MicroRNAs (miRNAs) alterations in patients with bipolar disorder (BD) are pivotal to the disease’s pathogenesis. Since obtaining brain tissue is challenging, most research has shifted to analyzing miRNAs in peripheral blood. One innovative solution is sequencing miRNAs in plasma extracellular vesicles (EVs), particularly those neural-derived EVs emanating from the brain.

We isolated plasma neural-derived EVs from 85 patients with BD and 39 healthy controls (HC) using biotinylated antibodies targeting a neural tissue marker, followed by miRNA sequencing and expression analysis. Furthermore, we conducted bioinformatic analyses and functional experiments to delve deeper into the underlying pathological mechanisms of BD.

Out of the 2,656 neural-derived miRNAs in EVs identified, 14 were differentially expressed between BD patients and HC. Moreover, the target genes of miR-143-3p displayed distinct expression patterns in the prefrontal cortex of BD patients versus HC, as sourced from the PsychENCODE database. The functional experiments demonstrated that the abnormal expression of miR-143-3p promoted the proliferation and activation of microglia and upregulated the expression of proinflammatory factors, including IL-1β, IL-6, and NLRP3. Through weighted gene co-expression network analysis, a module linking to the clinical symptoms of BD patients was discerned. Enrichment analyses unveiled these miRNAs’ role in modulating the axon guidance, the Ras signaling pathway, and ErbB signaling pathway.

Our findings provide the first evidence of dysregulated plasma miRNAs within neural-derived EVs in BD patients and suggest that neural-derived EVs might be involved in the pathophysiology of BD through related biological pathways, such as neurogenesis and neuroinflammation.

Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic resonance imaging (MRI) to identify similarities and differences in abnormal aging between bipolar disorder (BD) and major depressive disorder (MDD) and pinpoint key brain regions of structural and functional change specific to each disorder.

Neuroimaging data from 340 healthy controls, 110 BD participants, and 68 MDD participants were included from the Taiwan Aging and Mental Illness cohort. We constructed 228 models using T1-weighted MRI, resting-state functional MRI, and diffusion tensor imaging data. Gaussian process regression was used to train models for estimating brain aging trajectories using structural and functional maps across various brain regions.

Our models demonstrated robust performance, revealing accelerated aging in 66 gray matter regions in BD and 67 in MDD, with 13 regions common to both disorders. The BD group showed accelerated aging in 17 regions on functional maps, whereas no such regions were found in MDD. Fractional anisotropy analysis identified 43 aging white matter tracts in BD and 39 in MDD, with 16 tracts common to both disorders. Importantly, there were also unique brain regions with accelerated aging specific to each disorder.

These findings highlight the potential of brain aging trajectories as biomarkers for BD and MDD, offering insights into distinct and overlapping neuroanatomical changes. Incorporating region-specific changes in brain structure and function over time could enhance the understanding and treatment of mental illness.

Diagnostic tools, such as the Mini International Neuropsychiatric Interview (MINI) 7.0.2 and the Structured Clinical Interview for the DSM-5 (SCID), aim to increase the validity and reliability of diagnostic assessment. However, these tools were created in high-income countries (HICs) with limited investigation of the psychometrics of these tools when used in low- and middle-income countries (LMICs). Thus, there is a need to examine the psychometric properties of these measures in LMICs. The present investigation aimed to examine the use of the MINI in Ethiopia, Kenya, and Uganda.

A multicountry comparison of the validity and reliability of the MINI was conducted in a study of 954 participants (n = 667 cases; n = 287 controls) with and without a psychotic spectrum disorder, defined as any psychotic or bipolar spectrum disorder for the NeuroGAP – Psychosis study. Test–retest reliability of the MINI was examined in a subset of 303 participants (n = 164 cases; n = 139 controls) from the overall sample.

Results revealed the MINI and SCID provided excellent diagnostic accuracy with area under the curve (AUC) values of .91 (SE = .01) for the MINI and .95 (SE = .01) for the SCID. Positive predictive values (PPV) were the highest for the SCID (93.8%) and slightly lower for the MINI (88.7%). Reliability analyses revealed substantial agreement for psychotic and bipolar diagnostic groups.

Similar patterns of results were observed at the country level with a few notable differences. Limitations and future directions are discussed.

Schizophrenia patients with auditory hallucinations have distinct morphological abnormalities, but whether this population have a progressive gray matter atrophy pattern and specific transmission chain of causal effects remains unclear. This study was designed to construct a causal structural covariance network in schizophrenia patients with persistent auditory hallucinations.

T1-weighted MRI images were acquired from 90 schizophrenia patients with persistent auditory hallucinations (pAH group) and 83 healthy controls (HC group). Stage-specific independent t tests of gray matter volume (GMV) comparisons between the two groups were used to depict the GMV atrophic pattern and locate the atrophic origin. In the pAH group, the causal structural covariance network (CaSCN) was constructed to map causal effects between the atrophic origin and other regions as the auditory hallucination severity increased.

With the ascending of hallucinatory severity, GMV reductions began from the thalamus, bilateral medial frontal gyri, left Rolandic operculum, and left calcarine, and expanded to other frontal and temporal regions, hippocampal complex, insula, anterior cingulate gyri, fusiform, and cerebellum. Using the peak region (thalamus) as the causal origin in the network, transitional nodes including the right opercular part of the inferior frontal gyrus, bilateral postcentral gyri, left thalamus, and right middle frontal gyrus received the casual information and projected to target nodes from the frontal, temporal, parietal, and occipital cortices, limbic system, and cerebellum.

Our study revealed causal effects from the thalamus and a specific transmission pattern of causal information within the network, indicating a thalamic–cortical–cerebellar circuitry dysfunction related to auditory hallucinations.

The optimal duration for maintaining antidepressant treatment in individuals with obsessive-compulsive disorder (OCD) who achieve symptom stabilization remains unclear.

This systematic review and pairwise meta-analysis of double-blind randomized placebo-controlled trials (DBRPCTs) compared antidepressant maintenance and antidepressant discontinuation groups in terms of relapse rate at each DBRPCT study endpoint (primary outcome), OCD symptom improvement, all-cause discontinuation, and adverse event-related discontinuation. Furthermore, relapse rates at 4, 8, 12, 16, 20, and 24 weeks were compared between the groups. Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated. The absolute risk reduction (ARR) and number needed to treat to benefit (NNTB) for relapse rates were also estimated.

Nine trials (n = 1084; mean age: 32.8 years; proportion of males: 53.3%) were included. The antidepressant maintenance group had lower relapse rates at each DBRPCT study endpoint (RR [95% CI] = 0.53 [0.42–0.68]; ARR = 21.0%; NNTB = 5) and lower all-cause and adverse event-related discontinuation rates than the antidepressant discontinuation group. The maintenance group also exhibited lower relapse rates at 4 weeks (RR [95% CI] = 0.47 [0.31–0.70]; ARR: not significant; NNTB: not significant), 8 weeks (0.42 [0.31–0.57]; 12.0%; 8), 12 weeks (0.43 [0.32–0.56]; 18.0%; 6), 16 weeks (0.41 [0.32–0.52]; 25.0%; 4), 20 weeks (0.43 [0.34–0.53]; 26.0%; 4), and 24 weeks (0.42 [0.33–0.52]; 27.0%; 4) than the discontinuation group. Moreover, the maintenance group outperformed the discontinuation group regarding OCD symptom improvement.

Individuals with OCD may benefit from continued antidepressant treatment, provided that it is well tolerated.

Posttraumatic stress disorder (PTSD) exhibits marked heterogeneity, with relational (R; interpersonal) and nonrelational (NR; environmental) trauma subtypes demonstrating distinct psychopathological trajectories. Despite clinical recognition of these differences, their neurobiological underpinnings of emotion processing remain poorly understood. Guided by the Nested Hierarchical Model of Self (NHMS) – which posits trauma-type-specific disruptions in hierarchical self-processing systems – this study investigated neural mechanisms differentiating among PTSD subtypes during implicit emotion regulation.

A sample of 122 participants, including patients with PTSD (R: n = 51; NR: n = 29) and trauma-exposed controls matched by trauma type (R: n = 22; NR: n = 20), underwent functional magnetic resonance imaging while performing the Shifted Attention Emotion Appraisal Task. Behavioral assessments and trauma typology coding were complemented by regions of interest (ROI)-based and whole-brain analyses.

Results revealed that PTSD-R showed hypoactivation in right superior frontal gyrus (during implicit emotion regulation; BA9; p = 0.049, ηp2 = 0.033), whereas PTSD-NR exhibited hyperactivation in fusiform (during emotion modulation by attention shifting; p = 0.036, ηp2 = 0.037). Symptom severity inversely correlated with social support (r = −0.353 to −0.417, p < 0.01), with relational PTSD reporting the lowest support (p < 0.001). Across conditions, dorsolateral prefrontal clusters (BA8/9) demonstrated anticorrelations with default-mode regions (r = −0.272 to −0.549, p < 0.01) aligning with NHMS’ predictive coding framework.

These findings validate trauma-type-specific neural hierarchies, suggesting relational trauma disrupts top-down self-identity schemas, while NR trauma amplifies bottom-up threat detection. The study advances precision psychiatry by linking implicit regulation biomarkers to targeted interventions – cognitive restructuring for PTSD-R and interoceptive recalibration for PTSD-NR.

Adolescence is a period marked by high vulnerability to onset of depression. Neuroimaging studies have revealed considerableatrophy of brain structure in patients with major depressive disorder (MDD). However, the causal structural networks underpinning gray matter atrophies in depressed adolescents remain unclear. This study aimed to examine the initial gray matter alterations in MDD adolescents and investigate their causal relationships of abnormalities within brain structural networks.

First-episode adolescent patients with MDD (n = 80, age = 15.57 ± 1.78) and age- and sex-matched healthy controls (n = 82, age = 16.11 ± 2.76) were included. We analyzed T1-weighted structural images using voxel-based morphometry to identify gray matter alterations in patients and the disease stage-specific abnormalities. Granger causality analysis was then conducted to construct causal structural covariance networks. We also identified potential pathways between the causal source and target.

Compared to controls, MDD patients with shorter illness duration showed gray matter atrophy in localized brain regions such as ventral medial prefrontal cortex (vmPFC), anterior cingulate cortex, and insula. With a prolonged course of MDD, gray matter atrophy extended to widespread brain areas. Causal network results demonstrated that early abnormalities had positive effects on the default mode, frontoparietal networks, and reward circuits. Moreover, vmPFC demonstrated the highest out-degree value, possibly representing the initial source of brain abnormality in adolescent depression.

These findings revealed the progression of gray matter atrophy in adolescent depression and demonstrated the directional influences between initial localized alterations and subsequent deterioration in widespread brain networks.

In patients with remitted psychosis, the dosage of antipsychotics can be lowered without increased risk of relapse. Whether dose tapering can lead to improved cognition is unclear. We compared changes in cognitive performance between patients undergoing dose tapering and those receiving a fixed maintenance dose.

A 2-year prospective trial of patients with stable schizophrenia-related psychotic disorders was conducted: one group received guided dose reduction (GDR) and one group received maintenance treatment. Cognitive function was assessed using the Wechsler Adult Intelligence Scale-Third Edition, Mandarin Chinese version, at baseline, 1, and 2 years. The relations between the ratio of reduced dose and the extent of cognitive improvement were examined by Spearman’s correlation coefficient. We also examined cognitive performance between aripiprazole (ARI) users and non-ARI users.

GDR patients exhibited significantly greater improvements in total intellectual quotient (IQ), particularly working memory, and information and arithmetic subtest scores, with no significant difference in relapse rates between groups. Statistically significant dose–response correlations were found between the degree of dose reduction and improvements in total IQ (n = 72, r = 0.242, p = 0.041), Working Memory Index (n = 72, r = 0.284, p = 0.016), and Arithmetic subtest (n = 72, r = 0.295, p = 0.012). There were no differences in cognitive changes between ARI users and non-users.

Lowering antipsychotic dosage may ameliorate patient performance in several cognitive domains. This finding is worthy of consideration while evaluating the risk-to-benefit ratio of tapering antipsychotics in patients with remitted psychosis.

Methadone maintenance treatment (MMT) and protracted abstinence (PA) effectively reduce the craving for heroin among individuals with heroin use disorder (HUD). However, the difference in their effects on brain function, especially the coupling among the large-scale brain networks (default mode [DMN], salience [SN], and executive control [ECN] networks), remains unclear. This study analyzed the effects of the MMT and PA on these networks and the predictive value of the bilateral resource allocation index (RAI) for craving for heroin.

Twenty-five individuals undergoing the MMT, 22 undergoing the PA, and 51 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI). Independent component analysis identified the ECN, DMN, and SN. The SN-ECN and SN-DMN connectivity and the bilateral RAI were evaluated. The relationships between network coupling and clinical and psychological characteristics were analyzed. The multiple linear regression model identified significant variables for predicting craving scores.

The MMT group showed significantly stronger SN-left ECN (lECN) coupling and left RAI than the PA group. In the MMT group, SN-lECN connectivity and bilateral RAI were positively correlated with the total methadone dose. In both treatment groups, SN-right ECN (rECN) connectivity and right RAI were negatively correlated with craving. The models revealed that the bilateral RAI and the MMT and PA were associated with the craving.

The MMT enhances SN-lECN coupling and the left RAI more than the PA, possibly due to higher control modulation. The RAI could help predict heroin craving in individuals with HUD undergoing either treatment program.

Although heightened anxiety associated with social interaction or evaluation is the core diagnostic criterion for social anxiety disorder (SAD), there is growing evidence that SAD is characterized by more pervasive reactivity beyond social situations. We employed Ecological Momentary Assessment (EMA) to describe the affective dynamics and emotional reactivity to daily events in a community-based sample of adults with SAD compared with other anxiety disorders, and controls without anxiety or mood disorders.

A sample of 236 adults with a lifetime diagnosis of SAD (n = 53), other anxiety disorders (n = 120), and no mood or anxiety disorder (n = 63) based on comprehensive diagnostic interviews answered brief electronic interviews that assessed daily life events and mood and anxiety symptoms four times a day for two weeks. Linear mixed models were used to quantify reactivity to daily life events.

Persons with SAD had higher average levels of sad and anxious mood than those with other anxiety disorders or controls. Irrespective of comorbid mood disorders, people with SAD also demonstrated significantly greater decreases in both sad and anxious mood following positive events, and a greater increase in anxious mood following negative, particularly non-social events.

Our findings regarding pervasive reactivity beyond the social context in people with SAD confirm the need for broader conceptualization of this disorder as well as expansion of interventions beyond the social context. This work also demonstrates the utility of EMA as a powerful tool to track individual variability and reactivity in daily life that can inform etiology, treatment and prevention.

Cannabis use in young adulthood is common, yet few studies have explored how it predicts changes in psychopathology and functional well-being in community samples. We assessed these links using both self-reported frequency of cannabis use and hair THC concentrations.

Data came from a community sample of young adults (N = 863) who reported cannabis use (weekly-to-daily use: n = 150) and provided hair samples at age 20 (cannabis detected: n = 110). Liquid chromatography–tandem mass spectrometry quantified delta-9-tetrahydrocannabinol (THC) and cannabinol (CBN) concentrations in hair. At ages 20 and 24, participants reported psychopathology (psychotic-like experiences, problematic substance use, internalizing symptoms, and aggression) and functional wellbeing (general well-being, delinquency, and not being in employment, education, or training). Multiple linear and logit regression models tested associations between six different continuous and dichotomous operationalizations of self-reported and objective cannabis exposure at age 20 and psychological and functional well-being at age 24, adjusting for sex, sociodemographic characteristics, and the outcomes measured at age 20.

Both self-reported frequency of cannabis use and hair THC concentrations predicted increases in psychotic-like experiences and internalizing symptoms, increased aggression, decreased general well-being, higher odds of not being in employment, training, or education, and more problematic substance use from age 20 to 24, with small effect sizes. Composite exposure scores derived from self-reports and hair data were not more informative than either source alone.

Frequent cannabis use predicted adverse changes in psychopathological outcomes from ages 20 to 24, regardless of how it was assessed.

Child video game playing (“gaming”) may lead to decreased child academic motivation. Conversely, children with low academic motivation may seek fulfillment through gaming. We examined bidirectional associations between child gaming and academic motivation across middle childhood.

Our analyses are based on 1,631 children (boys = 785) followed in the context of the Quebec Longitudinal Study of Child Development. Data on gaming and academic motivation were collected repeatedly at ages 7, 8, and 10. Measures of child gaming were parent-reported and reflect daily video game playing time. Measures of academic motivation were child self-reported and reflect enjoyment in learning mathematics, reading, and writing. To disentangle the directionality of associations, we estimated a random-intercept cross-lagged panel model to estimate bidirectional, within-person associations between gaming and academic motivation in a cohort of school-aged Canadian children.

Our results revealed unidirectional associations whereby more frequent gaming by boys at age 7 years predicted lower academic motivation at age 8 years (β = −.11, 95% confidence interval [CI]: −.22 to −.01), and similarly, gaming by boys at age 8 years predicted lower academic motivation at age 10 years (β = −.10, 95% CI: −.19 to −.01). Changes in boys’ academic motivation did not contribute to subsequent changes in gaming. There were no associations between gaming and academic motivation for girls.

More time devoted to gaming among school-aged boys is associated with reduced academic motivation during a critical developmental period for the development of academic skills. Fostering healthy gaming habits may help promote academic motivation and success.

Antipsychotic (AP) medication in individuals at clinical high risk for psychosis (CHR-P) is not routinely recommended by clinical guidelines but is commonly prescribed. Since little is known about the predictors of AP inception in CHR-P, we analyzed data from two observational cohorts.

To avoid baseline predictors being confounded by previous treatment, participants were selected for analysis from the 764 participants at CHR-P enrolled in NAPLS-2 and the 710 enrolled in NAPLS-3 by excluding those with lifetime histories of AP use. Baseline clinical variables available in both studies were employed as predictors of subsequent AP inception over the next 6 months in univariable and multivariable analyses.

Preliminary analyses indicated no important effects of sample. The final combined population included 79 AP inception participants and 580 participants who did not have AP inception. The AP medications most commonly prescribed were risperidone, aripiprazole, and quetiapine. Univariable analyses identified seven significant predictors of AP inception. The final logistic regression model including these variables was highly significant (χ2 = 36.53, df = 7, p = <0.001). Three variables (current major depression, fewer education years, and current benzodiazepine use) emerged as significant independent predictors of AP inception.

This study is the first to determine baseline characteristics that predict subsequent AP initiation in CHR-P. Some AP use in CHR-P appears to be intended as augmentation of antidepressant treatment for comorbid major depression. Some prescribers may not have detected the attenuated positive symptoms characteristic of CHR-P since their severity did not significantly predict AP inception.

Genetic research on nicotine dependence has utilized multiple assessments that are in weak agreement.

We conducted a genome-wide association study (GWAS) of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry [EUR], 10,231 of African ancestry, and 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes.

We replicated the well-known association at the CHRNA5 locus (lead single-nucleotide polymorphism [SNP]: rs147144681, p = 1.27E−11 in EUR; lead SNP = rs2036527, p = 6.49e−13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder criterion count and all 11 individual diagnostic criteria in the independent National Epidemiologic Survey on Alcohol and Related Conditions-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than a “problematic tobacco use” factor (a combination of cigarettes per day and nicotine dependence defined by the Fagerström Test for Nicotine Dependence). Finally, DSM-NicDep showed a strong genetic correlation with a GWAS of tobacco use disorder as defined in electronic health records (EHRs).

Our results suggest that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.

Schizophrenia (SCZ) and genetic high-risk (GHR) individuals exhibit deficits in brain functional networks and cognitive function, potentially impacted by SCZ risk genes. This study aims to delineate these impairments in SCZ and GHR individuals, and further explore how risk genes affect brain networks and executive function.

A total sample size of 292 participants (100 SCZ, 68 GHR, and 124 healthy controls [HCs]) in the study. The Wisconsin Card Sorting Test (WCST) and resting-state functional magnetic resonance imaging (rs-fMRI) are utilized to evaluate executive function and brain network topology. SCZ-related polygenic risk scores (SCZ-PRS) were used to evaluate genetic risk levels. WCST and PRS were not applied to all participants.

Significant reductions in nodal efficiency and degree centrality (Dnodal) were observed within the right median cingulate and paracingulate gyri (MCPG_R) in both SCZ and GHR groups, compared to HCs. There were significant correlations between SCZ-PRS, Dnodal in MCPG_R, and WCST scores. Moreover, Dnodal in MCPG_R completely mediated the relationship between SCZ-PRS and executive function. The enrichment analysis of these risk genes indicates their involvement in biological processes of signal transduction and synaptic transmission.

This study highlights the pivotal role of impaired cingulate function in mediating the effects of genetic risks on executive deficits, offering new insights into the genetic-neuro-cognitive nexus in schizophrenia and potential targets for clinical interventions.