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Introduction: The phenotypic expression of mental health (MH) conditions among people with HIV (PWH) in Uganda and worldwide are heterogeneous. Accordingly, there has been a shift toward identifying MH phenotypes using data-driven methods capable of identifying novel insights into mechanisms of divergent MH phenotypes among PWH. We leverage the analytic strengths of machine learning combined with inferential methods to identify novel MH phenotypes among PWH and the underlying explanatory features., Methods: A total of 277 PWH (46% female, median age = 44; 93% virally suppressed [<50copies/mL]) were included in the analyses. Participants completed the Patient Health Questionnaire (PHQ-9), Beck Anxiety Inventory (BAI), and the PTSD Checklist-Civilian (PCL-C). A clustering pipeline consisting of dimension reduction with UMAP followed by HBDScan was used to identify MH subtypes using total symptom scores. Inferential statistics compared select demographic (age, sex, education), viral load, and early life adversity between clusters., Results: We identified four MH phenotypes. Cluster 1 ( n  = 76; PTSD phenotype ) endorsed clinically significant PTSD symptoms (average PCL-C total score > 33). Clusters 2 ( n  = 32; anxiety phenotype ) and 3 ( n  = 130; mixed anxiety/depression phenotype ) reported minimal PTSD symptoms, with modest BAI (Cluster 2) and PHQ-9 (Cluster 3) elevations. Cluster 4 ( n  = 39; minimal symptom phenotype ) reported no clinical MH symptom elevations. Comparisons revealed higher rates of sexual abuse during childhood among the PTSD phenotype vs. the minimal symptom phenotype ( p  = 0.03)., Discussion: We identified unique MH phenotypes among PWH and confirmed the importance of early life adversity as an early risk determinant for unfavorable MH among PWH in adulthood., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2025 Rubin, Cho, Bolzenius, Mannarino, Easter, Dastgheyb, Anok, Tomusange, Saylor, Wawer, Nakasujja, Nakigozi and Paul.)

Objectives: Previous research suggests that cognitive performance worsens during manic and depressed states in bipolar disorder (BD). However, studies have often relied upon between-subject, cross-sectional analyses and smaller sample sizes. The current study examined the relationship between mood symptoms and cognition in a within-subject, longitudinal study with a large sample., Methods: Seven hundred and seventy-three individuals with BD completed a neuropsychological battery and mood assessments at baseline and 1-year follow-up. The battery captured eight domains of cognition: fine motor dexterity, visual memory, auditory memory, emotion processing, and four aspects of executive functioning: verbal fluency and processing speed; conceptual reasoning and set shifting; processing speed with influence resolution; and inhibitory control. Structural equation modeling was conducted to examine the cross-sectional and longitudinal relationships between depressive symptoms, manic symptoms, and cognitive performance. Age and education were included as covariates. Eight models were run with the respective cognitive domains., Results: Baseline mood positively predicted 1-year mood, and baseline cognition positively predicted 1-year cognition. Mood and cognition were generally not related for the eight cognitive domains. Baseline mania was predictive in one of eight baseline domains (conceptual reasoning and set shifting); baseline cognition predicted 1-year symptoms (inhibitory control-depression symptoms, visual memory-manic symptoms)., Conclusions: In a large community sample of patients with bipolar spectrum disorder, cognitive performance appears to be largely unrelated to depressive and manic symptoms, suggesting that cognitive dysfunction is stable in BD and is not dependent on mood state in BD. Future work could examine how treatment affects relationship between cognition and mood., Significant Outcomes: Cognitive dysfunction appears to be largely independent of mood symptoms in bipolar disorder., Limitations: The sample was generally highly educated (M = 15.22), the majority of the subsample with elevated manic symptoms generally presented with concurrent depressive elevated symptoms, and the study did not stratify recruitment based on mood state., (© 2022 The Authors. Acta Psychiatrica Scandinavica published by John Wiley & Sons Ltd.)

Background: Resting-state graph-based network edges can be powerful tools for identification of mood disorders. We address whether these edges can be integrated with Research Domain Criteria (RDoC) constructs for accurate identification of mood disorder-related markers, while minimizing active symptoms of disease., Methods: We compared 132 individuals with currently remitted or euthymic mood disorder with 65 healthy comparison participants, ages 18-30 years. Subsets of smaller brain parcels, combined into three prominent networks and one network of parcels overlapping across these networks, were used to compare edge differences between groups. Consistent with the RDoC framework, we evaluated individual differences with performance measure regressors of inhibitory control and reward responsivity. Within an omnibus regression model, we predicted edges related to diagnostic group membership, performance within both RDoC domains, and relevant interactions., Results: There were several edges of mood disorder group, predominantly of greater connectivity across networks, different than those related to individual differences in inhibitory control and reward responsivity. Edges related to diagnosis and inhibitory control did not align well with prior literature, whereas edges in relation to reward responsivity constructs showed greater alignment with prior literature. Those edges in interaction between RDoC constructs and diagnosis showed a divergence for inhibitory control (negative interactions in default mode) relative to reward (positive interactions with salience and emotion network)., Conclusions: In conclusion, there is evidence that prior simple network models of mood disorders are currently of insufficient biological or diagnostic clarity or that parcel-based edges may be insufficiently sensitive for these purposes., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Adolescent-onset depression often results in a chronic and recurrent course, and is associated with worse outcomes relative to adult-onset depression. Targeting habitual depressive rumination, a specific known risk factor for relapse, may improve clinical outcomes for adolescents who have experienced a depressive episode. Randomized controlled trials (RCTs) thus far have demonstrated that rumination-focused cognitive behavioral therapy (RFCBT) reduces depressive symptoms and relapse rates in patients with residual depression and adolescents and young adults with elevated rumination. This was also observed in a pilot RCT of adolescents at risk for depressive relapse. Rumination can be measured at the self-report, behavioral, and neural levels- using patterns of connectivity between the Default Mode Network (DMN) and Cognitive Control Network (CCN). Disrupted connectivity is a putative important mechanism for understanding reduced rumination via RFCBT. A feasibility trial in adolescents found that reductions in connectivity between DMN and CCN regions following RFCBT were correlated with change in rumination and depressive symptoms., Method: This is a phase III two-arm, two-stage, RCT of depression prevention. The trial tests whether RFCBT reduces identified risk factors for depressive relapse (rumination, patterns of neural connectivity, and depressive symptoms) in adolescents with partially or fully remitted depression and elevated rumination. In the first stage, RFCBT is compared to treatment as usual within the community. In the second stage, the comparator condition is relaxation therapy. Primary outcomes will be (a) reductions in depressive rumination, assessed using the Rumination Response Scale, and (b) reductions in resting state functional magnetic resonance imaging connectivity of DMN (posterior cingulate cortex) to CCN (inferior frontal gyrus), at 16 weeks post-randomization. Secondary outcomes include change in symptoms of depression following treatment, recurrence of depression over 12 months post-intervention period, and whether engagement with therapy homework (as a dose measure) is related to changes in the primary outcomes., Discussion: RFCBT will be evaluated as a putative preventive therapy to reduce the risk of depressive relapse in adolescents, and influence the identified self-report, behavioral, and neural mechanisms of change. Understanding mechanisms that underlie change in rumination is necessary to improve and further disseminate preventive interventions., Trial Registration: ClinicalTrials.gov Identifier: NCT03859297 , registered 01 March 2019.

Background: Individuals with mood disorders experience a higher rate of obesity than the general population, putting them at risk for poorer outcomes. The relationship between obesity and a core feature of the mood disorders, neurocognition, is less understood. We examined the interaction of obesity as indexed by body mass index (BMI) and working memory performance in a large sample of individuals with bipolar disorder (BD), major depressive disorder (MDD), and healthy controls (HC)., Methods: Participants with BD (n = 133), MDD (n = 78), and HC (n = 113) (age range 18-40) completed a spatial working memory (SWM) task that included three-graded increases in the number of target locations. Participants were subdivided by BMI classification into six diagnostic-BMI (BMI groups: Normal Weight, Overweight/Obese) subgroups. Performance on the task was indexed by number of errors within each difficulty level., Results: The number of errors, across all groups, increased with task difficulty. There was an interaction between errors and diagnostic-BMI group. Post-hoc analyses indicated that while the Normal Weight-BD group did not differ in performance from the other groups, the Overweight/Obese-BD group performed significantly worse than HC groups., Limitations: Metabolic effects of psychotropic medications due to the naturalistic nature of the study, younger age of the MDD sample, and utilizing self-reported indicators of obesity may limit generalizability., Conclusions: Individuals with BD with increased metabolic burden exhibit increased working memory errors than non-psychiatric controls who also have increased metabolic burden. Future work could address prevention and amelioration of such difficulties to reduce associated functional morbidity., Competing Interests: Declaration of Competing Interest Dr. Marshall, Dr. Ryan, Ms. Lamping, Ms. Easter, and Ms. Babu report no competing interests Dr. Langenecker has served as a consultant for Cogstate, Ltd, EPI-Q, and Easter Seals, Inc, in work unrelated to the present work. Dr. McInnis has affiliations with Janssen Pharmaceuticals, (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objectives: The present study examined the 5-year longitudinal course of cognitive functioning in a large sample of well-characterized patients with bipolar disorder (BP), compared to healthy controls (HCs), and the influence of cognitive reserve factors (e.g., education and IQ) on cognitive change over time., Methods: Participants included 159 individuals diagnosed with BP and 54 HCs recruited as part of a longitudinal naturalistic study of BP who had completed neuropsychological testing at the time of their enrollment and again 5 years later., Results: The overall relative rate of change did not differ between the BP and HC groups. In total, 46.5% of the BP group and 37% of the HC group showed evidence of decline on at least one measure over time. T-test analyses did not find differences between BP 'decliners' and 'non-decliners' in cognitive reserve variables. However, we found that higher baseline intellectual ability was associated with more stability in cognitive test scores over time for the BP group. Results of linear regression modeling revealed that lower verbal IQ and education were related to increased cognitive decline in specific domains in the BP group., Conclusions: This study has explored the influence of cognitive reserve on preservation of specific cognitive abilities over time in BP. The BP group did not demonstrate accelerated cognitive decline over 5 years compared to the HC group. Although the trajectory of cognitive change over time was similar between BP patients and HCs, higher overall intellectual ability may be a protective factor against cognitive decline, particularly for BP patients., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)