cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1528665
title: Classification of suicidal thoughts and behaviour in children: results from penalized logistic regression analyses in the Adolescent Brain Cognitive Development study

description: Background: Despite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained unsuccessful.
Aims: We apply a novel machine-learning approach and examine whether children with suicide thoughts or behaviours could be differentiated from children without suicide thoughts or behaviours based on a combination of traditional (sociodemographic, physical health, social-environmental, clinical psychiatric) risk factors, but also more novel risk factors (cognitive, neuroimaging and genetic characteristics).
Method: The study included 5885 unrelated children (50% female, 67% White, 9-11 years of age) from the Adolescent Brain Cognitive Development (ABCD) study. We performed penalised logistic regression analysis to distinguish between: (a) children with current or past suicide thoughts or behaviours; (b) children with a mental illness but no suicide thoughts or behaviours (clinical controls); and (c) healthy control children (no suicide thoughts or behaviours and no history of mental illness). The model was subsequently validated with data from seven independent sites involved in the ABCD study (n = 1712).
Results: Our results showed that we were able to distinguish the suicide thoughts or behaviours group from healthy controls (area under the receiver operating characteristics curve: 0.80 child-report, 0.81 for parent-report) and clinical controls (0.71 child-report and 0.76-0.77 parent-report). However, we could not distinguish children with suicidal ideation from those who attempted suicide (AUROC: 0.55-0.58 child-report; 0.49-0.53 parent-report). The factors that differentiated the suicide thoughts or behaviours group from the clinical control group included family conflict, prodromal psychosis symptoms, impulsivity, depression severity and history of mental health treatment.
Conclusions: This work highlights that mostly clinical psychiatric factors were able to distinguish children with suicide thoughts or behaviours from children without suicide thoughts or behaviours. Future research is needed to determine if these variables prospectively predict subsequent suicidal behaviour.
DOI: 10.15154/1528667
title: Associations Between Dimensions of Parent and Child Emotion Regulation: a Bayesian Gaussian Graphical Model

description: Background: Research on the association between parent (PER) and child emotion regulation (CER) have focused on overall emotion regulation (ER) as opposed to specific dimensions. Using a network analysis approach, the current study explores the cross-sectional and conditional [in]dependencies between dimensions of PER and CER.  
Method:  This study applied a Bayesian Gaussian Graphical model (BGGM) using data from the ABCD Study. The 36-item Difficulties with ER Scale (DERS) was used to assess PER and CER. 
Results: Between PER and CER, decisive evidence for positive associations were found between child lack of emotional clarity and parent limited access to emotion regulation strategies and between many dimensions of ER within PER and CER. 
Discussion: Findings illuminate potential for ER interventions that focus on helping children understand emotions and equipping parents with skills to regulate negative emotions. Future research efforts should focus on expanding these relations beyond cross-sectional data.
DOI: 10.15154/1528668
title: Perinatal SSRI Exposure Impacts Innate Fear Circuit Activation and Behavior in Mice and Humans

description: Serotonin shapes brain structure and function during early development across phylogenetically diverse species1–3. In mice and humans, perinatal SSRI exposure produces brain alterations and increases anxiety/depression-related behaviors in the offspring4–12. It remains unclear whether shared brain circuit changes underlie the behavioral impact of perinatal SSRIs across species. We examine how developmental SSRI-exposure in mice and humans changes fear-related brain activation and behavior. SSRI-administered mice showed increased defense responses to a predator odor that were associated with stronger fMRI-based fear circuit activation when compared to saline controls. Similarly, human adolescents exposed to SSRIs in utero showed greater activation of fear brain structures and exhibited higher anxiety and depressive symptoms than unexposed adolescents. Perinatal SSRI enhances innate fear-related responses and fear brain circuit activation that are conserved across species.
DOI: 10.15154/1528673
title: Perturbation of the treatment resistant depression connectome by fast-acting therapies (PDC) Release 1.0

description: The Perturbation of the treatment resistant depression connectome by fast-acting therapies study leveraged the optimized MRI technologies of the NIH-funded Human Connectome Project (HCP) to address how interventions with rapid and robust effects on mood and behavior modulate brain networks (or the connectome) in major depression. This study was part of the broader Connectomes Related to Human Diseases (CRHD) initiative subsumed under the parent HCP.  The data being shared include multimodal MRI data collected using image acquisition protocols identical to the Human Connectome Lifespan Project for Aging (HCP-A, U01AG052564), with the exception of one of the two fMRI tasks administered. Demographic and behavioral measures collected for this CRHD cohort also overlap with the HCP-A project, though the diagnostic and clinical assessments collected are unique to this project, which includes patients with major depressive disorder (MDD). However, some of these MDD-specific assessments are similar to those used for other CRHD projects focused on mood and anxiety disorders. The specific objectives of this CRHD project are to 1) identify connectome-specific correlates and predictors of treatment outcome to electroconvulsive therapy (ECT), serial ketamine treatment and experimental total sleep deprivation (TSD), which each have rapidly-acting antidepressant effects via neurostimulation, pharmacological or behavioral perturbation, and to 2) characterize alterations in neural connectivity associated with individual clinical, behavioral or physiological factors that distinguish patients with severe depression from non-depressed controls.
DOI: 10.15154/1528675
title: Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity

description: Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are generally referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels limits their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Further investigation suggests that homotopic parcels assigned to different large-scale networks exhibit lower homotopic correlations. Homotopic parcels with greater language and motor activation lateralization also exhibit weaker homotopic correlations. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the cerebral cortex and will be a useful dimensionality reduction tool for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).
DOI: 10.15154/1528685
title: Adolescent Neurodevelopment and Psychopathology: The Interplay between Adversity Exposure and Genetic Risk for Accelerated Brain Ageing

description: In adulthood, stress exposure and genetic risk heighten psychological vulnerability by accelerating neurobiological senescence. To investigate whether molecular and brain network maturation processes play a similar role in adolescence, we analysed genetic, as well as longitudinal task neuroimaging (inhibitory control, incentive processing) and early life adversity (i.e., material deprivation, violence) data from the Adolescent Brain and Cognitive Development study (N = 980, age range: 9-13 years). Genetic risk was estimated separately for Major Depressive Disorder (MDD) and Alzheimer’s Disease (AD), two pathologies linked to stress exposure and allegedly sharing a causal connection (MDD-to-AD). Adversity and genetic risk for MDD/AD jointly predicted functional network segregation patterns suggestive of accelerated (GABA-linked) visual/attentional, but delayed (dopamine [D2]/glutamate [GLU5R]-linked) somatomotor/association system development. A positive relationship between brain maturation and psychopathology emerged only among the less vulnerable adolescents, thereby implying that normatively maladaptive neurodevelopmental alterations could foster adjustment among the more exposed and genetically more stress susceptible youths. Transcriptomic analyses suggested that sensitivity to stress may underpin the joint neurodevelopmental effect of adversity and genetic risk for MDD/AD, in line with the proposed role of negative emotionality as a precursor to AD, likely to account for the alleged causal impact of MDD on dementia onset.
DOI: 10.15154/1528694
title: Breastfeeding duration is associated with larger cortical gray matter volumes in children from the ABCD study

description: Background: Despite the numerous studies in favor of breastfeeding for its benefits in cognition and mental health, the long-term effects of breastfeeding on brain structure are still largely unknown. Our main objective was to study the relationship between breastfeeding duration and cerebral gray matter volumes. We also explored the potential mediatory role of brain volumes on behavior.

Methods: We analyzed 7,860 magnetic resonance images of children 9–11 years of age from the Adolescent Brain Cognitive Development (ABCD) dataset in order to study the relationship between breastfeeding duration and cerebral gray matter volumes. We also obtained several behavioral data (cognition, behavioral problems, prodromal psychotic experiences, prosociality, impulsivity) to explore the potential mediatory role of brain volumes on behavior.

Results: In the 7,860 children analyzed (median age=9 years and11 months; 49.9% female), whole-brain voxel-based morphometry analyses revealed an association mainly between breastfeeding duration and larger bilateral volumes of the pars orbitalis and the lateral orbitofrontal cortex. In particular, the association with the left pars orbitalis and the left lateral orbitofrontal cortex proved to be very robust to the addition of potentially confounding covariates, random selection of siblings, and splitting the sample in two. The volume of the left pars orbitalis and the left lateral orbitofrontal cortex appeared to mediate the relationship between breastfeeding duration and the negative urgency dimension of the UPPS-P Impulsive Behavior Scale. Global gray matter volumes were also significant mediators for behavioral problems as measured with the Child Behavior Checklist.

Conclusions: Our findings suggest that breastfeeding is a relevant factor in the proper development of thebrain, particularly for the pars orbitalis and lateral orbitofrontal cortex regions. This, in turn, may impact impulsive personality and mental health in early puberty.
DOI: 10.15154/1528707
title: Sleep Is My Superpower: Sleep Quality as a Protective Factor against Behavioral Problems for Sexual-Minority Youth Facing Discrimination

description: Sexual-minority youth (SMY) are systematically affected by symptoms of mental illness, and SMY experiencing discrimination are placed at greater risk of developing behavior problems (Institute of Medicine Committee, 2011; Meyer, 2003). Sleep quality is known to be protective against externalizing behavior among youth generally (Kelly & El-Sheikh, 2014). Given the risk of mental illness, and possible protection of sleep, the present study tests sleep quality as a moderator of relations between discrimination and externalizing problems for SMY. 

A community sample of 211 SMY were drawn from the NIH-led Adolescent Brain and Cognitive Development Study. Youth were racially diverse (60% White, 24% multiracial, 12% Latinx, 3% Black, 1% Asian) pre- and early adolescents (age: M = 11.99 years, SD = 7.34 months; Tanner stage: M = 3.20, SD = 0.80). Youth completed questionnaires in a lab setting responding dichotomously (yes/no) to the questions, “Are you gay or bisexual?” and “In the past 12 months, have you felt discriminated against because someone thought you were gay, lesbian, or bisexual?” Youth wore FitBit Charge HR devices at home for 3 weeks to provide 2 objective indicators of nighttime sleep quality: sleep latency (minutes between laying down and sleep onset) and minutes of wake after sleep onset (WASO). Parents reported on youth behavior problems using the externalizing composite (T score) of the Child Behavior Checklist (Achenbach & Rescorla, 2001), which indexes aggression and rule-breaking behavior.

Separate path models testing interactions of Discrimination x Sleep Quality demonstrated that sleep latency and WASO moderated relations between discrimination and externalizing problems for SMY. Interaction plots and tests of simple slopes showed that SMY with longer sleep latency (B = 4.42, SE = 2.37, p = 0.06; Figure 1A) and more WASO (B = 4.98, SE = 2.26, p < .05; Figure 1B) were at risk for more externalizing problems when they faced discrimination. For youth with shorter latency (B = –1.75, SE = 2.47, p = .48) or less WASO (B = –2.81, SE = 2.34, p = .23), the relationship between discrimination and problem behaviors was non-significant. 

These promising results suggest that sleep is a health behavior which might enhance the resilience of SMY experiencing minority stress (Meyer, 2015). Practitioners supporting youth might utilize sleep hygiene interventions in order to lessen behavior problems among sexual-minority adolescents who face harm.
DOI: 10.15154/1528709
title: Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study

description: Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
DOI: 10.15154/1528714
title: Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies

description: Importance: Major depressive disorder (MDD) is a heterogeneous condition; multiple underlying neurobiological substrates could be associated with treatment response variability. Understanding the sources of this variability and predicting outcomes has been elusive. Machine learning (ML) has shown promise in predicting treatment response in MDD, but one limitation has been the lack of clinical interpretability of machine learning models, limiting clinician confidence in model results.
Objective: To develop a machine learning model to derive treatment-relevant patient profiles using clinical and demographic information.
Design: We analyzed data from six clinical trials of pharmacological treatment for depression (total n = 5438) using the Differential Prototypes Neural Network (DPNN), a neural network model that derives patient prototypes which can be used to derive treatment-relevant patient clusters while learning to generate probabilities for differential treatment response. A model classifying remission and outputting individual remission probabilities for five first-line monotherapies and three combination treatments was trained using clinical and demographic data.
Setting: Previously-conducted clinical trials of antidepressant medications.
Participants: Patients with MDD.
Main outcomes and measures: Model validity and clinical utility were measured based on area under the curve (AUC) and expected improvement in sample remission rate with model-guided treatment, respectively. Post-hoc analyses yielded clusters (subgroups) based on patient prototypes learned during training. Prototypes were evaluated for interpretability by assessing differences in feature distributions (e.g. age, sex, symptom severity) and treatment-specific outcomes.
Results: A 3-prototype model achieved an AUC of 0.66 and an expected absolute improvement in population remission rate of 6.5% (relative improvement of 15.6%). We identified three treatment-relevant patient clusters. Cluster A patients tended to be younger, to have increased levels of fatigue and more severe symptoms. Cluster B patients tended to be older, female with less severe symptoms, and the highest remission rates. Cluster C patients had more severe symptoms, lower remission rates, more psychomotor agitation, more intense suicidal ideation, more somatic genital symptoms, and showed improved remission with venlafaxine.
Conclusion and Relevance: It is possible to produce novel treatment-relevant patient profiles using machine learning models; doing so may improve precision medicine for depression. Note: This model is not currently the subject of any active clinical trials and is not intended for clinical use.
DOI: 10.15154/1528722
title: The Mediating Role of Family Acceptance and Conflict on Suicidality among Sexual and Gender Minority Youth

description: Prior research suggests sexual and gender minority (SGM) youth are profoundly impacted by levels of parental support. This study assessed mediating effects of generalized family acceptance and conflict on lifetime suicidal behaviors among a large diverse sample comprising both SGM and non-SGM youth in early adolescence, when intervention to optimize family dynamics may be critical. Using data from the first-year follow-up of the Adolescent Brain Cognitive Development Study based in the United States, mediation was tested using a binary logistic regression model fitted with a generalized structural equation. Models included SGM status as the independent variable, family acceptance or family conflict sum score as the mediator, and the presence of lifetime suicidal behaviors as the dependent variable. Models adjusted for age, birth-assigned sex (as reported by the parent/guardian), and race/ethnicity. Of 11,235 youths, lifetime suicidal behaviors were reported by 1.5% (n = 164). Youths with SGM identities reported 40% less parental acceptance and 47% greater family conflict, compared to non-SGM peers. Both parental acceptance and family conflict partially mediated associations between SGM identification and odds of lifetime suicidal behavior (ps = .001). Identification of modifiable risk factors for suicidality in this vulnerable population, including parental acceptance and family conflict, is critical to improving health outcomes. Clinicians should work with SGM youth and their families starting in childhood to optimize family dynamics and bolster acceptance to potentially reduce adverse health outcomes.
DOI: 10.15154/1528723
title: Longitudinal Associations between Perceived Discrimination and Suicidality in Youth

description: Research among adults reveals robust associations between discrimination and suicidality. However, these relationships remain understudied in youth. Participants in the Adolescent Brain Cognitive Development (ABCD) study completed a measure of
discrimination based on multiple attributes. The KSADS was administered one-year later to assess depressive disorders and suicidality (ideation and behavior). Logistic regressions, adjusting for age, sex, race/ethnicity, family income, lifetime depressive
disorders, and body composition were conducted. Adjusting for covariates, discrimination based on weight (OR: 2.12), race/ethnicity/color (OR: 3.21), and sexual orientation (OR: 3.83) were associated with greater odds of reporting suicidality one-
year later (ps < 0.025). Compared to those reporting no discrimination, youths reporting discrimination based on two or more attributes had nearly five times greater odds of recent suicidality (OR: 4.72; p<0.001). The current study highlights the
deleterious impacts of discrimination on mental health among youths reporting multiple forms of discrimination.