Virtual reality-assessment of social interactions and prognosis in depression.

BACKGROUND: Freud proposed that excessive self-blame-related motivations such as self-punishing tendencies play a key role in depression. Most of the supporting evidence, however, is based on cross-sectional studies and questionnaire measures. METHODS: In this pre-registered (NCT04593537) study, we used a novel Virtual Reality (VR) task to determine whether maladaptive self-blame-related action tendencies prospectively identify a subgroup of depression with poor prognosis when treated as usual over four months in primary care. Ninety-eight patients with depression (Patient Health Questionnaire-9 ≥ 15), screening negatively for bipolar and alcohol/substance use disorders, completed the VR-task at baseline (n = 93 completed follow-up). RESULTS: Our pre-registered statistical/machine learning model prospectively predicted a cross-validated 19 % of variance in depressive symptoms. Contrary to our specific predictions, and in accordance with Freud's observations, feeling like punishing oneself emerged as prognostically relevant rather than feeling like hiding or creating a distance from oneself. Using a principal components analysis of all pre-registered continuous measures, a factor most strongly loading on feeling like punishing oneself for other people's wrongdoings (ß = 0.23, p = 0.01), a baseline symptom factor (ß = 0.30, p = 0.006) and Maudsley Staging Method treatment-resistance scores (ß = 0.28, p = 0.009) at baseline predicted higher depressive symptoms after four months. LIMITATIONS: Patients were not assessed with a diagnostic interview. CONCLUSIONS: Independently and apart from known clinical variables, feeling like punishing oneself emerged as a distinctly relevant prognostic factor and should therefore be assessed and tackled in personalised care pathways for difficult-to-treat depression.

Neural responses to facial emotions and subsequent clinical outcomes in difficult-to-treat depression.

BACKGROUND: Amygdala and dorsal anterior cingulate cortex responses to facial emotions have shown promise in predicting treatment response in medication-free major depressive disorder (MDD). Here, we examined their role in the pathophysiology of clinical outcomes in more chronic, difficult-to-treat forms of MDD. METHODS: Forty-five people with current MDD who had not responded to ⩾2 serotonergic antidepressants (n = 42, meeting pre-defined fMRI minimum quality thresholds) were enrolled and followed up over four months of standard primary care. Prior to medication review, subliminal facial emotion fMRI was used to extract blood-oxygen level-dependent effects for sad v. happy faces from two pre-registered a priori defined regions: bilateral amygdala and dorsal/pregenual anterior cingulate cortex. Clinical outcome was the percentage change on the self-reported Quick Inventory of Depressive Symptomatology (16-item). RESULTS: We corroborated our pre-registered hypothesis (NCT04342299) that lower bilateral amygdala activation for sad v. happy faces predicted favorable clinical outcomes (rs[38] = 0.40, p = 0.01). In contrast, there was no effect for dorsal/pregenual anterior cingulate cortex activation (rs[38] = 0.18, p = 0.29), nor when using voxel-based whole-brain analyses (voxel-based Family-Wise Error-corrected p < 0.05). Predictive effects were mainly driven by the right amygdala whose response to happy faces was reduced in patients with higher anxiety levels. CONCLUSIONS: We confirmed the prediction that a lower amygdala response to negative v. positive facial expressions might be an adaptive neural signature, which predicts subsequent symptom improvement also in difficult-to-treat MDD. Anxiety reduced adaptive amygdala responses.

The Role of Subgenual Resting-State Connectivity Networks in Predicting Prognosis in Major Depressive Disorder.

Background: A seminal study found higher subgenual frontal cortex resting-state connectivity with 2 left ventral frontal regions and the dorsal midbrain to predict better response to psychotherapy versus medication in individuals with treatment-naïve major depressive disorder (MDD). Here, we examined whether these subgenual networks also play a role in the pathophysiology of clinical outcomes in MDD with early treatment resistance in primary care. Methods: Forty-five people with current MDD who had not responded to ≥2 serotonergic antidepressants (n = 43, meeting predefined functional magnetic resonance imaging minimum quality thresholds) were enrolled and followed over 4 months of standard care. Functional magnetic resonance imaging resting-state connectivity between the preregistered subgenual frontal cortex seed and 3 previously identified left ventromedial, ventrolateral prefrontal/insula, and dorsal midbrain regions was extracted. The clinical outcome was the percentage change on the self-reported 16-item Quick Inventory of Depressive Symptomatology. Results: We observed a reversal of our preregistered hypothesis in that higher resting-state connectivity between the subgenual cortex and the a priori ventrolateral prefrontal/insula region predicted favorable rather than unfavorable clinical outcomes (rs39 = -0.43, p = .006). This generalized to the sample including participants with suboptimal functional magnetic resonance imaging quality (rs43 = -0.35, p = .02). In contrast, no effects (rs39 = 0.12, rs39 = -0.01) were found for connectivity with the other 2 preregistered regions or in a whole-brain analysis (voxel-based familywise error-corrected p < .05). Conclusions: Subgenual connectivity with the ventrolateral prefrontal cortex/insula is relevant for subsequent clinical outcomes in current MDD with early treatment resistance. Its positive association with favorable outcomes could be explained primarily by psychosocial rather than the expected pharmacological changes during the follow-up period.

Evidence has shown that connectivity of the subgenual cortex, a frontal midline brain region, with 3 other brain regions can predict whether people with never-treated depression benefit more from psychological or medication-based treatments. Here, using resting-state fMRI, we show that subgenual connections with one of these regions, the left ventrolateral prefrontal/insula, also predict future average depression levels in people with difficult-to-treat depression. These data suggest that functional connectivity between these regions may be linked to clinical outcomes in major depressive disorder.

Self-blame-selective hyper-connectivity between anterior temporal and subgenual cortices predicts prognosis in major depressive disorder.

BACKGROUND: Self-blame-related fMRI measures were shown to predict subsequent recurrence in remitted major depressive disorder (MDD). Their role in current MDD, however, is unknown. We hypothesised that these neural signatures reflect a highly recurrent but remitting course of MDD and therefore predict favourable outcomes over a four-month follow-up period in current MDD. METHODS: Forty-five participants with current MDD and non-responders to at least two serotonergic antidepressants, were encouraged to optimise their medication and followed up after receiving four months of primary care treatment-as-usual. Prior to their medication review, participants completed an fMRI paradigm in which they viewed self- and other-blame emotion-evoking statements. Thirty-nine participants met pre-defined fMRI data minimum quality thresholds. Psychophysiological interaction analysis was used to determine baseline connectivity of the right superior anterior temporal lobe (RSATL), with an a priori BA25 region-of-interest for self-blaming vs other-blaming emotions, using Quick Inventory of Depressive Symptomatology (16-item) percentage change as a covariate. RESULTS: We corroborated our pre-registered hypothesis that a favourable clinical outcome was associated with higher self-blame-selective RSATL-BA25 connectivity (Family-Wise Error-corrected p <.05 over the a priori BA25 region-of-interest; rs(34) = -0.47, p =.005). This generalised to the sample including participants with suboptimal fMRI quality (rs(39) = -0.32, p =.05). CONCLUSIONS: This study shows that neural signatures of overgeneralised self-blame are relevant for prognostic stratification of current treatment-resistant MDD. Future studies need to confirm whether this neural signature indeed represents a trait-like feature of a fully remitting subtype of MDD, or whether it is also modulated by depressive state and related to treatment effects.

Antidepressant Advisor (ADeSS): a decision support system for antidepressant treatment for depression in UK primary care - a feasibility study.

OBJECTIVES: To develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to general practitioners (GPs) in UK primary care. DESIGN: A parallel group, cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation. SETTING: South London NHS GP practices. PARTICIPANTS: Ten practices and eighteen patients with treatment-resistant current major depressive disorder. INTERVENTIONS: Practices were randomised to two treatment arms: (a) treatment-as-usual, (b) computerised decision support tool. RESULTS: Ten GP practices participated in the trial, which was within our target range (8-20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the COVID-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the decision tool arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects. CONCLUSIONS: Overall, feasibility was not shown in the current study and the following modifications would be needed to attempt to overcome the limitations found: (a) inclusion of patients who have only tried one Selective Serotonin Reuptake Inhibitor, rather than two, to improve recruitment and pragmatic relevance of the study; (b) approaching community pharmacists to implement tool recommendations rather than GPs; (c) further funding to directly interface between the decision support tool and self-reported symptom app; (d) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report. TRIAL REGISTRATION NUMBER: NCT03628027.

Remote virtual reality assessment elucidates self-blame-related action tendencies in depression.

BACKGROUND: Action tendencies are implicit cognitive and motivational states before an action is taken, such as feeling like hiding when experiencing shame or guilt, independent of the actions people decide to take. Such "action tendencies" are key to understanding the maladaptive impact of self-blame in depression. For example, feeling like "hiding" in a text-based task was previously associated with recurrence risk in remitted depression. Despite their functional importance, action tendencies have not been systematically investigated in current depression, which was the aim of this pre-registered study. METHODS: We developed and validated the first virtual reality (VR) assessment of blame-related action tendencies and compared current depression (n = 98) with control participants (n = 40). The immersive VR-task, pre-programmed on devices sent to participants' homes, used hypothetical social interactions, in which either participants (self-agency) or their friend (other-agency) were described to have acted inappropriately. RESULTS: Compared with controls, people with depression showed a maladaptive profile: particularly in the other-agency condition, rather than feeling like verbally attacking their friend, they were prone to feeling like hiding, and punishing themselves. Interestingly, feeling like punishing oneself was associated with a history of self-harm but not suicide attempts. CONCLUSIONS: Current depression and self-harm history were linked with distinctive motivational signatures, paving the way for remote VR-based stratification and treatment.

Neurocognitive Measures of Self-blame and Risk Prediction Models of Recurrence in Major Depressive Disorder.

BACKGROUND: Overgeneralized self-blaming emotions, such as self-disgust, are core symptoms of major depressive disorder and prompt specific actions (i.e., action tendencies), which are more functionally relevant than the emotions themselves. We have recently shown, using a novel cognitive task, that when feeling self-blaming emotions, maladaptive action tendencies (feeling like hiding and feeling like creating a distance from oneself) and an overgeneralized perception of control are characteristic of major depressive disorder, even after remission of symptoms. Here, we probed the potential of this cognitive signature, and its combination with previously employed functional magnetic resonance imaging (fMRI) measures, to predict individual recurrence risk. For this purpose, we developed a user-friendly hybrid machine/statistical learning tool, which we make freely available. METHODS: A total of 52 medication-free patients with remitted major depressive disorder, who had completed the action tendencies task and our self-blame fMRI task at baseline, were followed up clinically over 14 months to determine recurrence. Prospective prediction models included baseline maladaptive self-blame-related action tendencies and anterior temporal fMRI connectivity patterns across a set of frontolimbic a priori regions of interest, as well as including established clinical and standard psychological predictors. Prediction models used elastic net regularized logistic regression with nested 10-fold cross-validation. RESULTS: Cross-validated discrimination was highly promising (area under the receiver-operating characteristic curve ≥ 0.86), and positive predictive values over 80% were achieved when including fMRI in multimodal models, but only up to 71% (area under the receiver-operating characteristic curve ≤ 0.74) when solely relying on cognitive and clinical measures. CONCLUSIONS: This study shows the high potential of multimodal signatures of self-blaming biases to predict recurrence risk at an individual level and calls for external validation in an independent sample.

Internal reliability of blame-related functional MRI measures in major depressive disorder.

BACKGROUND: In major depressive disorder (MDD), self-blame-related fMRI measures have shown the potential to be used as prognostic markers for recurrence risk. Like most potential fMRI markers, however, their reliability is unclear. Here, we probed the internal reliability of self-blame-related fMRI measures, as well as the impact of different modelling approaches on reliability metrics and validity. METHODS: Internal consistency (i.e. split-half reliability) was calculated for blood oxygen level-dependent (BOLD) responses and psychophysiological interactions (PPI) related to self-blame-related biases in medication-free remitted MDD participants (n = 81) and healthy controls (n = 41). Trial-length was modelled using three durations (0, 2 and 5 s), which was convolved with the haemodynamic response function (HRF) with and without time and dispersion derivatives. Intraclass correlation coefficients (ICCs) were calculated for simple contrasts examining activation to self-blaming emotions and other-blaming emotions and the more complex contrast of the subtraction-based difference between self- and other-blaming emotions within the following a priori ROIs: right superior anterior temporal lobe seed region, anterior subgenual cingulate cortex, posterior subgenual cortex and right striatum / pallidum. RESULTS: Across ROIs, we obtained fair reliability (ICC ≥ 0.40) for simple, but poor reliability (ICC < 0.40) for more complex fMRI measures related to self-blame. Despite this low internal consistency of complex measures at the individual level, we observed robust activation at the group-level, reproducing previously published results. CONCLUSIONS: While simple BOLD contrasts had fair reliability, previously employed PPI models had poor reliability and simple connectivity measures lacked predictive validity. This calls for the development of functional connectivity measures that strike a better balance between reliability and validity for future clinical applications, which require robust measures at the individual rather than group-level.

Development and validation of the Maudsley Modified Patient Health Questionnaire (MM-PHQ-9).

BACKGROUND: The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use. AIMS: We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure. METHOD: A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items' factor structure. RESULTS: The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. CONCLUSIONS: These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.

Study protocol for the antidepressant advisor (ADeSS): a decision support system for antidepressant treatment for depression in UK primary care: a feasibility study.

INTRODUCTION: The Antidepressant Advisor Study is a feasibility trial of a computerised decision-support tool which uses an algorithm to provide antidepressant treatment guidance for general practitioners (GPs) in the UK primary care service. The tool is the first in the UK to implement national guidelines on antidepressant treatment guidance into a computerised decision-support tool. METHODS AND ANALYSIS: The study is a parallel group, cluster-randomised controlled feasibility trial where participants are blind to treatment allocation. GPs were assigned to two treatment arms: (1) treatment-as-usual (TAU) and (2) computerised decision-support tool to assist with antidepressant choices. The study will assess recruitment and lost to follow-up rates, GP satisfaction with the tool and impact on health service use. A meaningful long-term roll-out unit cost will be calculated for the tool, and service use data will be collected at baseline and follow-up to inform a full economic evaluation of a future trial. ETHICS AND DISSEMINATION: The study has received National Health Service ethical approval from the London-Camberwell St Giles Research Ethics Committee (ref: 17/LO/2074). The trial was pre-registered in the Clinical Trials.gov registry. The results of the study will be published in a pre-publication archive within 1 year of completion of the last follow-up assessment. TRIAL REGISTRATION NUMBER: NCT03628027.

Effect of Flavin-Containing Monooxygenase Genotype, Mouse Strain, and Gender on Trimethylamine N-oxide Production, Plasma Cholesterol Concentration, and an Index of Atherosclerosis.

The objectives of the study were to determine the contribution, in mice, of members of the flavin-containing monooxygenase (FMO) family to the production of trimethylamine (TMA) N-oxide (TMAO), a potential proatherogenic molecule, and whether under normal dietary conditions differences in TMAO production were associated with changes in plasma cholesterol concentration or with an index of atherosclerosis (Als). Concentrations of urinary TMA and TMAO and plasma cholesterol were measured in 10-week-old male and female C57BL/6J and CD-1 mice and in mouse lines deficient in various Fmo genes (Fmo1-/- , 2-/- , 4-/- , and Fmo5-/- ). In female mice most TMA N-oxygenation was catalyzed by FMO3, but in both genders 11%-12% of TMA was converted to TMAO by FMO1. Gender-, Fmo genotype-, and strain-related differences in TMAO production were accompanied by opposite effects on plasma cholesterol concentration. Plasma cholesterol was negatively, but weakly, correlated with TMAO production and urinary TMAO concentration. Fmo genotype had no effect on Als. There was no correlation between Als and either TMAO production or urinary TMAO concentration. Our results indicate that under normal dietary conditions TMAO does not increase plasma cholesterol or act as a proatherogenic molecule.

Identification of Flavin-Containing Monooxygenase 5 (FMO5) as a Regulator of Glucose Homeostasis and a Potential Sensor of Gut Bacteria.

We have previously identified flavin-containing monooxygenase 5 (FMO5) as a regulator of metabolic aging. The aim of the present study was to investigate the role of FMO5 in glucose homeostasis and the impact of diet and gut flora on the phenotype of mice in which the Fmo5 gene has been disrupted (Fmo5-/- mice). In comparison with wild-type (WT) counterparts, Fmo5-/- mice are resistant to age-related changes in glucose homeostasis and maintain the higher glucose tolerance and insulin sensitivity characteristic of young animals. When fed a high-fat diet, they are protected against weight gain and reduction of insulin sensitivity. The phenotype of Fmo5-/- mice is independent of diet and the gut microbiome and is determined solely by the host genotype. Fmo5-/- mice have metabolic characteristics similar to those of germ-free mice, indicating that FMO5 plays a role in sensing or responding to gut bacteria. In WT mice, FMO5 is present in the mucosal epithelium of the gastrointestinal tract where it is induced in response to a high-fat diet. In comparison with WT mice, Fmo5-/- mice have fewer colonic goblet cells, and they differ in the production of the colonic hormone resistin-like molecule ßFmo5-/- mice have lower concentrations of tumor necrosis factor α in plasma and of complement component 3 in epididymal white adipose tissue, indicative of improved inflammatory tone. Our results implicate FMO5 as a regulator of body weight and of glucose disposal and insulin sensitivity and, thus, identify FMO5 as a potential novel therapeutic target for obesity and insulin resistance.

Trimethylamine and Trimethylamine N-Oxide, a Flavin-Containing Monooxygenase 3 (FMO3)-Mediated Host-Microbiome Metabolic Axis Implicated in Health and Disease.

Flavin-containing monooxygenase 3 (FMO3) is known primarily as an enzyme involved in the metabolism of therapeutic drugs. On a daily basis, however, we are exposed to one of the most abundant substrates of the enzyme trimethylamine (TMA), which is released from various dietary components by the action of gut bacteria. FMO3 converts the odorous TMA to nonodorous TMA N-oxide (TMAO), which is excreted in urine. Impaired FMO3 activity gives rise to the inherited disorder primary trimethylaminuria (TMAU). Affected individuals cannot produce TMAO and, consequently, excrete large amounts of TMA. A dysbiosis in gut bacteria can give rise to secondary TMAU. Recently, there has been much interest in FMO3 and its catalytic product, TMAO, because TMAO has been implicated in various conditions affecting health, including cardiovascular disease, reverse cholesterol transport, and glucose and lipid homeostasis. In this review, we consider the dietary components that can give rise to TMA, the gut bacteria involved in the production of TMA from dietary precursors, the metabolic reactions by which bacteria produce and use TMA, and the enzymes that catalyze the reactions. Also included is information on bacteria that produce TMA in the oral cavity and vagina, two key microbiome niches that can influence health. Finally, we discuss the importance of the TMA/TMAO microbiome-host axis in health and disease, considering factors that affect bacterial production and host metabolism of TMA, the involvement of TMAO and FMO3 in disease, and the implications of the host-microbiome axis for management of TMAU.