Previous research has shown abnormal functional network gradients in Alzheimer’s disease (AD). Structural network gradient is capable of capturing continuous changes in brain morphology and has the ability to elucidate the underlying processes of neurodevelopment. However, it remains unclear whether structural network gradients are altered in AD and what associations exist between these changes and cognitive function, and gene expression profiles.

By constructing an individualized structural network gradient decomposition framework, we calculated the morphological similarity network (MSN) gradients for 404 subjects (186 AD patients and 218 normal controls). We investigated AD-related alterations in MSN gradients, along with the associations between MSN gradients and cognitive function, MSN topological properties, and gene expression profiles.

Our findings indicated that the principal MSN gradient alterations in AD were primarily characterized by an increase in the primary and secondary sensory cortices and a decrease in the association cortex 1. The primary and higher-order cortices exhibited opposite associations with cognition, including executive function, language skills, and memory processes. Moreover, the principal MSN gradients were found to significantly predict cognitive function in AD. The altered gradient pattern was 14.8% attributable to gene expression profiles, and the genes demonstrating the highest correlation are involved in metabolic activity and synaptic signaling.

Our results offered novel insights into the underlying mechanisms of structural brain network impairment in AD patients, enhancing our understanding of the neurobiological processes responsible for impaired cognition in patients with AD, and offering a new dimensional structural biomarker for AD.

Symptoms of complex post-traumatic stress disorder (cPTSD) may play a role in the maintenance of psychotic symptoms. Network analyses have shown interrelationships between post-traumatic sequelae and psychosis, but the temporal dynamics of these relationships in people with psychosis and a history of trauma remain unclear. We aimed to explore, using network analysis, the temporal order of relationships between symptoms of cPTSD (i.e. core PTSD and disturbances of self-organization [DSOs]) and psychosis in the flow of daily life.

Participants with psychosis and comorbid PTSD (N = 153) completed an experience-sampling study involving multiple daily assessments of psychosis (paranoia, voices, and visions), core PTSD (trauma-related intrusions, avoidance, hyperarousal), and DSOs (emotional dysregulation, interpersonal difficulties, negative self-concept) over six consecutive days. Multilevel vector autoregressive modeling was used to estimate three complementary networks representing different timescales.

Our between-subjects network suggested that, on average over the testing period, most cPTSD symptoms related to at least one positive psychotic symptom. Many average relationships persist in the contemporaneous network, indicating symptoms of cPTSD and psychosis co-occur, especially paranoia with hyperarousal and negative self-concept. The temporal network suggested that paranoia reciprocally predicted, and was predicted by, hyperarousal, negative self-concept, and emotional dysregulation from moment to moment. cPTSD did not directly relate to voices in the temporal network.

cPTSD and positive psychosis symptoms mutually maintain each other in trauma-exposed people with psychosis via the maintenance of current threat, consistent with cognitive models of PTSD. Current threat, therefore, represents a valuable treatment target in phased-based trauma-focused psychosis interventions.

Cannabis is one of the most commonly used drugs globally, although its legal status varies across regions. Public support for its decriminalization has increased, but gaps in our understanding of the health consequences of cannabis use remain, particularly related to its impact on mental health. This article provides an updated systematic review and meta-analysis (previous being Lev-Ran et al., 2014) looking at the relationship between cannabis and depression.

Literature available before March 2023 was screened for longitudinal studies that included cannabis use and depression. Cross-sectional studies and those only looking at special populations were excluded. Studies must have also controlled for depression at baseline to allow for investigation of a temporal relationship. Extracted data included cannabis measures, depression outcomes, adjusted odds ratios, and study settings. Meta-analysis employed a random effects model with multilevel meta-regression for effect size moderators.

The search yielded 1,599 titles from various databases, resulting in 22 studies for meta-analysis, including 14 from Lev-Ran et al. Eleven studies were US-based, with participants mostly under 18. Meta-analysis showed a higher risk of depression among cannabis users (OR: 1.29, 95% CI: 1.13–1.46). Risk of bias assessment showed medium risk across studies with exposure measurement being a key bias area. The funnel plot and Egger’s Sandwich test did not suggest publication bias.

This study underscores the association between cannabis use and depression but also emphasizes the need for further research, especially in understanding usage patterns, heavy use definitions, and long-term effects on depression risk amidst changing cannabis trends.

Impaired emotion regulation has been proposed as a putative endophenotype in bipolar disorder (BD). Functional magnetic resonance imaging (fMRI) studies investigating this in unaffected first-degree relatives (UR) have thus far yielded incongruent findings. Hence, the current paper examines neural subgroups among UR during emotion regulation.

71 UR of patients with BD and 66 healthy controls (HC) underwent fMRI scanning while performing an emotion regulation task. Hierarchical cluster analysis was performed on extracted signal change during emotion down-regulation in pre-defined regions of interest (ROIs). Identified subgroups were compared on neural activation, demographic, clinical, and cognitive variables.

Two subgroups of UR were identified: subgroup 1 (39 UR; 55%) was characterized by hypo-activity in the dorsolateral, dorsomedial, and ventrolateral prefrontal cortex and the bilateral amygdalae, but comparable activation to HC in the other ROIs; subgroup 2 (32 UR; 45%) was characterized by hyperactivity in all ROIs. Subgroup 1 had lower success in emotion regulation compared to HC and reported more childhood trauma compared to subgroup 2 and HC. Subgroup 2 reported more anxiety, lower functioning, and greater attentional vigilance toward fearful faces compared to HC. Relatives from both subgroups were poorer in recognizing positive faces compared to HC.

These findings may explain the discrepancy in earlier fMRI studies on emotion regulation in UR, showing two different subgroups of UR that both exhibited aberrant neural activity during emotion regulation, but in opposite directions. Furthermore, the results suggest that impaired recognition of positive facial expressions is a broad endophenotype of BD.

Psychosis prediction has been a key focus of psychiatry research for over 20 years. The two dominant approaches to identifying psychosis risk have been the clinical high-risk (CHR) and the familial high-risk (FHR) approaches. To date, the real-world sensitivity of these approaches – that is, the proportion of all future psychotic disorders in the population that they identify – has not been systematically reviewed.

We systematically reviewed and meta-analysed studies in MEDLINE, Embase, PsychINFO, and Web of Science (from inception until September 2024) that reported data on the sensitivity of CHR and FHR approaches – i.e., individuals with a psychosis diagnosis preceded by a CHR diagnosis or a history of parental psychosis (PROSPERO: CRD42024542268).

We identified four CHR studies and four FHR studies reporting relevant data. The pooled estimate of the sensitivity of the CHR approach was 6.7% (95% CI: 1.5–15.0%) and of the FHR approach was 6.5% (95% CI: 4.4–8.9%). There was a high level of heterogeneity between studies. Most FHR studies had a low risk of bias, but most CHR studies had a high risk of bias.

Pooled data suggest that CHR and FHR approaches, each, capture only about 6–7% of future psychotic disorders. These findings demonstrate the need for additional approaches to identify risk for psychosis.

We conducted a prospective study to advance knowledge of biological factors that predict the future onset of binge eating and compensatory weight control behaviors because few biological risk factors for eating pathology have been identified.

Adolescent girls free of binge eating or compensatory behaviors (N = 88; Mage = 14.5; [SD = 0.9]) completed functional magnetic resonance imaging tasks assessing individual differences in neural responsivity hypothesized to increase risk for onset of binge eating and compensatory behaviors, along with additional self-report measures, and were assessed over a 4-year follow-up.

Elevated responsivity of regions implicated in attention and valuation (dorsal anterior cingulate cortex; ventromedial prefrontal cortex) to thin models and lower responsivity of a reward valuation region (caudate) to anticipated milkshake tastes (which correlated with feeling fat) predicted the future onset of binge eating or compensatory behaviors over 4-year follow-up. Parental history of binge eating and compensatory behaviors, emotionality, weight/shape overvaluation, feeling fat, and elevated BMI also predicted the future onset of binge eating or compensatory behaviors.

The evidence that elevated attentional bias for, and valuation of the thin ideal, in combination with lower valuation of high-calorie foods, predicted the future onset of eating-disordered behaviors are novel findings. The evidence that weight/shape overvaluation, feeling fat, elevated body mass, emotionality, and parental history of eating pathology predicted the future onset of eating-disordered behaviors extend past findings.

The COVID-19 pandemic has had a significant impact on the health of millions of people worldwide, and many manifest new or persistent symptoms long after the initial onset of the infection. One of the leading symptoms of long-COVID is cognitive impairment, which includes memory loss, lack of concentration, and brain fog. Understanding the nature and underlying mechanisms of cognitive impairment in long-COVID is important for developing preventive and therapeutic interventions.

Our present study investigated functional connectivity (FC) changes in patients with long-COVID and their associations with cognitive impairment. Resting-state functional MRI data from 60 long-COVID patients and 52 age- and sex-matched healthy controls were analyzed using seed-based functional connectivity analysis.

We found increased FC between the right caudate nucleus and both the left and right precentral gyri in long-COVID patients compared with healthy controls. In addition, elevated FC was observed between the right anterior globus pallidus and posterior cingulate cortex as well as the right temporal pole in long-COVID patients. Importantly, the magnitude of FC between the caudate and the left precentral gyrus showed a significant negative correlation with Montreal Cognitive Assessment (MoCA) scores and a negative correlation with Trail Making Test B performance in the patient group.

Patients with long-COVID present enhanced FC between the caudate and the left precentral gyrus. Furthermore, those FC alterations are related to the severity of cognitive impairment, particularly in the domain of executive functions.

Impulsivity is a multidimensional trait associated with substance use disorders (SUDs), but the relationship between distinct impulsivity facets and stages of substance use involvement remains unclear.

We used genomic structural equation modeling and genome-wide association studies (N = 79,729–903,147) to examine the latent genetic architecture of nine impulsivity traits and seven substance use (SU) and SUD traits.

We found that the SU and SUD factors were strongly genetically inter-correlated (rG=0.77) but their associations with impulsivity facets differed. Lack of premeditation, negative and positive urgency were equally positively genetically correlated with both the SU (rG=.0.30–0.50) and SUD (rG=0.38–0.46) factors; sensation seeking was more strongly genetically correlated with the SU factor (rG=0.27 versus rG=0.10); delay discounting was more strongly genetically correlated with the SUD factor (rG=0.31 versus rG=0.21); and lack of perseverance was only weakly genetically correlated with the SU factor (rG=0.10). After controlling for the genetic correlation between SU/SUD, we found that lack of premeditation was independently genetically associated with both the SU (β=0.42) and SUD factors (β=0.21); sensation seeking and positive urgency were independently genetically associated with the SU factor (β=0.48, β=0.33, respectively); and negative urgency and delay discounting were independently genetically associated with the SUD factor (β=0.33, β=0.36, respectively).

Our findings show that specific impulsivity facets confer risk for distinct stages of substance use involvement, with potential implications for SUDs prevention and treatment.

Cognitive behavioural therapy for insomnia (CBT-I) is the recommended first-line treatment for insomnia. However, scaling this proven effective intervention to areas of high need remains a challenge, necessitating sensitive adaptation and evaluation.

A randomised waitlist-controlled trial evaluated the efficacy of a hybrid digital CBT-I and emotion regulation (dCBT-I + ER) intervention delivered through workplaces. Participants with at least mild insomnia and depression or anxiety symptoms were randomised to the intervention or waitlist control groups. The intervention was delivered via a web-based platform and four video-conferencing therapy sessions. Participants tracked their sleep using actigraphy and a sleep diary that was used to pace the intervention delivered. Assessments occurred at baseline and 8 weeks post-randomisation, measuring insomnia, depression, anxiety, psychological well-being, quality of life, and work productivity.

Of the 159 participants (mean age 43.6 ± 9.4 years, 76.7% female, 80.5% white), 80 received the intervention and 79 were in the control group. The intervention group showed significant improvements in insomnia (F1, 134 = 71.46, p < .0001); depression (F1, 134 = 35.67, p < .0001); and anxiety (F1, 134 = 17.63, p < .0001), with large effect sizes (d = 0.7–1.5). Sleep diary data supported these findings, whereas actigraphy data did not. Improvements in psychological well-being were significant (F1, 132.13 = 10.64, p < 0.001), whereas quality of life, work productivity, and satisfaction outcomes were not.

This study suggests that a hybrid dCBT-I + ER intervention, delivered via workplaces, effectively improves insomnia, depression, and anxiety. It holds promise as a scalable solution, warranting further investigation into its long-term efficacy and economic impact.

Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g. air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation. This study investigated distinct exposure profiles, estimated their associations with persistent distressing psychotic-like experiences (PLE), and evaluated whether involvement in physical activity partially explains this association.

Analyses included 8,145 young adolescents from the Adolescent Brain and Cognitive Development Study. Data from the baseline and three follow-ups were included. Area-level geocoded variables spanning various domains of SDOH, including socioeconomic status, education, crime, built environment, social context, and crime, were clustered using a self-organizing map method to identify exposure profiles. Generalized linear mixed modeling tested the association between exposure profiles and persistent distressing PLE and physical activities (i.e. team and individual sports), adjusting for individual-level covariates including age, sex, race/ethnicity, highest level of parent education, family-relatedness, and study sites.

Five exposure profiles were identified. Compared to the reference Profile 1 (suburban affluent areas), Profile 3 (rural areas with low walkability and high ozone), and Profile 4 (urban areas with high SES deprivation, high crime, and high pollution) were associated with greater persistent distressing PLE. Team sports mediated 6.14% of the association for Profile 3.

This study found that neighborhoods characterized by rural areas with low walkability and urban areas with high socioeconomic deprivation, pollution concentrations, and crime were associated with persistent distressing PLE. Findings suggest that various social-environmental factors may differentially impact the development of psychosis.

According to the aberrant salience proposal, reward processing abnormality, specifically erroneous reward prediction error (RPE) signaling due to stimulus-independent release of dopamine, underlies delusions in schizophrenia. However, no studies to date have examined RPE-associated brain activations in relation to this symptom.

Seventy-eight patients with a DSM-5 diagnosis of schizophrenia/schizoaffective disorder and 43 healthy individuals underwent fMRI while they performed a probabilistic monetary reward task designed to generate a measure of RPE. Ratings of delusions and referentiality were made in the patients.

Using whole-brain, voxel-based analysis, schizophrenia patients showed only minor differences in RPE-associated activation compared to healthy controls. Within the patient group, however, severity of delusions was inversely associated with RPE-associated activation in areas including the caudate nucleus, the thalamus and the left pallidum, as well as the lateral frontal cortex bilaterally, the pre- and postcentral gyrus and supplementary motor area, the middle cingulate gyrus, and parts of the temporal and parietal cortex. A broadly similar pattern of association was seen for referentiality.

According to this study, while patients with schizophrenia as a group do not show marked alterations in RPE signaling, delusions and referentiality are associated with reduced activation in parts of the prefrontal cortex and the basal ganglia, though not specifically the ventral striatum. The direction of the changes is on the face of it contrary to that predicted by aberrant salience theory.

Major depressive disorder (MDD) is a heterogeneous condition characterized by significant intersubject variability in clinical presentations. Recent neuroimaging studies have indicated that MDD involves altered brain connectivity across widespread regions. However, the variability in abnormal connectivity among MDD patients remains understudied.

Utilizing a large, multi-site dataset comprising 1,276 patients with MDD and 1,104 matched healthy controls, this study aimed to investigate the intersubject variability of structural covariance (IVSC) and functional connectivity (IVFC) in MDD.

Patients with MDD demonstrated higher IVSC in the precuneus and lingual gyrus, but lower IVSC in the medial frontal gyrus, calcarine, cuneus, and cerebellum anterior lobe. Conversely, they exhibited an overall increase in IVFC across almost the entire brain, including the middle frontal gyrus, anterior cingulate cortex, hippocampus, insula, striatum, and precuneus. Correlation and mediation analyses revealed that abnormal IVSC was positively correlated with gray matter atrophy and mediated the relationship between abnormal IVFC and gray matter atrophy. As the disease progressed, IVFC increased in the left striatum, insula, right lingual gyrus, posterior cingulate, and left calcarine. Pharmacotherapy significantly reduced IVFC in the right insula, superior temporal gyrus, and inferior parietal lobule. Furthermore, we found significant but distinct correlations between abnormal IVSC and IVFC and the distribution of neurotransmitter receptors, suggesting potential molecular underpinnings. Further analysis confirmed that abnormal patterns of IVSC and IVFC were reproducible and MDD specificity.

These results elucidate the heterogeneity of abnormal connectivity in MDD, underscoring the importance of addressing this heterogeneity in future research.

Loneliness is a risk factor for late-life dementia. There is less consistent evidence of its association with cognitive performance. This study examined the replicability of the association between loneliness and overall and domain-specific cognitive function and informant-rated cognitive decline in cohorts from seven countries: the United States, England, India, China, South Africa, Mexico, and Chile.

Data were from the Harmonized Cognitive Assessment Protocol administered in seven population-based studies (total N > 20,000). Participants reported their loneliness, completed a battery of cognitive tests, and nominated a knowledgeable informant to rate their cognitive decline. Random-effect meta-analyses were used to summarize the associations from each cohort.

Loneliness was associated with poor overall cognitive performance and informant-rated cognitive decline controlling for sociodemographic factors (meta-analytic correlation for overall cognition = −.10 [95% CI = −.13, −.06] and informant-rated decline = .16 [95% CI = .14, .17]). Despite some heterogeneity, the associations were significant across samples from Africa, Asia, Europe, North, Central, and South America. The meta-analysis also indicated an association with specific cognitive domains: episodic memory, speed-attention, visuospatial abilities, numeric reasoning, and verbal fluency. The associations were attenuated but persisted when depressive symptoms were added as a covariate. Depression, cognitive impairment, and sociodemographic factors did not consistently moderate the associations across samples.

Loneliness is associated with poor performance across multiple domains of cognition and observer-rated cognitive decline, associations that replicated across diverse world regions and cultures.

Neuropsychological evidence suggests that dissociation might disturb emotional learning, which is a fundamental mechanism of psychotherapy. However, a recent meta-analysis on the impact of dissociation on treatment outcomes in psychotherapy trials for posttraumatic stress disorder (PTSD) reported inconsistent results and concluded that further high-quality clinical trials are needed to test whether dissociation affects the efficacy of psychotherapies. We had two main aims: First, to test whether the efficacy of two evidence-based psychotherapies for individuals with trauma-related PTSD is affected by the level of pretreatment dissociation. Second, we investigated whether a significant reduction in dissociation at an early stage of treatment is beneficial for subsequent efficacy.

The potential impact of dissociation on efficacy was studied in 193 women with PTSD related to childhood abuse who were randomized to dialectical behavior therapy for PTSD (DBT-PTSD) or cognitive processing therapy (CPT). Efficacy was operationalized as a change in the Clinician-Administered PTSD Scale (CAPS). Dissociation was assessed with the Dissociation Tension Scale (DSS). The analyses accounted for major confounders (in particular initial PTSD severity).

Two main findings emerged from this study. First, baseline dissociation was a negative predictor for treatment efficacy. Second, a significant drop in dissociation at the initial stages of treatment was beneficial for subsequent efficacy.

Dissociation likely reduces the efficacy of trauma-focused therapies. Accordingly, successful reduction of dissociation at an early stage of treatment assists the efficacy of trauma-focused psychotherapies.

Patients with schizophrenia experience accelerated aging, accompanied by abnormalities in biomarkers such as shorter telomere length. Brain age prediction using neuroimaging data has gained attention in schizophrenia research, with consistently reported increases in brain-predicted age difference (brain-PAD). However, its associations with clinical symptoms and illness duration remain unclear.

We developed brain age prediction models using structural magnetic resonance imaging (MRI) data from 10,938 healthy individuals. The models were validated on an independent test dataset comprising 79 healthy controls, 57 patients with recent-onset schizophrenia, and 71 patients with chronic schizophrenia. Group comparisons and the clinical associations of brain-PAD were analyzed using multiple linear regression. SHapley Additive exPlanations (SHAP) values estimated feature contributions to the model, and between-group differences in SHAP values and group-by-SHAP value interactions were also examined.

Patients with recent-onset schizophrenia and chronic schizophrenia exhibited increased brain-PAD values of 1.2 and 0.9 years, respectively. Between-group differences in SHAP values were identified in the right lateral prefrontal area (false discovery rate [FDR] p = 0.022), with group-by-SHAP value interactions observed in the left prefrontal area (FDR p = 0.049). A negative association between brain-PAD and Full-scale Intelligence Quotient scores in chronic schizophrenia was noted, which did not remain significant after correction for multiple comparisons.

Brain-PAD increases were pronounced in the early phase of schizophrenia. Regional brain abnormalities contributing to brain-PAD likely vary with illness duration. Future longitudinal studies are required to overcome limitations related to sample size, heterogeneity, and the cross-sectional design of this study.