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.

Association of Changes in Neural Targets and Dietary Outcomes among Patients with Comorbid Obesity and Depression: Post hoc Analysis of ENGAGE-2 Mechanistic Clinical Trial.

BACKGROUND: Disruptions in brain circuits that regulate cognition and emotion can hinder dietary change and weight loss among individuals with obesity and depression. OBJECTIVE: The study aimed to investigate whether changes in brain targets in the cognitive control, negative affect, and positive affect circuits after 2-mo problem-solving therapy (PST) predict changes in dietary outcomes at 2 and 6 mo. METHODS: Adults with obesity and depression from an academic health system were randomly assigned to receive PST (7-step problem-solving and behavioral activation strategies) over 2 mo or usual care. Seventy participants (mean age = 45.9 ± 11.6 y; 75.7% women, 55.7% Black, 17.1% Hispanic, 20.0% White; mean BMI = 36.5 ± 5.3 kg/m2; mean Patient Health Questionnaire-9 depression score = 12.7 ± 2.8) completed functional MRI and 24-h food recalls. Ordinary least square regression analyses were performed. RESULTS: Among intervention participants, increased left dorsal lateral prefrontal cortex (dLPFC) activity of the cognitive control circuit at 2 mo was associated with increased diet quality (ß: 0.20; 95% CI: -0.02, 0.42) and decreased calories (ß: -0.19; 95% CI: -0.33, -0.04), fat levels (ß: -0.22; 95% CI: -0.39, -0.06), and high-sugar food intake (ß: -0.18; 95% CI: -0.37, 0.01) at 6 mo. For the negative affect circuit, increased right dLPFC-amygdala connectivity at 2 mo was associated with increased diet quality (ß: 0.32; 95% CI: -0.93, 1.57) and fruit and vegetable intake (ß: 0.38; 95% CI: -0.75, 1.50) and decreased calories (ß: -0.37; 95% CI: -1.29, 0.54), fat levels (ß: -0.37; 95% CI: -1.50, 0.76), sodium concentrations (ß: -0.36; 95% CI: -1.32, 0.60), and alcohol intake (ß: -0.71; 95% CI: -2.10, 0.68) at 2 but not at 6 mo. The usual care group showed opposing associations. The 95% CIs of all between-group differences did not overlap the null, suggesting a significant treatment effect. CONCLUSIONS: Among adults with obesity and depression who underwent PST compared with those under usual care, improved dLPFC-amygdala regulation of negative affective brain states predicted dietary improvements at 2 mo, whereas improvements in dLPFC-based cognitive control predicted dietary improvements at 6 mo. These findings warrant confirmatory studies. This trial was at clinicaltrials.gov as NCT03841682.

Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies.

Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.

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.

Brain response to emotional faces in anxiety and depression: neural predictors of cognitive behavioral therapy outcome and predictor-based subgroups following therapy.

BACKGROUND: Neuroimaging studies have shown variance in brain response to emotional faces predicts cognitive behavioral therapy (CBT) outcome. An important next step is to determine if individual differences in neural predictors of CBT response represent distinct patient groups. METHODS: In total, 90 patients with internalizing disorders completed a face-matching task during functional magnetic resonance imaging before and after 12 weeks of CBT and 45 healthy controls completed the task before and after 12 weeks. Patients exhibiting a pre-to-post CBT >50% reduction in symptom severity on two measures were considered treatment responders. Regions of interest (ROIs) for angry, fearful, and happy faces were submitted to receiver operating characteristic (ROC) curve analysis. Significant ROIs were then submitted to decision tree analysis to classify responder/non-responder subgroups. Psychophysiological interactions (PPI) were used to explore functional connectivity in the region(s) that delineated subgroups. RESULTS: A total of 51 patients were treatment responders and ROC curve results were significant for all face types though specific regions varied. Decision tree results revealed superior occipital response to angry faces identified patient subgroups such that the subgroup with 'high' occipital activity had more responders than the 'low' occipital subgroup. Following CBT, the high, relative to low, occipital subgroup was less symptomatic. Controls exhibited stable superior occipital activation over time. Whole-brain PPI showed reduced baseline superior occipital-postcentral gyrus functional connectivity in responders compared to non-responders. CONCLUSIONS: Preliminary findings indicate patients characterized by relatively more pre-treatment superior occipital gyrus engagement to angry faces and reduced superior occipital-postcentral gyrus connectivity, relative to non-responders, may represent a phenotype likely to benefit from CBT.

Impact of interventions targeting anxiety and depression in adults with asthma.

OBJECTIVE: High rates of anxiety and depression exist among asthma patient populations. This scoping review will examine the existing interventional therapies that address depression and anxiety symptoms in patients with asthma. DATA SOURCES: PubMed, Cochrane, Psychinfo, CINAHL, Google Scholar and EMBASE databases were searched using the following search terms: 'anxiety asthma', 'panic disorder asthma' and 'depression asthma' with a randomized clinical trial filter and additional filters to exclude exclusion criteria. STUDY SELECTIONS: Study selections included only randomized control trials with anxiety and/or depression and/or panic disorder outcomes as primary or secondary outcomes. Only full-text articles in the English language were included. RESULTS: This search yielded interventions from pharmacologic (n = 3), psychological (n = 7), lifestyle medicine (n = 10) and complementary and alternative medicine (CAM; n = 1) using a range of outcomes from physiologic to psychologic. While the pharmacologic and CAM studies were inconclusive, psychologic and lifestyle interventions showed improvements in asthma (quality of life, symptoms, asthma attacks) and psychological (anxiety, panic fear, depression) outcomes. Variations in selection methods, outcome measures and diagnostic criteria hindered a direct comparison of the studies. Most studies had small sample sizes, high attrition rates and short study durations. CONCLUSION: There is limited evidence on best approaches for managing co-morbid anxiety and/or depression in patients with asthma. Psychological and lifestyle medicine interventions are promising with improvements in both asthma and mental health outcomes. Well-designed randomized controlled studies with larger sample sizes, standardized outcomes and longer durations, are needed to better understand the role of depression and anxiety in adults with asthma.

Integrated collaborative care intervention for depression and obesity in primary care: translation from research to practice.

The objective of this study was to present lessons learned about engagement, delivery modality and pandemic impact while delivering a collaborative care intervention with a socioeconomically, racially and ethnically diverse sample. Participants completed a post-intervention survey (n = 41) on experiences and preferred intervention delivery modality, coronavirus 2019 (COVID-19) Impact Survey (n = 50) and provided open-ended feedback about the intervention (n = 27). Intervention process data included attendance, modality, and withdrawals. Data were analyzed using descriptive statistics and inductive content analyses. Of 71 intervention participants, 6 (8%) withdrew before session 1. Completers adhered to intervention timeline better than withdrawals. Participants liked the in-person interaction, efficient coach support, accountability of in-person and Zoom vs. phone sessions and the flexibility and convenience of phone and Zoom vs. in-person sessions. A majority of participants reported experiencing pandemic impacts such as heightened emotional distress, decreased activity engagement, poorer eating behaviors and being unable to meet basic needs. Participants deviating from intervention timelines may be re-engaged by targeted outreach attempts. Videoconference has the potential for providing as-needed coaching. Future interventions may be optimized to account for and address areas impacted by the pandemic. Findings revealed specific strategies that can be implemented in future interventions to improve emotional and physical health among diverse populations.

Association of physical activity levels and brain white matter in older Latino adults.

OBJECTIVE: Investigate the associations between self-reported physical activity (PA) engagement and white matter (WM) health (i.e. volume, integrity, and hyperintensities) in older Latinos. DESIGN: Cross-sectional study with community-dwelling older adults from predominantly Latino neighborhoods. Participants: Thirty-four cognitively healthy older Latinos from two different cohorts. Measurements: Participants self-reported demographic information, PA engagement [Community Healthy Activities Model Program for Seniors (CHAMPS) Physical Activity Questionnaire for Older Adults] and magnetic resonance imaging (MRI). We used high-resolution three-dimensional T1- and T2-FLAIR weighted images and diffusion tensor imaging acquired via 3 T MRI. We performed a series of hierarchical linear regression models with the addition of relevant covariates to examine the associations between self-reported PA levels and WM volume, integrity, and hyperintensities (separately). We adjusted p-values with the use of the Benjamini-Hochberg's false discovery rate procedure. RESULTS: Higher reported levels of leisure-time moderate-to-vigorous PA were significantly associated with higher WM volume of the posterior cingulate (ß = 0.220, SE = 0.125, 95% CI 0.009-0.431, p = 0.047) and isthmus cingulate (ß = 0.212, SE = 0.110, 95% CI 0.001-0.443, p = 0.044) after controlling for intracranial volume. Higher levels of total PA were significantly associated with higher overall WM volume of these same regions (posterior cingulate: ß = 0.220, SE = 0.125, CI 0.024-0.421, p = 0.046; isthmus cingulate: ß = 0.220, SE = 0.125, 95% CI 0.003-0.393; p = 0.040). Significant p-values did not withstand Benjamini-Hochberg's adjustment. PA was not significantly associated with WM integrity or WM hyperintensities. CONCLUSION: Higher levels of PA, particularly higher leisure-time moderate-to-vigorous PA, might be associated with greater WM volume in select white matter regions key to brain network integration for physical and cognitive functioning in older Latinos. More research is needed to further confirm these associations.

rest2vec: Vectorizing the resting-state functional connectome using graph embedding.

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used in connectomics for studying the functional relationships between regions of the human brain. rs-fMRI connectomics, however, has inherent analytical challenges, such as how to properly model negative correlations between BOLD time series. In addition, functional relationships between brain regions do not necessarily correspond to their anatomical distance, making the functional topology of the brain less well understood. Recent machine learning techniques, such as word2vec, have used embedding methods to map high-dimensional data into vector spaces, where words with more similar meanings are mapped closer to one another. Inspired by this approach, we have developed the graph embedding pipeline rest2vec for studying the vector space of functional connectomes. We demonstrate how rest2vec uses the phase angle spatial embedding (PhASE) method with dimensionality reduction to embed the connectome into lower dimensions, where the functional definition of a brain region is represented continuously in an intrinsic "functional space." Furthermore, we show how the "functional distance" between brain regions in this space can be applied to discover biologically-relevant connectivity gradients. Interestingly, rest2vec can be conceptualized in the context of the recently proposed maximum mean discrepancy (MMD) metric, followed by a double-centering approach seen in kernel PCA. In sum, rest2vec creates a low-dimensional representation of the rs-fMRI connectome where brain regions are mapped according to their functional relationships, giving a more informed understanding of the functional organization of the brain.

Sex Moderates Treatment Effects of Integrated Collaborative Care for Comorbid Obesity and Depression: The RAINBOW RCT.

BACKGROUND: Sex influences health and related behaviors due to biological and psychosocial/socioeconomic factors. Assessing sex-specific responses to integrated treatment for comorbid obesity and depression could inform intervention targeting. PURPOSE: To test (a) whether sex moderates the effects of integrated collaborative care on weight and depression outcomes through 24 months and (b) whether treatment response at 6 months predicts 12 and 24 month outcomes by sex. METHODS: Secondary data analyses on weight and depression severity (SCL-20) measured over 24 months among 409 adults with obesity and depression in the Research Aimed at Improving Both Mood and Weight trial. RESULTS: Men achieved significantly greater weight reductions in intervention versus usual care than women, whereas women achieved significantly greater percentage reductions in SCL-20 than men at both 12 and 24 months. In logistic models, at 80% specificity for correctly identifying participants not achieving clinically significant long-term outcomes, women who lost <3.0% weight and men who lost <4.1% weight at 6 months had ≥84% probability of not meeting 5% weight loss at 24 months. Similarly, at 80% specificity, women who reduced SCL-20 by <39.5% and men who reduced by <53.0% at 6 months had ≥82% probability of not meeting 50% decrease in SCL-20 at 24 months. CONCLUSIONS: Sex modified the integrated treatment effects for obesity and depression. Sex-specific responses at 6 months predicted clinically significant weight loss and depression outcomes through 24 months. Based on early responses, interventions may need to be tailored to address sex-specific barriers and facilitators to achieving healthy weight and depression outcomes at later time points. CLINICAL TRIAL REGISTRATION: NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).

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.

Connectome Signatures of Hyperexcitation in Cognitively Intact Middle-Aged Female APOE-ε4 Carriers.

Synaptic dysfunction is hypothesized to be one of the earliest brain changes in Alzheimer's disease, leading to "hyperexcitability" in neuronal circuits. In this study, we evaluated a novel hyperexcitation indicator (HI) for each brain region using a hybrid resting-state structural connectome to probe connectome-level excitation-inhibition balance in cognitively intact middle-aged apolipoprotein E (APOE) ε4 carriers with noncarriers (16 male/22 female in each group). Regression with three-way interactions (sex, age, and APOE-ε4 carrier status) to assess the effect of APOE-ε4 on excitation-inhibition balance within each sex and across an age range of 40-60 years yielded a significant shift toward higher HI in female carriers compared with noncarriers (beginning at 50 years). Hyperexcitation was insignificant in the male group. Further, in female carriers the degree of hyperexcitation exhibited significant positive correlation with working memory performance (evaluated via a virtual Morris Water task) in three regions: the left pars triangularis, left hippocampus, and left isthmus of cingulate gyrus. Increased excitation of memory-related circuits may be evidence of compensatory recruitment of neuronal resources for memory-focused activities. In sum, our results are consistent with known Alzheimer's disease sex differences; in that female APOE-ε4 carriers have globally disrupted excitation-inhibition balance that may confer greater vulnerability to disease neuropathology.

Beyond non-inferior: how telepsychiatry technologies can lead to superior care.

Telepsychiatry refers to the use of technology to support the remote provision of psychiatric services. Discussions of this technology have often focussed on the use of video conferencing in place of in-person visits and how such care is found to be non-inferior to traditional care. New developments in the fields of remote-sensing and digital phenotyping have the potential to overcome the limitations inherent in remote visits as well as the limitations of current outpatient care models more generally. Such technologies may enable the collection of more relevant, objective clinical data which could lead to improved care quality and transformed care delivery models. The development and implementation of these new technologies raise important ethical questions.

Impaired biophysical integrity of macromolecular protein pools in the uncinate circuit in late-life depression.

Major depressive disorder is a common mood disorder in the elderly. Although the neuroanatomical abnormalities have been identified in patients with late-life depression (LLD), the precise biological basis of LLD remains largely unknown. The purpose of this study was to examine the biophysical integrity of macromolecular protein pools in the nodal regions of the "uncinate circuit," a component of fronto-limbic circuitry that is connected by the uncinate fasciculus and is critical in the regulation of mood and emotions, using novel magnetization transfer (MT) imaging. Twenty-four patients with LLD and 27 non-depressed healthy control subjects (HCs) of comparable age, sex, and race were recruited from the communities of the greater Chicago Area. The nodal regions of the uncinate circuit, i.e., bilateral amygdala, hippocampus, and lateral and medial orbitofrontal cortices (OFCs), were examined. Compared with HCs, patients with LLD had significantly lower magnetization transfer ratio (MTR), a measure of the biophysical integrity of macromolecular protein pools, in bilateral amygdala and hippocampus. The lower MTR was negatively correlated with the depression score. Moreover, the MTR of these regions decreased with age and positively correlated with neuropsychological performance in the LLD group but not in the HC group. These findings suggest that LLD is associated with compromised biophysical integrity of macromolecular protein pools in nodal regions of the uncinate circuit, and that major depression may accentuate age-related attenuation of the biophysical integrity of macromolecular protein pools in this circuit. These findings provide important new insights into the neurobiological mechanisms of the pathophysiology of LLD.

Combinatorial Pharmacogenomic Testing Improves Outcomes for Older Adults With Depression.

OBJECTIVE: Evaluate the clinical utility of combinatorial pharmacogenomic testing for informing medication selection among older adults who have experienced antidepressant medication failure for major depressive disorder (MDD). DESIGN: Post hoc analysis of data from a blinded, randomized controlled trial comparing two active treatment arms. SETTING: Psychiatry specialty and primary care clinics across 60 U.S. community and academic sites. PARTICIPANTS: Adults age 65 years or older at baseline (n = 206), diagnosed with MDD and inadequate response to at least one medication on the combinatorial pharmacogenomic test report during the current depressive episode. INTERVENTION: Combinatorial pharmacogenomic testing to inform medication selection (guided-care), compared with treatment as usual (TAU). OUTCOMES: Mean percent symptom improvement, response rate, and remission rateat week 8, measured using the 17-item Hamilton Depression Rating Scale; medication switching; and comorbidity moderator analysis. RESULTS: At week 8, symptom improvement was not significantly different for guided-care than for TAU (∆ = 8.1%, t = 1.64, df = 187; p = 0.102); however, guided-care showed significantly improved response (∆ = 13.6%, t = 2.16, df = 187; p = 0.032) and remission (∆ = 12.7%, t = 2.49, df = 189; p = 0.014) relative to TAU. By week 8, more than twice as many patients in guided-care than in TAU were on medications predicted to have no gene-drug interactions (χ2 = 19.3, df = 2; p <0.001). Outcomes in the guided-care arm showed consistent improvement through the end of the open-design 24-week trial, indicating durability of the effect. Differences in outcomes between arms were not significantly impacted by comorbidities. CONCLUSIONS: Combinatorial pharmacogenomic test-informed medication selection improved outcomes over TAU among older adults with depression.

Altered dynamic electroencephalography connectome phase-space features of emotion regulation in social anxiety.

Emotion regulation deficits are commonly observed in social anxiety disorder (SAD). We used manifold-learning to learn the phase-space connectome manifold of EEG brain dynamics in twenty SAD participants and twenty healthy controls. The purpose of the present study was to utilize manifold-learning to understand EEG brain dynamics associated with emotion regulation processes. Our emotion regulation task (ERT) contains three conditions: Neutral, Maintain and Reappraise. For all conditions and subjects, EEG connectivity data was converted into series of temporally-consecutive connectomes and aggregated to yield this phase-space manifold. As manifold geodesic distances encode intrinsic geometry, we visualized this space using its geodesic-informed minimum spanning tree and compared neurophysiological dynamics across conditions and groups using the corresponding trajectory length. Results showed that SAD participants had significantly longer trajectory lengths during Neutral and Maintain. Further, trajectory lengths during Reappraise were significantly associated with the habitual use of reappraisal strategies, while Maintain trajectory lengths were significantly associated with the negative affective state during Maintain. In sum, an unsupervised connectome manifold-learning approach can reveal emotion regulation associated phase-space features of brain dynamics.

Cardiovascular disease risk factors, tract-based structural connectomics, and cognition in older adults.

Cardiovascular disease risk factors (CVD-RFs) are associated with decreased gray and white matter integrity and cognitive impairment in older adults. Less is known regarding the interplay between CVD-RFs, brain structural connectome integrity, and cognition. We examined whether CVD-RFs were associated with measures of tract-based structural connectivity in 94 non-demented/non-depressed older adults and if alterations in connectivity mediated associations between CVD-RFs and cognition. Participants (age = 68.2 years; 52.1% female; 46.8% Black) underwent CVD-RF assessment, MRI, and cognitive evaluation. Framingham 10-year stroke risk (FSRP-10) quantified CVD-RFs. Graph theory analysis integrated T1-derived gray matter regions of interest (ROIs; 23 a-priori ROIs associated with CVD-RFs and dementia), and diffusion MRI-derived white matter tractography into connectivity matrices analyzed for local efficiency and nodal strength. A principal component analysis resulted in three rotated factor scores reflecting executive function (EF; FAS, Trail Making Test (TMT) B-A, Letter-Number Sequencing, Matrix Reasoning); attention/information processing (AIP; TMT-A, TMT-Motor, Digit Symbol); and memory (CVLT-II Trials 1-5 Total, Delayed Free Recall, Recognition Discriminability). Linear regressions between FSRP-10 and connectome ROIs adjusting for word reading, intracranial volume, and white matter hyperintensities revealed negative associations with nodal strength in eight ROIs (p-values<.05) and negative associations with efficiency in two ROIs, and a positive association in one ROI (p-values<.05). There was mediation of bilateral hippocampal strength on FSRP-10 and AIP, and left rostral middle frontal gyrus strength on FSRP-10 and AIP and EF. Stroke risk plays differential roles in connectivity and cognition, suggesting the importance of multi-modal neuroimaging biomarkers in understanding age-related CVD-RF burden and brain-behavior.

Disruption of Neural Homeostasis as a Model of Relapse and Recurrence in Late-Life Depression.

The significant public health burden associated with late-life depression (LLD) is magnified by the high rates of recurrence. In this manuscript, we review what is known about recurrence risk factors, conceptualize recurrence within a model of homeostatic disequilibrium, and discuss the potential significance and challenges of new research into LLD recurrence. The proposed model is anchored in the allostatic load theory of stress. We review the allostatic response characterized by neural changes in network function and connectivity and physiologic changes in the hypothalamic-pituitary-adrenal axis, autonomic nervous system, immune system, and circadian rhythm. We discuss the role of neural networks' instability following treatment response as a source of downstream disequilibrium, triggering and/or amplifying abnormal stress response, cognitive dysfunction and behavioral changes, ultimately precipitating a full-blown recurrent episode of depression. We propose strategies to identify and capture early change points that signal recurrence risk through mobile technology to collect ecologically measured symptoms, accompanied by automated algorithms that monitor for state shifts (persistent worsening) and variance shifts (increased variability) relative to a patient's baseline. Identifying such change points in relevant sensor data could potentially provide an automated tool that could alert clinicians to at-risk individuals or relevant symptom changes even in a large practice.

Associations between pro-inflammatory cytokines, learning, and memory in late-life depression and healthy aging.

OBJECTIVES: Pro-inflammatory cytokines may play a role in learning and memory difficulties and may be exacerbated in late-life depression (LLD), where pro-inflammatory markers are already elevated because of aging and age-related vascular risk. METHODS: Learning and memory, and pro-inflammatory cytokines-Interleukin-1ß (IL-1ß), tumor necrosis factor-α (TNF-α), and Interleukin-6 (IL-6) were measured in 24 individuals with LLD and 34 healthy older adults (HOA). Hippocampal volumes were segmented using Freesurfer software. RESULTS: Pro-inflammatory cytokines were higher in LLD compared with HOA. Regression analyses demonstrated that educational level and right hippocampal volume significantly contributed to explaining the variance in learning. For memory performance, educational level, right hippocampal volume and a group-by-IL-6 interaction significantly contributed to the model. CONCLUSIONS: High levels of IL-6 impact cognition in LLD but not HOA. Results suggest that high levels of inflammation alone are not sufficient to account for cognitive difficulties, but may interact with other factors in at-risk populations like LLD, to contribute to memory difficulties. Copyright © 2017 John Wiley & Sons, Ltd.

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.