cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1528724
title: The Prospective Relationship between Weight-Based Discrimination and Eating  Pathology among Youth

description: Among adults and adolescents, weight-based discrimination is associated with disordered eating. However, these relationships remain understudied in children. Given that weight-based discrimination is commonly reported among youth, and that
childhood is a crucial developmental period for the onset of disordered eating, the current study assessed prospective associations between weight-based discrimination and eating pathology among participants in the Adolescent Brain Cognitive Development Study. At the one-year visit, children indicated whether they had experienced discrimination due to their weight within the past year. Parents completed a computerized clinical interview to determine the presence of sub-or-full threshold eating disorders (AN, BN, and BED) among their children. At the two-year visit, youths completed the same assessment. Height and fasting weight were obtained. Logistic regressions, adjusting for age, sex, race/ethnicity, family income, BMI%ile, and parent-reported presence of the respective eating disorder at one-year, were conducted to assess the associations between weight-based discrimination and eating pathology. Participants were 10,299 youths who completed measures at both the one- and two-year visits (Mage at one-year: 10.92 ± 0.64, 47.6% female, 45.9% racial/ethnic minority). The presence of weight-based discrimination, reported by 5.6% (n = 574) of youths, was significantly associated with a greater likelihood of reporting AN, BN, and BED one-year later (ORs: 1.94 – 4.91). Findings suggest that weight-based discrimination may confer additional risk for the onset of disordered eating, beyond the contribution of body weight. Intersectional research is needed to examine the role of multiple forms of discrimination in relation to the development of eating pathology.
DOI: 10.15154/1528725
title: E-cigarette and combustible tobacco use among children with asthma and their peers in the  ABCD study

description: Children with asthma are more likely to use e-cigarettes and combustible tobacco and may hold more positive smoking expectancies than their peers. Study aims were to i) compare rates of e- cigarette and combustible tobacco use; ii) compare smoking expectancies and other risk factors between children with and without asthma; and iii) examine the association of asthma status and other risk factors with subsequent use. The sample consisted of 6,251 children from ABCD’s 4.0
release; M age = 12.90 years; 52.73% male, 58.25% White. 1.10% of children with asthma had used e-cigarettes or combustible tobacco compared to 1.81% of children without asthma. We found no significant association between smoking expectancies, other risk factors, and asthma status. We found an association of peer use and sensation seeking with use at 2- or 3-year follow-
up. Findings contribute to a better understanding of child asthma, e-cigarette and combustible tobacco use, and smoking expectancies.
DOI: 10.15154/1528746
title: Electroencephalographic Network Topologies Predict Antidepressant Responses in Patients With Major Depressive Disorder.

description: Medication therapy seems to be an effective treatment for major depressive disorder (MDD). However, although the efficacies of various medicines are equal or similar on average, they vary widely among individuals. Therefore, an understanding of methods for the timely evaluation of short-term therapeutic response and prediction of symptom improvement after a specific course of medication at the individual level at the initial stage of treatment is very important. In our present study, we sought to identify a neurobiological signature of the response to short-term antidepressant treatment. Related brain network analysis was applied in resting-state electroencephalogram (EEG) datasets from patients with MDD. The corresponding EEG networks were constructed accordingly and then quantitatively measured to predict the efficacy after eight weeks of medication, as well as to distinguish the therapeutic responders from non-responders. The results of our present study revealed that the corresponding resting-state EEG networks became significantly weaker after one week of treatment, and the eventual medication efficacy was reliably predicted using the changes in those network properties within the one-week medication regimen. Moreover, the corresponding resting-state networks at baseline were also proven to precisely distinguish those responders from other individuals with an accuracy of 96.67% when using the spatial network topologies as the discriminative features. These findings consistently provide a deeper neurobiological understanding of antidepressant treatment and a reliable and quantitative approach for personalized treatment of MDD.
DOI: 10.15154/1528747
title: Pathways link environmental and genetic factors with structural brain networks and psychopathology in youth

description: 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.
DOI: 10.15154/1528748
title: Interindividual Variability in Functional Connectivity Discovers Differential Development of Cognition and Transdiagnostic Dimensions of Psychopathology 

description: Cognitive and psychological development during adolescence is different from one another, which is rooted in individual differences in maturational changes in the adolescent brain. This study employed multi-modal MRI data and characterized interindividual variability in functional connectivity (IVFC) and its associations with cognition and psychopathology using the Philadelphia Neurodevelopmental Cohort (PNC) of 755 youth. We employed resting state functional MRI (rs-fMRI) and diffusion weighted images (DWIs) to estimate brain structural and functional networks. We computed the IVFC of individuals and examined its relation with structural and functional organizations. We further employed sparse partial least squares (sparse-PLS) and meta-analysis to examine the developmental associations of the IVFC with cognition and transdiagnostic dimensions of psychopathology in early, middle, and late adolescence. Our results revealed that the IVFC spatial topography reflects the brain functional integration and structure-function decoupling. Age effects on the IVFC of association networks were mediated by the FC among the triple networks, including frontoparietal, salience, and default mode networks (DMN), while those of primary and cerebellar networks were mediated by the cerebello-cortical FC. The IVFC of the triple and cerebellar networks explained the variance of executive functions and externalizing behaviors in early adolescence and then the variance of emotion and internalizing and psychosis in middle and late adolescence. We further evaluated this finding via meta-analysis on task-based studies on cognition and psychopathology. These findings implicate the emerging importance of the IVFC of the triple and cerebellar networks in cognitive, emotional, and psychopathological development during adolescence.
DOI: 10.15154/1528751
title: 16p11.2 deletion is associated with hyperactivation of human iPSC-derived dopaminergic neuron networks and is rescued by RHOA inhibition in vitro.

description: Reciprocal copy number variations (CNVs) of 16p11.2 are associated with a wide spectrum of neuropsychiatric and neurodevelopmental disorders. Here, we use human induced pluripotent stem cells (iPSCs)-derived dopaminergic (DA) neurons carrying CNVs of 16p11.2 duplication (16pdup) and 16p11.2 deletion (16pdel), engineered using CRISPR-Cas9. We show that 16pdel iPSC-derived DA neurons have increased soma size and synaptic marker expression compared to isogenic control lines, while 16pdup iPSC-derived DA neurons show deficits in neuronal differentiation and reduced synaptic marker expression. The 16pdel iPSC-derived DA neurons have impaired neurophysiological properties. The 16pdel iPSC-derived DA neuronal networks are hyperactive and have increased bursting in culture compared to controls. We also show that the expression of RHOA is increased in the 16pdel iPSC-derived DA neurons and that treatment with a specific RHOA-inhibitor, Rhosin, rescues the network activity of the 16pdel iPSC-derived DA neurons. Our data suggest that 16p11.2 deletion-associated iPSC-derived DA neuron hyperactivation can be rescued by RHOA inhibition.
DOI: 10.15154/1528762
title: Relationship Between Prediction Accuracy and Feature Importance Reliability: an Empirical and Theoretical Study 

description: There is significant interest in using neuroimaging data to predict behavior. The predictive models are often interpreted by the computation of feature importance, which quantifies the predictive relevance of an imaging feature. Tian and Zalesky (2021) suggest that feature importance estimates exhibit low split-half reliability, as well as a trade-off between prediction accuracy and feature importance reliability across parcellation resolutions. However, it is unclear whether the trade-off between prediction accuracy and feature importance reliability is universal. Here, we demonstrate that, with a sufficient sample size, feature importance (operationalized as Haufe-transformed weights) can achieve fair to excellent split-half reliability. With a sample size of 2600 participants, Haufe-transformed weights achieve average intra-class correlation coefficients of 0.75, 0.57 and 0.53 for cognitive, personality and mental health measures respectively. Haufe-transformed weights are much more reliable than original regression weights and univariate FC-behavior correlations. Original regression weights are not reliable even with 2600 participants. Intriguingly, feature importance reliability is strongly positively correlated with prediction accuracy across phenotypes. Within a particular behavioral domain, there is no clear relationship between prediction performance and feature importance reliability across regression models. Furthermore, we show mathematically that feature importance reliability is necessary, but not sufficient, for low feature importance error. In the case of linear models, lower feature importance error is mathematically related to lower prediction error. Therefore, higher feature importance reliability might yield lower feature importance error and higher prediction accuracy. Finally, we discuss how our theoretical results relate with the reliability of imaging features and behavioral measures. Overall, the current study provides empirical and theoretical insights into the relationship between prediction accuracy and feature importance reliability.
DOI: 10.15154/1528765
title: Does Anxiety Mediate the Relationship between Sensory Hyperresponsiveness and Restricted, Repetitive Behaviors during Early Development?

description: Sensory hyperresponsiveness, anxiety, and restricted, repetitive behaviors are known to be associated with one another, especially in autistic youth, and may be important to the development and presentation of autism over time. Few studies, however, have studied the nature of this three-way relationship prospectively, or in young children at elevated likelihood for autism. The goals of the current study were to gain greater insight into the development of autism from a symptom level before a diagnosis can be made, and specifically, to examine the relationship between sensory hyperresponsiveness, anxiety, and restricted, repetitive behaviors across time during early development in children at elevated likelihood for autism. Extant longitudinal data for a group of children at elevated likelihood for autism (N = 147) were used to conduct path analyses for two mediation model configurations, which included measures of sensory hyperresponsiveness at baseline, and anxiety and restricted and repetitive behaviors at follow-up. Results did not indicate mediating effects for either model; however, higher levels of sensory hyperresponsiveness at baseline were significantly associated with higher levels of anxiety symptoms at follow-up (b = 0.09, SE = 0.04, β = 0.24, p = 0.005, 95% CIs [0.07, 0.40]). Findings suggest that sensory hyperresponsiveness during early development later predicts anxiety symptoms in children at elevated likelihood for autism, which is consistent with prior findings in both autistic (Green et al., 2012) and non-autistic children (Carpenter et al., 2019). Although we are unable to determine whether this is a unidirectional or bidirectional relationship in the current study given the lack of concurrent data on anxiety symptoms at baseline, this result adds to emerging research suggesting that sensory hyperresponsiveness may be a risk factor for later developing anxiety.
DOI: 10.15154/1528767
title: Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p.

description: The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism's common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.
DOI: 10.15154/1528768
title: Tissue- and cell-type-specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models.

description: Chromosome 16p11.2 reciprocal genomic disorder, resulting from recurrent copy-number variants (CNVs), involves intellectual disability, autism spectrum disorder (ASD), and schizophrenia, but the responsible mechanisms are not known. To systemically dissect molecular effects, we performed transcriptome profiling of 350 libraries from six tissues (cortex, cerebellum, striatum, liver, brown fat, and white fat) in mouse models harboring CNVs of the syntenic 7qF3 region, as well as cellular, transcriptional, and single-cell analyses in 54 isogenic neural stem cell, induced neuron, and cerebral organoid models of CRISPR-engineered 16p11.2 CNVs. Transcriptome-wide differentially expressed genes were largely tissue-, cell-type-, and dosage-specific, although more effects were shared between deletion and duplication and across tissue than expected by chance. The broadest effects were observed in the cerebellum (2,163 differentially expressed genes), and the greatest enrichments were associated with synaptic pathways in mouse cerebellum and human induced neurons. Pathway and co-expression analyses identified energy and RNA metabolism as shared processes and enrichment for ASD-associated, loss-of-function constraint, and fragile X messenger ribonucleoprotein target gene sets. Intriguingly, reciprocal 16p11.2 dosage changes resulted in consistent decrements in neurite and electrophysiological features, and single-cell profiling of organoids showed reciprocal alterations to the proportions of excitatory and inhibitory GABAergic neurons. Changes both in neuronal ratios and in gene expression in our organoid analyses point most directly to calretinin GABAergic inhibitory neurons and the excitatory/inhibitory balance as targets of disruption that might contribute to changes in neurodevelopmental and cognitive function in 16p11.2 carriers. Collectively, our data indicate the genomic disorder involves disruption of multiple contributing biological processes and that this disruption has relative impacts that are context specific.
DOI: 10.15154/1528776
title: Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder.

description: Cerebral organoids can be used to gain insights into cell type specific processes perturbed by genetic variants associated with neuropsychiatric disorders. However, robust and scalable phenotyping of organoids remains challenging. Here, we perform RNA sequencing on 71 samples comprising 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to integrate bulk RNA and single-cell RNA sequence data. We apply Orgo-Seq to 16p11.2 deletions and 15q11-13 duplications, two loci associated with autism spectrum disorder, to identify immature neurons and intermediate progenitor cells as critical cell types for 16p11.2 deletions. We further applied Orgo-Seq to identify cell type-specific driver genes. Our work presents a quantitative phenotyping framework to integrate multi-transcriptomic datasets for the identification of cell types and cell type-specific co-expressed driver genes associated with neuropsychiatric disorders.
DOI: 10.15154/1528793
title: Changes in patterns of age-related network connectivity are associated with risk for schizophrenia

description: Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in unaffected siblings (SIB) and first-degree relatives (FHR) of SCZ patients with neurotypical controls (NC) at the same age-stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Some of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.09). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlate with genetic risk for SCZ and are detectable with MRI in young participants.
DOI: 10.15154/1528803
title: Association of Mental Health Burden With Prenatal Cannabis Exposure From Childhood to Early Adolescence: Longitudinal Findings From the Adolescent Brain Cognitive Development (ABCD) Study 

description: Dramatic increases in cannabis use during pregnancy are alarming because of evidence that prenatal exposure may be associated with a host of adverse outcomes.1 We previously found that prenatal cannabis exposure (PCE) following maternal knowledge of pregnancy is associated with increased psychopathology during middle childhood using baseline data from the Adolescent Brain Cognitive Development (ABCD) study.2 Here, leveraging longitudinal ABCD study data (data release 4.0), we examined whether associations with psychopathology persist into early adolescence.
DOI: 10.15154/1528808
title: Polygenic Effects on Individual Rule Breaking, Peer Rule Breaking, and Alcohol Sips across Early Adolescence in the ABCD Study

description: Genetic influences can underlie risky and delinquent behavior during adolescence as well as contribute to peer behavior via gene-environment correlations (rGE), which collectively increases risk for alcohol use. However, little research has examined this in early adolescence and even fewer studies exist in large diverse racial/ethnic populations. Data from the Adolescent Brain Cognitive Development (ABCD) study at age 11-12 (Mage=11.55; range 10-14) and age 12-13 (Mage=12.42; range 11-14) were used to examine a cross-time cross-lagged model in which polygenic scores for risky behavior were considered predictors of individual rule breaking, peer rule breaking, and alcohol sips. This was examined separately in European American (n=5113; 47% female), African American (n=1159; 50% female), and Hispanic (n=1624; 48% female) subgroups accounting for age, gender, site, income, and genetic principal components. In European Americans, polygenic scores were associated with individual and peer rule breaking at both ages. Individual and peer rule breaking were associated with one another within and across time. In African American and Hispanic subgroups, polygenic scores were associated with individual rule breaking at age 11-12. Individual and peer rule breaking were associated at age 11-12 in both subgroups and age 12-13 in the Hispanic subgroup. In all subgroups, peer rule breaking at 12-13 was associated with alcohol sips at 12-13. Results indicate that individual and peer rule breaking can influence one another within and across time with rGE likely implicated in European Americans. As a result, peer rule breaking can contribute to alcohol sips in early adolescence.