methods: We analyzed behavioral and brain MRI data from 11,876 children who participated in the Adolescent Brain Cognitive Development (ABCD) Study. Mixed-effects models were used to examine the longitudinal association between mTBI and mental health outcomes. Bayesian methods were used to investigate brain regions that are intermediate between mTBI and symptoms of poor mental health.
Results: There were 199 children with mTBI and 527 with possible mTBI across the three ABCD Study visits. There was a 7% (IRR = 1.07, 95% CI: 1.01, 1.13) and 15% (IRR = 1.16, 95% CI: 1.05, 1.26) increased risk of emotional or behavioral problems in children that experienced possible mTBI or mTBI, respectively. Possible mTBI was associated with a 17% (IRR: 1.17, 95% CI: 0.99, 1.40) increased risk of experiencing distress following a psychotic-like experience. We did not find any brain regions that meaningfully mediated the relationship between mTBI and mental health outcomes. Analysis of volumetric measures found that 3 to 5% of the total effect of mTBI on mental health outcomes operated through total cortical volume. Image intensity measure analyses determined that 2 to 5% of the total effect was mediated through the left-hemisphere of the dorsolateral prefrontal cortex.
Conclusion: Results indicate an increased risk of emotional and behavioral problems in children that experienced possible mTBI or mTBI. Mediation analyses did not elucidate the mechanisms underlying the association between mTBI and mental health outcomes.
| 8659/11875 | Secondary Analysis | Private |
| Differences in cortical morphology and child internalizing or externalizing problems: accounting for the co-occurrence | Background: Childhood internalizing and externalizing problems frequently co-occur. Many studies report neural correlates of either internalizing or externalizing problems, but few account for their co-occurrence. We aimed to assess specific cortical substrates of these psychiatric problems.
Methods: We used data from 9,635 children aged 9-11 years in the baseline Adolescent Brain Cognitive Development Study. Internalizing and externalizing problem composite scales scores were derived from the Child Behavior Checklist. We standardized FreeSurfer-derived volumes of 68 cortical regions. We examined internalizing and externalizing problems separately and jointly (covariate-adjustment) in relation to cortical volumes, with and without adjusting for total brain volume (TBV) in multivariate linear regressions adjusted for demographics and multiple comparisons. We fit bifactor models to confirm the consistency of patterns exploring specific internalizing and specific externalizing problems. Sensitivity analyses included a vertex-wide analysis and a replication in another large population-based study.
Results: In separate TBV-unadjusted analyses, externalizing and internalizing problems were associated with smaller cortical volumes. If adjusted for externalizing behavior, however, larger cortical volumes were associated with internalizing problems, while smaller cortical volumes remained associated with externalizing problems after adjustment for internalizing problems. The bifactor model produced similar results, which were consistently replicated in another pre-adolescent neuroimaging sample. These associations likely represent global effects: adjusting for TBV rendered most associations non-significant. Vertex-wise analyses confirmed global patterns.
Conclusion: Our results suggest that internalizing and externalizing problems have globally opposing, and non-specific associations with cortical morphology in childhood, which are only apparent if analyses account for their co-occurrence.
| 7131/11815 | Secondary Analysis | Private |
| Structural alterations in the frontal lobe mediate the impact of snoring and associated symptoms on childhood behavior | Parents frequently report behavioral problems among children who snore. Our understanding of the relationship between symptoms of obstructive sleep disordered breathing (oSDB)—e.g. snoring—and childhood behavioral problems attributable to brain structural alterations is limited. Therefore, we examined the relationships among oSDB symptoms, problem behaviors and brain morphometry in a diverse dataset comprising 10,140 preadolescents. We demonstrate that the symptoms of oSDB strongly predicted composite and domain-specific behavioral measures. Cortical morphometric alterations demonstrating the strongest negative associations with oSDB symptoms were most pronounced within the frontal lobe. The relationships between oSDB symptoms and behavioral measures were mediated by significantly smaller volumes of multiple frontal lobe regions. These results provide population-level evidence for regional structural alterations in cortical gray matter accompanying problem behaviors in children with oSDB. Timely recognition and treatment of oSDB may ameliorate these changes and the associated neurobehavioral morbidity while the frontal lobe still retains age-dependent plasticity. | 6904/11752 | Secondary Analysis | Private |
| Neuroanatomical correlates of impulsive traits in children aged 9 to 10 | Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples. | 8253/11051 | Secondary Analysis | Shared |
| Effect of exposure to maternal diabetes during pregnancy on offspring’s brain cortical thickness and neurocognitive functioning | OBJECTIVE: Maternal diabetes may affect the developing brain of the fetus, which may adversely affect the neurocognitive functioning (NCF) of diabetes-exposed children. We examined the effect of prenatal exposure to maternal diabetes (DP) on brain structure and neurocognition in preadolescent children, ages 9-10.
RESEARCH DESIGN AND METHODS: This secondary data analysis study used cross-sectional structural neuroimaging and NCF data from the Adolescent Brain and Cognitive Development (ABCD) study (N=9,963). Differences in brain cortical thickness (CTh) and five cognitive abilities (executive function, working and episodic memory, processing speed, and language abilities) between diabetes-exposed and unexposed children were examined. Generalized linear models were used to adjust for the effect of confounding variables. Indirect effect of CTh into the relationship between maternal DP and NCF were also examined.
RESULTS: The average age of the children was 9.9 years (SD 7.5); half of them were male and non-Hispanic White. Diabetes-exposed children (n=714) had lower CTh of the whole-brain (2.744mm VS 2.756mm; p 0.008) and lower scores in processing speed task (85.97 VS 87.28; p=0.021 compared to unexposed children (n=9249) after adjusting for demographic and other confounding variables. Diabetes-exposed children also had lower score in fluid intelligence [β (95%CI): -0.837 (-1.604, -0.171)]) and total cognition [β (95%CI): -0.728 (-1.338,-0.119)]. CTh partially mediated [Direct effect=β (95%CI): -3.239 (-5.834, -0.644); indirect effect=β (95%CI): -3.239 (-5.834, -0.644)] the effect of maternal DP on offspring’s processing speed.
CONCLUSION: Diabetes-exposed children have reduced CTh and NCF during preadolescence age, which may have implications for psychomotor development during later life. Prospective studies are needed to confirm our findings | 7435/10218 | Secondary Analysis | Shared |
| Effect of maternal hypertensive disorder on their children’s neurocognitive functioning | Objective: The aim of the study was to examine the effect of prenatal exposure to maternal HDP on brain structure and NCF in singleton children aged between 9-10 years the baseline wave of the Adolescent Brain and Cognitive Development (ABCD) Study.
Methods: The ABCD Study® interviewed each child (and their parents), measured NCF, and performed neuroimaging. Exposure to maternal high blood pressure (HBP) and preeclampsia or eclampsia (PE/EL) were extracted from the developmental history questionnaire. Differences in cortical thickness (CTh) and five cognitive abilities (executive function, working and episodic memory, processing speed, and language abilities) between exposed and unexposed children were examined using generalized linear models. The mediating effects of CTh, birthweight, and BMI on the relationship between maternal HDP on NCF were also examined.
Result: A total of 584-children exposed to HBP, 387-children exposed to PE/EL, and 5,877 unexposed children were included in the analysis. Neither CTh nor NCF differed between the exposed and unexposed children with or without adjusting for the confounders including the child’s age, sex, race, education, and birth histories. The whole-brain CTh did not mediate any of the relationships between HDP and NCF. However, the relationship between HDP and most of the NCF was mediated by birthweight and BMI.
Conclusions: Our results do not support maternal HDP, in comparison to other perinatal risk factors, as a direct risk factor for later-life cognitive functions. Prospective longitudinal studies, following up from infancy, are needed to further delineate the effect of HDP on children’s cognitive abilities. | 7408/10183 | Secondary Analysis | Shared |
| Explainable machine learning approach to predict and explain the relationship between task-based fMRI and individual differences in cognition | Despite decades of costly research, we still cannot accurately predict individual differences in cognition from task-based functional magnetic resonance imaging (fMRI). Moreover, aiming for methods with higher prediction is not sufficient. To understand brain-cognition relationships, we need to explain how these methods draw brain information to make the prediction. Here we applied an explainable machine-learning (ML) framework to predict cognition from task-based fMRI during the n-back working-memory task, using data from the Adolescent Brain Cognitive Development (n = 3,989). We compared 9 predictive algorithms in their ability to predict 12 cognitive abilities. We found better out-of-sample prediction from ML algorithms over the mass-univariate and ordinary least squares (OLS) multiple regression. Among ML algorithms, Elastic Net, a linear and additive algorithm, performed either similar to or better than nonlinear and interactive algorithms. We explained how these algorithms drew information, using SHapley Additive explanation, eNetXplorer, Accumulated Local Effects, and Friedman’s H-statistic. These explainers demonstrated benefits of ML over the OLS multiple regression. For example, ML provided some consistency in variable importance with a previous study and consistency with the mass-univariate approach in the directionality of brain-cognition relationships at different regions. Accordingly, our explainable-ML framework predicted cognition from task-based fMRI with boosted prediction and explainability over standard methodologies. | 6989/9468 | Secondary Analysis | Shared |
| Differentiating distinct and converging neural correlates of types of systemic environmental exposures | Background: Systemic environmental disadvantage relates to a host of health and functional outcomes. Specific structural factors have seldom been linked to neural structure, however, clouding understanding of putative mechanisms. Examining relations during childhood/preadolescence, a dynamic period of neurodevelopment, could aid bridge this gap.
Methods: A total of 10,213 youth were recruited from the Adolescent Brain and Cognitive Development study. Self-report and objective measures (Census and Federal bureau of investigation metrics extracted using geocoding) of environmental exposures were used, including stimulation indexing lack of safety and high attentional demands, discrepancy indexing social exclusion/lack of belonging, and deprivation indexing lack of environmental enrichment. Environmental measures were related to cortical thickness, surface area and subcortical volume regions, controlling for other environmental exposures and accounting for other brain regions.
Results: Self-report (|β|=0.04-0.09) and objective (|β|=0.02-0.06) environmental domains related to area/thickness in overlapping (e.g. insula, caudal anterior cingulate), and unique regions (e.g. for discrepancy, rostral anterior and isthmus cingulate, implicated in socioemotional functions; for stimulation, precuneus, critical for cue reactivity and integration of environmental cues, and for deprivation, superior frontal, integral to executive functioning). For stimulation and discrepancy exposures, self-report and objective measures showed similarities in correlate regions, while deprivation exposures evidenced distinct correlates for self-report and objective measures.
Conclusions: Results represent a necessary step toward broader work aimed at establishing mechanisms and correlates of structural disadvantage, highlighting the relevance of going beyond aggregate models by considering types of environmental factors, and the need to incorporate both subjective and objective measurements in these efforts. | 6961/9043 | Primary Analysis | Shared |
| Microstructural development from 9 to 14 years: Evidence from the ABCD Study | During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n = 8086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9–14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes. | 7288/9040 | Secondary Analysis | Private |
| Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex | Despite its central role in revealing the neurobiological mechanisms of behavior, neuroimaging research faces the challenge of producing reliable biomarkers for cognitive processes and clinical outcomes. Statistically significant brain regions, identified by mass univariate statistical models commonly used in neuroimaging studies, explain minimal phenotypic variation, limiting the translational utility of neuroimaging phenotypes. This is potentially due to the observation that behavioral traits are influenced by variations in neuroimaging phenotypes that are globally distributed across the cortex and are therefore not captured by thresholded, statistical parametric maps commonly reported in neuroimaging studies. Here, we developed a novel multivariate prediction method, the Bayesian polyvertex score, that turns a unthresholded statistical parametric map into a summary score that aggregates the many but small effects across the cortex for behavioral prediction. By explicitly assuming a globally distributed effect size pattern and operating on the mass univariate summary statistics, it was able to achieve higher out-of-sample variance explained than mass univariate and popular multivariate methods while still preserving the interpretability of a generative model. Our findings suggest that similar to the polygenicity observed in the field of genetics, the neural basis of complex behaviors may rest in the global patterning of effect size variation of neuroimaging phenotypes, rather than in localized, candidate brain regions and networks. | 6626/8892 | Primary Analysis | Private |
| Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet | In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature denoising, feature selection, training a StackNet, and predicting fluid intelligence. The extracted feature is the distribution of different brain tissues in different brain parcellation regions. The proposed StackNet consists of three layers and 11 models. Each layer uses the predictions from all previous layers including the input layer. The proposed StackNet is tested on a public benchmark Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge 2019 and achieves a mean squared error of 82.42 on the combined training and validation set with 10-fold cross-validation. In addition, the proposed StackNet also achieves a mean squared error of 94.25 on the testing data. The source code is available on GitHub. | 8670/8670 | Secondary Analysis | Shared |
| Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study | Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task. | 5837/7999 | Secondary Analysis | Shared |
| Rare copy number variants in males and females with childhood attention-deficit/hyperactivity disorder | While childhood attention-deficit/hyperactivity disorder (ADHD) is more prevalent in males than females, genetic contributors to this effect have not been established. Here, we explore sex differences in the contribution of common and/or rare genetic variants to ADHD. Participants were from the Adolescent Brain and Cognitive Development study (N=1,253 youth meeting DSM-5 criteria for ADHD [mean age=11.46 years [SD=0.87]; 31% female] and 5,577 unaffected individuals [mean age= 11.42 years [SD=0.89]; 50% female], overall 66% White, non-Hispanic (WNH), 19% Black/African American, and 15% other races. Logistic regression tested for interactions between sex (defined genotypically) and both rare copy number variants (CNV) and polygenic (common variant) risk in association with ADHD. There was a significant interaction between sex and the presence of a CNV deletion larger than 200 kb, both in the entire cohort (β = -0.74, CI = [-1.27 to -0.20], FDR-corrected p = 0.048) and, at nominal significance levels in the WNH ancestry subcohort (β = -0.86, CI = [-1.51 to -0.20], p = 0.010). Additionally, the number of deleted genes interacted with sex in association with ADHD (whole cohort. β = -0.13, CI = [-0.23 to -0.029], FDR-corrected p = 0.048; WNH. β = -0.17, CI = [-0.29 to -0.050], FDR-corrected p = 0.044) as did the total length of CNV deletions (whole cohort. β = -0.12, CI = [-0.19 to -0.044], FDR-corrected p = 0.028; WNH. β = -0.17, CI = [-0.28 to -0.061], FDR-corrected p = 0.034). This sex effect was driven by increased odds of childhood ADHD for females but not males in the presence of CNV deletions. No similar sex effect was found for CNV duplications or polygenic risk scores. The association between CNV deletions and ADHD was partially mediated by measures of cognitive flexibility. In summary, CNV deletions were associated with increased odds for childhood ADHD in females, but not males. | 5834/7849 | Secondary Analysis | Private |
| Stability of polygenic scores across discovery genome-wide association studies | Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications. | 4415/5962 | Secondary Analysis | Shared |
| ABCD Neurocognitive Prediction Challenge 2019: Test Set | The test data set for the ABCD Neurocognitive Prediction Challenge 2019 contains skull stripped and segmented T1-weighted MRIs, and volumetric brain measures of 3648 participants of the ABCD study.
https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline.
The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases | 4515/4516 | Secondary Analysis | Shared |
| Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer’s disease and/ or major depressive disorder | Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both Major Depressive Disorder (MDD) and Alzheimer’s Disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood. | 3535/4499 | Secondary Analysis | Shared |
| Shared heritability of human face and brain shape | Evidence from model organisms and clinical genetics suggests coordination between the developing brain and face, but the role of this link in common genetic variation remains unknown. We performed a multivariate genome-wide association study of cortical surface morphology in 19,644 individuals of European ancestry, identifying 472 genomic loci influencing brain shape, of which 76 are also linked to face shape. Shared loci include transcription factors involved in craniofacial development, as well as members of signaling pathways implicated in brain-face cross-talk. Brain shape heritability is equivalently enriched near regulatory regions active in either forebrain organoids or facial progenitors. However, we do not detect significant overlap between shared brain-face genome-wide association study signals and variants affecting behavioral-cognitive traits. These results suggest that early in embryogenesis, the face and brain mutually shape each other through both structural effects and paracrine signaling, but this interplay may not impact later brain development associated with cognitive function. | 3640/4470 | Secondary Analysis | Shared |
| Associations among household and neighborhood socioeconomic disadvantages, resting-state frontoamygdala connectivity, and internalizing symptoms in youth | Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED is a multifaceted construct and the precise processes by which SED confer deleterious effects are less clear. Using a large and diverse sample of preadolescents (ages 9-10 at baseline; N = 4,038; 49% female) from the Adolescent Brain Cognitive Development Study, we examined associations among SED at both household (i.e., income-to-needs and material hardship) and neighborhood (i.e., area deprivation and neighborhood unsafety) levels, frontoamygdala resting-state functional connectivity, and internalizing symptoms at baseline and 1-year follow-up. SED were positively associated with internalizing symptoms at baseline, and indirectly predicted symptoms one year later through elevated symptoms at baseline. At the household level, youth in households characterized by higher disadvantage (i.e., lower income-to-needs ratio) exhibited more strongly negative frontoamygdala coupling, particularly between the bilateral amygdala and medial orbitofrontal (mOFC) regions within the Frontoparietal Network. While more strongly positive amygdala-mOFC coupling was associated with higher levels of internalizing symptoms at baseline and 1-year follow-up, it did not mediate the association between income-to-needs ratio and internalizing symptoms. However, at the neighborhood level, amygdala-mOFC functional coupling moderated the effect of neighborhood deprivation on internalizing symptoms. Specifically, higher neighborhood deprivation was associated with higher internalizing symptoms for youth with more strongly positive connectivity, but not for youth with more strongly negative connectivity, suggesting a potential buffering effect. Findings highlight the importance of capturing multileveled socioecological contexts in which youth develop to identify youth who are most likely to benefit from early interventions. Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED is a multifaceted construct and the precise processes by which SED confer deleterious effects are less clear. Using a large and diverse sample of preadolescents (ages 9-10 at baseline; N = 4,038; 49% female) from the Adolescent Brain Cognitive Development Study, we examined associations among SED at both household (i.e., income-to-needs and material hardship) and neighborhood (i.e., area deprivation and neighborhood unsafety) levels, frontoamygdala resting-state functional connectivity, and internalizing symptoms at baseline and 1-year follow-up. SED were positively associated with internalizing symptoms at baseline, and indirectly predicted symptoms one year later through elevated symptoms at baseline. At the household level, youth in households characterized by higher disadvantage (i.e., lower income-to-needs ratio) exhibited more strongly negative frontoamygdala coupling, particularly between the bilateral amygdala and medial orbitofrontal (mOFC) regions within the Frontoparietal Network. While more strongly positive amygdala-mOFC coupling was associated with higher levels of internalizing symptoms at baseline and 1-year follow-up, it did not mediate the association between income-to-needs ratio and internalizing symptoms. However, at the neighborhood level, amygdala-mOFC functional coupling moderated the effect of neighborhood deprivation on internalizing symptoms. Specifically, higher neighborhood deprivation was associated with higher internalizing symptoms for youth with more strongly positive connectivity, but not for youth with more strongly negative connectivity, suggesting a potential buffering effect. Findings highlight the importance of capturing multileveled socioecological contexts in which youth develop to identify youth who are most likely to benefit from early interventions. | 4014/4163 | Secondary Analysis | Shared |
| Fluid Intelligence Classification Based On Cortical WM/GM Contrast, Cortical Thickness and Volumetry | Fluid intelligence refers to the ability of solving and reasoning problems. The recent Neurocognitive Prediction Challenge (ABCD-NP-Challenge 2019) demonstrated that predicting residual fluid intelligence from structural MR images is indeed challenging; the correlation between predicted and actual intelligence scores was extremely weak. The correlation was low for all entries including the winner (r = 0.03). In order to better understand this apparent non-relationship we (i) considered a simplified version of the prediction problem by grouping the top and bottom 10% of children on fluid intelligence scores and attempting to classify these two groups; (ii) tested different classification methods on this problem; and (iii) investigated the role that scanner heterogeneity might be playing in producing these poor predictions by using either data from all scanners or a single scanner. | 4153/4153 | Secondary Analysis | Private |
| Childhood obesity, cortical structure and executive function in healthy children | The development of executive function is linked to maturation of prefrontal cortex in childhood. Childhood obesity has been associated with changes in brain structure, particularly in prefrontal cortex, as well as deficits in executive functions. We aimed to determine whether differences in cortical structure mediate the relationship between executive function and childhood obesity. We analysed MR-derived measures of cortical thickness for 2,700 children between the ages of 9-11 years, recruited as part of the NIH ABCD study. We related our findings to measures of executive function and body mass index (BMI).
In our analysis, increased BMI was associated with significantly reduced mean cortical thickness, as well as specific bilateral reduced cortical thickness in prefrontal cortical regions. This relationship remained after accounting for age, sex, race, parental education, household income, birth-weight and in-scanner motion. Increased BMI was also associated with lower executive function. Reduced cortical thickness was found to mediate the relationship between BMI and executive function such that reduced thickness in the rostral medial and superior frontal cortex, the inferior frontal gyrus and the lateral orbitofrontal cortex accounted for partial reductions in executive function.
These results suggest that childhood obesity is associated with compromised executive function. This relationship may be partly explained by BMI-associated reduced cortical thickness in the prefrontal cortex.
| 3766/3921 | Secondary Analysis | Shared |
| ABCD Neurocognitive Prediction Challenge 2019: Training Set | Training data set for the ABCD Neurocognitive Prediction Challenge 2019 containing skull stripped and segmented T1-weighted MRIs, volumetric brain measures, and residual fluid intelligence scores of 3739 participants of the ABCD study.
https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline.
The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases | 3739/3739 | Secondary Analysis | Shared |
| Relating neighborhood deprivation to childhood obesity in the ABCD Study®: evidence for theories of neuroinflammation and neuronal stress | Objective: We evaluated whether relationships between area deprivation (ADI), body mass index (BMI) and brain structure (e.g., cortical thickness, subcortical volume) during pre-adolescence supported the immunologic model of self-regulation failure (NI) and/or neuronal stress (NS) theories of overeating. The NI theory proposes that ADI causes structural alteration in the brain due to the neuroinflammatory effects of overeating unhealthy foods. The NS theory proposes that ADI-related stress negatively impacts brain structure, which causes stress-related overeating and subsequent obesity.
Methods: Data were gathered from the Adolescent Brain Cognitive DevelopmentSM Study® (9-12-years-old; n=3,087, 51% male). Linear mixed-effects models identified brain regions that were associated with both ADI and BMI; longitudinal associations were evaluated with mediation models. The NI model included ADI and BMI at 9/10-years-old and brain data at 11/12-years-old. The NS model included ADI and brain data at 9/10-years-old and BMI at 11/12-years-old.
Results: BMI at 9/10-years-old partially mediated the relationship between ADI and Ventral DC volume at 11/12-years-old. Additionally, the Ventral DC at 9/10-years-old partially mediated the relationship between ADI and BMI at 11/12-years-old, even in youth who at baseline, were of a healthy weight. Results were unchanged when controlling for differences in brain structure and weight across the two-years.
Conclusion: Greater area deprivation may indicate fewer access to resources that support healthy development, like nutritious food and nonstressful environments. Our findings provide evidence in support of the NI and NS theories of overeating, specifically, with greater ADI influencing health outcomes of obesity via brain structure alterations.
| 2769/3087 | Secondary Analysis | Shared |
| What Is the Link Between Attention-Deficit/Hyperactivity Disorder and Sleep Disturbance? A Multimodal Examination of Longitudinal Relationships and Brain Structure Using Large-Scale Population-Based Cohorts | Background: Attention-deficit/hyperactivity disorder (ADHD) comorbid with sleep disturbances can produce profound disruption in daily life and negatively impact quality of life of both the child and the family. However, the temporal relationship between ADHD and sleep impairment is unclear, as are underlying common brain mechanisms.
Methods: This study used data from the Quebec Longitudinal Study of Child Development (n = 1601, 52% female) and the Adolescent Brain Cognitive Development Study (n = 3515, 48% female). Longitudinal relationships between symptoms were examined using cross-lagged panel models. Gray matter volume neural correlates were identified using linear regression. The transcriptomic signature of the identified brain-ADHD-sleep relationship was characterized by gene enrichment analysis. Confounding factors, such as stimulant drugs for ADHD and socioeconomic status, were controlled for.
Results: ADHD symptoms contributed to sleep disturbances at one or more subsequent time points in both cohorts. Lower gray matter volumes in the middle frontal gyrus and inferior frontal gyrus, amygdala, striatum, and insula were associated with both ADHD symptoms and sleep disturbances. ADHD symptoms significantly mediated the link between these structural brain abnormalities and sleep dysregulation, and genes were differentially expressed in the implicated brain regions, including those involved in neurotransmission and circadian entrainment.
Conclusions: This study indicates that ADHD symptoms and sleep disturbances have common neural correlates, including structural changes of the ventral attention system and frontostriatal circuitry. Leveraging data from large datasets, these results offer new mechanistic insights into this clinically important relationship between ADHD and sleep impairment, with potential implications for neurobiological models and future therapeutic directions. | 2974/3075 | Secondary Analysis | Shared |
| Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children. | The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems. | 2201/3004 | Secondary Analysis | Shared |
| Neurocognition ABCD 1.1 | Difficulties with higher-order cognitive functions in youth are a potentially important vulnerability factor for the emergence of problematic behaviors and a range of psychopathologies. This study examined 2,0139-10 year olds in the first data release from theAdolescent Brain Cognitive Development21-site consortium study inorder to identify resting state functional connectivity patterns that predict individual-differences in three domainsof higher-order cognitive functions:General Ability, Speed/Flexibility, and Learning/Memory.For General Ability scores in particular, we observed consistent cross-site generalizability, with statistically significant predictions in 14outof 15held-outsites.These resultssurvived several tests forrobustness includingreplication in split half analysis and in a low head motion subsample.Weadditionallyfound that connectivity patterns involving task control networks and defaultmode network were prominently implicated in predicting differencesinGeneral Abilityacrossparticipants. These findings demonstrate that restingstate connectivity can be leveraged to produce generalizable markers of neurocognitive functioning. Additionally, they highlight the importance of task control-default mode network interconnectionsas a major locus of individual differences in cognitive functioning in early adolescence. | 2122/2206 | Secondary Analysis | Private |
| A morphometrics approach for inclusion of localised characteristics from medical imaging studies into genome-wide association studies | Medical images, such as magnetic resonance or computed tomography, are increasingly being used to investigate the genetic architecture of neurological diseases like Alzheimer's disease, or psychiatric disorders like attention-deficit hyperactivity disorder. The quantified global or regional brain imaging measures are commonly known as imaging-specific or -derived phenotypes (IDPs) when conducting genotype-phenotype association studies. Inclusion of whole medical images rather than derived tabular data as IDPs has been done by either a voxel-wise approach or a global approach of whole medical images via principal component analysis. Limitations with multiple testing and inability to isolate high variation regions within the principal components arise with either of these approaches. This work proposes a principal component analysis-like localised approach of dimensionality reduction using diffeomorphic morphometry allowing for the selection of distances to model more regional effects.The main benefit of the proposed method is that it can can reduce the dimensionality of the problem considerably in comparison to the medical image's variability it is describing while grouping spatial information potentially lost in dimensionality reduction techniques like principal component analyses. Moreover, the approach not only allows to include locality in the analysis but can also be used as a generative model to explore the morphometric changes across an axis of particular components of interest. To demonstrate the feasibility of this pipeline for inclusion in a multivariate genome-wide association study, it was applied to 1,359 subjects from the Adolescent Brain Cognitive Development Study for traits related to attention-deficit disorder. The results show that the proposed method can identify more specific morphometric features associated with genome regions. | 1107/1359 | Secondary Analysis | Shared |
| Predicting multilingual effects on executive function and individual connectomes in children: An ABCD study | While there is a substantial amount of work studying multilingualism’s effect on cognitive functions, little is known about how the multilingual experience modulates the brain as a whole. In this study, we analyzed data of over 1,000 children from the Adolescent Brain Cognitive Development (ABCD) Study to examine whether monolinguals and multilinguals differ in executive function, functional brain connectivity, and brain–behavior associations. We observed significantly better performance from multilingual children than monolinguals in working-memory tasks. In one finding, we were able to classify multilinguals from monolinguals using only their whole-brain functional connectome at rest and during an emotional n-back task. Compared to monolinguals, the multilingual group had different functional connectivity mainly in the occipital lobe and subcortical areas during the emotional n-back task and in the occipital lobe and prefrontal cortex at rest. In contrast, we did not find any differences in behavioral performance and functional connectivity when performing a stop-signal task. As a second finding, we investigated the degree to which behavior is reflected in the brain by implementing a connectome-based behavior prediction approach. The multilingual group showed a significant correlation between observed and connectome-predicted individual working-memory performance scores, while the monolingual group did not show any correlations. Overall, our observations suggest that multilingualism enhances executive function and reliably modulates the corresponding brain functional connectome, distinguishing multilinguals from monolinguals even at the developmental stage. | 1030/1075 | Secondary Analysis | Shared |
| Longitudinal assessment of brain structure and behavior in youth with rapid weight gain: Potential contributing causes and consequences | Objective: Independent of weight status, rapid weight gain has been associated with underlying brain structure variation in regions associated with food intake and impulsivity among pre-adolescents. Yet, we lack clarity on how developmental maturation coincides with rapid weight gain and weight stability.
Methods: We identified brain predictors of two-year rapid weight gain and its longitudinal effects on brain structure and impulsivity in the Adolescent Brain Cognitive DevelopmentSM Study®. Youth were categorized as Healthy Weight/Weight Stable (WSHW, n=527) or Weight Gainers (WG, n=221, >38lbs); 63% of the WG group were healthy weight at 9-to-10-years-old.
Results: A five-fold cross-validated logistic elastic-net regression revealed that rapid weight gain was associated with structural variation amongst 39 brain features at 9-to-10-years-old in regions involved with executive functioning, appetitive control, and reward sensitivity. Two years later, WG youth showed differences in change over time in several of these regions and performed worse on measures of impulsivity.
Conclusions: These findings suggest that brain structure in pre-adolescence may predispose some to rapid weight gain and that weight gain itself may alter maturational brain change in regions important for food intake and impulsivity. Behavioral interventions that target inhibitory control may improve trajectories of brain maturation and facilitate healthier behaviors.
| 693/748 | Secondary Analysis | Shared |
| Resting State Cortical Hub Nodes in Youths | abstract here | 407/500 | Primary Analysis | Private |
| ABCD Neurocognitive Prediction Challenge 2019: Validation set | Validation data set for the ABCD Neurocognitive Prediction Challenge 2019 containing skull stripped and segmented T1-weighted MRIs, volumetric brain measures, and residual fluid intelligence scores of 415 participants of the ABCD study.
https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline.
The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases | 415/415 | Secondary Analysis | Shared |
| Parsing Concussion Heterogeneity | Concussions have a high incidence rate, especially in children and adolescents. Despite considerable time and money invested in research, no clinical trials have been successful in advancing concussion pharmacotherapy. The main factor underlying this stagnation is heterogeneity in pre-injury and injury-related factors, leading to an array of varied neuropathological and clinical presentations. In contrast, most prior concussion neuroimaging research has employed conventional group comparison approaches to average out heterogeneity in order to define a putative concussion biomarker. In this study, we used a double multivariate approach to find patterns in, rather than average out, heterogeneity in white matter structure and symptoms in children within the ABCD Study who had previously sustained concussions. We processed diffusion MRI images using a novel algorithm called Tractoflow, extracted conventional and emerging diffusion measures, and used principal components analysis to combine these measures into biologically-interpretable indices of white matter microstructure. We then used partial least squares correlation analysis on these white matter measures as well as 19 symptom measures to delineate linear combinations of white matter features that maximally covaried with linear combinations of symptoms. We called these hidden relationships "multi-tract multi-symptom pairs". We found highly informative relationships which were averaged out when analyses were performed using conventional techniques. Further, the expression of these multi-tract multi-symptom pairs predicted adverse psychiatric outcomes in an unseen subset of the data. This study introduces a fundamentally novel way of studying concussions by leveraging heterogeneity instead of averaging out. | 297/345 | Primary Analysis | Private |
