Psychological Medicine最新文献

Background: Rates of loneliness have increased over the past several decades worldwide, particularly among people with serious mental illnesses. A better understanding of the neurocognitive mechanisms underlying loneliness could provide useful information for the efforts to address this public health problem.

Methods: To investigate these mechanisms, a functional magnetic resonance imaging (fMRI) study was conducted which accounted for known cognitive biases associated with loneliness. Participants with (n = 40) and without (n = 60) psychotic disorders (PD) viewed images of faces that appeared to approach or withdraw from the participants while fMRI data were collected. Following the scanning, participants rated the trustworthiness of the faces, and these ratings were included as weights in the fMRI analyses. Neural responses to approaching versus withdrawing faces were measured, and whole-brain regression analyses, with loneliness as the regressor, were performed.

Results: In the PD and full samples, a higher level of loneliness was significantly associated with greater responses of the hippocampus and areas of the basal ganglia to withdrawing (versus approaching) face stimuli. Moreover, the effects in the hippocampus, but not the basal ganglia, remained significant after controlling for potential confounds such as social activity levels, depression and social anhedonia. Finally, in a subset of the full sample (n = 66), greater hippocampal responses to withdrawing faces predicted greater loneliness 1 year later.

Conclusions: Heightened responses of the hippocampus to withdrawing faces may represent a candidate neurobiological marker of loneliness that could be modified by interventions targeting loneliness.

Autobiographical memory (AM) dysfunction has been proposed as a neurocognitive mechanism underlying the development and maintenance of depression. However, case-control neuroimaging studies investigating the neural correlates of AM in depression have yielded inconsistent findings. The present study utilized neuroimaging meta-analyses to identify robust neural markers of AM dysfunction in depression and characterize the associated behavioral and network-level mechanisms. A preregistered neuroimaging meta-analysis (https://osf.io/35xtf) was conducted, incorporating data from 341 patients with unipolar depression, 82 individuals at risk of depression, and 261 healthy controls across case-control functional magnetic resonance imaging studies examining AM processing. Meta-analytic network-level and behavioral decoding analyses were performed to aid interpretation of the findings. Compared with controls, the depression group displayed increased activation in the right paracingulate cortex (dorsal anterior cingulate [dACC]) and precuneus, and decreased activation in the anterior insula during AM recall. Exploratory valence-specific analyses revealed that negative AM recall was associated with increased activity the dACC and precuneus. Meta-analytic decoding linked the dACC to the salience network and to domains related to negative affect and executive control, while the precuneus was associated with the default mode network and with processes related to social cognition and AM. Findings do not support prevailing models emphasizing altered amygdala and hippocampal function in AM deficits in depression. Instead, they highlight the involvement of core regions within the salience and default mode networks as key neural substrates of AM dysfunction. These regions may contribute to affective, social-cognitive, and mnemonic disturbances that shape the valence-specific nature of AM deficits in depression.

Background: While mobile gaming addiction (MGA) behavior is increasingly prevalent among children and adolescents, the role of specific emotional-behavioral profiles - particularly their latent patterns - in associating with MGA behavior remains poorly understood. This study aimed to examine these associations and age-related variations.

Methods: Data were analyzed from 507,188 participants aged 6-18 years in the Children's Growth Environment, Lifestyle, and Physical and Mental Health Development Project, conducted in Guangzhou, China, in 2020. Latent class analysis was performed on parent-reported Strengths and Difficulties Questionnaire (SDQ) data to identify subgroups with distinct emotional and behavioral problems. Associations between SDQ dimensions, latent classes, and MGA behavior were examined using logistic regression analysis.

Results: Five latent classes were identified: 'Low symptom' (82.2%), 'Internalizing' (0.8%), 'Peer and prosocial issues' (4.3%), 'High difficulties' (5.0%), and 'Hyperactive' (7.6%). Compared to the 'Low symptom' class, all other latent classes showed significantly higher risks for MGA, with the strongest association observed in the 'Internalizing' class (adjusted odds ratio [AOR]: 2.84; 95% confidence interval [95% CI]: 2.67-3.02). Among SDQ subscales, conduct problems presented the highest association (AOR: 2.08; 95% CI: 2.04-2.12), though all SDQ subdimensions were significantly positively correlated with MGA behavior (all p < 0.05). Notably, these associations were consistently stronger in adolescents (aged 13-18 years) than in children (aged 6-12 years).

Conclusions: This study identifies specific SDQ-based risk characteristics for MGA behavior, with adolescents (aged 13-18 years) being the most vulnerable. Future longitudinal studies should verify these associations, and clinicians may prioritize early screening for internalizing and conduct-related difficulties.

Background: Substantial evidence supports the efficacy of cognitive bias modification (CBM) for attention and interpretation. However, CBM targeting memory bias (CBM-M) remains underexplored despite its clinical relevance. This study examines the effectiveness and neurobiological mechanisms of CBM-M.

Methods: Fifty-eight individuals with elevated anxious and depressive personality traits (>1 SD) were randomly assigned to either CBM-M or sham training (n = 29 per group) in a parallel, double-blind, randomized controlled trial. The intervention involved eight sessions over 1 month. CBM-M aimed to enhance positive autobiographical memory (AM) recall by focusing on positive and negative words, whereas sham training lacked this enhancement module. Anxiety and depressive traits and symptoms, explicit and implicit memory biases, and AM specificity were assessed. Additionally, intrinsic functional connectivity was measured via functional magnetic resonance imaging, and cortisol levels were assayed via saliva collected at 10 time points across 2 days before and after the intervention.

Results: Both groups showed reduced anxiety and depressive traits from pre- to post-intervention. Compared with sham training, CBM-M specifically reduced stress vulnerability, negative explicit memory bias, and daytime cortisol levels, with a large effect size. Improvement in memory bias correlated with stress vulnerability and cortisol reductions. CBM-M also enhanced amygdala functional connectivity with the anteromedial orbitofrontal cortex in comparison with sham training from pre- to post-intervention.

Conclusions: CBM-M reduced stress vulnerability and elicited neural changes in amygdala-anteromedial orbitofrontal cortex interactions, which were involved in social reward and AM recall. Future research should identify the most responsive populations and elucidate underlying mechanisms.

Background: Although the short-term preventive effects of mHealth consultation intervention on postpartum depressive symptoms have been demonstrated, the long-term effects and role of alleviating loneliness on depressive symptoms remain unclear.

Methods: This follow-up study extended our previous trial, which ended at three months postpartum, by continuing observation to 12 months. Participants in the original trial were randomized to the mHealth group (n = 365) or the usual care group (n = 369). Women in the mHealth group had access to free, unlimited mHealth consultation services with healthcare professionals from enrollment through four months postpartum. The primary outcome of this study was the risk of elevated postpartum depressive symptoms at 12 months post-delivery (Edinburgh Postnatal Depression Scale score of ≥9). The mediation effect of alleviating loneliness on the primary outcome was also evaluated, using the UCLA loneliness scale at three months postpartum.

Results: A total of 515 women completed the follow-up questionnaires (mHealth group, 253/365; usual care group, 262/369; 70.2% of the original participants). Compared to the usual care group, the mHealth group had a lower risk of elevated postpartum depressive symptoms at 12 months post-delivery (36/253 [14.2%] vs. 55/262 [21.0%], risk ratio: 0.68 [95% confidence interval: 0.46-0.99]). Mediation analysis showed that reducing loneliness at three months post-delivery mediated approximately 20% of the total effect of the intervention on depressive symptoms 12 months post-delivery.

Conclusions: mHealth consultation services provided during the early perinatal period may help alleviate depressive symptoms at 12 months postpartum.

Background: Low self-esteem is an important and potentially modifiable risk factor for the development and outcome of psychotic disorders. The factors involved in low self-esteem in psychotic disorders are not yet fully understood. The current study aims to investigate the cross-sectional and longitudinal associations between (changes in) self-esteem and severity of psychotic symptoms, internalized stigma, negative reaction to antipsychotics, personal recovery, childhood bullying, childhood trauma, and social support in symptomatically remitted first-episode psychosis (FEP) patients.

Methods: Data from the ongoing longitudinal Handling Antipsychotic Medication: Long-term Evaluation of Targeted Treatment study were used. Participants were in symptomatic remission for 3-6 months after the FEP. Cross-sectional associations (N = 299) were investigated through Pearson's correlations, and longitudinal changes (N = 238) were investigated via linear regressions with inverse probability weighting.

Results: Cross-sectionally, we found that lower self-esteem was related to higher severity of symptoms, higher internalized stigma, higher childhood trauma (specifically emotional neglect), higher childhood bullying, more negative side effects of antipsychotic medication, lower personal recovery, and lower social support. Longitudinally, contrary to our hypothesis, we found that higher baseline internalized stigma, higher childhood trauma (specifically emotional abuse), and a higher baseline negative subjective reaction to antipsychotics predicted an increase in self-esteem after 6 months. Furthermore, a decrease in psychotic symptoms, internalized stigma, and negative subjective reaction to antipsychotics, and an increase in social support predicted an increase in self-esteem.

Conclusions: Early intervention programs for psychotic disorders should target factors related to changes in self-esteem. This might improve self-esteem and thereby promote recovery.

Background: Early life adversity (ELA) is common and cross-sectionally associated with brain gray matter structure, including cortical thickness, cortical surface area, and subcortical volumes in childhood. However, to which degree ELA influences the trajectory of gray matter macrostructural and microstructural development during childhood and adolescence remains largely unexplored.

Methods: We included 6414 participants from the Adolescent Brain Cognitive Development study at ages 9-11, where 1923 were followed to ages 11-13. We used linear mixed-effects models to test for associations between MRI-derived longitudinal measures of gray matter macro- (cortical thickness, surface area, subcortical volume) or microstructure (T1w/T2w ratio) and trauma exposure, parental acceptance, household abuse, and being resilient or susceptible to trauma in terms of developing an internalizing disorder.

Results: At ages 9-11, higher levels of parental acceptance, trauma exposure, and being trauma resilient were associated with lower levels of cortical thickness. In contrast, being trauma susceptible was negatively related to hippocampal volume and cortical surface area. Longitudinally, more parental acceptance at baseline was associated with more cortical thinning between ages 9-11 and 11-13, while more household abuse was associated with less change in T1w/T2w ratio over time.

Conclusions: Parental acceptance and trauma resilience are linked to accelerated pace of apparent cortical thinning in youth aged 9-13 years, while household abuse is associated with slower microstructural development, as reflected by smaller longitudinal changes in the T1w/T2w ratio. Threat and deprivation may be distinctly associated with gray matter developmental trajectories in late childhood.

Background: Structural brain alterations in bipolar disorder (BD) have been widely reported, yet the hierarchical organization of cortical morphometric networks and their molecular and cognitive underpinnings remain unclear.

Methods: We applied the morphometric inverse divergence (MIND) network approach to structural MRI data from 49 BD patients and 119 healthy controls. Principal MIND gradients were derived using diffusion map embedding, followed by multiscale analyses linking gradient alterations to neurotransmitter systems, cognitive-behavioral domains, and transcriptomic profiles from the Allen Human Brain Atlas. Validation was performed in three independent, cross-scanner, cross-race, and cross-age validation datasets.

Results: Bipolar disorder patients showed significant principal gradient alterations in the left rostral middle frontal and lateral occipital cortices, with network-level decreases in the ventral attention and motor networks and increases in frontoparietal and visual networks. Gradient alterations spatially correlated with acetylcholine (VAChT) and GABA (GABA_A/BZ) systems, and were associated with cognitive processes involving executive control and visual attention. Transcriptomic analyses identified gene sets enriched for BD-related GWAS loci, expressed predominantly in excitatory and inhibitory neurons, astrocytes, and oligodendrocytes, with preferential enrichment in cortical layers III-IV and developmental windows spanning early fetal to young adulthood.

Conclusions: These findings reveal disrupted hierarchical cortical organization in BD and link macroscale morphometric alterations to specific neurotransmitter systems and transcriptional architectures. The MIND gradient emerges as a potential biomarker bridging structural disruptions with molecular and cognitive mechanisms in BD.

Background: Decades of research have identified a strong association between heavy cannabis use and schizophrenia (SCZ), with evidence of correlated genetic factors. However, many studies on the genetic relationship between cannabis use and psychosis have lacked data on both phenotypes within the same individuals, creating challenges due to unmeasured confounding. We aimed to address this by using multimodal data from the All of Us Research Program, which contains genetic data as well as information on SCZ diagnosis and cannabis use.

Methods: We tested the association between cannabis use disorder (CUD) and SCZ polygenic scores (PGSs) with SCZ and heavy cannabis use. We tested models where both CUD and SCZ PGSs were included as joint predictors of heavy cannabis use and SCZ case status. We defined three sets of cases based on comorbidities: relaxed (assessing for only the primary condition), strict (excluding comorbidity), and dual-comorbidity.

Results: CUD and SCZ polygenic liability were independently associated with heavy cannabis use; the SCZ PGS effect was very modest. In contrast, both SCZ and CUD PGSs were independently associated with SCZ, with independent significant effects of CUD PGS. Polygenic liability to CUD was associated with SCZ in individuals without a documented history of cannabis use, suggesting widespread pleiotropy.

Conclusions: These findings underscore the need for comprehensive models that integrate genetic risk factors for heavy cannabis use to advance our understanding of SCZ etiology.

Background: Antidepressants are the primary treatment for major depressive disorder (MDD), yet their precise neurobiological mechanisms remain incompletely understood. This study aimed to elucidate neural differences between medicated and unmedicated MDD patients by analyzing resting-state functional magnetic resonance imaging data.

Methods: We conducted a coordinate-based meta-analysis, complemented by behavioral, genetic, and neurotransmitter-level evaluations to identify potential therapeutic targets and diagnostic biomarkers. Using seed-based d-mapping with permutation of subject images (SDM-PSI), we assessed brain activation changes associated with antidepressant treatment. The identified regions were further characterized using large-scale molecular and functional brain databases.

Results: A total of 59 studies on unmedicated MDD (2,618 patients, 2,486 controls) and 15 studies on medicated MDD (541 patients, 483 controls) were included. The meta-analysis revealed significantly increased activation in the left striatum among medicated patients, a region linked to cognitive functions such as memory and perception. Gene expression analysis highlighted SLC5A7 and prolactin (PRL) as key genes in this region, while neurotransmitter mapping showed associations with serotonin (5-HT1a, 5-HT2a) and dopamine (D1, D2) receptors. Additionally, reduced activation in the left middle occipital gyrus (MOG) was observed across both medicated and unmedicated groups. This region, implicated in recognition and face processing, showed high expression of TFAP2B and PRL and was associated with serotonin and norepinephrine transporter distributions.

Conclusions: These findings suggest that the left striatum may represent a core neurofunctional target of antidepressant treatment, while the left MOG may serve as a stable neurobiological marker for MDD diagnosis, independent of pharmacological status.