Faculty Bibliography

BACKGROUND:Conduct disorder (CD) is a common syndrome with far-reaching effects. Risk factors for the development of CD span social, psychological, and biological domains. Researchers note that predictive models of CD are limited if the focus is on a single risk factor or even a single domain. Machine learning methods are optimized for the extraction of trends across multidomain data but have yet to be implemented in predicting the development of CD. METHODS:Social (e.g., family, income), psychological (e.g., psychiatric, neuropsychological), and biological (e.g., resting-state graph metrics) risk factors were measured using data from the baseline visit of the Adolescent Brain Cognitive Development Study when youth were 9 to 10 years old (N = 2368). Applying a feed-forward neural network machine learning method, risk factors were used to predict CD diagnoses 2 years later. RESULTS:A model with factors that included social, psychological, and biological domains outperformed models representing factors within any single domain, predicting the presence of a CD diagnosis with 91.18% accuracy. Within each domain, certain factors stood out in terms of their relationship to CD (social: lower parental monitoring, more aggression in the household, lower income; psychological: greater attention-deficit/hyperactivity disorder and oppositional defiant disorder symptoms, worse crystallized cognition and card sorting performance; biological: disruptions in the topology of subcortical and frontoparietal networks). CONCLUSIONS:The development of an accurate, sensitive, and specific predictive model of CD has the potential to aid in prevention and intervention efforts. Key risk factors for CD appear best characterized as reflecting unpredictable, impulsive, deprived, and emotional external and internal contexts.

BACKGROUND/UNASSIGNED:The mental health issues due to COVID-19, such as intolerance of uncertainty (IOU), anxiety, stress, and depression, have attracted extensive attention from researchers. The challenges for Pakistani university students could be worse than developed countries due to the lack of online courses/programs and online mental health support provided by academic institutions. Therefore, the current study aims to assess the intolerance of uncertainty, depression, anxiety, and stress of Pakistani university students after the second wave of COVID-19 and the relationship among these constructs. METHODS/UNASSIGNED:A convenience cross-sectional sampling method was used to collect data from university students in Pakistan between January 2021 and April 2022 via a structured online questionnaire. The Descriptive analysis focused on frequencies, percentages, mean, and standard deviation (SD) were calculated on IOU-12 and DASS-21. Covariance for the research model and confirmatory factor analyses fit indices for the IOU-12 and DASS-21 were analyzed by AMOS statistical packages. RESULTS/UNASSIGNED:As expected, anxiety, depression, and stress persist among Pakistani university students. On average, they report mild to moderate mental health problems regarding anxiety, depression, stress, and intolerance of uncertainty. Our results indicate a strong positive relationship among the three emotional distress components - anxiety, depression, and stress. However, our results suggest no significant relationship between IOU and the three subcomponents of emotional distress (anxiety, depression, and stress). LIMITATIONS/UNASSIGNED:First, the cross-sectional survey design means we cannot conclude on the causal relations. Second, the self-report questionnaire embeds subjectivity issues. Last, the generalizability of the sample to the whole student population in Pakistan is limited, considering the sampling method. CONCLUSION/UNASSIGNED:This study expanded the current knowledge in the psychological health domain (intolerance of uncertainty, anxiety, depression, and stress) due to the COVID-19 pandemic. In practice, higher education institutions should further mitigate university students' mental health issues. For researchers, our findings inspire future studies to delve into the relationship between IOU and mental health issues due to COVID-19 since our findings display contrary evidence for various reasons.

OBJECTIVE:Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level. METHODS:In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied. RESULTS:Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD. CONCLUSIONS:Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.

Early treatment of behavioral problems can prevent their progression into intractable disorders. This study examined the impact of a multiple family group (MFG) intervention for children with behavior symptoms and their families. Fifty-four (n = 54) caregiver/child dyads with sub-clinical levels of oppositional defiant disorder (ODD) participated in a 16-week MFG. Child, caregiver, and family outcomes were assessed at baseline, post-treatment, and at 6 months follow-up. Significant decreases in impairment with parents, family members, and peers, and improvements in child self-esteem were found from baseline to follow-up. Caregiver stress increased; no significant changes in depression or perceived social support were found over time. The effectiveness of MFG as a preventive approach and areas of future research are discussed.

BACKGROUND/UNASSIGNED:More than 50 million people in the United States serve as uncompensated informal caregivers to chronically ill friends or family members. Providing care to a sick loved one can contribute to personal growth but can also cause significant strain. Caregiver distress refers to a constellation of physiological, psychological, interpersonal, and spiritual impairments that typically result when an individual's own health becomes affected while caring for another. Caregiver distress is highly prevalent, affecting an estimated 30-70% of individuals across various caregiver populations. Although evidence-based treatments for caregiver distress exist, they do not sufficiently address all its components. In recent years, clinical trials have demonstrated that psychedelic-assisted psychotherapy (PAP) may have applications for treating a range of medical and psychiatric conditions that have significant overlap in symptoms to those seen in caregiver distress. While no studies to date have examined PAP for caregiver distress, this article provides a rationale for investigating PAP as a potential novel treatment for this indication. METHODS/UNASSIGNED:A narrative review on the effects and clinical applications of PAP that significantly overlap with the dimensions of caregiver distress was conducted. Safety considerations, psychedelic selection, and therapeutic structure for studying PAP in the treatment of caregiver distress were also examined. RESULTS/UNASSIGNED:Psychologically, PAP has been shown to treat anxiety, depression, and reduce suicidal ideation. Physiologically, evidence suggests that psychedelics have anti-inflammatory properties, which may aid caregivers suffering from chronic inflammation. Interpersonally, PAP has been demonstrated to enhance feelings of empathy, connectedness, and strengthen social relationships, which can often become strained while caregiving. Spiritually, PAP has been shown to ameliorate existential distress and hopelessness in cancer patients, which may similarly benefit demoralized caregivers. CONCLUSION/UNASSIGNED:PAP has the potential to comprehensively treat all biopsychosocial-spiritual dimensions of caregiver distress.

In many species, including mice, female animals show markedly different pup-directed behaviours based on their reproductive state^1,2. Naive wild female mice often kill pups, while lactating female mice are dedicated to pup caring^3,4. The neural mechanisms that mediate infanticide and its switch to maternal behaviours during motherhood remain unclear. Here, on the basis of the hypothesis that maternal and infanticidal behaviours are supported by distinct and competing neural circuits^5,6, we use the medial preoptic area (MPOA), a key site for maternal behaviours^7-11, as a starting point and identify three MPOA-connected brain regions that drive differential negative pup-directed behaviours. Functional manipulation and in vivo recording reveal that oestrogen receptor α (ESR1)-expressing cells in the principal nucleus of the bed nucleus of stria terminalis (BNSTpr^ESR1) are necessary, sufficient and naturally activated during infanticide in female mice. MPOA^ESR1 and BNSTpr^ESR1 neurons form reciprocal inhibition to control the balance between positive and negative infant-directed behaviours. During motherhood, MPOA^ESR1 and BNSTpr^ESR1 cells change their excitability in opposite directions, supporting a marked switch of female behaviours towards the young.

Longitudinal analysis is a core aspect of many medical applications for understanding the relationship between an anatomical subject's function and its trajectory of shape change over time. Whereas mixed-effects (or hierarchical) modeling is the statistical method of choice for analysis of longitudinal data, we here propose its extension as hierarchical geodesic polynomial model (HGPM) for multilevel analyses of longitudinal shape data. 3D shapes are transformed to a non-Euclidean shape space for regression analysis using geodesics on a high dimensional Riemannian manifold. At the subject-wise level, each individual trajectory of shape change is represented by a univariate geodesic polynomial model on timestamps. At the population level, multivariate polynomial expansion is applied to uni/multivariate geodesic polynomial models for both anchor points and tangent vectors. As such, the trajectory of an individual subject's shape changes over time can be modeled accurately with a reduced number of parameters, and population-level effects from multiple covariates on trajectories can be well captured. The implemented HGPM is validated on synthetic examples of points on a unit 3D sphere. Further tests on clinical 4D right ventricular data show that HGPM is capable of capturing observable effects on shapes attributed to changes in covariates, which are consistent with qualitative clinical evaluations. HGPM demonstrates its effectiveness in modeling shape changes at both subject-wise and population levels, which is promising for future studies of the relationship between shape changes over time and the level of dysfunction severity on anatomical objects associated with disease.

Neighborhood threats can increase risk for externalizing problems, including aggressive, oppositional, and delinquent behavior. Yet, there is substantial variability in how youth respond to neighborhood threats. Difficulty with cognitive functioning, particularly in the face of emotional information, may increase risk for externalizing in youth who live in neighborhoods with higher threats. However, little research has examined: 1) associations between neighborhood threats and executive networks involved in cognitive functioning or 2) whether executive networks may amplify risk for externalizing in the context of neighborhood threats. Further, most research on neighborhood threats does not account for youth's experiences in other social contexts. Utilizing the large, sociodemographically diverse cohort of youth (ages 9-10) included in the Adolescent Brain Cognitive Development^SM Study, we identified four latent profiles of youth based on threats in their neighborhoods, families, and schools: low threat in all contexts, elevated family threat, elevated neighborhood threat, and elevated threat in all contexts. The elevated neighborhood threat and elevated all threat profiles showed lower behavioral performance on an emotional n-back task relative to low threat and elevated family threat profiles. Lower behavioral performance in the elevated neighborhood threat profile specifically was paralleled by lower executive network activity during a cognitive challenge. Moreover, among youth with lower executive network activity, higher probability of membership in the elevated neighborhood threat profile was associated with higher externalizing. Together, these results provide evidence that interactions between threats that are concentrated in youth's neighborhoods and attenuated executive network function may contribute to risk for externalizing problems.

Although increasing evidence links microbial dysbiosis with the risk for psychiatric symptoms through the microbiome-gut-brain axis (MGBA), the specific mechanisms remain poorly characterized. In a diagnostically heterogeneous group of treated psychiatric cases and nonpsychiatric controls, we characterized the gut and oral microbiome, plasma cytokines, and hippocampal inflammatory processes via proton magnetic resonance spectroscopic imaging (¹H-MRSI). Using a transdiagnostic approach, these data were examined in association with schizophrenia-related symptoms measured by the Positive and Negative Syndrome Scale (PANSS). Psychiatric cases had significantly greater heterogeneity of gut alpha diversity and an enrichment of pathogenic taxa, like Veillonella and Prevotella, in the oral microbiome, which was an accurate classifier of phenotype. Cases exhibited significantly greater positive, negative, and general PANSS scores that uniquely correlated with bacterial taxa. Strong, positive correlations of bacterial taxa were also found with cytokines and hippocampal gliosis, dysmyelination, and excitatory neurotransmission. This pilot study supports the hypothesis that the MGBA influences psychiatric symptomatology in a transdiagnostic manner. The relative importance of the oral microbiome in peripheral and hippocampal inflammatory pathways was highlighted, suggesting opportunities for probiotics and oral health to diagnose and treat psychiatric conditions.