Stress induces behavioral abnormalities by increasing expression of phagocytic receptor MERTK in astrocytes to promote synapse phagocytosis.

Childhood neglect and/or abuse can induce mental health conditions with unknown mechanisms. Here, we identified stress hormones as strong inducers of astrocyte-mediated synapse phagocytosis. Using in vitro, in vivo, and human brain organoid experiments, we showed that stress hormones increased the expression of the Mertk phagocytic receptor in astrocytes through glucocorticoid receptor (GR). In post-natal mice, exposure to early social deprivation (ESD) specifically activated the GR-MERTK pathway in astrocytes, but not in microglia. The excitatory post-synaptic density in cortical regions was reduced in ESD mice, and there was an increase in the astrocytic engulfment of these synapses. The loss of excitatory synapses, abnormal neuronal network activities, and behavioral abnormalities in ESD mice were largely prevented by ablating GR or MERTK in astrocytes. Our work reveals the critical roles of astrocytic GR-MERTK activation in evoking stress-induced abnormal behaviors in mice, suggesting GR-MERTK signaling as a therapeutic target for stress-induced mental health conditions.

Neurobiology and systems biology of stress resilience.

Stress resilience is the phenomenon that some people maintain their mental health despite exposure to adversity or show only temporary impairments followed by quick recovery. Resilience research attempts to unravel the factors and mechanisms that make resilience possible and to harness its insights for the development of preventative interventions in individuals at risk for acquiring stress-related dysfunctions. Biological resilience research has been lagging behind the psychological and social sciences but has seen a massive surge in recent years. At the same time, progress in this field has been hampered by methodological challenges related to finding suitable operationalizations and study designs, replicating findings, and modeling resilience in animals. We embed a review of behavioral, neuroimaging, neurobiological, and systems biological findings in adults in a critical methods discussion. We find preliminary evidence that hippocampus-based pattern separation and prefrontal-based cognitive control functions protect against the development of pathological fears in the aftermath of singular, event-type stressors [as found in fear-related disorders, including simpler forms of posttraumatic stress disorder (PTSD)] by facilitating the perception of safety. Reward system-based pursuit and savoring of positive reinforcers appear to protect against the development of more generalized dysfunctions of the anxious-depressive spectrum resulting from more severe or longer-lasting stressors (as in depression, generalized or comorbid anxiety, or severe PTSD). Links between preserved functioning of these neural systems under stress and neuroplasticity, immunoregulation, gut microbiome composition, and integrity of the gut barrier and the blood-brain barrier are beginning to emerge. On this basis, avenues for biological interventions are pointed out.

Smartphones and the Neuroscience of Mental Health.

Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal data sets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness.

Key language markers of depression on social media depend on race.

Depression has robust natural language correlates and can increasingly be measured in language using predictive models. However, despite evidence that language use varies as a function of individual demographic features (e.g., age, gender), previous work has not systematically examined whether and how depression's association with language varies by race. We examine how race moderates the relationship between language features (i.e., first-person pronouns and negative emotions) from social media posts and self-reported depression, in a matched sample of Black and White English speakers in the United States. Our findings reveal moderating effects of race: While depression severity predicts I-usage in White individuals, it does not in Black individuals. White individuals use more belongingness and self-deprecation-related negative emotions. Machine learning models trained on similar amounts of data to predict depression severity performed poorly when tested on Black individuals, even when they were trained exclusively using the language of Black individuals. In contrast, analogous models tested on White individuals performed relatively well. Our study reveals surprising race-based differences in the expression of depression in natural language and highlights the need to understand these effects better, especially before language-based models for detecting psychological phenomena are integrated into clinical practice.

Depressive symptoms during the transition to adolescence: Left hippocampal volume as a marker of social context sensitivity.

The transition to adolescence is a critical period for mental health development. Socio-experiential environments play an important role in the emergence of depressive symptoms with some adolescents showing more sensitivity to social contexts than others. Drawing on recent developmental neuroscience advances, we examined whether hippocampal volume amplifies social context effects in the transition to adolescence. We analyzed 2-y longitudinal data from the Adolescent Brain Cognitive Development (ABCD®) study in a diverse sample of 11,832 youth (mean age: 9.914 y; range: 8.917 to 11.083 y; 47.8% girls) from 21 sites across the United States. Socio-experiential environments (i.e., family conflict, primary caregiver's depressive symptoms, parental warmth, peer victimization, and prosocial school environment), hippocampal volume, and a wide range of demographic characteristics were measured at baseline. Youth's symptoms of major depressive disorder were assessed at both baseline and 2 y later. Multilevel mixed-effects linear regression analyses showed that negative social environments (i.e., family conflict, primary caregiver's depressive symptoms, and peer victimization) and the absence of positive social environments (i.e., parental warmth and prosocial school environment) predicted greater increases in youth's depressive symptoms over 2 y. Importantly, left hippocampal volume amplified social context effects such that youth with larger left hippocampal volume experienced greater increases in depressive symptoms in more negative and less positive social environments. Consistent with brain-environment interaction models of mental health, these findings underscore the importance of families, peers, and schools in the development of depression during the transition to adolescence and show how neural structure amplifies social context sensitivity.

Changes in well-being among socially isolated older people during the COVID-19 pandemic: An outcome-wide analysis.

Older adults experienced major changes during the COVID-19 pandemic and ensuing restrictions, and it might be expected that those who were already socially isolated before the pandemic were particularly vulnerable. We apply an outcome-wide longitudinal design on 4,636 participants (mean age 66.8 y) from the English Longitudinal Study of Ageing, observed in 2018/19 and early (June/July 2020) and later (November/December 2020) in the pandemic. Social isolation is defined using an index including marital status, social contact, and social participation in 2018/19. Using mixed models, we compare changes in well-being, health, health behaviors, financial well-being, and Internet use, between isolated and nonisolated participants. From before to during the pandemic, isolated participants (29%) experienced smaller declines in life satisfaction and quality of life and a smaller increase in loneliness. They showed greater declines in smoking and physical activity and were more likely to remain worried about their future financial situation. They also did not change in their likelihood of regular Internet use, contrasting with nonisolated participants who increased in this regard. The groups followed a similar trend for general health and sleep quality (no change), depression and anxiety (increase), and expectations of future financial difficulties (decrease). Although isolated older adults generally show poorer outcomes than their socially connected counterparts, they were somewhat protected during the pandemic on some fronts. Our findings highlight the need to continually care for isolated older adults but also to be attentive in times of unexpected crises to those experiencing extreme changes related to necessary policy responses.

It matters what you see: Graphic media images of war and terror may amplify distress.

Media exposure to graphic images of violence has proliferated in contemporary society, particularly with the advent of social media. Extensive exposure to media coverage immediately after the 9/11 attacks and the Boston Marathon bombings (BMB) was associated with more early traumatic stress symptoms; in fact, several hours of BMB-related daily media exposure was a stronger correlate of distress than being directly exposed to the bombings themselves. Researchers have replicated these findings across different traumatic events, extending this work to document that exposure to graphic images is independently and significantly associated with stress symptoms and poorer functioning. The media exposure-distress association also appears to be cyclical over time, with increased exposure predicting greater distress and greater distress predicting more media exposure following subsequent tragedies. The war in Israel and Gaza, which began on October 7, 2023, provides a current, real-time context to further explore these issues as journalists often share graphic images of death and destruction, making media-based graphic images once again ubiquitous and potentially challenging public well-being. For individuals sharing an identity with the victims or otherwise feeling emotionally connected to the Middle East, it may be difficult to avoid viewing these images. Through a review of research on the association between exposure to graphic images and public health, we discuss differing views on the societal implications of viewing such images and advocate for media literacy campaigns to educate the public to identify mis/disinformation and understand the risks of viewing and sharing graphic images with others.

The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster.

As disasters increase due to climate change, population density, epidemics, and technology, information is needed about postdisaster consequences for people's mental health and how stress-related mental disorders affect multiple spheres of life, including labor-market attachment. We tested the causal hypothesis that individuals who developed stress-related mental disorders as a consequence of their disaster exposure experienced subsequent weak labor-market attachment and poor work-related outcomes. We leveraged a natural experiment in an instrumental variables model, studying a 2004 fireworks factory explosion disaster that precipitated the onset of stress-related disorders (posttraumatic stress disorder, anxiety, and depression) among individuals in the local community (N = 86,726). We measured labor-market outcomes using longitudinal population-level administrative data: sick leave, unemployment benefits, early retirement pension, and income from wages from 2007 to 2010. We found that individuals who developed a stress-related disorder after the disaster were likely to go on sickness benefit, both in the short- and long-term, were likely to use unemployment benefits and to lose wage income in the long term. Stress-related disorders did not increase the likelihood of early retirement. The natural experiment design minimized the possibility that omitted confounders biased these effects of mental health on work outcomes. Addressing the mental health and employment needs of survivors after a traumatic experience may improve their labor-market outcomes and their nations' economic outputs.

Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

The researcher's guide to selecting biomarkers in mental health studies.

Clinical mental health researchers may understandably struggle with how to incorporate biological assessments in clinical research. The options are numerous and are described in a vast and complex body of literature. Here we provide guidelines to assist mental health researchers seeking to include biological measures in their studies. Apart from a focus on behavioral outcomes as measured via interviews or questionnaires, we advocate for a focus on biological pathways in clinical trials and epidemiological studies that may help clarify pathophysiology and mechanisms of action, delineate biological subgroups of participants, mediate treatment effects, and inform personalized treatment strategies. With this paper we aim to bridge the gap between clinical and biological mental health research by (1) discussing the clinical relevance, measurement reliability, and feasibility of relevant peripheral biomarkers; (2) addressing five types of biological tissues, namely blood, saliva, urine, stool and hair; and (3) providing information on how to control sources of measurement variability.

Differential spatial-social accessibility to mental health care and suicide.

In recent years, the United States has been experiencing historically high suicide rates. In the face of mental health care provider shortages that leave millions needing to travel longer to find providers with schedule openings, if any are available at all, the inaccessibility of mental health care has become increasingly central in explaining suicidality. To examine the relationship between access to care and suicide, we leverage a dataset mapping all licensed US psychiatrists and psychotherapists (N= 711,214), as of early 2020, and employ real-world transportation data to model patients' mobility barriers. We find a strong association between reduced mental health care provider spatial-social accessibility and heightened suicide risk. Using a machine learning approach to condition on a host of 22 contextual factors known to be implicated in suicide (e.g., race, education, divorce, gun shop prevalence), we find that in locales where individuals seeking care can access fewer mental health care providers, already more likely to be saturated by demand, suicide risk is increased (3.2% for each reduced SD of psychiatrist accessibility; 2.3% for psychotherapists). Additionally, we observe that local spatial-social accessibility inequalities are associated with further heightened risk of suicide, underscoring the need for research to account for the highly localized barriers preventing many Americans from accessing needed mental health services.

Air pollution and suicide in rural and urban America: Evidence from wildfire smoke.

Air pollution poses well-established risks to physical health, but little is known about its effects on mental health. We study the relationship between wildfire smoke exposure and suicide risk in the United States in 2007 to 2019 using data on all deaths by suicide and satellite-based measures of wildfire smoke and ambient fine particulate matter (PM2.5) concentrations. We identify the causal effects of wildfire smoke pollution on suicide by relating year-over-year fluctuations in county-level monthly smoke exposure to fluctuations in suicide rates and compare the effects across local areas and demographic groups that differ considerably in their baseline suicide risk. In rural counties, an additional day of smoke increases monthly mean PM2.5 by 0.41 µg/m3 and suicide deaths by 0.11 per million residents, such that a 1-µg/m3 (13%) increase in monthly wildfire-derived fine particulate matter leads to 0.27 additional suicide deaths per million residents (a 2.0% increase). These effects are concentrated among demographic groups with both high baseline suicide risk and high exposure to outdoor air: men, working-age adults, non-Hispanic Whites, and adults with no college education. By contrast, we find no evidence that smoke pollution increases suicide risk among any urban demographic group. This study provides large-scale evidence that air pollution elevates the risk of suicide, disproportionately so among rural populations.

Global trends in emotional distress.

In this study, we examined emotional distress using annual representative survey data from 1.53 million individuals surveyed in 113 countries from 2009 to 2021. Participants reported whether they had experienced worry, sadness, stress, or anger during a lot of the previous day. Within-country estimates showed that the prevalence of feelings of emotional distress increased from 25 to 31% between 2009 and 2021, with those with low levels of education and income experiencing the largest increases in distress. On a global level, the pandemic period was characterized by an initial increase in distress in 2020 followed by recovery in 2021.

Multilevel cultural evolution: From new theory to practical applications.

Evolutionary science has led to many practical applications of genetic evolution but few practical uses of cultural evolution. This is because the entire study of evolution was gene centric for most of the 20th century, relegating the study and application of human cultural change to other disciplines. The formal study of human cultural evolution began in the 1970s and has matured to the point of deriving practical applications. We provide an overview of these developments and examples for the topic areas of complex systems science and engineering, economics and business, mental health and well-being, and global change efforts.

Fostering Psychological Safety and Supporting Mental Health Among Cardiovascular Health Care Workers: A Science Advisory From the American Heart Association.

The psychological safety of health care workers is an important but often overlooked aspect of the rising rates of burnout and workforce shortages. In addition, mental health conditions are prevalent among health care workers, but the associated stigma is a significant barrier to accessing adequate care. More efforts are therefore needed to foster health care work environments that are safe and supportive of self-care. The purpose of this brief document is to promote a culture of psychological safety in health care organizations. We review ways in which organizations can create a psychologically safe workplace, the benefits of a psychologically safe workplace, and strategies to promote mental health and reduce suicide risk.

Symptoms of mental disorders and oral contraception use: A systematic review and meta-analysis.

Worldwide, over 150 million adolescent and adult women use oral contraceptives (OC). An association between OC-use and the emergence of symptoms of mental disorders has been suggested. This systematic review and meta-analysis provide an overview of published research regarding symptoms of mental disorders in association with OC-use, factoring the influence of OC types, age of first-use, duration of OC-intake, and previous diagnoses of mental disorders. A systematic literature search was conducted between June-July 2022. 22 studies were included. While most found no significant OC-use effects on mental symptoms, some hinted at OCs as a potential risk. The existing evidence regarding the potential link between progestin-only OC-use and an elevated risk of mental symptoms in comparison to combined OC-use remains inconclusive. However, due to emerging indications suggesting that the formulation of OC might play a role in mental health outcomes, this topic warrants further investigation. Moreover, indications of an increased risk for depressive symptoms in adolescent OC-users should be noted. Hence, while general population effects seem unlikely, they cannot be completely disregarded. The decision on OC-use should depend on the patient's medical history and should be re-evaluated regularly.

HMM for discovering decision-making dynamics using reinforcement learning experiments.

Major depressive disorder (MDD), a leading cause of years of life lived with disability, presents challenges in diagnosis and treatment due to its complex and heterogeneous nature. Emerging evidence indicates that reward processing abnormalities may serve as a behavioral marker for MDD. To measure reward processing, patients perform computer-based behavioral tasks that involve making choices or responding to stimulants that are associated with different outcomes, such as gains or losses in the laboratory. Reinforcement learning (RL) models are fitted to extract parameters that measure various aspects of reward processing (e.g. reward sensitivity) to characterize how patients make decisions in behavioral tasks. Recent findings suggest the inadequacy of characterizing reward learning solely based on a single RL model; instead, there may be a switching of decision-making processes between multiple strategies. An important scientific question is how the dynamics of strategies in decision-making affect the reward learning ability of individuals with MDD. Motivated by the probabilistic reward task within the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, we propose a novel RL-HMM (hidden Markov model) framework for analyzing reward-based decision-making. Our model accommodates decision-making strategy switching between two distinct approaches under an HMM: subjects making decisions based on the RL model or opting for random choices. We account for continuous RL state space and allow time-varying transition probabilities in the HMM. We introduce a computationally efficient Expectation-maximization (EM) algorithm for parameter estimation and use a nonparametric bootstrap for inference. Extensive simulation studies validate the finite-sample performance of our method. We apply our approach to the EMBARC study to show that MDD patients are less engaged in RL compared to the healthy controls, and engagement is associated with brain activities in the negative affect circuitry during an emotional conflict task.

Strength and resilience of developing brain circuits predict adolescent emotional and stress responses during the COVID-19 pandemic.

The COVID-19 pandemic has had profound but incompletely understood adverse effects on youth. To elucidate the role of brain circuits in how adolescents responded to the pandemic's stressors, we investigated their prepandemic organization as a predictor of mental/emotional health in the first ~15 months of the pandemic. We analyzed resting-state networks from n = 2,641 adolescents [median age (interquartile range) = 144.0 (13.0) months, 47.7% females] in the Adolescent Brain Cognitive Development study, and longitudinal assessments of mental health, stress, sadness, and positive affect, collected every 2 to 3 months from May 2020 to May 2021. Topological resilience and/or network strength predicted overall mental health, stress and sadness (but not positive affect), at multiple time points, but primarily in December 2020 and May 2021. Higher resilience of the salience network predicted better mental health in December 2020 (ß = 0.19, 95% CI = [0.06, 0.31], P = 0.01). Lower connectivity of left salience, reward, limbic, and prefrontal cortex and its thalamic, striatal, amygdala connections, predicted higher stress (ß = -0.46 to -0.20, CI = [-0.72, -0.07], P < 0.03). Lower bilateral robustness (higher fragility) and/or connectivity of these networks predicted higher sadness in December 2020 and May 2021 (ß = -0.514 to -0.19, CI = [-0.81, -0.05], P < 0.04). These findings suggest that the organization of brain circuits may have played a critical role in adolescent stress and mental/emotional health during the pandemic.

Reading language of the eyes in female depression.

Aberrations in non-verbal social cognition have been reported to coincide with major depressive disorder. Yet little is known about the role of the eyes. To fill this gap, the present study explores whether and, if so, how reading language of the eyes is altered in depression. For this purpose, patients and person-by-person matched typically developing individuals were administered the Emotions in Masked Faces task and Reading the Mind in the Eyes Test, modified, both of which contained a comparable amount of visual information available. For achieving group homogeneity, we set a focus on females as major depressive disorder displays a gender-specific profile. The findings show that facial masks selectively affect inferring emotions: recognition of sadness and anger are more heavily compromised in major depressive disorder as compared with typically developing controls, whereas the recognition of fear, happiness, and neutral expressions remains unhindered. Disgust, the forgotten emotion of psychiatry, is the least recognizable emotion in both groups. On the Reading the Mind in the Eyes Test patients exhibit lower accuracy on positive expressions than their typically developing peers, but do not differ on negative items. In both depressive and typically developing individuals, the ability to recognize emotions behind a mask and performance on the Reading the Mind in the Eyes Test are linked to each other in processing speed, but not recognition accuracy. The outcome provides a blueprint for understanding the complexities of reading language of the eyes within and beyond the COVID-19 pandemic.

The interplay of gut microbiota, obesity, and depression: insights and interventions.

The gut microbiome, body weight, and related comorbidities are intricately linked through a complex interaction of microbial, genetic, environmental, and psychological factors. Alterations in gut microbiota can contribute to the development of weight disorders and depressive symptoms, with the potential for these relationships to be bidirectional. Effective management of these interconnected conditions often involves a combination of lifestyle modifications and psychological support. Medical interventions, including treatments for obesity, antidiabetic drugs, antidepressants, antibiotics, and probiotics, can have beneficial and detrimental effects on gut microbiota and mental health. Further research is needed to better understand their impact on gut microbiome and mental health in the context of obesity.