Limited time-specific and longitudinal effects of depressive and manic symptoms on cognition in bipolar spectrum disorders.

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.

Mechanisms of rumination change in adolescent depression (RuMeChange): study protocol for a randomised controlled trial of rumination-focused cognitive behavioural therapy to reduce ruminative habit and risk of depressive relapse in high-ruminating adolescents.

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.

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study.

BACKGROUND: Mood disorders are common and associated with significant morbidity and mortality. Better tools are needed for their diagnosis and treatment. Deeper phenotypic understanding of these disorders is integral to the development of such tools. This study is the first effort to use passively collected mobile phone keyboard activity to build deep digital phenotypes of depression and mania. OBJECTIVE: The objective of our study was to investigate the relationship between mobile phone keyboard activity and mood disturbance in subjects with bipolar disorders and to demonstrate the feasibility of using passively collected mobile phone keyboard metadata features to predict manic and depressive signs and symptoms as measured via clinician-administered rating scales. METHODS: Using a within-subject design of 8 weeks, subjects were provided a mobile phone loaded with a customized keyboard that passively collected keystroke metadata. Subjects were administered the Hamilton Depression Rating Scale (HDRS) and Young Mania Rating Scale (YMRS) weekly. Linear mixed-effects models were created to predict HDRS and YMRS scores. The total number of keystrokes was 626,641, with a weekly average of 9791 (7861), and that of accelerometer readings was 6,660,890, with a weekly average 104,076 (68,912). RESULTS: A statistically significant mixed-effects regression model for the prediction of HDRS-17 item scores was created: conditional R2=.63, P=.01. A mixed-effects regression model for YMRS scores showed the variance accounted for by random effect was zero, and so an ordinary least squares linear regression model was created: R2=.34, P=.001. Multiple significant variables were demonstrated for each measure. CONCLUSIONS: Mood states in bipolar disorder appear to correlate with specific changes in mobile phone usage. The creation of these models provides evidence for the feasibility of using passively collected keyboard metadata to detect and monitor mood disturbances.

Equivalent linear change in cognition between individuals with bipolar disorder and healthy controls over 5 years.

OBJECTIVES: Cognitive dysfunction is a key feature of bipolar disorder (BD). However, not much is known about its temporal stability, as some studies have demonstrated a neurodegenerative model in BD while others have shown no change in cognitive functioning over time. Building upon our prior work, which examined the natural course of executive functioning, the current study aimed to investigate the natural course of memory, emotion processing, and fine motor dexterity over a 5-year period in BD and healthy control (HC) samples. METHODS: Using a 5-year longitudinal cohort, 90 individuals with BD and 17 HCs were administered a battery of neuropsychological tests at study baseline and at 1 and 5 years after study entry that captured four areas of cognitive performance: visual memory, auditory memory, emotion processing, and fine motor dexterity. RESULTS: Latent growth curve modeling showed no group differences in the slopes of any of the cognitive factors between the BD and HC groups. Age at baseline was negatively associated with visual memory, emotion processing, and fine motor dexterity. Education level was positively associated with auditory and visual memory and fine motor. Female gender was negatively associated with emotion processing. CONCLUSIONS: Extending our prior work on longitudinal evaluation of executive functioning, individuals with BD show similar linear change in other areas of cognitive functioning including memory, emotion processing, and fine motor dexterity as compared to unaffected HCs. Age, education, and gender may have some differential effects on cognitive changes.

Influence of cognitive reserve on neuropsychological functioning in bipolar disorder: Findings from a 5-year longitudinal study.

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.

Relations of gray matter volume to dimensional measures of cognition and affect in mood disorders.

Understanding the relationship between brain measurements and behavioral performance is an important step in developing approaches for early identification of any psychiatric difficulties and interventions to modify these challenges. Conventional methods to identify associations between regional brain volume and behavioral measures are not optimized, either in scale, scope, or specificity. To find meaningful associations between brain and behavior with greater sensitivity and precision, we applied data-driven factor analytic models to identify and extract individual differences in latent cognitive functions embedded across several computerized cognitive tasks. Furthermore, we simultaneously utilized a keyword-based neuroimaging meta-analytic tool (i.e., NeuroSynth), restricted atlas-parcel matching, and factor-analytic models to narrow down the scope of search and to further aggregate gray matter volume (GMV) data into empirical clusters. We recruited an early adult community cross-sectional sample (Total n = 177, age 18-30) that consisted of individuals with no history of any mood disorder (healthy controls, n = 44), those with remitted major depressive disorder (rMDD, n = 104), and those with a diagnosis of bipolar disorder currently in euthymic state (eBP, n = 29). Study participants underwent structural magnetic resonance imaging (MRI) scans and separately completed behavioral testing using computerized measures. Factor-analyzing five computerized tasks used to assess aspects of cognitive and affective processing resulted in seven latent dimensions: (a) Emotional Memory, (b) Interference Resolution, (c) Reward Sensitivity, (d) Complex Inhibitory Control, (e) Facial Emotion Sensitivity, (f) Sustained attention, and (g)Simple Impulsivity/Response Style. These seven dimensions were then labeled with specific keywords which were used to create neuroanatomical maps using NeuroSynth. These masks were further subdivided into GMV clusters. Using regression, we identified GMV clusters that were predictive of individual differences across each of the aforementioned seven cognitive dimensions. We demonstrate that a dimensional approach consistent with core principles of RDoC can be utilized to identify structural variability predictive of critical dimensions of human behavior.

Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control.

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.

A Smartphone App to Monitor Mood Symptoms in Bipolar Disorder: Development and Usability Study.

BACKGROUND: There is considerable scientific interest in finding new and innovative ways to capture rapid fluctuations in functioning within individuals with bipolar disorder (BD), a severe, recurrent mental disorder associated with frequent shifts in symptoms and functioning. The use of smartphones can provide valid and real-world tools for use in measurement-based care and could be used to inform more personalized treatment options for this group, which can improve standard of care. OBJECTIVE: We examined the feasibility and usability of a smartphone to capture daily fluctuations in mood within BD and to relate daily self-rated mood to smartphone use behaviors indicative of psychomotor activity or symptoms of the illness. METHODS: Participants were 26 individuals with BD and 12 healthy control individuals who were recruited from the Prechter Longitudinal Study of BD. All were given a smartphone with a custom-built app and prompted twice a day to complete questions of mood for 28 days. The app automatically and unobtrusively collected phone usage data. A poststudy satisfaction survey was also completed. RESULTS: Our sample showed a very high adherence rate to the daily momentary assessments (91% of the 58 prompts completed). Multivariate mixed effect models showed that an increase in rapid thoughts over time was associated with a decrease in outgoing text messages (ß=-.02; P=.04), and an increase in impulsivity self-ratings was related to a decrease in total call duration (ß=-.29; P=.02). Participants generally reported positive experiences using the smartphone and completing daily prompts. CONCLUSIONS: Use of mobile technology shows promise as a way to collect important clinical information that can be used to inform treatment decision making and monitor outcomes in a manner that is not overly burdensome to the patient or providers, highlighting its potential use in measurement-based care.

Decreased working memory capacity among individuals with a mood disorder who have increased metabolic burden.

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.