Childhood unpredictability and the development of exploration.

Early in development, the process of exploration helps children gather new information that fosters learning about the world. Yet, it is unclear how childhood experiences may influence the way humans approach new learning. What influences decisions to exploit known, familiar options versus trying a novel alternative? We found that childhood unpredictability, characterized by unpredictable caregiving and unstable living environments, was associated with reduced exploratory behavior. This effect holds while controlling for individual differences, including anxiety and stress. Individuals who perceived their childhoods as unpredictable explored less and were instead more likely to repeat previous choices (habitual responding). They were also more sensitive to uncertainty than to potential rewards, even when the familiar options yielded lower rewards. We examined these effects across multiple task contexts and via both in-person (N = 78) and online replication (N = 84) studies among 10- to 13-y-olds. Results are discussed in terms of the potential cascading effects of unpredictable environments on the development of decision-making and the effects of early experience on subsequent learning.

The impact of COVID-19 on a college freshman sample reveals genetic and nongenetic forms of susceptibility and resilience to stress.

Using a longitudinal approach, we sought to define the interplay between genetic and nongenetic factors in shaping vulnerability or resilience to COVID-19 pandemic stress, as indexed by the emergence of symptoms of depression and/or anxiety. University of Michigan freshmen were characterized at baseline using multiple psychological instruments. Subjects were genotyped, and a polygenic risk score for depression (MDD-PRS) was calculated. Daily physical activity and sleep were captured. Subjects were sampled at multiple time points throughout the freshman year on clinical rating scales, including GAD-7 and PHQ-9 for anxiety and depression, respectively. Two cohorts (2019 to 2021) were compared to a pre-COVID-19 cohort to assess the impact of the pandemic. Across cohorts, 26 to 40% of freshmen developed symptoms of anxiety or depression (N = 331). Depression symptoms significantly increased in the pandemic years and became more chronic, especially in females. Physical activity was reduced, and sleep was increased by the pandemic, and this correlated with the emergence of mood symptoms. While low MDD-PRS predicted lower risk for depression during a typical freshman year, this genetic advantage vanished during the pandemic. Indeed, females with lower genetic risk accounted for the majority of the pandemic-induced rise in depression. We developed a model that explained approximately half of the variance in follow-up depression scores based on psychological trait and state characteristics at baseline and contributed to resilience in genetically vulnerable subjects. We discuss the concept of multiple types of resilience, and the interplay between genetic, sex, and psychological factors in shaping the affective response to different types of stressors.

Rare GPR37L1 Variants Reveal Potential Association between GPR37L1 and Disorders of Anxiety and Migraine.

GPR37L1 is an orphan receptor that couples through heterotrimeric G-proteins to regulate physiological functions. Since its role in humans is not fully defined, we used an unbiased computational approach to assess the clinical significance of rare G-protein-coupled receptor 37-like 1 (GPR37L1) genetic variants found among 51,289 whole-exome sequences from the DiscovEHR cohort. Rare GPR37L1 coding variants were binned according to predicted pathogenicity and analyzed by sequence kernel association testing to reveal significant associations with disease diagnostic codes for epilepsy and migraine, among others. Since associations do not prove causality, rare GPR37L1 variants were functionally analyzed in SK-N-MC cells to evaluate potential signaling differences and pathogenicity. Notably, receptor variants exhibited varying abilities to reduce cAMP levels, activate mitogen-activated protein kinase (MAPK) signaling, and/or upregulate receptor expression in response to the agonist prosaptide (TX14(A)), as compared with the wild-type receptor. In addition to signaling changes, knock-out (KO) of GPR37L1 or expression of certain rare variants altered cellular cholesterol levels, which were also acutely regulated by administration of the agonist TX14(A) via activation of the MAPK pathway. Finally, to simulate the impact of rare nonsense variants found in the large patient cohort, a KO mouse line lacking Gpr37l1 was generated. Although KO animals did not recapitulate an acute migraine phenotype, the loss of this receptor produced sex-specific changes in anxiety-related disorders often seen in chronic migraineurs. Collectively, these observations define the existence of rare GPR37L1 variants associated with neuropsychiatric conditions in the human population and identify the signaling changes contributing to pathological processes.

Hemorrhoidal disease and its genetic association with depression, bipolar disorder, anxiety disorders, and schizophrenia: a bidirectional mendelian randomization study.

BACKGROUND: Hemorrhoids and psychiatric disorders exhibit high prevalence rates and a tendency for relapse in epidemiological studies. Despite this, limited research has explored their correlation, and these studies are often subject to reverse causality and residual confounding. We conducted a Mendelian randomization (MR) analysis to comprehensively investigate the association between several mental illnesses and hemorrhoidal disease. METHODS: Genetic associations for four psychiatric disorders and hemorrhoidal disease were obtained from large consortia, the FinnGen study, and the UK Biobank. Genetic variants associated with depression, bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease at the genome-wide significance level were selected as instrumental variables. Screening for potential confounders in genetic instrumental variables using PhenoScanner V2. Bidirectional MR estimates were employed to assess the effects of four psychiatric disorders on hemorrhoidal disease. RESULTS: Our analysis revealed a significant association between genetically predicted depression and the risk of hemorrhoidal disease (IVW, OR=1.20,95% CI=1.09 to 1.33, P <0.001). We found no evidence of associations between bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease. Inverse MR analysis provided evidence for a significant association between genetically predicted hemorrhoidal disease and depression (IVW, OR=1.07,95% CI=1.04 to 1.11, P <0.001). CONCLUSIONS: This study offers MR evidence supporting a bidirectional causal relationship between depression and hemorrhoidal disease.

A network model of depressive and anxiety symptoms: a statistical evaluation.

BACKGROUND: Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks. METHODS: A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression. RESULTS: Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model. CONCLUSION: Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

Risk for diagnosis or treatment of mood or anxiety disorders in adults after SARS-CoV-2 infection, 2020-2022.

COVID-19 is associated with increased risks for mood or anxiety disorders, but it remains uncertain how the association evolves over time or which patient groups are most affected. We conducted a retrospective cohort study using a nationwide database of electronic health records to determine the risk of depressive or anxiety disorder diagnoses after SARS-CoV-2 infection by 3-month blocks from January 2020 to April 2022. The study population comprised 822,756 patients (51.8% female; mean age 42.8 years) with COVID-19 and 2,034,353 patients with other respiratory tract infections (RTIs) (53.5% female, mean age 30.6 years). First time diagnoses of depressive or anxiety disorders 14 days to 3 months after infection, as well as new or new plus recurrent prescriptions of antidepressants or anxiolytics, were compared between propensity score matched cohorts using Kaplan-Meier survival analysis, including hazard ratio (HR) and 95% confidence interval (CI). Risk of a new diagnosis or prescription was also stratified by age, sex, and race to better characterize which groups were most affected. In the first three months of the pandemic, patients infected with SARS-CoV-2 had significantly increased risk of depression or anxiety disorder diagnosis (HR 1.65 [95% CI, 1.30-2.08]). October 2021 to January 2022 (HR, 1.12 [95% CI, 1.06-1.18]) and January to April 2022 (HR, 1.08 [95% CI, 1.01-1.14]). Similar temporal patterns were observed for antidepressant and anxiolytic prescriptions, when the control group was patients with bone fracture, when anxiety and depressive disorders were considered separately, when recurrent depressive disorder was tested, and when the test period was extended to 6 months. COVID-19 patients ≥65 years old demonstrated greatest absolute risk at the start of the pandemic (6.8%), which remained consistently higher throughout the study period (HR, 1.20 [95% CI, 1.13-1.27]), and overall, women with COVID-19 had greater risk than men (HR 1.35 [95% CI 1.30-1.40]).

Key subphenotypes of bipolar disorder are differentially associated with polygenic liabilities for bipolar disorder, schizophrenia, and major depressive disorder.

Bipolar disorder (BD) features heterogenous clinical presentation and course of illness. It remains unclear how subphenotypes associate with genetic loadings of BD and related psychiatric disorders. We investigated associations between the subphenotypes and polygenic risk scores (PRS) for BD, schizophrenia, and major depressive disorder (MDD) in two BD cohorts from Sweden (N = 5180) and the UK (N = 2577). Participants were assessed through interviews and medical records for inter-episode remission, psychotic features during mood episodes, global assessment of functioning (GAF, function and symptom burden dimensions), and comorbid anxiety disorders. Meta-analyses based on both cohorts showed that inter-episode remission and GAF-function were positively correlated with BD-PRS but negatively correlated with schizophrenia-PRS (SCZ-PRS) and MDD-PRS. Moreover, BD-PRS was negatively, and MDD-PRS positively, associated with the risk of comorbid anxiety disorders. Finally, SCZ-PRS was positively associated with psychotic symptoms during mood episodes. Assuming a higher PRS of certain psychiatric disorders in cases with a positive family history, we further tested the associations between subphenotypes in index BD people and occurrence of BD, schizophrenia, or MDD in their relatives using Swedish national registries. BD patients with a relative diagnosed with BD had: (1) higher GAF and lower risk of comorbid anxiety than those with a relative diagnosed with schizophrenia or MDD, (2) lower risk of psychotic symptoms than those with a relative diagnosed with schizophrenia. Our findings shed light on the genetic underpinnings of the heterogeneity in clinical manifestations and course of illness in BD, which ultimately provide insights for developing personalized approaches to the diagnosis and treatment.

Patterns of stressful life events and polygenic scores for five mental disorders and neuroticism among adults with depression.

The dominant ('general') version of the diathesis-stress theory of depression views stressors and genetic vulnerability as independent risks. In the Australian Genetics of Depression Study (N = 14,146; 75% female), we tested whether polygenic scores (PGS) for major depression, bipolar disorder, schizophrenia, anxiety, ADHD, and neuroticism were associated with reported exposure to 32 childhood, past-year, lifetime, and accumulated stressful life events (SLEs). In false discovery rate-corrected models, the clearest PGS-SLE relationships were for the ADHD- and depression-PGSs, and to a lesser extent, the anxiety- and schizophrenia-PGSs. We describe the associations for childhood and accumulated SLEs, and the 2-3 strongest past-year/lifetime SLE associations. Higher ADHD-PGS was associated with all childhood SLEs (emotional abuse, emotional neglect, physical neglect; ORs = 1.09-1.14; p's < 1.3 × 10-5), more accumulated SLEs, and reported exposure to sudden violent death (OR = 1.23; p = 3.6 × 10-5), legal troubles (OR = 1.15; p = 0.003), and sudden accidental death (OR = 1.14; p = 0.006). Higher depression-PGS was associated with all childhood SLEs (ORs = 1.07-1.12; p's < 0.013), more accumulated SLEs, and severe human suffering (OR = 1.17; p = 0.003), assault with a weapon (OR = 1.12; p = 0.003), and living in unpleasant surroundings (OR = 1.11; p = 0.001). Higher anxiety-PGS was associated with childhood emotional abuse (OR = 1.08; p = 1.6 × 10-4), more accumulated SLEs, and serious accident (OR = 1.23; p = 0.004), physical assault (OR = 1.08; p = 2.2 × 10-4), and transportation accident (OR = 1.07; p = 0.001). Higher schizophrenia-PGS was associated with all childhood SLEs (ORs = 1.12-1.19; p's < 9.3-8), more accumulated SLEs, and severe human suffering (OR = 1.16; p = 0.003). Higher neuroticism-PGS was associated with living in unpleasant surroundings (OR = 1.09; p = 0.007) and major financial troubles (OR = 1.06; p = 0.014). A reversed pattern was seen for the bipolar-PGS, with lower odds of reported physical assault (OR = 0.95; p = 0.014), major financial troubles (OR = 0.93; p = 0.004), and living in unpleasant surroundings (OR = 0.92; p = 0.007). Genetic risk for several mental disorders influences reported exposure to SLEs among adults with moderately severe, recurrent depression. Our findings emphasise that stressors and diatheses are inter-dependent and challenge diagnosis and subtyping (e.g., reactive/endogenous) based on life events.

Adapt conservation biology teaching to address eco-anxiety in students.

The fear of environmental doom (eco-anxiety) is a new and growing source of mental distress that could particularly affect the next generation of conservation biologists. With care and empathy, educators can help to prevent worsening the mental health of students.

Association between white matter hyperintensity and anxiety/depression.

Although previous studies have explored the associations of white matter hyperintensity with psychiatric disorders, the sample size is small and the conclusions are inconsistent. The present study aimed to further systematically explore the association in a larger sample. All data were extracted from the UK Biobank. First, general linear regression models and logistic regression models were used to assess the association between white matter hyperintensity volume and anxiety/depression. White matter hyperintensity has been classified into periventricular white matter hyperintensity and deep white matter hyperintensity. Anxiety was determined by General Anxiety Disorder-7 score (n = 17,221) and self-reported anxiety (n = 15,333), depression was determined by Patient Health Questionnaire-9 score (n = 17,175), and self-reported depression (n = 14,519). Moreover, we employed Cox proportional hazard models to explore the association between white matter hyperintensity volume and anxiety/depression. The covariates included in fully adjusted model are age, gender, body mass index, Townsend deprivation index, healthy physical activity, cigarette consumption, alcohol consumption, educational attainment, diabetes, hypertension, and coronary heart disease. The results of the fully adjusted model showed that white matter hyperintensity volume was significantly associated with General Anxiety Disorder-7 score (periventricular white matter hyperintensity: ß = 0.152, deep white matter hyperintensity: ß = 0.094) and Patient Health Questionnaire-9 score (periventricular white matter hyperintensity: ß = 0.168). Logistic regression analysis results indicated that periventricular white matter hyperintensity volume (odds ratio = 1.153) was significantly associated with self-reported anxiety. After applying the Cox proportional hazard models, we found that larger white matter hyperintensity volume was associated with increased risk of depression (periventricular white matter hyperintensity: hazard ratio = 1.589, deep white matter hyperintensity: hazard ratio = 1.200), but not anxiety. In summary, our findings support a positive association between white matter hyperintensity volume and depression.

Opinion dynamics in financial markets via random networks.

We investigate financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize individuals in a financial market according to their trading strategy, namely, whether they are noise traders or fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the decisions of fundamentalist agents. We introduce a noise parameter, q, to represent the level of anxiety and perceived uncertainty regarding market behavior, enabling the possibility of adrift financial action. We place individuals as nodes in an Erdös-Rényi random graph, where the links represent their social interactions. At any given time, individuals assume one of two possible opinion states ±1 regarding buying or selling an asset. The model exhibits fundamental qualitative and quantitative real-world market features such as the distribution of logarithmic returns with fat tails, clustered volatility, and the long-term correlation of returns. We use Student's t distributions to fit the histograms of logarithmic returns, showing a gradual shift from a leptokurtic to a mesokurtic regime depending on the fraction of fundamentalist agents. Furthermore, we compare our results with those concerning the distribution of the logarithmic returns of several real-world financial indices.

Hypothalamic deep brain stimulation as a strategy to manage anxiety disorders.

Fear is essential for survival, but excessive anxiety behavior is debilitating. Anxiety disorders affecting millions of people are a global health problem, where new therapies and targets are much needed. Deep brain stimulation (DBS) is established as a therapy in several neurological disorders, but is underexplored in anxiety disorders. The lateral hypothalamus (LH) has been recently revealed as an origin of anxiogenic brain signals, suggesting a target for anxiety treatment. Here, we develop and validate a DBS strategy for modulating anxiety-like symptoms by targeting the LH. We identify a DBS waveform that rapidly inhibits anxiety-implicated LH neural activity and suppresses innate and learned anxiety behaviors in a variety of mouse models. Importantly, we show that the LH DBS displays high temporal and behavioral selectivity: Its affective impact is fast and reversible, with no evidence of side effects such as impaired movement, memory loss, or epileptic seizures. These data suggest that acute hypothalamic DBS could be a useful strategy for managing treatment-resistant anxiety disorders.

Multiscale neural signatures of major depressive, anxiety, and stress-related disorders.

The extent of shared and distinct neural mechanisms underlying major depressive disorder (MDD), anxiety, and stress-related disorders is still unclear. We compared the neural signatures of these disorders in 5,405 UK Biobank patients and 21,727 healthy controls. We found the greatest case­control differences in resting-state functional connectivity and cortical thickness in MDD, followed by anxiety and stress-related disorders. Neural signatures for MDD and anxiety disorders were highly concordant, whereas stress-related disorders showed a distinct pattern. Controlling for cross-disorder genetic risk somewhat decreased the similarity between functional neural signatures of stress-related disorders and both MDD and anxiety disorders. Among cases and healthy controls, reduced within-network and increased between-network frontoparietal and default mode connectivity were associated with poorer cognitive performance (processing speed, attention, associative learning, and fluid intelligence). These results provide evidence for distinct neural circuit function impairments in MDD and anxiety disorders compared to stress disorders, yet cognitive impairment appears unrelated to diagnosis and varies with circuit function.

Morphological similarity of amygdala-ventral prefrontal pathways represents trait anxiety in younger and older adults.

Stronger amygdala-ventral prefrontal white matter connectivity has been associated with lower trait anxiety, possibly reflecting an increased capacity for efficient communication between the two regions. However, there are also reports arguing against this brain-anxiety association. To address these inconsistencies in the literature, we tested the possibility that idiosyncratic tract morphology may account for meaningful individual differences in trait anxiety, even among those with comparable microstructural integrity. Here, we adopted intersubject representational similarity analysis, an analytic framework that captures multivariate patterns of similarity, to analyze the morphological similarity of amygdala-ventral prefrontal pathways. Data drawn from the Leipzig Study for Mind-Body-Emotion Interactions dataset showed that younger adults (20 to 35 y of age) with low trait anxiety, in contrast to trait-anxious individuals, had consistently similar morphological configurations in their left amygdala-ventral prefrontal pathways. Additional tests on an independent sample of older adults (60 to 75 y of age) validated this finding. Our study reveals a generalizable pattern of brain-anxiety association that is embedded within the shared geometries between fiber tract morphology and trait anxiety data.

Disrupted Cacna1c gene expression perturbs spontaneous Ca2+ activity causing abnormal brain development and increased anxiety.

The L-type voltage-gated Ca2+ channel gene CACNA1C is a risk gene for various psychiatric conditions, including schizophrenia and bipolar disorder. However, the cellular mechanism by which CACNA1C contributes to psychiatric disorders has not been elucidated. Here, we report that the embryonic deletion of Cacna1c in neurons destined for the cerebral cortex using an Emx1-Cre strategy disturbs spontaneous Ca2+ activity and causes abnormal brain development and anxiety. By combining computational modeling with electrophysiological membrane potential manipulation, we found that neural network activity was driven by intrinsic spontaneous Ca2+ activity in distinct progenitor cells expressing marginally increased levels of voltage-gated Ca2+ channels. MRI examination of the Cacna1c knockout mouse brains revealed volumetric differences in the neocortex, hippocampus, and periaqueductal gray. These results suggest that Cacna1c acts as a molecular switch and that its disruption during embryogenesis can perturb Ca2+ handling and neural development, which may increase susceptibility to psychiatric disease.

Pavlovian Fear Conditioning Is More than You Think It Is.

A common neuroscience application of Pavlovian fear conditioning is to manipulate neuron-type activity, pair a cue with foot shock, then measure cue-elicited freezing in a novel context. If the manipulation reduces freezing, the neuron type is implicated in Pavlovian fear conditioning. This application reduces Pavlovian fear conditioning to a single concept. In this Viewpoint, I describe experiments supporting the view that Pavlovian fear conditioning refers to three distinct concepts: procedure, process, and behavior. An experimenter controls procedure, observes behavior, but infers process. Distinguishing these concepts is essential because: (1) a shock-paired cue can engage numerous processes and behaviors; (2) experimenter decisions about procedure influence the processes engaged and behaviors elicited; and (3) many processes are latent, imbuing the cue with properties that only manifest outside of the original conditioning setting. This means we could understand the complete neural basis of freezing, yet know little about the neural basis of fear. Neuroscientists can choose to use a variety of procedures to study a diversity of processes and behaviors. Manipulating neuron-type activity in multiple procedures can reveal specific, general, or complex neuron-type contributions to cue-elicited processes and behaviors. The results will be a broader and more detailed neural basis of fear with greater relevance to the spectrum of symptoms defining anxiety and stressor-related disorders.

Irrelevant Threats Linger and Affect Behavior in High Anxiety.

Threat-related information attracts attention and disrupts ongoing behavior, and particularly so for more anxious individuals. Yet, it is unknown how and to what extent threat-related information leave lingering influences on behavior (e.g., by impeding ongoing learning processes). Here, human male and female participants (N = 47) performed probabilistic reinforcement learning tasks where irrelevant distracting faces (neutral, happy, or fearful) were presented together with relevant monetary feedback. Behavioral modeling was combined with fMRI data (N = 27) to explore the neurocomputational bases of learning relevant and irrelevant information. In two separate studies, individuals with high trait anxiety showed increased avoidance of objects previously paired with the combination of neutral monetary feedback and fearful faces (but not neutral or happy faces). Behavioral modeling revealed that high anxiety increased the integration of fearful faces during feedback learning, and fMRI results (regarded as provisional, because of a relatively small sample size) further showed that variance in the prediction error signal, uniquely accounted for by fearful faces, correlated more strongly with activity in the right DLPFC for more anxious individuals. Behavioral and neuronal dissociations indicated that the threat-related distractors did not simply disrupt learning processes. By showing that irrelevant threats exert long-lasting influences on behavior, our results extend previous research that separately showed that anxiety increases learning from aversive feedbacks and distractibility by threat-related information. Our behavioral results, combined with the proposed neurocomputational mechanism, may help explain how increased exposure to irrelevant affective information contributes to the acquisition of maladaptive behaviors in more anxious individuals.SIGNIFICANCE STATEMENT In modern-day society, people are increasingly exposed to various types of irrelevant information (e.g., intruding social media announcements). Yet, the neurocomputational mechanisms influenced by irrelevant information during learning, and their interactions with increasingly distracted personality types are largely unknown. Using a reinforcement learning task, where relevant feedback is presented together with irrelevant distractors (emotional faces), we reveal an interaction between irrelevant threat-related information (fearful faces) and interindividual anxiety levels. fMRI shows provisional evidence for an interaction between anxiety levels and the coupling between activity in the DLPFC and learning signals specifically elicited by fearful faces. Our study reveals how irrelevant threat-related information may become entrenched in the anxious psyche and contribute to long-lasting abnormal behaviors.

Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Central role of the habenulo-interpeduncular system in the neurodevelopmental basis of susceptibility and resilience to anxiety in mice.

Having experienced stress during sensitive periods of brain development strongly influences how individuals cope with later stress. Some are prone to develop anxiety or depression, while others appear resilient. The as-yet-unknown mechanisms underlying these differences may lie in how genes and environmental stress interact to shape the circuits that control emotions. Here, we investigated the role of the habenulo-interpeduncular system (HIPS), a critical node in reward circuits, in early stress-induced anxiety in mice. We found that habenular and IPN components characterized by the expression of Otx2 are synaptically connected and particularly sensitive to chronic stress (CS) during the peripubertal period. Stress-induced peripubertal activation of this HIPS subcircuit elicits both HIPS hypersensitivity to later stress and susceptibility to develop anxiety. We also show that HIPS silencing through conditional Otx2 knockout counteracts these effects of stress. Together, these results demonstrate that a genetic factor, Otx2, and stress interact during the peripubertal period to shape the stress sensitivity of the HIPS, which is shown to be a key modulator of susceptibility or resilience to develop anxiety.

Choline metabolism in regulating inflammatory bowel disease-linked anxiety disorders: A multi-omics exploration of the gut-brain axis.

Anxiety and depression caused by inflammatory bowel disease (IBD) negatively affect the mental health of patients. Emerging studies have demonstrated that the gut-brain axis (GBA) mediates IBD-induced mood disorders, but the underlying mechanisms of these findings remain unknown. Therefore, it's vital to conduct comprehensive research on the GBA in IBD. Multi-omics studies can provide an understanding of the pathological mechanisms of the GBA in the development of IBD, helping to uncover the mechanisms underlying the onset and progression of the disease. Thus, we analyzed the prefrontal cortex (PFC) of Dextran Sulfate Sodium Salt (DSS)-induced IBD mice using transcriptomics and metabolomics. We observed increased mRNA related to acetylcholine synthesis and secretion, along with decreased phosphatidylcholine (PC) levels in the PFC of DSS group compared to the control group. Fecal metagenomics also revealed abnormalities in the microbiome and lipid metabolism in the DSS group. Since both acetylcholine and PC are choline metabolites, we posited that the DSS group may experience choline deficiency and choline metabolism disorders. Subsequently, when we supplemented CDP-choline, IBD mice exhibited improvements, including decreased anxiety-like behaviors, reduced PC degradation, and increased acetylcholine synthesis in the PFC. In addition, administration of CDP-choline can restore imbalances in the gut microbiome and disruptions in lipid metabolism caused by DSS treatment. This study provides compelling evidence to suggest that choline metabolism plays a crucial role in the development and treatment of mood disorders in IBD. Choline and its metabolites appear to have a significant role in maintaining the stability of the GBA.