PhenX: a toolkit for interdisciplinary genetics research

Concordance in Child-Parent Reporting of Social Victimization Experiences in the Adolescent Brain Cognitive Development (ABCD) Study

OBJECTIVE

To investigate child-parent concordance in reporting social victimization experiences and whether parent concordance with child report of victimization was associated with child behavioral symptoms.

METHODS

This was an observational study with data from the Adolescent Brain Cognitive Development Social Development (ABCD-SD) substudy. The analytic sample was 2415 pre-adolescent children from the United States. We assessed parent-child concordance on six domains of child social victimization: conventional crime, peer victimization, witnessing violence, internet victimization, school victimization, and gun violence. Child behavior symptoms were measured using the parent-report Child Behavior Checklist. Interrater agreement and multiple linear and logistic regression analyses were conducted to assess parent concordance with child report of victimization and its relationship to behavioral symptoms.

RESULTS

Interrater agreement in parent-child social victimizations reports was low, with Cohen's Kappa values ranging from 0.10 to 0.23. Compared to parent-child dyads in which neither reported victimization, parent concordance with child report of victimization across multiple domains of social victimization was associated with more internalizing/externalizing behaviors, as was parent discordance with child reports that did not indicate victimization. Among children who reported victimization, parents' perceptions of greater neighborhood safety were associated with lower odds of concordant parent report of conventional crime (OR = 0.94, 95% CI = 0.90-0.98) and witnessing violence (OR = 0.94, 95% CI-0.89-0.98).

CONCLUSIONS

Parents and children do not necessarily agree in reporting social victimization experiences. Parent reports of child social victimization, whether they were concordant with positive child reports or discordant with negative child reports, were associated with parent reports of behavioral symptoms and thus may be an indicator of the severity of experiences, underscoring the need to consider multiple informants when screening for adversity.

Happy children! A network of psychological and environmental factors associated with the development of positive affect in 9-13 children

To deepen the development of positive affect during early adolescence and shed new light on its predictors, this study adopts an exploratory network approach to first identify the main domains that describe the variability of children's psychological, environmental, and behavioral characteristics, and then use these domains to longitudinally predict positive affect and its development within a latent growth framework. To this aim, we considered 10,904 US participants (9 years old at baseline; 13 years old 42 months later), six measurement occasions of positive affect, and 46 baseline indicators from the ABCD study. Our results not only confirm that positive affect declines between 9 and 13 years old, but also show that among the five domains identified (behavioral dysregulation, cognitive functioning, psychological problems, supportive social environment, and extracurricular activities), only a supportive social environment consistently predicts positive affect. This is crucial for practitioners and policymakers, as it can help them focus on the elements within our complex network of psychological, social, and environmental variability.

Childhood adversity is associated with reduced BOLD response in inhibitory control regions amongst preadolescents from the ABCD study

Adolescence is characterized by dynamic neurodevelopment, which poses opportunities for risk and resilience. Adverse childhood experiences (ACEs) confer additional risk to the developing brain, where ACEs have been associated with alterations in functional magnetic resonance imaging (fMRI) BOLD signaling in brain regions underlying inhibitory control. Socioenvironmental factors like the family environment may amplify or buffer against the neurodevelopmental risks associated with ACEs. Using baseline to Year 2 follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study, the current study examined how ACEs relate to fMRI BOLD signaling during successful inhibition on the Stop Signal Task in regions associated with inhibitory control and examined whether family conflict levels moderated that relationship. Results showed that greater ACEs were associated with reduced BOLD response in the right opercular region of the inferior frontal gyrus and bilaterally in the pre-supplementary motor area, which are key regions underlying inhibitory control. Further, greater BOLD response was correlated with less impulsivity behaviorally, suggesting reduced activation may not be behaviorally adaptive at this age. No significant two or three-way interactions with family conflict levels or time were found. Findings highlight the continued utility of examining the relationship between ACEs and neurodevelopmental outcomes and the importance of intervention/prevention of ACES.

The Toronto Adolescent and Youth Cohort Study: Study Design and Early Data Related to Psychosis Spectrum Symptoms, Functioning, and Suicidality

BACKGROUND

Psychosis spectrum symptoms (PSSs) occur in a sizable percentage of youth and are associated with poorer cognitive performance, poorer functioning, and suicidality (i.e., suicidal thoughts and behaviors). PSSs may occur more frequently in youths already experiencing another mental illness, but the antecedents are not well known. The Toronto Adolescent and Youth (TAY) Cohort Study aims to characterize developmental trajectories in youths with mental illness and understand associations with PSSs, functioning, and suicidality.

METHODS

The TAY Cohort Study is a longitudinal cohort study that aims to assess 1500 youths (age 11-24 years) presenting to tertiary care. In this article, we describe the extensive diagnostic and clinical characterization of psychopathology, substance use, functioning, suicidality, and health service utilization in these youths, with follow-up every 6 months over 5 years, including early baseline data.

RESULTS

A total of 417 participants were enrolled between May 4, 2021, and February 2, 2023. Participants met diagnostic criteria for an average of 3.5 psychiatric diagnoses, most frequently anxiety and depressive disorders. Forty-nine percent of participants met a pre-established threshold for PSSs and exhibited higher rates of functional impairment, internalizing and externalizing symptoms, and suicidality than participants without PSSs.

CONCLUSIONS

Initial findings from the TAY Cohort Study demonstrate the feasibility of extensive clinical phenotyping in youths who are seeking help for mental health problems. PSS prevalence is much higher than in community-based studies. Our early data support the critical need to better understand longitudinal trajectories of clinical youth cohorts in relation to psychosis risk, functioning, and suicidality.

Large-scale investigation of white matter structural differences in bilingual and monolingual children: An adolescent brain cognitive development data study

Emerging research has provided valuable insights into the structural characteristics of the bilingual brain from studies of bilingual adults; however, there is a dearth of evidence examining brain structural alterations in childhood associated with the bilingual experience. This study examined the associations between bilingualism and white matter organization in bilingual children compared to monolingual peers leveraging the large-scale data from the Adolescent Brain Cognitive Development (ABCD) Study. Then, 446 bilingual children (ages 9-10) were identified from the participants in the ABCD data and rigorously matched to a group of 446 monolingual peers. Multiple regression models for selected language and cognitive control white matter pathways were used to compare white matter fractional anisotropy (FA) values between bilinguals and monolinguals, controlling for demographic and environmental factors as covariates in the models. Results revealed significantly lower FA values in bilinguals compared to monolinguals across established dorsal and ventral language network pathways bilaterally (i.e., the superior longitudinal fasciculus and inferior frontal-occipital fasciculus) and right-hemispheric pathways in areas related to cognitive control and short-term memory (i.e., cingulum and parahippocampal cingulum). In contrast to the enhanced FA values observed in adult bilinguals relative to monolinguals, our findings of lower FA in bilingual children relative to monolinguals may suggest a protracted development of white matter pathways associated with language and cognitive control resulting from dual language learning in childhood. Further, these findings underscore the need for large-scale longitudinal investigation of white matter development in bilingual children to understand neuroplasticity associated with the bilingual experience during this period of heightened language learning.

Genetic and brain similarity independently predict childhood anthropometrics and neighborhood socioeconomic conditions

Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ an integrative approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, associations between cortical thickness similarity and traits were limited to anthropometrics such as height, weight, and birth weight, as well as a marker of neighborhood socioeconomic conditions. Common genetic variants explained significant proportions of variance across nearly all included outcomes, although estimates were somewhat lower than previous reports. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as neighborhood socioeconomic conditions and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample.

Hispanic/Latinx ethnic differences in the relationships between behavioral inhibition, anxiety, and substance use in youth from the ABCD cohort

Introduction

Elevated levels of behavioral inhibition (BI) may connote risk for both anxiety and substance use disorders. BI has consistently been shown to be associated with increased levels of anxiety, while the association between BI and substance use has been mixed. It is possible that the relationship between BI and substance use varies by individual difference factors. Hispanic/Latinx (H/L) youth in particular may have stronger relationships between BI, anxiety, and substance use.

Methods

The present study therefore evaluated (1) the prospective relationships between BI [assessed via self-reported behavioral inhibition system (BIS) scale scores], anxiety, and substance use in youth (n = 11,876) across baseline, 1-, and 2-year follow-ups of the Adolescent Brain Cognitive Development (ABCD) Study (ages 9-12) and (2) whether these relationships differed by H/L ethnicity while covarying for average behavioral approach system scores, race, sex, age, highest parental income, highest parental education, and past-year substance use (for analyses involving substance use outcomes).

Results

Baseline levels of BIS scores predicted increased anxiety symptoms at both 1- and 2-year follow-ups and did not differ by H/L ethnicity. Baseline levels of BIS scores also prospectively predicted increased likelihood of substance use at 2-year follow-up, but only for H/L youth and not at 1-year follow-up.

Discussion

High scores on the BIS scale contribute risk to anxiety across ethnicities and may uniquely contribute to risk for substance use in H/L youth.

Characterization and prediction of individual functional outcome trajectories in schizophrenia spectrum disorders (PREDICTS study): Study protocol

Schizophrenia spectrum disorders (SSDs) are associated with significant functional impairments, disability, and low rates of personal recovery, along with tremendous economic costs linked primarily to lost productivity and premature mortality. Efforts to delineate the contributors to disability in SSDs have highlighted prominent roles for a diverse range of symptoms, physical health conditions, substance use disorders, neurobiological changes, and social factors. These findings have provided valuable advances in knowledge and helped define broad patterns of illness and outcomes across SSDs. Unsurprisingly, there have also been conflicting findings for many of these determinants that reflect the heterogeneous population of individuals with SSDs and the challenges of conceptualizing and treating SSDs as a unitary categorical construct. Presently it is not possible to identify the functional course on an individual level that would enable a personalized approach to treatment to alter the individual's functional trajectory and mitigate the ensuing disability they would otherwise experience. To address this ongoing challenge, this study aims to conduct a longitudinal multimodal investigation of a large cohort of individuals with SSDs in order to establish discrete trajectories of personal recovery, disability, and community functioning, as well as the antecedents and predictors of these trajectories. This investigation will also provide the foundation for the co-design and testing of personalized interventions that alter these functional trajectories and improve outcomes for people with SSDs.

Developing Clinical Phenotype Data Collection Standards for Research in Africa

Modern biomedical research is characterised by its high-throughput and interdisciplinary nature. Multiproject and consortium-based collaborations requiring meaningful analysis of multiple heterogeneous phenotypic datasets have become the norm; however, such analysis remains a challenge in many regions across the world. An increasing number of data harmonisation efforts are being undertaken by multistudy collaborations through either prospective standardised phenotype data collection or retrospective phenotype harmonisation. In this regard, the Phenotype Harmonisation Working Group (PHWG) of the Human Heredity and Health in Africa (H3Africa) consortium aimed to facilitate phenotype standardisation by both promoting the use of existing data collection standards (hosted by PhenX), adapting existing data collection standards for appropriate use in low- and middle-income regions such as Africa, and developing novel data collection standards where relevant gaps were identified. Ultimately, the PHWG produced 11 data collection kits, consisting of 82 protocols, 38 of which were existing protocols, 17 were adapted, and 27 were novel protocols. The data collection kits will facilitate phenotype standardisation and harmonisation not only in Africa but also across the larger research community. In addition, the PHWG aims to feed back adapted and novel protocols to existing reference platforms such as PhenX.

Pathways link environmental and genetic factors with structural brain networks and psychopathology in youth

Adolescence is a period of significant brain development and maturation, and it is a time when many mental health problems first emerge. This study aimed to explore a comprehensive map that describes possible pathways from genetic and environmental risks to structural brain organization and psychopathology in adolescents. We included 32 environmental items on developmental adversity, maternal substance use, parental psychopathology, socioeconomic status (SES), school and family environment; 10 child psychopathological scales; polygenic risk scores (PRS) for 10 psychiatric disorders, total problems, and cognitive ability; and structural brain networks in the Adolescent Brain Cognitive Development study (ABCD, n = 9168). Structural equation modeling found two pathways linking SES, brain, and psychopathology. Lower SES was found to be associated with lower structural connectivity in the posterior default mode network and greater salience structural connectivity, and with more severe psychosis and internalizing in youth (p < 0.001). Prematurity and birth weight were associated with early-developed sensorimotor and subcortical networks (p < 0.001). Increased parental psychopathology, decreased SES and school engagement was related to elevated family conflict, psychosis, and externalizing behaviors in youth (p < 0.001). Increased maternal substance use predicted increased developmental adversity, internalizing, and psychosis (p < 0.001). But, polygenic risks for psychiatric disorders had moderate effects on brain structural connectivity and psychopathology in youth. These findings suggest that a range of genetic and environmental factors can influence brain structural organization and psychopathology during adolescence, and that addressing these risk factors may be important for promoting positive mental health outcomes in young people.

Concordance in Child-Parent Reporting of Social Victimization Experiences in the Adolescent Brain Cognitive Development Study

OBJECTIVE

To investigate child-parent concordance in reporting social victimization experiences and whether concordance was associated with child behavioral symptoms.

METHODS

This was an observational study with data from the Adolescent Brain Cognitive Development study. The analytic sample was 11,235 9- or 10-year-old children from the United States. Exposure variables were demographic and protective factors (child perceptions of parental relationships, school protective factors, neighborhood safety). The outcome was parent-child concordance on 6 domains of child social victimization: conventional crime, peer victimization, witnessing violence, internet victimization, school victimization, and gun violence. Child behavior symptoms were measured using the Child Behavior Checklist.

RESULTS

Exposure to social victimization was low (9% of the sample). Concordance ranged from 18% to 50%. The highest levels of concordance were observed for conventional crime (k = 0.48, P < .001) and witnessing violence (k = 0.48, P < .001). Parents' perceptions of greater neighborhood safety was associated with lower odds of concordant conventional crime (odds ratio [OR] = 0.92, 95% confidence interval [CI] 0.86-0.99) and witnessing violence (OR = 0.92, 95% CI0.84-0.99). Concordance was associated with more internalizing/externalizing behaviors.

CONCLUSIONS

Parents under-report social victimization in relation to children. Concordance in reporting social victimization may be an indicator of the severity of experiences, underscoring the need to consider child reports when screening for adversity.

Prevalence and Correlates of Mental Disorders in Children Aged 9 and 10 Years: Results From the ABCD Study

OBJECTIVE

To estimate the prevalence of current DSM-5 disorders in children, ages 9 to 10 years, and their associations with sociodemographic and physical characteristics.

METHOD

In this analysis of the Adolescent Brain Cognitive Development (ABCD) first wave study data, current child mental disorders were based on the computerized parent version of the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 (N=11,874) supplemented with the child version for mood and selected anxiety disorders and with teacher Brief Problem Monitor ratings for the attention and externalizing scales. Child sociodemographic (race/ethnicity, nativity, parental marital status, parental education, family income) and physical characteristics (sex, pubertal stage, weight status, maternal age) were derived from parent report and anthropometric measurement. Odds ratios (OR) with 95% Confidence Intervals (95%CI) assessed associations with child mental disorders.

RESULTS

The prevalence of any current mental disorder was 10.11% including 11.48% among boys and 8.68% among girls. After controlling for several sociodemographic and physical characteristics, boys (OR=1.53; 95%CI=1.17-1.99), children from families with incomes below $25,000 (OR=2.05; 95%CI=1.31-3.22), incomes of $25,000-$49,000 (OR=1.90; 95%CI=1.20-3.00) ($75,000, reference) and obese children (OR=1.45, 95%CI=1.16-1.81) (healthy weight, reference) were at increased risk for any current child mental disorder. Children from the lowest family income group were at particularly high risk for ADHD (OR=3.86, 95%CI=1.69-8.79) and disruptive behavior behaviors (OR=4.13; 95%CI=1.86-9.15).

CONCLUSION

These patterns underscore the importance of strengthening service planning, preventive interventions, and etiological research focused on children from low income families.

Treatment of US Children With Attention-Deficit/Hyperactivity Disorder in the Adolescent Brain Cognitive Development Study

Importance

Characterizing the extent and pattern of unmet needs for treatment of children with attention-deficit/hyperactivity disorder (ADHD) could help target efforts to improve access to ADHD medications and outpatient mental health care.

Objective

To describe current ADHD medication use and lifetime outpatient mental health care among a large national sample of children with ADHD.

Design, Setting, and Participants

This study uses cross-sectional survey data from the first wave of the Adolescent Brain and Cognitive Development Study (n = 11 723), conducted from June 1, 2016, to October 15, 2018, among 1206 school children aged 9 and 10 years who met parent-reported Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria for current ADHD. Statistical analysis was performed from March 23, 2022, to March 10, 2023.

Main Outcomes and Measures

Current ADHD medications including stimulants and nonstimulants, lifetime outpatient mental health care, or either treatment. Weighted results are reported.

Results

Among a sample of 11 723 children, 1206 had parent-reported ADHD (aged 9-10 years; 826 boys [68.2%]; 759 White, non-Hispanic children [62.2%]), 149 (12.9%) were currently receiving ADHD medications. Children receiving ADHD medications included a significantly higher percentage of boys (15.7% [121 of 826]) than girls (7.0% [28 of 108]), White children (14.8% [104 of 759]) than Black children (9.4% [22 of 206]), children of parents without a high school education (32.2% [9 of 36]) than of parents with a bachelor's degree or higher (11.5% [84 of 715]), and children with the combined subtype of ADHD (17.0% [83 of 505]) than with the inattentive subtype (9.5% [49 of 523]). Approximately 26.2% of children (301 of 1206) with parent-reported ADHD had ever received outpatient mental health care. Children receiving outpatient mental health care included a significantly higher percentage of children whose parents had a high school education (36.2% [29 of 90]) or some college (31.0% [109 of 364]) than a bachelor's degree or higher (21.3% [153 of 715]), children with family incomes of less than $25 000 (36.5% [66 of 176]) or $25 000 to $49 999 (27.7% [47 of 174]) than $75 000 or more (20.1% [125 of 599]), and children with the combined subtype of ADHD (33.6% [166 of 505]) than with the predominantly inattentive subtype (20.0% [101 of 523]) or the hyperactive-impulsive subtype (22.4% [34 of 178]) of ADHD.

Conclusions and Relevance

This cross-sectional study of children with parent-reported ADHD suggests that most were not receiving ADHD medications and had never received outpatient mental health care. Gaps in treatment, which were not directly associated with socioeconomic disadvantage, underscore the challenges of improving communication and access to outpatient mental health care for children with ADHD.

The propensity to sign-track is associated with externalizing behavior and distinct patterns of reward-related brain activation in youth

Externalizing behaviors in childhood often predict impulse control disorders in adulthood; however, the underlying bio-behavioral risk factors are incompletely understood. In animals, the propensity to sign-track, or the degree to which incentive motivational value is attributed to reward cues, is associated with externalizing-type behaviors and deficits in executive control. Using a Pavlovian conditioned approach paradigm, we quantified sign-tracking in 40 healthy 9-12-year-olds. We also measured parent-reported externalizing behaviors and anticipatory neural activations to outcome-predicting cues using the monetary incentive delay fMRI task. Sign-tracking was associated with attentional and inhibitory control deficits and the degree of amygdala, but not cortical, activation during reward anticipation. These findings support the hypothesis that youth with a propensity to sign-track are prone to externalizing tendencies, with an over-reliance on subcortical cue-reactive brain systems. This research highlights sign-tracking as a promising experimental approach delineating the behavioral and neural circuitry of individuals at risk for externalizing disorders.

Eye Dynamics and Engineering Network Consortium: Baseline Characteristics of a Randomized Trial in Healthy Adults

PURPOSE

To improve understanding of intraocular pressure (IOP) and its variance, this project identifies systemic and ocular characteristics of healthy eyes of adult volunteers including IOP variation, ocular biometrics, and aqueous humor dynamics (AHDs). These data serve as baseline controls for further studies from the Eye Dynamics and Engineering Network (EDEN) Consortium.

DESIGN

Multicenter open-label clinical trial in healthy adults randomized to 1 week treatment with 2 approved glaucoma drugs in a crossover design.

PARTICIPANTS

Among 135 healthy participants, 122 participants (aged 55.2 ± 8.8 years; 92 females, 30 males) completed the protocol.

METHODS

Participants from the University of Michigan, Mayo Clinic, and University of Nebraska Medical Center underwent measurements of ocular biometrics, AHD, and IOP using 4 tonometers. Intraocular pressure data during 3 study visits without glaucoma medications were used in the analysis. The PhenX Toolkit survey acquired standardized data on medical history, surgical history, medications, smoking and alcohol exposures, and physical measures.

MAIN OUTCOME MEASURES

The variability of IOP measurements within eyes was assessed as visit-to-visit IOP variation, within-visit IOP variation, and within-visit positional IOP variation. The concordance (or correlation) between eyes was also assessed.

RESULTS

Average positional change of > 4.7 mmHg was detected with a range of 0.5-11.0 mmHg. Pearson correlation of IOP between eyes within a visit was 0.87 (95% confidence interval [CI], 0.82-0.91) for Goldmann applanation tonometry, 0.91 (95% CI, 0.88-0.94) for Icare rebound tonometry, and 0.91 (95% CI, 0.88-0.94) for pneumatonometry. There was a 4% to 12% asymmetric fluctuation of 3 mmHg or more between eyes between visits using rebound tonometry, 9% with Goldmann applanation tonometry, and 3% to 4% by pneumotonometry. The coefficient of variation between visits for the same eye ranged from 11.2% to 12.9% for pneumatonometry, from 13.6% to 17.4% for rebound tonometry, and 15.8% to 16.2% for Goldmann applanation tonometry.

CONCLUSIONS

The current study from the EDEN Consortium describes measurement methods and data analyses with emphasis on IOP variability. Future papers will focus on changes in ocular biometrics and AHD with timolol or latanoprost treatment.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

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.

Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.

Application of the RDoC Framework to Predict Alcohol Use and Suicidal Thoughts and Behaviors among Early Adolescents in the Adolescent Brain and Cognitive Development (ABCD) Study

Alcohol use confers risk for suicidal thoughts and behaviors (ideation, attempt) in early adolescents. The Research Domain Criteria provides a framework for examination of multidimensional and modifiable risk factors. We examined distinct latent profiles based on patterns of positive valence (reward responsivity) and cognitive systems (neurocognition) from the ABCD Study (age 9−10, N = 10,414) at baseline enrollment. Longitudinal associations were determined between baseline positive valence and cognitive profiles and group classification (alcohol use, suicidal thoughts and behaviors, or their co-occurrence) two-years after initial assessment (ages 11−12). Three unique profiles of positive valence, cognition, alcohol use, and suicidal thoughts and behaviors were identified. Two baseline profiles predicted alcohol use and suicidal thoughts and behaviors, two-years after initial assessment. Low positive valence with high cognition (but low impulsivity) predicted alcohol use (OR = 1.414, p< 0.001), while high positive valence with low cognition (but high impulsivity) predicted suicidal thoughts and behaviors (OR = 1.25, p = 0.038), compared to average positive valence and cognition. Unique profiles of positive valence and cognitive systems among 9−12-year-olds may be predictive of alcohol use and suicidal thoughts and behaviors over a two-year period. Findings underscore the potential for trajectory research on positive valence and cognitive profiles to enhance prevention for early-adolescents.

Individual-, peer-, and parent-level substance use-related factors among 9- and 10-year-olds from the ABCD Study: Prevalence rates and sociodemographic differences

Background

Although a relatively large body of research has identified multiple factors associated with adolescent substance use, less is known about earlier substance-related factors during preadolescence, including curiosity to use substances. The present study examined individual-, peer-, and parent-level domains pertaining to substance use and how these domains vary by sociodemographic subgroups and substance type.

Methods

Participants were 11,864 9- and 10-year-olds from the baseline sample of the Adolescent Brain Cognitive Development (ABCD) Study. Youth-reported measures were curiosity to use substances and perceived peer substance use. Parent-reported measures were availability of and rules about substances. Generalized logistic mixed models (GLMM) were used to compare these measures across alcohol, nicotine, and marijuana and across sociodemographic subgroupings (sex, race/ethnicity, household income, and family history of alcohol problems). GLMM was then used to examine predictors of curiosity to use by substance type.

Results

The most striking descriptive differences were found between race/ethnicity and income categories (e.g., positive associations between greater income and greater availability of alcohol). In multivariable analyses, greater curiosity to use alcohol was associated with being male, higher household income, perceived peer alcohol use, and easy alcohol availability; greater curiosity to use nicotine was associated with being male, perceived peer cigarette use, easy availability of cigarettes, and no parental rules about cigarette use.

Conclusions

This study identified substance use-related individual-, peer-, and parent-level factors among a diverse, national sample. Findings highlight the importance of considering sociodemographic and substance-specific variability and may help identify risk and protective factors preceding adolescent substance use.

Internalizing-externalizing comorbidity and regional brain volumes in the ABCD study

Despite nonoverlapping diagnostic criteria, internalizing and externalizing disorders show substantial comorbidity. This comorbidity is attributable, at least in part, to transdiagnostic neuroaffective mechanisms. Both unipolar depression and externalizing disorders are characterized by structural and functional compromises in the striatum and its projections to the anterior cingulate cortex (ACC) and other frontal regions. Smaller volumes and dampened reward responding in these regions are associated with anhedonia and irritability - mood states that cut across the internalizing and externalizing spectra. In contrast, smaller amygdala volumes and dampened amygdala function differentiate externalizing disorders from internalizing disorders. Little is known, however, about associations between internalizing-externalizing comorbidity and brain volumes in these regions, or whether such patterns differ by sex. Using a transdiagnostic, research domain criteria (RDoC)-informed approach, we evaluate associations between heterotypic (Internalizing × Externalizing) symptom interactions and striatal, amygdalar, and ACC volumes among participants in the Adolescent Brain Cognitive Development study (N = 6,971, mean age 9.9 years, 51.6% female). Heterotypic symptoms were associated with ACC volumes for both sexes, over and above the main effects of internalizing and externalizing alone. However, heterotypic comorbidity was associated with larger ACC volumes for girls, but with smaller ACC volumes for boys. These findings suggest a need for further studies and transdiagnostic assessment by sex.

Pubertal timing and functional neurodevelopmental alterations independently mediate the effect of family conflict on adolescent psychopathology

This study tested the hypothesis that early life adversity (ELA) heightens psychopathology risk by concurrently altering pubertal and neurodevelopmental timing, and associated gene transcription signatures. Analyses focused on threat- (family conflict/neighbourhood crime) and deprivation-related ELAs (parental inattentiveness/unmet material needs), using longitudinal data from 1514 biologically unrelated youths in the Adolescent Brain and Cognitive Development (ABCD) study. Typical developmental changes in white matter microstructure corresponded to widespread BOLD signal variability (BOLDsv) increases (linked to cell communication and biosynthesis genes) and region-specific task-related BOLDsv increases/decreases (linked to signal transduction, immune and external environmental response genes). Increasing resting-state (RS), but decreasing task-related BOLDsv predicted normative functional network segregation. Family conflict was the strongest concurrent and prospective contributor to psychopathology, while material deprivation constituted an additive risk factor. ELA-linked psychopathology was predicted by higher Time 1 threat-evoked BOLDSV (associated with axonal development, myelination, cell differentiation and signal transduction genes), reduced Time 2 RS BOLDsv (associated with cell metabolism and attention genes) and greater Time 1 to Time 2 control/attention network segregation. Earlier pubertal timing and neurodevelopmental alterations independently mediated ELA effects on psychopathology. Our results underscore the differential roles of the immediate and wider external environment(s) in concurrent and longer-term ELA consequences.

Demographic and mental health assessments in the adolescent brain and cognitive development study: Updates and age-related trajectories

The Adolescent Brain Cognitive Development (ABCD) Study of 11,880 youth incorporates a comprehensive range of measures assessing predictors and outcomes related to mental health across childhood and adolescence in participating youth, as well as information about family mental health history. We have previously described the logic and content of the mental health assessment battery at Baseline and 1-year follow-up. Here, we describe changes to that battery and issues and clarifications that have emerged, as well as additions to the mental health battery at the 2-, 3-, 4-, and 5-year follow-ups. We capitalize on the recent release of longitudinal data for caregiver and youth report of mental health data to evaluate trajectories of dimensions of psychopathology as a function of demographic factors. For both caregiver and self-reported mental health symptoms, males showed age-related decreases in internalizing and externalizing symptoms, while females showed an increase in internalizing symptoms with age. Multiple indicators of socioeconomic status (caregiver education, family income, financial adversity, neighborhood poverty) accounted for unique variance in both caregiver and youth-reported externalizing and internalizing symptoms. These data highlight the importance of examining developmental trajectories of mental health as a function of key factors such as sex and socioeconomic environment.

Using the PhenX Toolkit to Select Standard Measurement Protocols for Your Research Study

The goals of PhenX (consensus measures for Phenotypes and eXposures) are to promote the use of standard measurement protocols and to help investigators identify opportunities for collaborative research and cross‐study analysis, thus increasing the impact of individual studies. The PhenX Toolkit (https://www.phenxtoolkit.org/) offers high‐quality, well‐established measurement protocols to assess phenotypes and exposures in studies with human participants. The Toolkit contains protocols representing 29 research domains and 6 specialty collections of protocols that add depth to the Toolkit in specific research areas (e.g., COVID‐19, Social Determinants of Health [SDoH], Blood Sciences Research [BSR], Mental Health Research [MHR], Tobacco Regulatory Research [TRR], and Substance Abuse and Addiction [SAA]). Protocols are recommended for inclusion in the PhenX Toolkit by Working Groups of domain experts using a consensus process that includes input from the scientific community. For each PhenX protocol, the Toolkit provides a detailed description, the rationale for inclusion, and supporting documentation. Users can browse protocols in the Toolkit, search the Toolkit using keywords, or use Browse Protocols Tree to identify protocols of interest. The PhenX Toolkit provides data dictionaries compatible with the database of Genotypes and Phenotypes (dbGaP), Research Electronic Data Capture (REDCap) data submission compatibility, and data collection worksheets to help investigators incorporate PhenX protocols into their study design. The PhenX Toolkit provides resources to help users identify published studies that used PhenX protocols. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.

Basic Protocol: Using the PhenX Toolkit to support or extend study design

Preliminary analysis of low-level alcohol use and suicidality with children in the adolescent brain and cognitive development (ABCD) baseline cohort

Cross-sectional analyses were conducted in the baseline cohort of the Adolescent Brain and Cognitive Development (ABCD) Study to determine if lifetime low-level alcohol use was associated with an increased likelihood of lifetime suicidality (N=10,773, ages 9-10). Among the lifetime suicide ideation and attempt groups, 37.7% and 36.2% reported lifetime low-level alcohol use, respectively; versus 22.2% in the non-suicidality group. Children reporting lifetime alcohol use (i.e., ≥ a sip) showed a nearly two-fold increase in their odds of lifetime suicidality compared to those with no previous alcohol use. Future prospective research with this cohort will continue to probe alcohol-suicidality associations.

The association between child alcohol sipping and alcohol expectancies in the ABCD study

BACKGROUND

Underage drinking is a serious societal concern, yet relatively little is known about child sipping of alcohol and its relation to beliefs about alcohol. The current study aimed to (1) examine the contexts in which the first sip of alcohol occurs (e.g., type of alcohol, who provided sip, sip offered or taken without permission); (2) examine the association between sipping and alcohol expectancies; and (3) explore how different contexts of sipping are related to alcohol expectancies. We expected to find that children who had sipped alcohol would have increased positive expectancies and reduced negative expectancies compared to children who had never sipped alcohol.

METHODS

Data were derived from the 2.0 release of the Adolescent Brain Cognitive Development (ABCD) study, a longitudinal study of children in the United States. We utilized data from 4,842 children ages 9-11; 52% were male, 60% were White, 19% were Hispanic/Latinx, and 9% were Black/African American.

RESULTS

We found that 22% of the sample had sipped alcohol. Children reported sipping beer most frequently, and the drink most often belonged to the child's father. We found that children who had sipped had higher positive alcohol expectancies than children who had not while accounting for variables related to alcohol expectancies. Child sipping was not significantly associated with negative expectancies and the context of the first sip of alcohol was not significantly associated with positive and negative expectancies.

CONCLUSIONS

Providing sips of alcohol to children is associated with them having more favorable expectations about drinking.

Caffeine exposure in utero is associated with structural brain alterations and deleterious neurocognitive outcomes in 9-10 year old children

Caffeine, a very widely used and potent neuromodulator, easily crosses the placental barrier, but relatively little is known about the long-term impact of gestational caffeine exposure (GCE) on neurodevelopment. Here, we leverage magnetic resonance imaging (MRI) data, collected from a very large sample of 9157 children, aged 9-10 years, as part of the Adolescent Brain and Cognitive Development^sm (ABCD ®) study, to investigate brain structural outcomes at 27 major fiber tracts as a function of GCE. Significant relationships between GCE and fractional anisotropy (FA) measures in the inferior fronto-occipito fasciculus and corticospinal tract of the left hemisphere (IFOF-LH; CST-LH) were detected via mixed effects binomial regression. We further investigated the interaction between these fiber tracts, GCE, cognitive measures (working memory, task efficiency), and psychopathology measures (externalization, internalization, somatization, and neurodevelopment). GCE was associated with poorer outcomes on all measures of psychopathology but had negligible effect on cognitive measures. Higher FA values in both fiber tracts were associated with decreased neurodevelopmental problems and improved performance on both cognitive tasks. We also identified a decreased association between FA in the CST-LH and task efficiency in the GCE group. These findings suggest that GCE can lead to future neurodevelopmental complications and that this occurs, in part, through alteration of the microstructure of critical fiber tracts such as the IFOF-LH and CST-LH. These data suggest that current guidelines regarding limiting caffeine intake during pregnancy may require some recalibration.

The Main and Interactive Associations between Demographic Factors and Psychopathology and Treatment Utilization in Youth: A Test of Intersectionality in the ABCD Study

Demographic factors may be associated with youth psychopathology due to social-contextual factors that may also pose barriers to intervention. Further, in line with intersectionality theory, youth with multiple non-dominant identities may be most likely to experience psychopathology and face barriers to care. This study examined rates of parent-reported psychopathology and mental health treatment utilization as a function of several demographic characteristics (in isolation and in concert) in a population-based, demographically diverse sample of 11,875 9- to 10-year-old youth. Results indicated most consistently that lower SES was associated with greater rates of psychopathology and greater likelihood of treatment utilization; that Asian American youth (relative to all other racial groups) and Hispanic/Latinx (relative to non-Hispanic/Latinx) youth were less likely to have a history of psychopathology or to have utilized treatment; and that male youth had greater rates of lifetime Obsessive Compulsive Disorder (OCD) and Oppositional Defiant Disorder (ODD) and were more likely to have utilized treatment. There was more modest support for interactive effects between demographic factors on psychopathology, which are discussed. The present study provides some support for differential rates of parent-reported psychopathology and treatment utilization as a function of demographic identities in youth. Potential explanations for these differences (e.g., cultural differences in symptom presentation; underreporting of symptoms) are discussed.

Pubertal development mediates the association between family environment and brain structure and function in childhood

Psychosocial acceleration theory suggests that pubertal maturation is accelerated in response to adversity. In addition, suboptimal caregiving accelerates development of the amygdala-medial prefrontal cortex circuit. These findings may be related. Here, we assess whether associations between family environment and measures of the amygdala-medial prefrontal cortex circuit are mediated by pubertal development in more than 2000 9- and 10-year-old children from the Adolescent Brain Cognitive Development Study (http://dx.doi.org/10.15154/1412097). Using structural equation modeling, demographic, child-reported, and parent-reported data on family dynamics were compiled into a higher level family environment latent variable. Magnetic resonance imaging preprocessing and compilations were performed by the Adolescent Brain Cognitive Development Study's data analysis core. Anterior cingulate cortex (ACC) thickness, area, white matter fractional anisotropy, amygdala volume, and cingulo-opercular network-amygdala resting-state functional connectivity were assessed. For ACC cortical thickness and ACC fractional anisotropy, significant indirect effects indicated that a stressful family environment relates to more advanced pubertal stage and more mature brain structure. For cingulo-opercular network-amygdala functional connectivity, results indicated a trend in the expected direction. For ACC area, evidence for quadratic mediation by pubertal stage was found. Sex-stratified analyses suggest stronger results for girls. Despite small effect sizes, structural measures of circuits important for emotional behavior are associated with family environment and show initial evidence of accelerated pubertal development.

Parental and social factors in relation to child psychopathology, behavior, and cognitive function

Parental and social factors have long-term impact on the neurodevelopment of offspring, but tend to highly covary with each other. Thus, it is difficult to parse out which parental and social factor contributes most to neurodevelopmental outcomes. This study aimed to assess clusters of parental and social factors associated with child psychopathology, behavioral problems, and cognition. This study employed the data of 11,875 children (9 to 11 years) from the Adolescent Brain Cognitive Development (ABCD) study. Principal component analysis (PCA) was performed on 39 environmental measures and 30 child behavior and cognitive measures separately to identify clusters of parental and social factors and clusters of child psychopathology, behaviour, and cognition. Regression analysis was used to examine independent effects of each cluster of parental and social factors on child psychopathology, behavioral problems, and cognition. Greater Parent Psychopathology cluster was associated with greater Child Psychopathology cluster. Moreover, greater Socioeconomic Status cluster was associated with greater child General Cognition and Executive Function but less Behavioral Inhibition clusters. Greater Proximal Social Environment and Interaction cluster were associated with less child Impulsive Behavior and Behavioral Inhibition, but greater Behavioral Activation cluster. The environmental clusters related to birth outcomes, maternal tobacco, and drug use were not significantly related to child psychopathology, behavior, and cognition. Our findings suggest that socioeconomic status, parental psychopathology, and social environment and interactions are the strongest risks for behavioral problems and cognitive performance in a general child population. Intervention programs should target modifiable factors within these domains.

Pubertal development mediates the association between family environment and brain structure and function in childhood

Psychosocial acceleration theory suggests that pubertal maturation is accelerated in response to adversity. In addition, suboptimal caregiving accelerates development of the amygdala-medial prefrontal cortex circuit. These findings may be related. Here, we assess whether associations between family environment and measures of the amygdala-medial prefrontal cortex circuit are mediated by pubertal development in more than 2000 9- and 10-year-old children from the Adolescent Brain Cognitive Development Study (http://dx.doi.org/10.15154/1412097). Using structural equation modeling, demographic, child-reported, and parent-reported data on family dynamics were compiled into a higher level family environment latent variable. Magnetic resonance imaging preprocessing and compilations were performed by the Adolescent Brain Cognitive Development Study's data analysis core. Anterior cingulate cortex (ACC) thickness, area, white matter fractional anisotropy, amygdala volume, and cingulo-opercular network-amygdala resting-state functional connectivity were assessed. For ACC cortical thickness and ACC fractional anisotropy, significant indirect effects indicated that a stressful family environment relates to more advanced pubertal stage and more mature brain structure. For cingulo-opercular network-amygdala functional connectivity, results indicated a trend in the expected direction. For ACC area, evidence for quadratic mediation by pubertal stage was found. Sex-stratified analyses suggest stronger results for girls. Despite small effect sizes, structural measures of circuits important for emotional behavior are associated with family environment and show initial evidence of accelerated pubertal development.

Analyzing Real-World Use of Research Common Data Elements

Common Data Elements (CDEs) are defined as "data elements that are common to multiple data sets across different studies" and provide structured, standardized definitions so that data may be collected and used across different datasets. CDE collections are traditionally developed prospectively by subject-matter and domain experts. However, there has been little systematic research and evidence to demonstrate how CDEs are used in real-world datasets and the subsequent impact on data discoverability. Our study builds upon previous mapping work to investigate the number of CDEs that could be identified using a varying level of commonness threshold in a real-world data repository, the Database of Phenotypes and Genotypes (dbGaP). In an analyzed collection of mapped variables from 426 dbGaP studies, only 1,414 PhenX variables (PHENotypes and eXposures; a CDE initiative) are observed out of all 24,938 defined PhenX variables. Results include CDEs that are identified with varying levels of commonness thresholds. After the semantic grouping of 68 PhenX variables collected in at least 15 studies (n=15), we observed 32 truly "common" common data elements. We discuss benefits of post-hoc mapping of study data to a CDE framework for purposes of findability and reuse, as well as the informatics challenges of pre-populating clinical research case report forms with data from Electronic Health Record that are typically coded in terminologies aimed at routine healthcare needs.

Heterogeneous network embedding for identifying symptom candidate genes

Objective

Investigating the molecular mechanisms of symptoms is a vital task in precision medicine to refine disease taxonomy and improve the personalized management of chronic diseases. Although there are abundant experimental studies and computational efforts to obtain the candidate genes of diseases, the identification of symptom genes is rarely addressed. We curated a high-quality benchmark dataset of symptom-gene associations and proposed a heterogeneous network embedding for identifying symptom genes.

Methods

We proposed a heterogeneous network embedding representation algorithm, which constructed a heterogeneous symptom-related network that integrated symptom-related associations and applied an embedding representation algorithm to obtain the low-dimensional vector representation of nodes. By measuring the relevance between symptoms and genes via calculating the similarities of their vectors, the candidate genes of given symptoms can be obtained.

Results

A benchmark dataset of 18 270 symptom-gene associations between 505 symptoms and 4549 genes was curated. We compared our method to baseline algorithms (FSGER and PRINCE). The experimental results indicated our algorithm achieved a significant improvement over the state-of-the-art method, with precision and recall improved by 66.80% (0.844 vs 0.506) and 53.96% (0.311 vs 0.202), respectively, for TOP@3 and association precision improved by 37.71% (0.723 vs 0.525) over the PRINCE.

Conclusions

The experimental validation of the algorithms and the literature validation of typical symptoms indicated our method achieved excellent performance. Hence, we curated a prediction dataset of 17 479 symptom-candidate genes. The benchmark and prediction datasets have the potential to promote investigations of the molecular mechanisms of symptoms and provide candidate genes for validation in experimental settings.

Associations between 24 hour movement behaviours and global cognition in US children: a cross-sectional observational study

BACKGROUND

Childhood and adolescence are crucial periods for brain development, and the behaviours during a typical 24 h period contribute to cognitive performance. The Canadian 24-Hour Movement Guidelines for Children and Youth recommend at least 60 min physical activity per day, 2 h or less recreational screen time per day, and 9-11 h sleep per night in children aged 8-11 years. We investigated the relationship between adherence to these recommendations and global cognition.

METHODS

In this cross-sectional observational study, we obtained data from the first annual curated release of the Adolescent Brain Cognitive Development study, a 10-year longitudinal, observational study. Data were collected from 21 study sites across the USA between Sept 1, 2016, and Sept 15, 2017. The participants were 4524 US children aged 8-11 years from 20 study sites. Exposures of interest were adherence to the physical activity, recreational screen time, and sleep duration guideline recommendations. The primary outcome was global cognition, assessed with the NIH Toolbox (National Institutes of Health, Bethesda, MD, USA), which we analysed with multivariable linear mixed-effects models to examine the relations with movement behaviour variables.

FINDINGS

Complete movement behaviour data were available for 4520 participants. The mean number of guideline recommendations met was 1·1 (SD 0·9). Overall, 2303 (51%) participants met the sleep recommendation, 1655 (37%) met screen time, and 793 (18%) met the physical activity recommendation. 3190 (71%) participants met at least one recommendation, whereas 216 (5%) of participants met all three recommendations. Global cognition was positively associated with each additional recommendation met (β=1·44, 95% CI 0·82-2·07, p<0·0001). Compared with meeting none of the recommendations, associations with superior global cognition were found in participants who met all three recommendations (β=3·89, 95% CI 1·43 to 6·34, p=0·0019), the screen time recommendation only (β=4·25, 2·50-6·01, p<0·0001), and both the screen time and the sleep recommendations (β=5·15, 3·56-6·74, p<0·0001).

INTERPRETATION

Meeting the 24 h movement recommendations was associated with superior global cognition. These findings highlight the importance of limiting recreational screen time and encouraging healthy sleep to improve cognition in children.

FUNDING

National Institutes of Health.

Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description

The Adolescent Brain and Cognitive Development (ABCD) Study incorporates a comprehensive range of measures assessing predictors and outcomes related to both mental and physical health across childhood and adolescence. The workgroup developed a battery that would assess a comprehensive range of domains that address study aims while minimizing participant and family burden. We review the major considerations that went into deciding what constructs to cover in the demographics, physical health and mental health domains, as well as the process of selecting measures, piloting and refining the originally proposed battery. We present a description of the baseline battery, as well as the six-month interim assessments and the one-year follow-up assessments. This battery includes assessments from the perspectives of both the parent and the target youth, as well as teacher reports. This battery will provide a foundational baseline assessment of the youth's current function so as to permit characterization of stability and change in key domains over time. The findings from this battery will also be utilized to identify both resilience markers that predict healthy development and risk factors for later adverse outcomes in physical health, mental health, and substance use and abuse.

From Data to Action: Neuroepidemiology Informs Implementation Research for Global Stroke Prevention and Treatment

As a scientific field of study, neuroepidemiology encompasses more than just the descriptive study of the frequency, distribution, determinants and outcomes of neurologic diseases in populations. It also includes experimental aspects that span the full spectrum of clinical and population science research. As such, neuroepidemiology has a strong potential to inform implementation research for global stroke prevention and treatment. This review begins with an overview of the progress that has been made in descriptive and experimental neuroepidemiology over the past quarter century with emphasis on standards for evidence generation, critical appraisal of that evidence and impact on clinical and public health practice at the national, regional and global levels. Specific advances made in high-income countries as well as in low- and middle-income countries are presented. Gaps in implementation as well as evidence gaps in stroke research, stroke burden, clinical outcomes and disparities between developed and developing countries are then described. The continuing need for high quality neuroepidemiologic data in low- and middle-income countries is highlighted. Additionally, persisting disparities in stroke burden and care by sex, race, ethnicity, income and socioeconomic status are discussed. The crucial role that national stroke registries have played in neuroepidemiologic research is also addressed. Opportunities presented by new directions in comparative effectiveness and implementation research are discussed as avenues for turning neuroepidemiological insights into action to maximize health impact and to guide further biomedical research on neurological diseases.

Neuroinformatics Software Applications Supporting Electronic Data Capture, Management, and Sharing for the Neuroimaging Community

Accelerating insight into the relation between brain and behavior entails conducting small and large-scale research endeavors that lead to reproducible results. Consensus is emerging between funding agencies, publishers, and the research community that data sharing is a fundamental requirement to ensure all such endeavors foster data reuse and fuel reproducible discoveries. Funding agency and publisher mandates to share data are bolstered by a growing number of data sharing efforts that demonstrate how information technologies can enable meaningful data reuse. Neuroinformatics evaluates scientific needs and develops solutions to facilitate the use of data across the cognitive and neurosciences. For example, electronic data capture and management tools designed to facilitate human neurocognitive research can decrease the setup time of studies, improve quality control, and streamline the process of harmonizing, curating, and sharing data across data repositories. In this article we outline the advantages and disadvantages of adopting software applications that support these features by reviewing the tools available and then presenting two contrasting neuroimaging study scenarios in the context of conducting a cross-sectional and a multisite longitudinal study.

The detection and characterization of pleiotropy: discovery, progress, and promise

The impact of a single genetic locus on multiple phenotypes, or pleiotropy, is an important area of research. Biological systems are dynamic complex networks, and these networks exist within and between cells. In humans, the consideration of multiple phenotypes such as physiological traits, clinical outcomes and drug response, in the context of genetic variation, can provide ways of developing a more complete understanding of the complex relationships between genetic architecture and how biological systems function in health and disease. In this article, we describe recent studies exploring the relationships between genetic loci and more than one phenotype. We also cover methodological developments incorporating pleiotropy applied to model organisms as well as humans, and discuss how stepping beyond the analysis of a single phenotype leads to a deeper understanding of complex genetic architecture.

Using the PhenX Toolkit to Add Standard Measures to a Study

The PhenX (consensus measures for Phenotypes and eXposures) Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measures of phenotypes and exposures for use by the scientific community. The goal is to promote the use of standard measures, enhance data interoperability, and help investigators identify opportunities for collaborative and translational research. The Toolkit contains 395 measures drawn from 22 research domains (fields of research), along with additional collections of measures for Substance Abuse and Addiction (SAA) research, Mental Health Research (MHR), and Tobacco Regulatory Research (TRR). Additional measures for TRR that are expected to be released in 2015 include Obesity, Eating Disorders, and Sickle Cell Disease. Measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The Toolkit provides a description of each PhenX measure, the rationale for including it in the Toolkit, protocol(s) for collecting the measure, and supporting documentation. Users can browse measures in the Toolkit or can search the Toolkit using the Smart Query Tool or a full text search. PhenX Toolkit users select measures of interest to add to their Toolkit. Registered Toolkit users can save their Toolkit and return to it later to revise or complete. They then have options to download a customized Data Collection Worksheet that specifies the data to be collected, and a Data Dictionary that describes each variable included in the Data Collection Worksheet. The Toolkit also has a Register Your Study feature that facilitates cross-study collaboration by allowing users to find other investigators using the same PhenX measures.

Gene-environment interplay in common complex diseases: forging an integrative model—recommendations from an NIH workshop

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies.

Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries

OBJECTIVES

Classification of data elements (DEs), which is used in clinical documents is challenging, even in across ISO/IEC 11179 compliant clinical metadata registries (MDRs) due to no existence of reliable standard for identifying DEs. We suggest the Clinical Data Element Ontology (CDEO) for unified indexing and retrieval of DEs across MDRs.

METHODS

The CDEO was developed through harmonization of existing clinical document models and empirical analysis of MDRs. For specific classification as using data element concept (DEC), The Simple Knowledge Organization System was chosen to represent and organize the DECs. Six basic requirements also were set that the CDEO must meet, including indexing target to be a DEC, organizing DECs using their semantic relationships. For evaluation of the CDEO, three indexers mapped 400 DECs to more than 1 CDEO term in order to determine whether the CDEO produces a consistent index to a given DEC. The level of agreement among the indexers was determined by calculating the intraclass correlation coefficient (ICC).

RESULTS

We developed CDEO with 578 concepts. Through two application use-case scenarios, usability of the CDEO is evaluated and it fully met all of the considered requirements. The ICC among the three indexers was estimated to be 0.59 (95% confidence interval, 0.52-0.66).

CONCLUSIONS

The CDEO organizes DECs originating from different MDRs into a single unified conceptual structure. It enables highly selective search and retrieval of relevant DEs from multiple MDRs for clinical documentation and clinical research data aggregation.

Sharing behavioral data through a grid infrastructure using data standards

OBJECTIVE

In an effort to standardize behavioral measures and their data representation, the present study develops a methodology for incorporating measures found in the National Cancer Institute's (NCI) grid-enabled measures (GEM) portal, a repository for behavioral and social measures, into the cancer data standards registry and repository (caDSR).

METHODS

The methodology consists of four parts for curating GEM measures into the caDSR: (1) develop unified modeling language (UML) models for behavioral measures; (2) create common data elements (CDE) for UML components; (3) bind CDE with concepts from the NCI thesaurus; and (4) register CDE in the caDSR.

RESULTS

UML models have been developed for four GEM measures, which have been registered in the caDSR as CDE. New behavioral concepts related to these measures have been created and incorporated into the NCI thesaurus. Best practices for representing measures using UML models have been utilized in the practice (eg, caDSR). One dataset based on a GEM-curated measure is available for use by other systems and users connected to the grid.

CONCLUSIONS

Behavioral and population science data can be standardized by using and extending current standards. A new branch of CDE for behavioral science was developed for the caDSR. It expands the caDSR domain coverage beyond the clinical and biological areas. In addition, missing terms and concepts specific to the behavioral measures addressed in this paper were added to the NCI thesaurus. A methodology was developed and refined for curation of behavioral and population science data.

PhenDisco: phenotype discovery system for the database of genotypes and phenotypes

The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI's dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaP's search engine Entrez. The system can be accessed at http://pfindr.net.

Pragmatic measures: what they are and why we need them

Pragmatic measures are important to facilitate implementation and dissemination, address stakeholder issues, and drive quality improvement. This paper proposes necessary and recommended criteria for pragmatic measures, provides examples of projects to develop and identify such measures, addresses potential concerns about these recommendations, and identifies areas for future research and application. Key criteria for pragmatic measures include importance to stakeholders in addition to researchers, low burden, broad applicability, sensitivity to change, and being actionable. Examples of pragmatic measures are provided, including ones for different settings (e.g., primary care, hospital) and levels (e.g., individual, practitioner, setting) that illustrate approaches to produce broad-scale dissemination and the development of brief, standardized measures for use in pragmatic studies. There is an important need for pragmatic measures to facilitate pragmatic research, guide quality improvement, and inform progress on public health goals, but few examples are currently available. Development and evaluation of pragmatic measures and metrics would provide useful resources to advance science, policy, and practice.

Quantifying diet for nutrigenomic studies

The field of nutrigenomics shows tremendous promise for improved understanding of the effects of dietary intake on health. The knowledge that metabolic pathways may be altered in individuals with genetic variants in the presence of certain dietary exposures offers great potential for personalized nutrition advice. However, although considerable resources have gone into improving technology for measurement of the genome and biological systems, dietary intake assessment remains inadequate. Each of the methods currently used has limitations that may be exaggerated in the context of gene × nutrient interaction in large multiethnic studies. Because of the specificity of most gene × nutrient interactions, valid data are needed for nutrient intakes at the individual level. Most statistical adjustment efforts are designed to improve estimates of nutrient intake distributions in populations and are unlikely to solve this problem. An improved method of direct measurement of individual usual dietary intake that is unbiased across populations is urgently needed.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Harmonization and semantic annotation of data dictionaries from the Pharmacogenomics Research Network: a case study

The Pharmacogenomics Research Network (PGRN) is a collaborative partnership of research groups funded by NIH to discover and understand how genome contributes to an individual's response to medication. Since traditional biomedical research studies and clinical trials are often conducted independently, common and standardized representations for data are seldom used. This leads to heterogeneity in data representation, which hinders data reuse, data integration and meta-analyses. This study demonstrates harmonization and semantic annotation work for pharmacogenomics data dictionaries collected from PGRN research groups. A semi-automated system was developed to support the harmonization/annotation process, which includes four individual steps, (1) pre-processing PGRN variables; (2) decomposing and normalizing variable descriptions; (3) semantically annotating words and phrases using controlled terminologies; (4) grouping PGRN variables into categories based on the annotation results and semantic types, for total 1514 PGRN variables. Our results demonstrate that there is a significant amount of variability in how pharmacogenomics data is represented and that additional standardization efforts are needed. This represents a critical first step toward identifying and creating data standards for pharmacogenomics studies.