Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

A latent state space model for estimating brain dynamics from electroencephalogram (EEG) data.

Modern neuroimaging technologies have substantially advanced the measurement of brain activity. Electroencephalogram (EEG) as a noninvasive neuroimaging technique measures changes in electrical voltage on the scalp induced by brain cortical activity. With its high temporal resolution, EEG has emerged as an increasingly useful tool to study brain connectivity. Challenges with modeling EEG signals of complex brain activity include interactions among unknown sources, low signal-to-noise ratio, and substantial between-subject heterogeneity. In this work, we propose a state space model that jointly analyzes multichannel EEG signals and learns dynamics of different sources corresponding to brain cortical activity. Our model borrows strength from spatially correlated measurements and uses low-dimensional latent states to explain all observed channels. The model can account for patient heterogeneity and quantify the effect of a subject's covariates on the latent space. The EM algorithm, Kalman filtering, and bootstrap resampling are used to fit the state space model and provide comparisons between patient diagnostic groups. We apply the developed approach to a case-control study of alcoholism and reveal significant attenuation of brain activity in response to visual stimuli in alcoholic subjects compared to healthy controls.

Shapes of subcortical structures in adolescents with and without familial history of substance use disorder.

It has been suggested that intergenerational transmission of risk for substance use disorder (SUD) manifests in the brain anatomy of substance naïve adolescents. While volume and shapes of subcortical structures (SSS) have been shown to be heritable, these structures, especially the pallidum, putamen, nucleus accumbens, and hippocampus, have also been associated with substance use disorders. However, it is not clear if those anatomical differences precede substance use or are the result of that use. Therefore, we examined if volume and SSS of adolescents with a family history (FH+) of SUD differed from adolescents without such a history (FH-). Because risk for SUD is associated with anxiety and impulsivity, we also examined correlations between these psychological characteristics and volume/SSS. Using structural MRI and FSL software, we segmented subcortical structures and obtained indices of SSS and volumes of 64 FH+ and 58 FH- adolescents. We examined group differences in volume and SSS, and the correlations between volume/SSS and trait anxiety and impulsivity. FH+ adolescents had a significant inward deformation in the shape of the right anterior hippocampus compared to FH- adolescents, while the volume of this structure did not differ between groups. Neither shape nor volume of the other subcortical structures differed between groups. In the FH+ adolescents, the left hippocampus shape was positively correlated with both trait anxiety and impulsivity, while in FH- adolescents a negative correlation pattern of SSS was seen in the hippocampus. SSS appears to capture local anatomical features that traditional volumetric analysis does not. The inward shape deformation in the right anterior hippocampus in FH+ adolescents may be related to the known increased risk for behavioral dysregulation leading to SUD in FH+ offspring. Hippocampus shape also exhibits opposite patterns of correlation with anxiety and impulsivity scores across the FH+ and FH- adolescents. These novel findings may reveal neural correlates, not captured by traditional volumetric analysis, of familial transmission of increased vulnerability to SUD.

Hearing Rehabilitative Treatment for Older Adults With Comorbid Hearing Loss and Depression: Effects on Depressive Symptoms and Executive Function.

OBJECTIVES: Recent research has revealed important neural and psychiatric consequences of hearing loss (HL) in older adults. This pilot study examined the neural effects of HL and the impact of hearing aids on neuropsychiatric outcomes in major depressive disorder (MDD). DESIGN: Twelve-week, double-blind, randomized controlled trial. PARTICIPANTS/INTERVENTION: N = 25 (≥60 years) with MDD and moderate-profound HL were randomized to receive hearing aids (100% gain targets) or sham hearing aids (flat 30 dB HL) in addition to psychiatric treatment-as-usual. MEASUREMENTS: Depressive symptoms (Hamilton Rating Scale for Depression [HRSD]), executive functioning (NIH Toolbox Flanker), integrity of auditory brain areas (structural MRI, diffusion tensor imaging). RESULTS: At baseline, worse speech discrimination was associated with auditory cortical thinning (Left anterior transverse temporal gyrus: r = 0.755, p = 0.012) and lower integrity of the superior longitudinal fasciculus (FA: Left r = 0.772, p = 0.025, Right r = 0.782, p = 0.022). After 12-weeks, hearing aids were effective at improving hearing functioning (Hearing Handicap for the Elderly: active -12.47 versus sham -4.19, t = -2.64, df = 18, p = 0.016) and immediate memory (active +14.9 versus sham +5.7, t = 2.28, df = 16, p = 0.037). Moderate improvement was observed for hearing aids on executive functioning but did not reach statistical significance (Flanker: active +4.8 versus sham -2.4, t = 1.95, df = 15, p = 0.071). No significant effect on depression was found (HRSD: active -5.50 versus sham -7.32, t = 0.75, df = 19, p = 0.46). CONCLUSIONS: HL can affect brain regions important for auditory and cognitive processing, and hearing remediation may have beneficial effects on executive functioning in MDD. Future studies may evaluate whether impairment in cognitive control consequent to HL may be an important risk mechanism for MDD.

Contributions of Cerebellar White Matter Microstructure to Social Difficulty in Nonverbal Learning Disability.

Emerging evidence suggests that the cerebellum may contribute to variety of cognitive capacities, including social cognition. Nonverbal learning disability (NVLD) is characterized by visual-spatial and social impairment. Recent functional neuroimaging studies have shown that children with NVLD have altered cerebellar resting-state functional connectivity, which is associated with various symptom domains. However, little is known about cerebellar white matter microstructure in NVLD and whether it contributes to social deficits. Twenty-seven children (12 with NVLD, 15 typically developing (TD)) contributed useable diffusion tensor imaging data. Tract-based spatial statistics (TBSS) were used to quantify fractional anisotropy (FA) in the cerebellar peduncles. Parents completed the Child Behavior Checklist, providing a measure of social difficulty. Children with NVLD had greater fractional anisotropy in the left and right inferior cerebellar peduncle. Furthermore, right inferior cerebellar peduncle FA was associated with social impairment as measured by the Child Behavior Checklist Social Problems subscale. Finally, the association between NVLD diagnosis and greater social impairment was mediated by right inferior cerebellar peduncle FA. These findings provide additional evidence that the cerebellum contributes both to social cognition and to the pathophysiology of NVLD.

Slowed Processing Speed Disrupts Patient Expectancy in Late Life Depression.

OBJECTIVE: Slowed processing speed and executive dysfunction are associated with poor outcomes in Late Life Depression (LLD), though it is unclear why. We investigated whether these variables interfere with the development of positive treatment expectancies in an antidepressant trial. METHODS: Depressed older subjects were randomized to Open (intended to increase patient expectancy) or Placebo-controlled (termed 'Hidden,' intended to decrease expectancy) administration of antidepressant medication for 8 weeks. Analysis of covariance analyzed the between-group difference on expectancy (Credibility and Expectancy Scale [CES]) and depression (Hamilton Rating Scale for Depression [HRSD], Clinical Global Impressions [CGI] Severity). Moderator analyses examined whether these Open versus Hidden differences varied based on higher versus lower processing speed and executive function. RESULTS: Among the 108 participants, a significant between-group difference was observed on expectancy (effect size [ES, Cohen's d] = 0.51 on CES Item 2; ES = 0.64 on Item 4), indicating the manipulation was effective. Processing speed as measured by the Stroop Color-Word Test (number color-words named in congruent condition) was a significant moderator of the Open versus Hidden effect on expectancy. Depressive symptom improvement was greater on average for Open versus Hidden participants who received active drug (CGI-severity ES = 1.25, HRSD ES = 0.41), but no neurocognitive moderators of the between-group difference reached statistical significance. CONCLUSIONS: Slowed processing speed impairs the development of expectancies in antidepressant trials for LLD, which may help explain lower antidepressant response among older adults. Future studies may address whether interventions to optimize treatment expectancies are capable of improving treatment outcomes.

Association of White Matter Integrity With Executive Function and Antidepressant Treatment Outcome in Patients With Late-Life Depression.

OBJECTIVE: While patients with late-life depression (LLD) often exhibit microstructural white matter alterations that can be identified with diffusion tensor imaging (DTI), there is a dearth of information concerning the links between DTI findings and specific cognitive performance, as well as between DTI measures and antidepressant treatment outcomes. DESIGN: Neuroimaging and cognitive tests were conducted at baseline in 71 older adults participating in a larger, 8-week duration antidepressant randomized controlled trial. Correlations between DTI measures of white matter integrity evaluated with tract-based spatial statistics, baseline neurocognitive performance, and prospective antidepressant treatment outcome were evaluated. RESULTS: Fractional anisotropy (FA), an index of white matter integrity, was significantly positively associated with better cognitive function as measured by the Initiation/Perseveration subscale of the Dementia Rating Scale in the bilateral superior longitudinal fasciculus (SLF), bilateral SLF-temporal, and right corticospinal tract (CST). An exploratory analysis limited to these tracts revealed that increased FA in the right CST, right SLF, and right SLF-temporal tracts was correlated with a greater decrease in depressive symptoms. Increased FA in the right CST predicted a greater chance of remission, while increased FA in the right CST and the right SLF predicted a greater chance of treatment response. CONCLUSION: In late-life depression LLD subjects, white matter integrity was positively associated with executive function in white matter tracts which act as key connecting structures underlying the cognitive control network. These tracts may play a role as a positive prognostic factor in antidepressant treatment outcome.

Socioeconomic factors, stress, hair cortisol, and white matter microstructure in children.

Socioeconomic disadvantage has been linked to increased stress exposure in children and adults. Exposure to stress in childhood has been associated with deleterious effects on cognitive development and well-being throughout the lifespan. Further, exposure to stress has been associated with differences in brain development in children, both in cortical and subcortical gray matter. However, less is known about the associations among socioeconomic disadvantage, stress, and children's white matter development. In this study, we investigated whether socioeconomic disparities would be associated with differences in white matter microstructure in the cingulum bundle, as has been previously reported. We additionally investigated whether any such differences could be explained by differences in stress exposure and/or physiological stress levels. White matter tracts were measured via diffusion tensor imaging in 58 children aged 5-9 years. Results indicated that greater exposure to stressful life events was associated with higher child hair cortisol concentrations. Further, physiological stress, as indexed by hair cortisol concentrations, were associated with higher fractional anisotropy in the cingulum bundle. These results have implications for better understanding how perceived and physiological stress may alter neural development during childhood.

Material hardship, prefrontal cortex-amygdala structure, and internalizing symptoms in children.

Material hardship, or difficulty affording basic resources such as food, housing, utilities, and health care, increases children's risk for internalizing problems. The uncinate fasciculus (UNC) and two of the gray matter regions it connects-the orbitofrontal cortex (OFC) and amygdala-may play important roles in the neural mechanisms underlying these associations. We investigated associations among material hardship, UNC microstructure, OFC and amygdala structure, and internalizing symptoms in children. Participants were 5-9-year-old children (N = 94, 61% female) from socioeconomically diverse families. Parents completed questionnaires assessing material hardship and children's internalizing symptoms. High-resolution, T1-weighted magnetic resonance imaging (n = 51), and diffusion tensor imaging (n = 58) data were acquired. UNC fractional anisotropy (FA), medial OFC surface area, and amygdala gray matter volume were extracted. Greater material hardship was significantly associated with lower UNC FA, smaller amygdala volume, and higher internalizing symptoms in children, after controlling for age, sex, and family income-to-needs ratio. Lower UNC FA significantly mediated the association between material hardship and internalizing symptoms in girls but not boys. These findings are consistent with the notion that material hardship may lead to altered white matter microstructure and gray matter structure in neural networks critical to emotion processing and regulation.

Structural neural markers of response to cognitive behavioral therapy in pediatric obsessive-compulsive disorder.

BACKGROUND: Cognitive behavioral therapy (CBT) is an effective, first-line treatment for pediatric obsessive-compulsive disorder (OCD). While neural predictors of treatment outcomes have been identified in adults with OCD, robust predictors are lacking for pediatric patients. Herein, we sought to identify brain structural markers of CBT response in youth with OCD. METHODS: Twenty-eight children/adolescents with OCD and 27 matched healthy participants (7- to 18-year-olds, M = 11.71 years, SD = 3.29) completed high-resolution structural and diffusion MRI (all unmedicated at time of scanning). Patients with OCD then completed 12-16 sessions of CBT. Subcortical volume and cortical thickness were estimated using FreeSurfer. Structural connectivity (streamline counts) was estimated using MRtrix. RESULTS: Thinner cortex in nine frontoparietal regions significantly predicted improvement in Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS) scores (all ts > 3.4, FDR-corrected ps < .05). These included middle and superior frontal, angular, lingual, precentral, superior temporal, and supramarginal gyri (SMG). Vertex-wise analyses confirmed a significant left SMG cluster, showing large effect size (Cohen's d = 1.42) with 72.22% specificity and 90.00% sensitivity in predicting CBT response. Ten structural connections between cingulo-opercular regions exhibited fewer streamline counts in OCD (all ts > 3.12, Cohen's ds > 0.92) compared with healthy participants. These connections predicted post-treatment CY-BOCS scores, beyond pretreatment severity and demographics, though not above and beyond cortical thickness. CONCLUSIONS: The current study identified group differences in structural connectivity (reduced among cingulo-opercular regions) and cortical thickness predictors of CBT response (thinner frontoparietal cortices) in unmedicated children/adolescents with OCD. These data suggest, for the first time, that cortical and white matter features of task control circuits may be useful in identifying which pediatric patients respond best to individual CBT.

Socioeconomic Disparities in Language Input Are Associated With Children's Language-Related Brain Structure and Reading Skills.

The mechanisms underlying socioeconomic disparities in children's reading skills are not well understood. This study examined associations among socioeconomic background, home linguistic input, brain structure, and reading skills in 5-to-9-year-old children (N = 94). Naturalistic home audio recordings and high-resolution, T1-weighted MRI scans were acquired. Children who experienced more adult-child conversational turns or adult words had greater left perisylvian cortical surface area. Language input mediated the association between parental education and left perisylvian cortical surface area. Language input was indirectly associated with children's reading skills via left perisylvian surface area. Left perisylvian surface area mediated the association between parental education and children's reading skills. Language experience may thus partially explain socioeconomic disparities in language-supporting brain structure and in turn reading skills.

Parental punitive discipline and children's depressive symptoms: Associations with striatal volume.

Although parental harshness has been consistently linked with increased depressive symptoms in youth, its associations with children's brain structure are not well understood. The striatum has been strongly implicated in depression in adolescents and adults. In this study, we investigated the associations among parental harsh discipline, striatal volume, and depressive symptoms in children. Participants were parents and their 5- to 9-year-old children (63% female; 29% African American; 47% Hispanic/Latino). Parents completed questionnaires about their parenting behaviors and children's depressive symptoms. Children participated in a high-resolution, T1-weighted MRI scan, and volumetric data for the caudate, putamen, and nucleus accumbens were extracted (n = 20 with both parenting and MRI data; n = 48 with both MRI and depressive symptom data). Findings indicated that more frequent parental harsh discipline was significantly associated with smaller dorsal striatal volume (caudate plus putamen). In addition, smaller dorsal striatal volume was significantly associated with increased depressive symptoms in children. These associations remained significant after accounting for child age, sex, whole brain volume, and parental depressive symptoms. These findings suggest that parental harsh discipline may be associated with children's striatal volume, which may in turn be associated with their level of depressive symptoms.

Altered frontal interhemispheric and fronto-limbic structural connectivity in unmedicated adults with obsessive-compulsive disorder.

BACKGROUND: Previous diffusion tensor imaging (DTI) studies of obsessive-compulsive disorder (OCD) have primarily used voxel- or tract-based methods to assess white matter microstructure in medicated patients. This is the first probabilistic tractography study to assess the structural connectivity of all major white matter tracts in unmedicated adults with OCD without comorbid psychopathology. We hypothesized that OCD compared to healthy participants would show reduced integrity in frontal interhemispheric and fronto-limbic tracts. METHODS: DTI data from 29 unmedicated adults with OCD were compared to that of 27 matched healthy control (HC) participants. TRACULA was used to assess probabilistic tractography and compare groups in the average fractional anisotropy (FA) of 8 bilateral tracts plus forceps minor and major, and explore group differences in axial (AD), radial (RD), and mean (MD) diffusivities in tracts where FA differed across groups. RESULTS: Significantly less FA was detected in OCD compared to HC participants in forceps minor, interhemispheric fibers of the frontal cortex, and right uncinate fasciculus (UNC), association fibers connecting frontal and limbic regions (p's < .05). FA in forceps minor was inversely associated with symptom severity in the OCD participants. Exploratory analyses revealed less AD in right UNC was inversely associated with OCD symptoms. CONCLUSIONS: Structural connectivity of frontal interhemispheric and fronto-limbic circuits may be altered in unmedicated adults with OCD, especially those with the most severe symptoms. These findings suggest a microstructural basis for the abnormal function and reduced resting-state connectivity of frontal regions and fronto-limbic circuits in OCD.

End-member extraction based on segmented vertex component analysis in hyperspectral images.

Hyperspectral images collected by a remote sensing hyperspectral imaging instrument have many mixed pixels, due to the limited resolution of image sensors and the complex diversity of nature. End-member extraction is the process that determines the end-members in mixed pixels. The results of traditional methods are inaccurate, due to the spatial complexity and noise of actual hyperspectral image data. This study presents segmented vertex component analysis (SVCA), wherein the relative complexities of hyperspectral images are segmented into a number of relatively simple spatial subsets to reduce the effect of uncorrelated pixels. The end-members are extracted by finding the vertices of the simplex that minimally encloses the hyperspectral image data in each spatial subset, and the inversion abundance is used to identify each major end-member in each subset. Experimental results demonstrate that the proposed method can effectively implement end-member extraction with high accuracy.

Explaining deep learning-based representations of resting state functional connectivity data: focusing on interpreting nonlinear patterns in autism spectrum disorder.

Background: Resting state Functional Magnetic Resonance Imaging fMRI (rs-fMRI) has been used extensively to study brain function in psychiatric disorders, yielding insights into brain organization. However, the high dimensionality of the rs-fMRI data presents significant challenges for data analysis. Variational autoencoders (VAEs), a type of neural network, have been instrumental in extracting low-dimensional latent representations of resting state functional connectivity (rsFC) patterns, thereby addressing the complex nonlinear structure of rs-fMRI data. Despite these advances, interpreting these latent representations remains a challenge. This paper aims to address this gap by developing explainable VAE models and testing their utility using rs-fMRI data in autism spectrum disorder (ASD). Methods: One-thousand one hundred and fifty participants (601 healthy controls [HC] and 549 patients with ASD) were included in the analysis. RsFC correlation matrices were extracted from the preprocessed rs-fMRI data using the Power atlas, which includes 264 regions of interest (ROIs). Then VAEs were trained in an unsupervised manner. Lastly, we introduce our latent contribution scores to explain the relationship between estimated representations and the original rs-fMRI brain measures. Results: We quantified the latent contribution scores for both the ASD and HC groups at the network level. We found that both ASD and HC groups share the top network connectivitives contributing to all estimated latent components. For example, latent 0 was driven by rsFC within ventral attention network (VAN) in both the ASD and HC. However, we found significant differences in the latent contribution scores between the ASD and HC groups within the VAN for latent 0 and the sensory/somatomotor network for latent 2. Conclusion: This study introduced latent contribution scores to interpret nonlinear patterns identified by VAEs. These scores effectively capture changes in each observed rsFC feature as the estimated latent representation changes, enabling an explainable deep learning model that better understands the underlying neural mechanisms of ASD.

Socioeconomic factors, sleep timing and duration, and amygdala resting-state functional connectivity in children.

Introduction: Reduced sleep health has been consistently linked with increased negative emotion in children. While sleep characteristics have been associated with neural function in adults and adolescents, much less is known about these associations in children while considering socioeconomic context. In this study, we examined the associations among socioeconomic factors, sleep duration and timing, and resting-state functional connectivity (rsFC) of the amygdala in children. Methods: Participants were typically-developing 5- to 9-year-olds from socioeconomically diverse families (61% female; N = 94). Parents reported on children's weekday and weekend bedtimes and wake-up times, which were used to compute sleep duration and midpoint. Analyses focused on amygdala-anterior cingulate cortex (ACC) connectivity followed by amygdala-whole brain connectivity. Results: Lower family income-to-needs ratio and parental education were significantly associated with later weekday and weekend sleep timing and shorter weekday sleep duration. Shorter weekday sleep duration was associated with decreased amygdala-ACC and amygdala-insula connectivity. Later weekend sleep midpoint was associated with decreased amygdala-paracingulate cortex and amygdala-postcentral gyrus connectivity. Socioeconomic factors were indirectly associated with connectivity in these circuits via sleep duration and timing. Discussion: These results suggest that socioeconomic disadvantage may interfere with both sleep duration and timing, in turn possibly altering amygdala connectivity in emotion processing and regulation circuits in children. Effective strategies supporting family economic conditions may have benefits for sleep health and brain development in children.

Characteristics of Adolescents with and without a Family History of Substance Use Disorder from a Minority Cohort.

Family history (FH+) of substance use disorder (SUD) is an established risk factor for offspring SUD. The extent to which offspring psychological traits or the family environment, each of which may be relevant to familial transmission of SUD risk, vary by FH+ in socioeconomically disadvantaged populations is less clear. We compared the family/social environmental and psychological characteristics of 73 FH+ and 69 FH- youth ages 12-16, from a study of parental criminal justice system involvement in a primarily low-income, minority urban population. A latent profile analysis (LPA) empirically identified groups of subjects with similar psychological characteristics, which were then compared by FH+. FH+ youths were found to have greater mean household size, greater parental psychological aggression, and a higher mean number of adverse childhood experiences, even without considering parental SUD. FH+ individuals had lower report card grades according to parental report and were more likely to have a history of externalizing disorders than FH- individuals. However, FH+ was not significantly associated with many psychological characteristics or with the class membership from the LPA. In conclusion, among a population of low-income, minority urban youth, FH+ was associated with differences in the family environment and only subtle differences in individual psychological characteristics.