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Theory predicts that biological processes of aging may contribute to poor mental health in late life. To test this hypothesis, we evaluated prospective associations between biological age and incident depression and anxiety in 424,299 UK Biobank participants. We measured biological age from clinical traits using the KDM-BA and PhenoAge algorithms. At baseline, participants who were biologically older more often experienced depression/anxiety. During a median of 8.7 years of follow-up, participants with older biological age were at increased risk of incident depression/anxiety (5.9% increase per standard deviation [SD] of KDM-BA acceleration, 95% confidence intervals [CI]: 3.3%–8.5%; 11.3% increase per SD of PhenoAge acceleration, 95% CI: 9.%–13.0%). Biological-aging-associated risk of depression/anxiety was independent of and additive to genetic risk measured by genome-wide-association-study-based polygenic scores. Advanced biological aging may represent a potential risk factor for incident depression/anxiety in midlife and older adults and a potential target for risk assessment and intervention. Theory indicates that biological aging may contribute to poor mental health in late life. Here, authors show advanced biological aging may represent a potential risk factor for incident depression/anxiety in midlife and older adults and a potential target for risk assessment and intervention.

To provide a contemporary global prevalence of mental health issues among the general population amid the coronavirus disease-2019 (COVID-19) pandemic. We searched electronic databases, preprint databases, grey literature, and unpublished studies from January 1, 2020, to June 16, 2020 (updated on July 11, 2020), with no language restrictions. Observational studies using validated measurement tools and reporting data on mental health issues among the general population were screened to identify all relevant studies. We have included information from 32 different countries and 398,771 participants. The pooled prevalence of mental health issues amid the COVID-19 pandemic varied widely across countries and regions and was higher than previous reports before the COVID-19 outbreak began. The global prevalence estimate was 28.0% for depression; 26.9% for anxiety; 24.1% for post-traumatic stress symptoms; 36.5% for stress; 50.0% for psychological distress; and 27.6% for sleep problems. Data are limited for other aspects of mental health issues. Our findings highlight the disparities between countries in terms of the poverty impacts of COVID-19, preparedness of countries to respond, and economic vulnerabilities that impact the prevalence of mental health problems. Research on the social and economic burden is needed to better manage mental health problems during and after epidemics or pandemics. Systematic review registration : PROSPERO CRD 42020177120.

There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or ‘biotypes’ to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free ( n  = 801) and after randomization to pharmacotherapy or behavioral therapy ( n  = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry. Personalized brain circuit measures quantified using a new imaging technology in 801 patients with depression and anxiety identify six biotypes with unique symptoms, behaviors and responses to different types of treatment.

University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I 2  = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I 2  = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of Ph.D. students are urgently needed.

We report a meta-analysis of virtual reality (VR) interventions for anxiety and depression outcomes, as well as treatment attrition. We included randomized controlled trials comparing VR interventions, alone or in combination, to control conditions or other active psychological interventions. Effects sizes (Hedges’ g ) for anxiety and depression outcomes, as post-test and follow-up, were pooled with a random-effects model. Drop-outs were compared using odds ratio (OR) with a Mantel-Haenszel model. We included 39 trials (52 comparisons). Trial risk of bias was unclear for most domains, and high for incomplete outcome data. VR-based therapies were more effective than control at post-test for anxiety, g = 0.79, 95% CI 0.57 to 1.02, and depression, g = 0.73, 95% CI 0.25 to 1.21, but not for treatment attrition, OR = 1.34, 95% CI 0.95 to 1.89. Heterogeneity was high and there was consistent evidence of small study effects. There were no significant differences between VR-based and other active interventions. VR interventions outperformed control conditions for anxiety and depression but did not improve treatment drop-out. High heterogeneity, potential publication bias, predominant use of waitlist controls, and high or uncertain risk of bias of most trials question the reliability of these effects.

Astrocytes and neurons extensively interact in the brain. Identifying astrocyte and neuron proteomes is essential for elucidating the protein networks that dictate their respective contributions to physiology and disease. Here we used cell-specific and subcompartment-specific proximity-dependent biotinylation 1 to study the proteomes of striatal astrocytes and neurons in vivo. We evaluated cytosolic and plasma membrane compartments for astrocytes and neurons to discover how these cells differ at the protein level in their signalling machinery. We also assessed subcellular compartments of astrocytes, including end feet and fine processes, to reveal their subproteomes and the molecular basis of essential astrocyte signalling and homeostatic functions. Notably, SAPAP3 (encoded by Dlgap3 ), which is associated with obsessive–compulsive disorder (OCD) and repetitive behaviours 2 – 8 , was detected at high levels in striatal astrocytes and was enriched within specific astrocyte subcompartments where it regulated actin cytoskeleton organization. Furthermore, genetic rescue experiments combined with behavioural analyses and molecular assessments in a mouse model of OCD 4 lacking SAPAP3 revealed distinct contributions of astrocytic and neuronal SAPAP3 to repetitive and anxiety-related OCD-like phenotypes. Our data define how astrocytes and neurons differ at the protein level and in their major signalling pathways. Moreover, they reveal how astrocyte subproteomes vary between physiological subcompartments and how both astrocyte and neuronal SAPAP3 mechanisms contribute to OCD phenotypes in mice. Our data indicate that therapeutic strategies that target both astrocytes and neurons may be useful to explore in OCD and potentially other brain disorders. Analyses of the proteomes of astrocytes and neurons in a cell-specific and subcompartment-specific manner reveal distinct roles for these cell types that are relevant to obsessive–compulsive disorder and perhaps other brain disorders.

Human intracranial amygdala recordings reveal fast-latency responses to broad and low, but not high, spatial frequency components of fearful, but not happy or neutral, faces, which are not observed with unpleasant scenes. Amygdala fearful face responses are faster than in fusiform cortex, supporting a phylogenetically old, subcortical pathway to human amygdala. A fast, subcortical pathway to the amygdala is thought to have evolved to enable rapid detection of threat. This pathway's existence is fundamental for understanding nonconscious emotional responses, but has been challenged as a result of a lack of evidence for short-latency fear-related responses in primate amygdala, including humans. We recorded human intracranial electrophysiological data and found fast amygdala responses, beginning 74-ms post-stimulus onset, to fearful, but not neutral or happy, facial expressions. These responses had considerably shorter latency than fear responses that we observed in visual cortex. Notably, fast amygdala responses were limited to low spatial frequency components of fearful faces, as predicted by magnocellular inputs to amygdala. Furthermore, fast amygdala responses were not evoked by photographs of arousing scenes, which is indicative of selective early reactivity to socially relevant visual information conveyed by fearful faces. These data therefore support the existence of a phylogenetically old subcortical pathway providing fast, but coarse, threat-related signals to human amygdala.

Fear is an adaptive emotion that mobilizes defensive resources upon confrontation with danger. However, fear becomes maladaptive and can give rise to the development of clinical anxiety when it exceeds the degree of threat, generalizes broadly across stimuli and contexts, persists after the danger is gone or promotes excessive avoidance behaviour. Pavlovian fear conditioning has been the prime research instrument that has led to substantial progress in understanding the multi-faceted psychological and neurobiological mechanisms of fear in past decades. In this Perspective, we suggest that fruitful use of Pavlovian fear conditioning as a laboratory model of clinical anxiety requires moving beyond the study of fear acquisition to associated fear conditioning phenomena: fear extinction, generalization of conditioned fear and fearful avoidance. Understanding individual differences in each of these phenomena, not only in isolation but also in how they interact, will further strengthen the external validity of the fear conditioning model as a tool with which to study maladaptive fear as it manifests in clinical anxiety.

High-quality diets have been increasingly acknowledged as a promising candidate to counter the growing prevalence of mental health disorders. This study aims to investigate the prospective associations of adhering to the EAT-Lancet reference diet with incident depression, anxiety and their co-occurrence in 180,446 UK Biobank participants. Degrees of adherence to the EAT-Lancet diet were translated into three different diet scores. Over 11.62 years of follow-up, participants in the highest adherence group of the Knuppel EAT-Lancet index showed lower risks of depression (hazard ratio: 0.806, 95% CI: 0.730–0.890), anxiety (0.818, 0.751–0.892) and their co-occurrence (0.756, 0.624–0.914), compared to the lowest adherence group. The corresponding hazard ratios (95% CIs) were 0.711 (0.627–0.806), 0.765 (0.687–0.852) and 0.659 (0.516–0.841) for the Stubbendorff EAT-Lancet index, and 0.844 (0.768–0.928), 0.825 (0.759–0.896) and 0.818 (0.682–0.981) for the Kesse-Guyot EAT-Lancet diet index. Our findings suggest that higher adherence to the EAT-Lancet diet is associated with lower risks of incident depression, anxiety and their co-occurrence. The EAT-Lancet reference diet has been proposed for improving both planetary and human health in 2019. Here, the authors show that higher adherence to the EAT-Lancet diet is associated with lower risks of depression, anxiety and their cooccurrence.

The authors use computational modeling of participants' performance on an aversive learning task to examine how decision-making is altered in anxiety. Results indicate that anxious individuals struggle to use information regarding the stability of action-outcome relationships to guide their choices. Pupillometry data link this deficit to altered norepinephrinergic function. Statistical regularities in the causal structure of the environment enable us to predict the probable outcomes of our actions. Environments differ in the extent to which action-outcome contingencies are stable or volatile. Difficulty in being able to use this information to optimally update outcome predictions might contribute to the decision-making difficulties seen in anxiety. We tested this using an aversive learning task manipulating environmental volatility. Human participants low in trait anxiety matched updating of their outcome predictions to the volatility of the current environment, as predicted by a Bayesian model. Individuals with high trait anxiety showed less ability to adjust updating of outcome expectancies between stable and volatile environments. This was linked to reduced sensitivity of the pupil dilatory response to volatility, potentially indicative of altered norepinephrinergic responsivity to changes in this aspect of environmental information.