cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1528128
title: Relations between executive functioning and internalizing symptoms vary as a function of frontoparietal-amygdala resting state connectivity

description: The prefrontal cortex and the frontoparietal network are associated with a variety of regulatory behaviors. Functional connections between these brain regions and the amygdala are implicated in risk for anxiety disorders. The prefrontal cortex and frontoparietal network are also linked to executive functioning, or behaviors that help orient action towards higher order goals. Where much research has been focused on deleterious effects of under-controlled behavior, a body of work suggests that over-controlled behavior may also pose a risk for internalizing problems. Indeed, while work suggests that high levels of attention shifting may still be protective against internalizing problems, there is evidence that high levels of inhibitory control may be a risk factor for socioemotional difficulties. In the ABCD sample, which offers large sample sizes as well as sociodemographic diversity, we test the interaction between frontoparietal network-amygdala resting state functional connectivity and executive functioning behaviors on longitudinal changes in internalizing symptoms from approximately 10 to 12 years of age. We found that higher proficiency in attention shifting indeed predicts fewer internalizing behaviors over time. In addition, higher proficiency in inhibitory control predicts fewer internalizing symptoms over time, but only for children showing resting state connectivity moderately above the sample average between the frontoparietal network and amygdala. This finding supports the idea that top-down control may not be adaptive for all children, and relations between executive functioning and anxiety risk may vary as a function of trait-level regulation.
DOI: 10.15154/1528131
title: Head, neck, and traumatic brain injury among children involved in sports: Results from the Adolescent Brain Cognitive Development study

description: Purpose
The purpose of this study was to assess the prevalence of head and neck injury (HNI) requiring hospitalization or emergency care and traumatic brain injury with loss of consciousness (TBI-LOC) among youth athletes and non-athletes (ages 9/10) using the baseline cohort of the Adolescent Brain Cognitive Development (ABCD) study.

Methods
Analysis of national data from the baseline cohort of the ABCD study (2016–2018; n=11,869).

Results
The analysis found that 12.1% of the sample indicated HNI during their lifetime, while .8% indicated TBI-LOC. Participation in multiple sports (aPRR=1.29, 95% CI=1.06,1.55), contact sports (aPRR=1.19, 95% CI=1.05,1.34), and who had participated in sport for 5 or more years (aPRR=1.42, 95% CI =1.16,1.73) had modestly higher prevalence rate ratios of reporting HNI compared to nonparticipants. Sport participation was not found to be associated with TBI-LOC.

Conclusions
The study provides needed epidemiological information on the prevalence of HNI and TBI-LOC among younger adolescents who participate in sports. While the risk of TBI-LOC appears to be low among youth athletes and non-athletes, the risk of more serious head injuries may increase due length of participation in sport and involvement in high contact sports.
DOI: 10.15154/1528132
title: Gender Differences in Adolescents’ Affective Symptoms and Behavioral Disorders after mTBI

description: Objective: Mild traumatic brain injuries (mTBI) are considered self-limiting and full recovery is expected. Recent studies identify deficits persisting years after mTBI. Large-scale prospective data permit testing the hypothesis that mTBI increases incidence of affective and behavioral symptoms after new, past, or new and past mTBI. 
Setting: The study involved secondary analyses of survey responses from the Adolescent Brain Cognitive Development (ABCD) Study. 
Participants: Adolescents in the ABCD Study (n=11,869; Wave 1, ages 9-10; Wave 2, ages 11-12) whose parents reported a new (n=157), past (n=1,318) or new and past (n=50) mTBI on the Ohio State University Injury Identification Method short form were compared to controls who had no history of mTBI (n=9,667).
Design: Multivariable binary logistic regression models examined associations between a new, past, or new and past mTBI, current affective (aggression, depression, anxiety) and behavioral (somatic, thought, social, attention, ADHD, conduct) disorders while controlling for demographic factors and baseline symptoms.
Main Measures: The primary measure was parental reports of psychiatric and behavioral symptoms on the Child Behavior Checklist (CBCL).
Results: Girls exhibited no significant effects after a new mTBI, although a past mTBI increased anxiety (aOR=1.83, 95% CI [1.15, 2.90]) and attention (1.89, [1.09, 3.28]) problems. Girls with new and past mTBIs reported elevated anxiety (17.90, [4.67, 68.7]), aggression (7.37, [1.49, 36.3]), social (9.07, [2.47, 33.30]), thought (7.58, [2.24, 25.60]) and conduct (6.39, [1.25, 32.50]) disorders. In boys, new mTBI increased aggression (aOR=3.83, 95% CI [1.42, 10.30]), whereas past mTBI heightened anxiety (1.91, 1.42, 2.95]), but new and past mTBIs had no significant effects. 
Conclusion: Adolescents are at greater risk of affective and behavioral symptoms after an mTBI. These effects differ as a function of gender and time of injury. Extended screening for mTBI history and monitoring of affective and behavioral disorders after mTBI in adolescents is warranted.
DOI: 10.15154/1528137
title: Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints

description: Precision medicine and the investigation of brain-behavior associations require biomarkers that are stable (low intraindividual variability) and unique (high interindividual variability) at the same time, hence calling them "fingerprints". The functional connectome (FC) has good "fingerprint properties", as individuals can be accurately identified in a database based on their FC. Importantly, research has shown lower intraindividual variability of more localized measures of brain function such as regional homogeneity (ReHo) and (fractional) amplitude of low-frequency fluctuations ((f)ALFF), compared to the FC. Here, with fMRI data from two publicly available datasets we demonstrate that individuals can be identified with near-perfect accuracies using local functional fingerprints, and especially the regional homogeneity (ReHo) fingerprint. Further analyses reveal that the dorsal attention network contributes most to the individual "uniqueness" of the ReHo fingerprint. Moreover, using a machine-learning setup, we show that the small intraindividual ReHo fingerprint variability across sessions is meaningful for explaining individual-level intelligence. Last, using two other publicly available datasets, clinical applicability is shown with high fingerprint accuracies and a significant correlation between fingerprint stability and intelligence in individuals with schizophrenia. Altogether, our findings suggest that the ReHo fingerprint is a good candidate for further exploration of applicability in precision medicine.
DOI: 10.15154/1528145
title: Characterizing sleep in youth: Evidence from the ABCD Study

description: Background: Previous research has shown that sleep disturbance and shorter sleep length are associated with a greater risk for mental disorders and other poor health outcomes in adolescents. Shorter sleep duration may be a predictor of anxiety disorders in youth and sleep disturbances have been found to be highly prevalent among children with mood, anxiety, substance use, and other behavior disorders. Because of the established relationship between sleep problems and poor mental and physical health outcomes, it is important to understand what factors contribute to poor sleep in youth.

Method: Participants were a part of the ABCD Study, a large-scale longitudinal study in the United States that follows children ages 9-11 over 10 years (n = 9,279). The study aims to examine developmental changes across multiple domains, including brain structure and function, cognition, behavior, and mental health in children and caregivers. To best estimate the longitudinal predictors of poor sleep, 82 distinct variables were used in ML analyses. The present study used the “wisdom of crowds” approach, combining predictions from various base learners (prediction algorithms) by meta ensemble. To train the stacked ensemble model, repeated nested cross-validation (rNCV) was used; the inner loop trained the base learners and the stacked model, while the outer loop was used to assess model performance and variable importance (VI). Three base learners were applied in the inner loop for each training set: elastic net, support vector regression (SVR), and conditional inference forest (CIF). After identifying the variables of highest importance using the ML model, follow-up analyses were conducted using linear mixed effects models variables of interest.

Results: Using ML, we identify a model with 82 variables that explains 18.71% of variance in sleep length, 66.86% of variance in sleep delay, and 35.05% of variance in sleep disturbances. The five most important variables as identified by ML for predicting sleep length, delay, and disturbance are as follows: Sleep length: race, Native American community contact, household income under $50,000, family history of mental illness, and weekday screen time; Sleep delay: child internalizing and externalizing symptoms, child symptoms of mania, parent internalizing symptoms, and parent age; Sleep disturbance: child internalizing and externalizing symptoms, child symptoms of mania, and parent internalizing and externalizing symptoms. 

Conclusion: These results confirm prior research indicating that youth with existing internalizing and externalizing symptoms and socioeconomic deprivation are at greatest risk for poor sleep health and further emphasize the demand for more research devoted to identifying protective factors for these populations.
DOI: 10.15154/1528147
title: Clonally selected lines after CRISPR/Cas editing are not isogenic

description: The CRISPR-Cas9 system has enabled researchers to precisely modify/edit the sequence of a genome. A typical editing experiment consists of two steps: (i) editing cultured cells; (ii) cell cloning and selection of clones with and without intended edit, presumed to be isogenic. The application of CRISPR-Cas9 system may result in off-target edits, while cloning will reveal culture-acquired mutations. We analyzed the extent of the former and the latter by whole genome sequencing in three experiments involving separate genomic loci and conducted by three independent laboratories. In all experiments we hardly found any off-target edits, while detecting hundreds to thousands of single nucleotide mutations unique to each clone after relatively short culture of 10-20 passages. Notably, clones also differed in copy number alterations that were several kb to several mb in size and represented the largest source of genomic divergence among clones. We suggest that screening of clones for mutations and copy number alterations acquired in culture is a necessary step to allow correct interpretation of DNA editing experiments. Furthermore, since culture associated mutations are inevitable, we propose that experiments involving derivation of clonal lines should compare a mix of multiple unedited lines and a mix of multiple edited lines.
DOI: 10.15154/1528193
title: ENIGMA plasticity GWAS

description: Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
DOI: 10.15154/1528197
title: Harmonization Benchmarking Tool for Neuroimaging Datasets

description: An open source tool was developed to streamline the evaluation and comparison of various harmonization techniques. To demonstrate the effectiveness of the tool, it was applied to co-registered fractional anisotropy images derived from ABCD Study diffusion MRI data. The extent of site effects was measured on a sample of the ABCD data before and after applying ComBat harmonization, and before and after applying a simpler harmonization technique.
DOI: 10.15154/1528283
title: COMT Val/Met, Stressful Life Events and Externalizing Behaviors in Youth: A Longitudinal Study from the Adolescent Brain Cognitive Development Sample

description: Early adolescence is a crucial time for understanding and detecting the risk factors that may influence youth externalizing/disruptive behaviors and disorders. Previous literature reported evidence that risk factors for disruptive behaviors include COMT Val158Met polymorphism and environmental influences. An unanswered question is whether there is a change in these risk factors over stages of youth development. This longitudinal study examines the interaction effect of Val158Met and stressful life events (SLE) on youth externalizing behaviors from ages 9-11. Participants were 2363 children of European ancestry recruited as part of the Adolescent Brain Cognitive Development study. Repeated measures linear mixed models were used to examine the effect of the interaction between Val158Met and SLE on disruptive behaviors over development. Externalizing behaviors were analyzed at both baseline and two-year follow-up. Both Val158Met genotype and SLE scores demonstrated significant main effects on disruptive behaviors in youth, and those effects were consistent at both time points. GxE did not statistically influence externalizing behaviors. Youth who carried the Val allele and/or were exposed to higher SLE had increased externalizing behavior scores. To our knowledge, this is the first study to longitudinally examine the interaction effects of Val158Met and SLE on externalizing behaviors in youth. The results highlight the importance of understanding the genetic and environmental factors underlying externalizing behaviors, and may lead to novel treatments and preventive strategies. Future studies should examine our hypothesis over a longer time period to further examine the effects of development, when data on new ABCD assessment time points become available.
DOI: 10.15154/1528288
title: Differences in the functional brain architecture of sustained attention and working memory in youth and adults

description: Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9–11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children—and captured individual differences in later recognition memory—but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed two network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.
DOI: 10.15154/1528296
title: Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents

description: Background
Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based ‘Regional Vulnerability Index’ (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1).

Methods
MDD-RVIs quantify the correlation of the individual’s corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed.

Results
In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099–0.281, PFDR = 0.001–0.043) than MDD-PRS (β = 0.056–0.152, PFDR = 0.140–0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084–0.086, p = 1.38 × 10−4−4.77 × 10−4) but not with any MDD-RVIs (β < 0.05, p > 0.05).

Conclusions
Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.
DOI: 10.15154/1528300
title: A morphometrics approach for inclusion of localised characteristics from medical imaging studies into genome-wide association studies

description: 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.
DOI: 10.15154/1528313
title: Prenatal development has stable and consistent effects on the human brain throughout the lifespan

description: 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, within 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 indicated the effects were partly environmental. 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.