Brain activity during reappraisal and associations with psychotherapy response in social anxiety and major depression: a randomized trial.

BACKGROUND: Cognitive behavioral therapy (CBT) is an effective treatment for patients with social anxiety disorder (SAD) or major depressive disorder (MDD), yet there is variability in clinical improvement. Though prior research suggests pre-treatment engagement of brain regions supporting cognitive reappraisal (e.g. dorsolateral prefrontal cortex [dlPFC]) foretells CBT response in SAD, it remains unknown if this extends to MDD or is specific to CBT. The current study examined associations between pre-treatment neural activity during reappraisal and clinical improvement in patients with SAD or MDD following a trial of CBT or supportive therapy (ST), a common-factors comparator arm. METHODS: Participants were 75 treatment-seeking patients with SAD (n = 34) or MDD (n = 41) randomized to CBT (n = 40) or ST (n = 35). Before randomization, patients completed a cognitive reappraisal task during functional magnetic resonance imaging. Additionally, patients completed clinician-administered symptom measures and a self-report cognitive reappraisal measure before treatment and every 2 weeks throughout treatment. RESULTS: Results indicated that pre-treatment neural activity during reappraisal differentially predicted CBT and ST response. Specifically, greater trajectories of symptom improvement throughout treatment were associated with less ventrolateral prefrontal cortex (vlPFC) activity for CBT patients, but more vlPFC activity for ST patients. Also, less baseline dlPFC activity corresponded with greater trajectories of self-reported reappraisal improvement, regardless of treatment arm. CONCLUSIONS: If replicated, findings suggest individual differences in brain response during reappraisal may be transdiagnostically associated with treatment-dependent improvement in symptom severity, but improvement in subjective reappraisal following psychotherapy, more broadly.

Low rate of performance validity failures among individuals with bipolar disorder.

OBJECTIVE: Assessing performance validity is imperative in both clinical and research contexts as data interpretation presupposes adequate participation from examinees. Performance validity tests (PVTs) are utilized to identify instances in which results cannot be interpreted at face value. This study explored the hit rates for two frequently used PVTs in a research sample of individuals with and without histories of bipolar disorder (BD). METHOD: As part of an ongoing longitudinal study of individuals with BD, we examined the performance of 736 individuals with BD and 255 individuals with no history of mental health disorder on the Test of Memory Malingering (TOMM) and the California Verbal Learning Test forced choice trial (CVLT-FC) at three time points. RESULTS: Undiagnosed individuals demonstrated 100% pass rate on PVTs and individuals with BD passed over 98% of the time. A mixed effects model adjusting for relevant demographic variables revealed no significant difference in TOMM scores between the groups, a = .07, SE = .07, p = .31. On the CVLT-FC, no clinically significant differences were observed (ps < .001). CONCLUSIONS: Perfect PVT scores were obtained by the majority of individuals, with no differences in failure rates between groups. The tests have approximately >98% specificity in BD and 100% specificity among non-diagnosed individuals. Further, nearly 90% of individuals with BD obtained perfect scores on both measures, a trend observed at each time point.

A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity.

The treatment of mood disorders, which can become a lifelong process, varies widely in efficacy between individuals. Most options to monitor mood rely on subjective self-reports and clinical visits, which can be burdensome and may not portray an accurate representation of what the individual is experiencing. A passive method to monitor mood could be a useful tool for those with these disorders. Some previously proposed models utilized sensors from smartphones and wearables, such as the accelerometer. This study examined a novel approach of processing accelerometer data collected from smartphones only while participants of the open-science branch of the BiAffect study were typing. The data were modeled by von Mises-Fisher distributions and weighted networks to identify clusters relating to different typing positions unique for each participant. Longitudinal features were derived from the clustered data and used in machine learning models to predict clinically relevant changes in depression from clinical and typing measures. Model accuracy was approximately 95%, with 97% area under the ROC curve (AUC). The accelerometer features outperformed the vast majority of clinical and typing features, which suggested that this new approach to analyzing accelerometer data could contribute towards unobtrusive detection of changes in depression severity without the need for clinical input.

Early Emergence of Rumination has no Association with Performance on a Non-affective Inhibitory Control Task.

Rumination is a vulnerability for depression and potentially linked to inhibitory control weaknesses. We aimed to replicate the association observed in adults between inhibitory control and rumination in adolescents, and to examine putative moderating roles of childhood maltreatment and perceived family cohesion in an adolescent sample at risk for depression due to familial/personal history. Ninety adolescents aged 11-17 (M = 14.6, SD = 1.8) completed self-report scales of rumination, maltreatment, and family cohesion, and performed a task assessing inhibitory control. Hierarchical regression models showed no significant relation between inhibitory control and moderator variables on rumination. However, adolescents who reported higher levels of maltreatment and who perceived lower family cohesion tended to indicate higher levels of rumination (BChilhood Maltreatment = 27.52, 95% CIs [5.63, 49.41], BFamily Cohesion = -0.40, 95% CIs [-0.65, -0.15]). These findings demonstrate an alternative understanding of factors that increase depression onset risk and recurrence in adolescents.

Early Life Trauma and Social Processing in HIV: The Role of Neuroendocrine Factors and Inflammation.

OBJECTIVE: Early life trauma (ELT) and HIV are associated with social processing deficits. In people with HIV (PWH), we examined whether facial emotion identification accuracy differs by ELT and whether neuroendocrine factors including cortisol, oxytocin (OT), and arginine vasopressin, and/or immune system measures play a role in the ELT-performance association. METHODS: We used secondary data from the placebo condition of a pharmacologic challenge study in PWH. Presence of ELT was measured with the Childhood Trauma Questionnaire (at least moderate experiences of sexual, physical, and/or emotional abuse). Social processing was measured with the Facial Emotion Perception Test (FEPT). Salivary immune system measures and cortisol were sampled across a 5-hour study session. Blood was collected at study session start (12 pm ) to measure OT and arginine vasopressin. We examined the association of ELT with FEPT and five biological moderators (from principal components analysis of 12 biomarkers) of ELT-FEPT associations. RESULTS: Of 58 PWH (42 men; mean [standard deviation] age = 33.7 [8.9] years), 50% endorsed ELT. ELT-exposed PWH demonstrated lower identification accuracy across all emotional expressions (unstandardized ß [ B ] = 0.13; standard error [SE] = 0.05; p = .021, d = 0.63) and had higher OT levels compared with ELT-unexposed PWH ( t(1,56) = 2.12, p = .039; d = 0.57). For total accuracy, an OT/C-reactive protein factor moderated the ELT-FEPT association ( B = 0.14; SE = 0.05; p = .014); accuracy was lower in ELT-exposed PWH versus ELT-unexposed PWH when the factor was low but not when high. Similar results were obtained for fearful, neutral, and happy faces ( p values < .05). Regardless of ELT, a myeloid migration (MCP-1/MMP-9) factor was associated with reduced accuracy ( p values < .05). CONCLUSIONS: Our pilot findings suggest that ELT may alter social processing in PWH, and OT and C-reactive protein may be a target for improving social processing in ELT-exposed PWH, and myeloid migration markers may be a target in PWH more generally.

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.

Cognitive subgroups and their longitudinal trajectories in bipolar disorder.

INTRODUCTION: Cognitive functioning in bipolar disorder is heterogeneous with evidence for multiple subgroups. However, cognitive subgroup change patterns over time remains unknown. While prior work suggests minimal differences in cognitive functioning patterns over time between those with bipolar disorder and controls, group-based analyses may obscure unique subgroup-based changes. MATERIAL AND METHODS: Participants diagnosed with bipolar disorder (I, II, NOS; n = 568) and unaffected controls (n = 234) completed baseline, one- and five-year neuropsychological assessments. Data reduction techniques were used to limit the number of neuropsychological variables. Bipolar disorder participant baseline neuropsychological data were entered into hierarchical cluster analyses and resultant clusters were entered in multilevel models, which tested for differences in baseline and longitudinal cognitive changes in cognition among the cluster groups and with controls. RESULTS: Results were consistent with bipolar disorder participants forming three subgroups with high (n = 209), mid (n = 259), and low (n = 100) cognition. These groups were associated with unique clinical characteristics. Multilevel models demonstrated that over a five-year period, the low group improved, relative to the high and mid groups, and with controls, in auditory memory. Over the five-year period, the mid group, in comparison with the high group, improved in visual memory; additionally, the high group remained stable, in comparison with a slight decline in the control group, in inhibitory control. CONCLUSION: These results demonstrate that cognition-based subgroups of bipolar disorder participants have minimal differences in their longitudinal course in relation to each other and with unaffected controls.

Social cognitive mechanisms in healthcare worker resilience across time during the pandemic.

PURPOSE: Healthcare workers are at increased risk for mental health problems during disasters such as the COVID-19 pandemic. Identifying resilience mechanisms can inform development of interventions for this population. The current study examined pathways that may support healthcare worker resilience, specifically testing enabling (social support enabled self-efficacy) and cultivation (self-efficacy cultivating support) models. METHODS: Healthcare workers (N = 828) in the Rocky Mountain West completed self-report measures at four time points (once per month from April to July of 2020). We estimated structural equation models to explore the potential mediating effects that received social support and coping self-efficacy had (at time 2 and time 3) between traumatic stress symptom severity (at time 1 and time 4). Models included covariates gender, age, minority status, and time lagged co-variations between the proposed mediators (social support and coping self-efficacy). RESULTS: The full model fit the data well, CFI = .993, SRMR = .027, RMSEA = .036 [90% CIs (0.013, 0.057)]. Tests of sequential mediation supported enabling model dynamics. Specifically, the effects of time 1 traumatic stress severity were mediated through received social support at time 2 and time 3 coping self-efficacy, in sequential order to reduce time 4 traumatic stress severity. CONCLUSIONS: Findings show the importance of received social support and coping self-efficacy in mitigating psychopathology risk. Interventions can support mental health by focusing on social resource engagement that facilitates coping empowerment, which may decrease risk for mental health job-related problems among frontline healthcare workers exposed to highly stressful events.

Sex-specific effects of low-dose hydrocortisone on threat detection in HIV.

One sex differences in the perception of emotion is that females, particularly those with high anxiety, often show heightened identification of fearful faces. To better understand the causal role of glucocorticoids in this sex difference, we examine these associations in people with HIV(PWH) where emotion perception is impaired and mental health disorders are frequent. In a double-blind, placebo-controlled, cross-over study, we used a single low-dose of hydrocortisone (10 mg; LDH) as a mechanistic probe of the effects of elevated glucocorticoids on negative emotion perception in 65 PWH (31 women). The primary outcome was accuracy in identifying emotional expressions on the Facial Emotion Perception Test (FEPT). Salivary cortisol, self-reported stress/anxiety, and childhood trauma were also assessed. LDH increased salivary cortisol levels versus placebo. The effect of LDH versus placebo on FEPT accuracy depended on the combined influence of facial expression and sex (P = 0.03). LDH influenced accuracy only for women (P = 0.03), specifically for fearful faces (Cohen's d = 0.44, P = 0.04). Women's enhanced threat detection varied with psychological burden (mood, anxiety, and post-traumatic stress symptoms), more pronounced among those with lower burden and trauma (P < 0.05). This result suggests a role of the HPA axis in sex differences for perception of fearful faces in women with HIV, potentially due to changes in glucocorticoid receptor availability/activity, or improved integration of signals from facial recognition and emotion processing regions. The blunting of this effect in men and in individuals with more severe trauma suggests that the mechanisms underlying threat detection differ by sex and trauma history and warrant further investigation.

Resting state functional connectivity correlates of rumination and worry in internalizing psychopathologies.

BACKGROUND: Rumination and worry are repetitive negative thinking (RNT) tendencies that contribute to the development and maintenance of internalizing psychopathologies. Accruing data suggest rumination and worry represent overlapping and unique transdiagnostic cognitive processes. Yet, prior neuroimaging research has mostly focused on rumination in depression, which points to involvement of resting-state brain activity in default mode, executive, salience, and/or affective networks. METHODS: The current study examined relations between brain activity during rest and RNT in a transdiagnostic sample. Resting-state fMRI data was analyzed in 80 unmedicated patients with internalizing conditions. Regression analysis, controlling for anxiety and depression symptoms, was performed with seed regions implicated in default mode, executive, salience, and affective networks. Rumination and worry were assessed with standard self-report measures. RESULTS: Whole-brain regression results showed more rumination and worry jointly corresponded with greater positive resting-state functional connectivity (rsFC) between the amygdala and prefrontal regions (i.e., middle frontal gyrus, inferior frontal gyrus). Conversely, more worry (controlling for rumination) corresponded with greater negative rsFC between amygdala and precuneus. No significant results were observed for rumination alone (controlling for worry). CONCLUSIONS: Findings indicate the affective network plays a role in RNT, and distinct patterns of connectivity between amygdala and regions implicated in the executive and default mode networks were observed across patients with internalizing conditions. Results suggest different mechanisms contribute to RNT as a unitary construct and worry as a unique construct.

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.

A Lifespan Model of Interference Resolution and Inhibitory Control: Risk for Depression and Changes with Illness Progression.

The cognitive processes involved in inhibitory control accuracy (IC) and interference resolution speed (IR) or broadly - inhibition - are discussed in this review, and both are described within the context of a lifespan model of mood disorders. Inhibitory control (IC) is a binary outcome (success or no for response selection and inhibition of unwanted responses) for any given event that is influenced to an extent by IR. IR refers to the process of inhibition, which can be manipulated by task design in earlier and later stages through use of distractors and timing, and manipulation of individual differences in response proclivity. We describe the development of these two processes across the lifespan, noting factors that influence this development (e.g., environment, adversity and stress) as well as inherent difficulties in assessing IC/IR prior to adulthood (e.g., cross-informant reports). We use mood disorders as an illustrative example of how this multidimensional construct can be informative to state, trait, vulnerability and neuroprogression of disease. We present aggregated data across numerous studies and methodologies to examine the lifelong development and degradation of this subconstruct of executive function, particularly in mood disorders. We highlight the challenges in identifying and measuring IC/IR in late life, including specificity to complex, comorbid disease processes. Finally, we discuss some potential avenues for treatment and accommodation of these difficulties across the lifespan, including newer treatments using cognitive remediation training and neuromodulation.

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders.

BACKGROUND: Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk. METHODS: Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups. RESULTS: Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%). CONCLUSIONS: These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.

Transdiagnostic neural correlates of volitional emotion regulation in anxiety and depression.

BACKGROUND: Individuals who suffer from anxiety and/or depression face difficulty in adaptively managing emotional responses, while accumulating evidence suggests impaired emotion regulation is a transdiagnostic feature of psychopathology. Effectual regulation in the context of negative stimuli is characterized by engagement of the prefrontal cortex (PFC) coupled with reduced amygdala reactivity. In anxiety disorders and major depression, PFC underengagement and atypical PFC-amygdala connectivity has been observed, although patient findings based on case-control studies have been mixed with regard to magnitude, locality, and extent of dysfunction. As anxiety disorders and major depression are heterogeneous disorders and frequently comorbid with one another, delineating relationships between reappraise-related substrates and symptoms may advance our understanding of emotion dysregulation in these populations. METHODS: We examined PFC activation and its functional connectivity (FC) to the amygdala using functional magnetic resonance imaging in a large sample of patients (N = 174) with primary generalized anxiety disorder (n = 47), social anxiety disorder (n = 78), or major depressive disorder (n = 49) during a reappraisal-based emotion regulation task. Comorbidity was permitted and the majority of participants had a concurrent psychiatric illnesses. RESULTS: Across participants, whole-brain results showed that (1) greater anxiety and depression symptom severity was related to less engagement of the dorsal anterior cingulate cortex (ACC) and (2) less FC between the amygdala and ventrolateral PFC. Results were driven by anxiety, while depression symptoms were not significant. CONCLUSION: These findings demonstrate that individual differences in anxiety and depression may help explain ACC and PFC dysfunction during emotion regulation observed across anxiety and depressive disorders.

Developmental changes in resting-state functional networks among individuals with and without internalizing psychopathologies.

BACKGROUND: Three well-established intrinsic connectivity networks (ICNs) involved in cognitive-affective processing include the cognitive control network (CCN), default mode network (DMN), and salience and emotional network (SEN). Despite recent advances in understanding developmental changes in these ICNs, the majority of research has focused on single seeds or networks in isolation with limited age ranges. Additionally, although internalizing psychopathologies (IPs), such as anxiety and depression, are often characterized by maladaptive cognitive-affective processing styles, it is not clear how IP history influences age-related changes in brain networks. METHOD: The current study aimed to characterize the normative development of the CCN, DMN, and SEN across a large age-span (7-29 year olds) of typically developing (TD) individuals (n = 97). We also explore how age may impact differences in network connectivity between TD individuals and patients with IPs (n = 136). RESULTS: Among TD individuals, DMN and CCN connectivity strengthened with age, whereas connectivity between the SEN and ventromedial prefrontal cortex weakened across development. When exploring group (IP vs. TD) differences, the IP group was characterized by greater connectivity between the CCN and cerebellum and between the SEN and caudate from childhood to early adulthood, relative to TD individuals. In addition, patients with IPs, versus TD individuals, exhibited reduced connectivity between the SEN and medial frontal gyrus from adolescence to adulthood. CONCLUSIONS: The current findings shed light on differential age-related changes in brain network patterns among psychiatrically free, TD individuals and those with internalizing disorders, and may provide plausible targets for novel mechanism-based treatments that differ based on developmental stage.

Self-reported affective biases, but not all affective performance biases, are present in depression remission.

OBJECTIVE: Individuals with active major depressive disorder (MDD) have shown affective biases in cognitive flexibility and memory, particularly for negatively valenced stimuli. We evaluated whether impairments in affective flexibility would remain even during remission (rMDD), potentially representing trait- or scar-like effects of illness. METHOD: Participants completed the Emotion Card Sort Test (ECST), a measure of cognitive flexibility containing emotionally valenced stimuli, and the Emotion Word Stimulus Test (EWST), a measure of affective biases in delayed recall and recognition memory, and several self-report measures. RESULTS: Healthy controls (HCs; n = 35) and individuals with rMDD (n = 93) did not differ on performance for any of the three word types on the ECST or EWT. However, individuals with rMDD demonstrated greater negative bias on EWT recognition trials relative to HCs (d = .36). On self-report measures, individuals with rMDD exhibited greater levels of neuroticism, problems with attentional control, pessimistic attributional style, and negative automatic thoughts compared to HCs. CONCLUSIONS: These results provide initial evidence that some performance, but not self-reported, indices of affective bias may improve during remission from MDD. Results of this study could suggest that some components of affective bias may represent state feature of illness and others trait-like risk or scar features. PRACTITIONER POINTS: This study suggests that self-reported affective biases may persist in remission of major depressive disorder (rMDD). Affective attentional biases and affective memory biases were not demonstrated in individuals with rMDD, with the exception of a bias for recognizing negatively versus neutrally valenced stimuli. CAUTIONS OR LIMITATIONS: A limitation of this study was its cross-sectional design. Under ideal conditions, the same individuals would be studied in both the active and remitted phases of illness. Another limitation of this study was the smaller number of healthy controls relative to individuals with rMDD.

Cluster analysis with MOODS-SR illustrates a potential bipolar disorder risk phenotype in young adults with remitted major depressive disorder.

OBJECTIVES: Delays in the diagnosis and detection of bipolar disorder can lead to adverse consequences, including improper treatment and increased suicide risk. The Mood Spectrum Self-Report Measure (MOODS-SR) was designed to capture the full spectrum of lifetime mood symptomology with factor scores for depression and mania symptom constellations. The utility of the MOODS-SR as a tool to investigate homogeneous subgroups was examined, with particular focus on a possible bipolar risk subgroup. Moreover, potential patterns of differences in MOODS-SR subtypes were probed using cognitive vulnerabilities, neuropsychological functioning, and ventral striatum connectivity. METHODS: K-mean cluster analysis based on factor scores of MOODS-SR was used to determine homogeneous subgroupings within a healthy and remitted depressed young adult sample (N = 86). Between-group comparisons (based on cluster subgroupings) were conducted on measures of cognitive vulnerabilities, neuropsychological functioning, and ventral striatum rs-fMRI connectivity. RESULTS: Three groups of participants were identified: one with minimal symptomology, one with moderate primarily depressive symptomology, and one with more severe manic and depressive symptomology. Differences in impulsivity, neuroticism, conscientiousness, facial perception accuracy, and rs-fMRI connectivity exist between moderate and severe groups. CONCLUSIONS: Within a sample of people with and without depression histories, a severe subgroup was identified with potentially increased risk of developing bipolar disorder through use of the MOODS-SR. This small subgroup had higher levels of lifetime depression and mania symptoms. Additionally, differences in traits, affective processing, and connectivity exist between those with a more prototypic unipolar subgrouping and those with potential risk for developing bipolar disorder.

Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI.

Predicting treatment response for major depressive disorder can provide a tremendous benefit for our overstretched health care system by reducing number of treatments and time to remission, thereby decreasing morbidity. The present study used neural and performance predictors during a cognitive control task to predict treatment response (% change in Hamilton Depression Rating Scale pre- to post-treatment). Forty-nine individuals diagnosed with major depressive disorder were enrolled with intent to treat in the open-label study; 36 completed treatment, had useable data, and were included in most data analyses. Participants included in the data analysis sample received treatment with escitalopram (n = 22) or duloxetine (n = 14) for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent reduction in Hamilton Depression Rating Scale scores after treatment. Haemodynamic response function-based contrasts and task-related independent components analysis (subset of sample: n = 29) were predictors. Independent components analysis component beta weights and haemodynamic response function modelling activation during Commission errors in the rostral and dorsal anterior cingulate, mid-cingulate, dorsomedial prefrontal cortex, and lateral orbital frontal cortex predicted treatment response. In addition, more commission errors on the task predicted better treatment response. Together in a regression model, independent component analysis, haemodynamic response function-modelled, and performance measures predicted treatment response with 90% accuracy (compared to 74% accuracy with clinical features alone), with 84% accuracy in 5-fold, leave-one-out cross-validation. Convergence between performance markers and functional magnetic resonance imaging, including novel independent component analysis techniques, achieved high accuracy in prediction of treatment response for major depressive disorder. The strong link to a task paradigm provided by use of independent component analysis is a potential breakthrough that can inform ways in which prediction models can be integrated for use in clinical and experimental medicine studies.

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.

Attenuated intrinsic connectivity within cognitive control network among individuals with remitted depression: Temporal stability and association with negative cognitive styles.

Many individuals with major depressive disorder (MDD) experience cognitive dysfunction including impaired cognitive control and negative cognitive styles. Functional connectivity magnetic resonance imaging studies of individuals with current MDD have documented altered resting-state connectivity within the default-mode network and across networks. However, no studies to date have evaluated the extent to which impaired connectivity within the cognitive control network (CCN) may be present in remitted MDD (rMDD), nor have studies examined the temporal stability of such attenuation over time. This represents a major gap in understanding stable, trait-like depression risk phenotypes. In this study, resting-state functional connectivity data were collected from 52 unmedicated young adults with rMDD and 47 demographically matched healthy controls, using three bilateral seeds in the CCN (dorsolateral prefrontal cortex, inferior parietal lobule, and dorsal anterior cingulate cortex). Mean connectivity within the entire CCN was attenuated among individuals with rMDD, was stable and reliable over time, and was most pronounced with the right dorsolateral prefrontal cortex and right inferior parietal lobule, results that were corroborated by supplemental independent component analysis. Attenuated connectivity in rMDD appeared to be specific to the CCN as opposed to representing attenuated within-network coherence in other networks (e.g., default-mode, salience). In addition, attenuated connectivity within the CCN mediated relationships between rMDD status and cognitive risk factors for depression, including ruminative brooding, pessimistic attributional style, and negative automatic thoughts. Given that these cognitive markers are known predictors of relapse, these results suggest that attenuated connectivity within the CCN could represent a biomarker for trait phenotypes of depression risk. Hum Brain Mapp 38:2939-2954, 2017. © 2017 Wiley Periodicals, Inc.