Hot metacognition: poorer metacognitive efficiency following acute but not traumatic stress.

Aberrations to metacognition-the ability to reflect on and evaluate self-performance-are a feature of poor mental health. Theoretical models of post-traumatic stress disorder propose that following severe stress or trauma, maladaptive metacognitive evaluations and appraisals of the event drive the development of symptoms. Empirical research is required in order to reveal whether disruptions to metacognition cause or contribute to symptom development in line with theoretical accounts, or are simply a consequence of ongoing psychopathology. In two experiments, using hierarchical Bayesian modelling of metacognition measured in a memory recognition task, we assessed whether distortions to metacognition occur at a state-level after an acute stress induction, and/or at a trait-level in a sample of individuals experiencing intrusive memories following traumatic stress. Results from experiment 1, an in-person laboratory-based experiment, demonstrated that heightened psychological responses to the stress induction were associated with poorer metacognitive efficiency, despite there being no overall change in metacognitive efficiency from pre- to post-stress (N = 27). Conversely, in experiment 2, an online experiment using the same metamemory task, we did not find evidence of metacognitive alterations in a transdiagnostic sample of patients with intrusive memory symptomatology following traumatic stress (N = 36, compared to 44 matched controls). Our results indicate a relationship between state-level psychological responses to stress and metacognitive alterations. The lack of evidence for pre- to post-stress differences in metamemory illustrates the importance for future studies to reveal the direction of this relationship, and consequently the duration of stress-associated metacognitive impairments and their impact on mental health.

Early-life stress biases responding to negative feedback and increases amygdala volume and vulnerability to later-life stress.

Early-life stress (ELS) or adversity, particularly in the form of childhood neglect and abuse, is associated with poor mental and physical health outcomes in adulthood. However, whether these relationships are mediated by the consequences of ELS itself or by other exposures that frequently co-occur with ELS is unclear. To address this question, we carried out a longitudinal study in rats to isolate the effects of ELS on regional brain volumes and behavioral phenotypes relevant to anxiety and depression. We used the repeated maternal separation (RMS) model of chronic ELS, and conducted behavioral measurements throughout adulthood, including of probabilistic reversal learning (PRL), responding on a progressive ratio task, sucrose preference, novelty preference, novelty reactivity, and putative anxiety-like behavior on the elevated plus maze. Our behavioral assessment was combined with magnetic resonance imaging (MRI) for quantitation of regional brain volumes at three time points: immediately following RMS, young adulthood without further stress, and late adulthood with further stress. We found that RMS caused long-lasting, sexually dimorphic biased responding to negative feedback on the PRL task. RMS also slowed response time on the PRL task, but without this directly impacting task performance. RMS animals were also uniquely sensitive to a second stressor, which disproportionately impaired their performance and slowed their responding on the PRL task. MRI at the time of the adult stress revealed a larger amygdala volume in RMS animals compared with controls. These behavioral and neurobiological effects persisted well into adulthood despite a lack of effects on conventional tests of 'depression-like' and 'anxiety-like' behavior, and a lack of any evidence of anhedonia. Our findings indicate that ELS has long-lasting cognitive and neurobehavioral effects that interact with stress in adulthood and may have relevance for understanding the etiology of anxiety and depression in humans.

Genetic variants associated with psychiatric disorders are enriched at epigenetically active sites in lymphoid cells.

Multiple psychiatric disorders have been associated with abnormalities in both the innate and adaptive immune systems. The role of these abnormalities in pathogenesis, and whether they are driven by psychiatric risk variants, remains unclear. We test for enrichment of GWAS variants associated with multiple psychiatric disorders (cross-disorder or trans-diagnostic risk), or 5 specific disorders (cis-diagnostic risk), in regulatory elements in immune cells. We use three independent epigenetic datasets representing multiple organ systems and immune cell subsets. Trans-diagnostic and cis-diagnostic risk variants (for schizophrenia and depression) are enriched at epigenetically active sites in brain tissues and in lymphoid cells, especially stimulated CD4+ T cells. There is no evidence for enrichment of either trans-risk or cis-risk variants for schizophrenia or depression in myeloid cells. This suggests a possible model where environmental stimuli activate T cells to unmask the effects of psychiatric risk variants, contributing to the pathogenesis of mental health disorders.

Methylome-wide association study of antidepressant use in Generation Scotland and the Netherlands Twin Register implicates the innate immune system.

Antidepressants are an effective treatment for major depressive disorder (MDD), although individual response is unpredictable and highly variable. Whilst the mode of action of antidepressants is incompletely understood, many medications are associated with changes in DNA methylation in genes that are plausibly linked to their mechanisms. Studies of DNA methylation may therefore reveal the biological processes underpinning the efficacy and side effects of antidepressants. We performed a methylome-wide association study (MWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in Generation Scotland (GS:SFHS, N = 6428, EPIC array) and the Netherlands Twin Register (NTR, N = 2449, 450 K array) and ran a meta-analysis of antidepressant use across these two cohorts. We found ten CpG sites significantly associated with self-reported antidepressant use in GS:SFHS, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 (ß = -0.055, pcorrected = 0.005). Other top loci were annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, which have previously been implicated in the innate immune response. Next, using penalised regression, we trained a methylation-based score of self-reported antidepressant use in a subset of 3799 GS:SFHS individuals that predicted antidepressant use in a second subset of GS:SFHS (N = 3360, ß = 0.377, p = 3.12 × 10-11, R2 = 2.12%). In an MWAS analysis of prescribed selective serotonin reuptake inhibitors, we showed convergent findings with those based on self-report. In NTR, we did not find any CpGs significantly associated with antidepressant use. The meta-analysis identified the two CpGs of the ten above that were common to the two arrays used as being significantly associated with antidepressant use, although the effect was in the opposite direction for one of them. Antidepressants were associated with epigenetic alterations in loci previously associated with mental health disorders and the innate immune system. These changes predicted self-reported antidepressant use in a subset of GS:SFHS and identified processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.

B-cells are abnormal in psychosocial stress and regulate meningeal myeloid cell activation.

There is increasing interest in how immune cells, including those within the meninges at the blood-brain interface, influence brain function and mood disorders, but little data on humoral immunity in this context. Here, we show that in mice exposed to psychosocial stress, there is increased splenic B cell activation and secretion of the immunoregulatory cytokine interleukin (IL)-10. Meningeal B cells were prevalent in homeostasis but substantially decreased following stress, whereas Ly6Chi monocytes increased, and meningeal myeloid cells showed augmented expression of activation markers. Single-cell RNA sequencing of meningeal B cells demonstrated the induction of innate immune transcriptional programmes following stress, including genes encoding antimicrobial peptides that are known to alter myeloid cell activation. Cd19-/- mice, that have reduced B cells, showed baseline meningeal myeloid cell activation and decreased exploratory behaviour. Together, these data suggest that B cells may influence behaviour by regulating meningeal myeloid cell activation.

Dysconnectivity of a brain functional network was associated with blood inflammatory markers in depression.

OBJECTIVE: There is increasing evidence for a subgroup of major depressive disorder (MDD) associated with heightened peripheral blood inflammatory markers. In this study, we aimed to understand the mechanistic brain-immune axis in inflammation-linked depression by investigating associations between functional connectivity (FC) of brain networks and peripheral blood immune markers in depression. METHODS: Resting-state functional magnetic resonance imaging (fMRI) and peripheral blood inflammatory markers (C-reactive protein; CRP, interleukin-6; IL-6 and immune cells) were collected on N = 46 healthy controls (HC; CRP ≤ 3 mg/L) and N = 83 cases of depression, stratified further into low CRP cases (loCRP cases; ≤ 3 mg/L; N = 50) and high CRP cases (hiCRP cases; > 3 mg/L; N = 33). In a two-part analysis, network-based statistics (NBS) was firstly used to ascertain whole-brain FC differences in HC vs hiCRP cases. Secondly, we investigated the association between this network of interconnected brain regions and continuous measures of peripheral CRP (N = 83), IL-6 (N = 72), neutrophils and CD4+ T-cells (N = 36) in depression cases only. RESULTS: Case-control NBS testing revealed a single network of abnormally attenuated FC in the high CRP depression cases compared to healthy controls. Connections within this network were mainly between brain regions located in the left insula/frontal operculum and posterior cingulate cortex, which were assigned to ventral attention and default mode canonical fMRI networks respectively. Within-group analysis across all depression cases, secondarily demonstrated that FC within the identified network significantly negatively scaled with CRP, IL-6 and neutrophils. CONCLUSIONS: The findings suggest that inflammation is associated with disruption of functional connectivity within a brain network deemed critical for interoceptive signalling, e.g. accurate communication of peripheral bodily signals such as immune states to the brain, with implications for the pathogenesis of inflammation-linked depression.

No evidence for differential gene expression in major depressive disorder PBMCs, but robust evidence of elevated biological ageing.

The increasingly compelling data supporting the involvement of immunobiological mechanisms in Major Depressive Disorder (MDD) might provide some explanation forthe variance in this heterogeneous condition. Peripheral blood measures of cytokines and chemokines constitute the bulk of evidence, with consistent meta-analytic data implicating raised proinflammatory cytokines such as IL6, IL1ß and TNF. Among the potential mechanisms linking immunobiological changes to affective neurobiology is the accelerated biological ageing seen in MDD, particularly via the senescence associated secretory phenotype (SASP). However, the cellular source of immunobiological markers remains unclear. Pre-clinical evidence suggests a role for peripheral blood mononuclear cells (PBMC), thus here we aimed to explore the transcriptomic profile using RNA sequencing in PBMCs in a clinical sample of people with various levels of depression and treatment response comparing it with that in healthy controls (HCs). There were three groups with major depressive disorder (MDD): treatment-resistant (n = 94), treatment-responsive (n = 47) and untreated (n = 46). Healthy controls numbered 44. Using PBMCs gene expression analysis was conducted using RNAseq to a depth of 54.5 million reads. Differential gene expression analysis was performed using DESeq2. The data showed no robust signal differentiating MDD and HCs. There was, however, significant evidence of elevated biological ageing in MDD vs HC. Biological ageing was evident in these data as a transcriptional signature of 888 age-associated genes (adjusted p < 0.05, absolute log2fold > 0.6) that also correlated strongly with chronological age (spearman correlation coefficient of 0.72). Future work should expand clinical sample sizes and reduce clinical heterogeneity. Exploration of RNA-seq signatures in other leukocyte populations and single cell RNA sequencing may help uncover more subtle differences. However, currently the subtlety of any PBMC signature mitigates against its convincing use as a diagnostic or predictive biomarker.

Inflammatory and cardiometabolic markers at presentation with first episode psychosis and long-term clinical outcomes: A longitudinal study using electronic health records.

Approximately one third of patients presenting with a first episode of psychosis need long-term support, but there is a limited understanding of the sociodemographic or biological factors that predict this outcome. We used electronic health records from a naturalistic cohort of consecutive patients referred to an early intervention in psychosis service to address this question. We extracted data on demographic (age, sex, ethnicity and marital status), immune (differential cell count measures and C-reactive protein (CRP)) and metabolic (cholesterol, triglycerides, glucose, glycated haemoglobin, blood pressure, body mass index (BMI)) factors at baseline, and subsequent need for long-term secondary (specialist) psychiatric care. Of 749 patients with outcome data available, 447 (60%) had a good outcome and were discharged to primary care, while 302 (40%) required follow-up by secondary mental health services indicating a worse outcome. The need for ongoing secondary mental healthcare was associated with high triglyceride levels (adjusted odds ratio/OR = 7.32, 95% CI 2.26-28.06), a low basophil:lymphocyte ratio (adjusted OR = 0.14, 95% CI 0.02-0.58), and a high monocyte count (adjusted OR = 2.78, 95% CI 1.02-8.06) at baseline. The associations for baseline basophil (unadjusted OR = 0.27 per SD, 95% CI 0.10-0.62) and platelet counts (unadjusted OR = 2.88, 95% CI 1.29-6.63) attenuated following adjustment for BMI. Baseline CRP levels or BMI were not associated with long-term psychiatric outcomes. In conclusion, we provide evidence that triglyceride levels and several blood cell counts measured at presentation may be clinically useful markers of long-term prognosis for first episode psychosis in clinical settings. These findings will require replication.

Peripheral Blood Cell-Stratified Subgroups of Inflamed Depression.

BACKGROUND: Depression has been associated with increased inflammatory proteins, but changes in circulating immune cells are less well defined. METHODS: We used multiparametric flow cytometry to count 14 subsets of peripheral blood cells in 206 depression cases and 77 age- and sex-matched controls (N = 283). We used univariate and multivariate analyses to investigate the immunophenotypes associated with depression and depression severity. RESULTS: Depression cases, compared with controls, had significantly increased immune cell counts, especially neutrophils, CD4+ T cells, and monocytes, and increased inflammatory proteins (C-reactive protein and interleukin-6). Within-group analysis of cases demonstrated significant associations between the severity of depressive symptoms and increased myeloid and CD4+ T-cell counts. Depression cases were partitioned into 2 subgroups by forced binary clustering of cell counts: the inflamed depression subgroup (n = 81 out of 206; 39%) had increased monocyte, CD4+, and neutrophil counts; increased C-reactive protein and interleukin-6; and more severe depression than the uninflamed majority of cases. Relaxing the presumption of a binary classification, data-driven analysis identified 4 subgroups of depression cases, 2 of which (n = 38 and n = 100; 67% collectively) were associated with increased inflammatory proteins and more severe depression but differed in terms of myeloid and lymphoid cell counts. Results were robust to potentially confounding effects of age, sex, body mass index, recent infection, and tobacco use. CONCLUSIONS: Peripheral immune cell counts were used to distinguish inflamed and uninflamed subgroups of depression and to indicate that there may be mechanistically distinct subgroups of inflamed depression.

Early-life stress and inflammation: A systematic review of a key experimental approach in rodents.

Repeated maternal separation is the most widely used pre-clinical approach to investigate the relationship between early-life chronic stress and its neuropsychiatric and physical consequences. In this systematic review, we identified 46 studies that conducted repeated maternal separation or single-episode maternal separation and reported measurements of interleukin-1b, interleukin-6, interleukin-10, tumour necrosis factor-alpha, or microglia activation and density. We report that in the short-term and in the context of later-life stress, repeated maternal separation has pro-inflammatory immune consequences in diverse tissues. Repeated maternal separation animals exhibit greater microglial activation and elevated pro-inflammatory cytokine signalling in key brain regions implicated in human psychiatric disorders. Notably, repeated maternal separation generally has no long-term effect on cytokine expression in any tissue in the absence of later-life stress. These observations suggest that the elevated inflammatory signalling that has been reported in humans with a history of early-life stress may be the joint consequence of ongoing stressor exposure together with potentiated neural and/or immune responsiveness to stressors. Finally, our findings provide detailed guidance for future studies interrogating the causal roles of early-life stress and inflammation in disorders such as major depression.

Detection of functional brain network reconfiguration during task-driven cognitive states.

Network science offers computational tools to elucidate the complex patterns of interactions evident in neuroimaging data. Recently, these tools have been used to detect dynamic changes in network connectivity that may occur at short time scales. The dynamics of fMRI connectivity, and how they differ across time scales, are far from understood. A simple way to interrogate dynamics at different time scales is to alter the size of the time window used to extract sequential (or rolling) measures of functional connectivity. Here, in n=82 participants performing three distinct cognitive visual tasks in recognition memory and strategic attention, we subdivided regional BOLD time series into variable sized time windows and determined the impact of time window size on observed dynamics. Specifically, we applied a multilayer community detection algorithm to identify temporal communities and we calculated network flexibility to quantify changes in these communities over time. Within our frequency band of interest, large and small windows were associated with a narrow range of network flexibility values across the brain, while medium time windows were associated with a broad range of network flexibility values. Using medium time windows of size 75-100s, we uncovered brain regions with low flexibility (considered core regions, and observed in visual and attention areas) and brain regions with high flexibility (considered periphery regions, and observed in subcortical and temporal lobe regions) via comparison to appropriate dynamic network null models. Generally, this work demonstrates the impact of time window length on observed network dynamics during task performance, offering pragmatic considerations in the choice of time window in dynamic network analysis. More broadly, this work reveals organizational principles of brain functional connectivity that are not accessible with static network approaches.

Cognitive network neuroscience.

Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.

Brain network adaptability across task states.

Activity in the human brain moves between diverse functional states to meet the demands of our dynamic environment, but fundamental principles guiding these transitions remain poorly understood. Here, we capitalize on recent advances in network science to analyze patterns of functional interactions between brain regions. We use dynamic network representations to probe the landscape of brain reconfigurations that accompany task performance both within and between four cognitive states: a task-free resting state, an attention-demanding state, and two memory-demanding states. Using the formalism of hypergraphs, we identify the presence of groups of functional interactions that fluctuate coherently in strength over time both within (task-specific) and across (task-general) brain states. In contrast to prior emphases on the complexity of many dyadic (region-to-region) relationships, these results demonstrate that brain adaptability can be described by common processes that drive the dynamic integration of cognitive systems. Moreover, our results establish the hypergraph as an effective measure for understanding functional brain dynamics, which may also prove useful in examining cross-task, cross-age, and cross-cohort functional change.

Functional connectivity and brain networks in schizophrenia.

Schizophrenia has often been conceived as a disorder of connectivity between components of large-scale brain networks. We tested this hypothesis by measuring aspects of both functional connectivity and functional network topology derived from resting-state fMRI time series acquired at 72 cerebral regions over 17 min from 15 healthy volunteers (14 male, 1 female) and 12 people diagnosed with schizophrenia (10 male, 2 female). We investigated between-group differences in strength and diversity of functional connectivity in the 0.06-0.125 Hz frequency interval, and some topological properties of undirected graphs constructed from thresholded interregional correlation matrices. In people with schizophrenia, strength of functional connectivity was significantly decreased, whereas diversity of functional connections was increased. Topologically, functional brain networks had reduced clustering and small-worldness, reduced probability of high-degree hubs, and increased robustness in the schizophrenic group. Reduced degree and clustering were locally significant in medial parietal, premotor and cingulate, and right orbitofrontal cortical nodes of functional networks in schizophrenia. Functional connectivity and topological metrics were correlated with each other and with behavioral performance on a verbal fluency task. We conclude that people with schizophrenia tend to have a less strongly integrated, more diverse profile of brain functional connectivity, associated with a less hub-dominated configuration of complex brain functional networks. Alongside these behaviorally disadvantageous differences, however, brain networks in the schizophrenic group also showed a greater robustness to random attack, pointing to a possible benefit of the schizophrenia connectome, if less extremely expressed.