Schizophrenia is associated with widespread abnormalities in large-scale brain organization; however, the mechanisms linking altered cortical hierarchy to disrupted neural communication and clinical symptoms remain unclear. By integrating functional connectivity gradient analysis and stepwise functional connectivity (SFC), we aimed to clarify how alterations in cortical hierarchy translate into disrupted connectome-based propagation in schizophrenia.

Resting-state functional MRI data from 820 participants (310 healthy controls and 510 patients with schizophrenia) were analyzed across multiple cohorts. Cortical hierarchy was characterized using functional connectivity gradients, focusing on the principal unimodal–transmodal gradient (G1). Connectome-based propagation was examined using SFC, with step counts indexing propagation efficiency across predefined hierarchical levels. Associations with clinical symptoms were assessed, including mediation analyses.

Global cortical hierarchy was preserved in schizophrenia; however, selective alterations were evident. Patients with schizophrenia showed significantly reduced G1 values in the dorsal attention network (DAN), with regional alterations primarily localized to dorsal attention and somatomotor regions. SFC analysis revealed delayed propagation toward higher-order association networks in schizophrenia, reflected by increased step counts to intermediate and transmodal hierarchical levels. Among patients with illness duration <5 years, delayed propagation to higher hierarchical levels was associated with greater positive and negative symptom severity. Mediation analyses demonstrated that delayed propagation significantly mediated the relationship between DAN hierarchical positioning and clinical symptoms.

These findings suggest that schizophrenia is characterized by selective disruption of cortical hierarchy within attentional control systems, leading to impaired large-scale connectome-based propagation that links cortical organization to clinical symptoms.

Prior work suggests girls with earlier subjective pubertal timing (i.e. girls who perceive themselves as maturing earlier than peers) engage in more antisocial behavior (ASB). Theories regarding mechanisms predominantly focus on social/environmental processes, but genetic influences may contribute, particularly given that ASB is heritable, and the stress associated with earlier subjective timing may activate or enhance these genetic vulnerabilities to increase risk. To date, no study has examined these gene × environment interactions (G×E) for ASB and subjective pubertal timing relative to peers.

Participants included 995 female twins (ages 8–16 years) from the MSU Twin Registry. Mothers reported children’s aggressive and rule-breaking behaviors using the Child Behavior Checklist. Subjective timing was assessed with a modified Pubertal Development Scale where twins reported their maturation on pubertal markers (e.g. breast development) as earlier, the same, or later compared to two reference groups: their co-twin and other girls their age.

Twin models revealed that genetic influences on aggression and rule breaking were stronger in earlier versus on-time and later-maturing girls. These effects were present when examining timing relative to co-twin and other girls, although effects were somewhat stronger for co-twin. Environmental influences on aggression and rule breaking were greater in later-maturing girls across both reference groups.

Results significantly inform etiologic models by highlighting G×E for associations between subjective timing and ASB in girls. Findings underscore the importance of considering genetic influences and the need to further explore the specific genetic/environmental factors that shift across perceptions of pubertal timing.

ADHD has been associated with BMI, across the lifespan. A possible mechanism linking ADHD and BMI is binge eating symptoms. Previous research has found associations between ADHD, binge eating symptoms, and BMI. However, the role of genetic and environmental influences on these associations remains unclear.

We utilized data from the Twins Early Development Study, comprising 4,363 monozygotic and 8,575 dizygotic twin pairs. ADHD symptoms in childhood and adolescence were assessed using parent-reported questionnaires. Adult ADHD symptoms were measured using both self-report and parent-report questionnaires. Phenotypic mediation models examined whether binge eating symptoms mediated the association between ADHD and BMI, without controlling for genetic confounding. Subsequently, the etiological architecture underlying the associations among the three traits across childhood, adolescence, and adulthood were investigated by incorporating genetic and environmental influences into the models.

Binge eating symptoms significantly mediated the association between ADHD symptoms and BMI in both adolescence and adulthood. However, these mediation effects were no longer present once genetic and environmental influences were incorporated into the models. The best-fitting model in childhood, adolescence, and adulthood was Cholesky decomposition models, where covariance between traits was explained by shared etiology.

This twin study reveals shared liability across ADHD, binge eating symptoms, and BMI. The mediating role of binge eating symptoms in the relationship between ADHD symptoms and BMI was largely confounded by shared genetic influences. Intervention strategies could focus more on common underlying behavioral and self-regulatory mechanisms across these traits, as well as placing more emphasis on symptom patterns within families.

Cognitive fusion (CF), a core maladaptive process in obsessive-compulsive disorder (OCD), describes overidentification with intrusive thoughts. While implicated in symptom maintenance, its neuroanatomical basis and treatment prediction utility remain poorly understood.

We enrolled 80 first-episode, drug-naïve OCD patients and 70 matched healthy controls. All participants underwent structural magnetic resonance imaging and clinical assessment. Patients received 8-week selective serotonin reuptake inhibitors treatment with endpoint reevaluation. Using multimodal neuroimaging, we examined group differences in gray matter volume (GMV) and structural covariance network (SCN), tested whether CF levels modulated connectivity, and evaluated baseline features for predicting treatment response. Transcriptomic analysis linked the findings to the Allen Human Brain Atlas data.

OCD patients showed GMV reductions in frontal-limbic regions and increases in parietal/inferior frontal areas. SCN analysis revealed enhanced structural covariance within fronto-parieto-cerebellar circuits. Higher CF scores were associated with stronger structural coupling between the left angular gyrus and the right middle temporal/medial superior frontal gyri. Baseline GMV in the left dorsolateral superior frontal gyrus (SFGdl) positively correlated with CF improvement, remaining significant after controlling for overall symptom reduction. Transcriptomic analysis indicated the left SFGdl GMV patterns spatially associated with glutamatergic synapse and calcium signaling pathways.

CF in OCD links to altered structural integration between large-scale networks, with the left SFGdl emerging as a potential CF-specific treatment predictor. This multiscale study highlights combining neuroimaging with psychological constructs to understand treatment-relevant changes in OCD.

Information from large national surveys is potentially useful for examining trends in mental health, but prior research has obtained inconsistent findings. This study attempts to determine whether Kessler 6 and Patient Health Questionnaire measures from different surveys consistently indicate trends in serious psychological distress or depression.

Annual rates of serious psychological distress or depression were computed for 18- to 64-year-olds from 2004 to 2019 or sub-periods from four major household surveys based on values of Kessler 6, Patient Health Questionnaire 2, and Patient Health Questionnaire 9 scales. The observed trends were then compared to those from four potential consequences of poor mental health.

The potential consequences of poor mental health increased over time, as did serious psychological distress measured by the Kessler K6 in the National Health Interview Survey and National Survey on Drug Use and Health, and serious depression using Patient Health Questionnaire 2 and 9 data from the National Health and Examination Survey. Conversely, rates of serious psychological distress/depression, proxied by Kessler 6 and Patient Health Questionnaire 2 scores from the Medical Expenditure Panel Survey fell sharply after 2012.

The mental health of prime-age US adults almost certainly deteriorated from 2004 to 2019 but, when based on Kessler 6 and Patient Health Questionnaire scales, the results from some high-quality national household surveys indicated the opposite trends, exhibited substantial year-to-year variation, or had large confidence intervals. This highlights the need for considerable care in estimating trends in serious psychological distress or depression, even when using high-quality surveys.

Loneliness has been linked to increased risk of mood disorders, but its relationship with bipolar disorder (BD) and underlying neurobiological mechanisms remain unclear.

This prospective cohort study utilized data from the UK Biobank, involving 491,472 individuals aged 38–73 years without prior BD diagnosis at baseline (2006–2010). Participants reported loneliness and provided data on demographic, socioeconomic, lifestyle factors, and polygenic risk scores (PRS) for BD. Follow-up extended until 2022, tracking incident BD cases. Neuroimaging analyses examined gray matter volume (GMV) associations with loneliness, considering genetic susceptibility.

Over 16 years, 1,316 participants developed BD. Loneliness was associated with a more than threefold increased risk of BD (hazard ratio [HR], 3.31; 95% CI, 2.97–3.69), which remained significant after adjusting for covariates (HR, 2.83; 95% CI, 2.47–3.23). Neuroimaging revealed that loneliness correlated with widespread reductions in GMV, particularly in regions involved in emotion regulation and social cognition. These neurobiological effects were more pronounced in individuals with higher BD PRS.

Loneliness is prospectively associated with a substantially increased hazard of BD and is linked to extensive brain structural changes, especially in genetically susceptible individuals. These findings highlight the importance of addressing loneliness to potentially mitigate BD risk and its neurobiological impact.

Although lack of assertiveness (LOA) and hostility are established risk factors for depression, the mechanisms linking them to depression and their genetic or environmental contributions remain unclear. We used the Swedish Adoption/Twin Study of Aging (SATSA) to test whether social support (SS) deficits mediated these pathways.

Community-dwelling twins (N = 2,034; 1,017 pairs) were followed for up to 23 years (1984–2007). We examined serial (LOA → hostility → SS → depression) and parallel (LOA + hostility → SS → depression) mediation models. Within-pair difference analyses in monozygotic (n = 317) and dizygotic (n = 645) pairs isolated non-shared environmental pathways.

Within monozygotic pairs, where genetic confounding is removed by design, LOA did not predict hostility. Hence, the serial indirect effect was not significant. The hostility → SS → depression indirect effect was significant in the serial model (b = 0.020, 95% CI [0.005, 0.038], β = 0.036); the parallel-model estimate was smaller and in the same direction. LOA and hostility directly predicted depression in both models (β = 0.100 to 0.227, p ≤ .039). Within dizygotic twins, where only 50% of additive genetic variance is removed on average, LOA predicted hostility (β = 0.089, p = .003).

The null monozygotic association between LOA and hostility is consistent with genetic confounding, although limited power and measurement-error attenuation cannot be ruled out. However, the hostility → SS → depression pathway and these direct effects are consistent with environmentally mediated processes that may be actionable intervention targets beyond genetic susceptibility.

When deciding on antidepressant maintenance with clinicians, remitted patients must weigh the burdens of continued use against the benefit of less time depressed. This benefit is often inferred qualitatively from relapse-frequency data, even though expected time depressed also depends on episode duration, antidepressant re-initiation, and how evidence from highly recurrent populations applies to patients with fewer prior episodes.

We developed a health-state transition model to combine evidence on recurrence, episode duration, re-initiation, and treatment effects into expected time depressed and time taking antidepressants under maintenance versus active monitoring. Adults in remission were simulated for 5 years across groups based on depression history. We summarized the trade-off as additional antidepressant use required to avert 1 month of depression. The decision framework links this estimate to patient preferences by comparing required with acceptable use, allowing patients who expect greater consequences of relapse or experience fewer treatment burdens to consider more antidepressant use acceptable.

Maintenance efficiency varied substantially with recurrence history. Each month of depression averted required 1.5 additional years of antidepressant use among patients with 4–5 prior episodes; 2.8 years with 2–3 prior episodes, 5.1 years after one moderate-to-severe episode, and 11.8 years after one mild episode. When these trade-offs are acceptable, patients are modeled to prefer maintenance.

The model expresses the maintenance trade-off as a ratio of benefits and burdens. Preferences and clinical judgment determine for whom the ratio is acceptable. Empirical work can determine whether this improves maintenance decisions in practice.

Adolescent major depressive disorder (MDD) has been associated with cortical structural abnormalities. However, whether these structural changes correlate with gene expression profiles remains unclear. Here, we investigated the cortical similarity network alterations and the associated transcriptional patterns in adolescents with MDD using a novel Morphometric Inverse Divergence (MIND) network model.

Using structural images from 174 adolescents with MDD and 82 healthy controls (HCs), we constructed individual MIND networks based on multiple morphological features. We compared regional MIND between groups and developed machine learning models to assess the potential of MIND for distinguishing patients from HCs. Spatial associations between MIND differences and gene expression profiles were assessed using partial least squares regression, followed by gene enrichment analyses to identify associated biological pathways, cell types, and developmental trajectories.

Regional MIND abnormalities in adolescent MDD patients were primarily located in the orbitofrontal cortex, as well as in sensorimotor and visual network regions. Using MIND features, the optimal machine learning model achieved a high area under the curve (AUC) of 0.824 and generalized well to the external independent dataset (AUC = 0.724). MIND changes were associated with gene expression related to synaptic signaling, neurodevelopment, metabolism, and specific cell types. Developmental trajectory analysis suggested distinct, region-specific susceptibility windows for adolescent MDD.

By linking MIND network alterations and transcriptional expression profiles, this study provides new insights into the neural basis and associated molecular mechanisms underlying adolescent MDD and underscores the diagnostic potential of MIND.

The World Health Organization (WHO) developed an assessment for healthy aging termed intrinsic capacity (IC). However, the association between IC and depression/anxiety remains poorly understood, with limited understanding of the underlying metabolic mechanisms.

This prospective cohort study comprised 212,033 UK Biobank participants recruited between 2006 and 2010. We calculated a UK Biobank-adapted four-domain IC deficit score using seven functional status indicators across psychological, sensory, vitality, and locomotor domains. Elastic net regression was employed to derive a metabolic signature that represented IC status. Polygenic risk scores (PRS) for depression and anxiety were computed from associated risk variants.

Compared with a 0 IC deficit score, participants with a 4+ score had higher risk, with hazard ratios (HRs) (95% CIs) of 3.96 (3.72–4.21) for depression and 3.03 (2.82–3.25) for anxiety. The metabolic signature of IC comprised 59 metabolites, with mediation effects of 1.007 (1.005, 1.008) for depression and 1.006 (1.004, 1.007) for anxiety. The highest hazards were observed in participants with high PRS and 4+ IC score; the HRs were 4.36 (3.70–5.13) for depression and 3.46 (2.87–4.17) for anxiety.

IC is associated with a higher risk of depression and anxiety, possibly mediated by its metabolic signature, with enhanced effects in genetically susceptible individuals.

Psilocybin use has increased in the US alongside promising therapeutic potential for depression, raising concerns that individuals may forgo conventional mental health treatment for unsupervised psilocybin use. However, no nationally representative studies have examined whether psilocybin use is associated with differential treatment utilization or perceived unmet need for mental health care among individuals with depression.

We analyzed data from 6,793 individuals aged ≥ 12 years with a past-year major depressive episode (MDE) from the 2024 National Survey on Drug Use and Health, a nationally representative survey of the noninstitutionalized US population. Sociodemographic and substance use characteristics were first compared by past-year psilocybin use. We then examined associations between past-year psilocybin use and eight past-year mental health treatment outcomes using Poisson regression, adjusting for sociodemographic characteristics, other past-year substance use, psychotherapeutic prescription misuse, and alcohol use disorder.

Among individuals with past-year MDE, an estimated 7.3% (95% CI: 6.4–8.3) used psilocybin in the past year. In multivariable models, psilocybin use was not associated with any mental health treatment utilization, including outpatient, inpatient, or telehealth treatment; prescription medication use for mental health; seeing a doctor for depressive feelings; or prescription medication use for depressive feelings. However, psilocybin use was associated with greater perceived unmet treatment need (52.0% vs. 33.9%; aPR = 1.44; 95% CI: 1.04–2.01).

Findings suggest that psilocybin use among individuals with depression co-occurs with perceived unmet need for conventional mental health care but is not associated with lower utilization of any conventional mental health treatments.

Adverse childhood experiences (ACEs) have long-lasting effects in Chinese older adults. Using China Health and Retirement Longitudinal Study (CHARLS) data, we examined ACEs’ impact on chronic sleep disturbances combining poor sleep quality and abnormal duration in China’s aging population.

We analyzed 20,450 CHARLS participants (2014 baseline). After excluding those with missing ACEs data (n = 11,006), incomplete sleep data, or aged <45 years and with psychiatric conditions, the final sample comprised 5,533 individuals. ACE exposure was categorized into: Class 1 (0 ACEs, n = 1,382), Class 2 (1 ACE, n = 1,769), Class 3 (2 ACEs, n = 1,264), and Class 4 (≥3 ACEs, n = 1,118). Composite sleep disturbances were defined by CES-D-10 self-reported sleep quality (4-point scale item ≥3) and abnormal duration (<6 or >9 hours). Multivariable logistic regression adjusted for age, sex, education, marital status, smoking, drinking, and chronic diseases, with trend tests modeling ACEs ordinally.

A graded association emerged: adjusted ORs increased from 1.30 (95% CI: 1.05–1.59) for 1 ACE to 2.1 (1.69–2.62) for ≥3 ACEs (Ptrend < 0.001). Five ACE types showed significant associations: household mental illness showed the strongest association (OR = 1.77, 1.53–32.06, P < 0.001). Subgroup analyses revealed consistent associations between ACE exposure (≥1) and increased risk of Chronic Sleep Disturbances across most population strata (OR range: 1.27–1.81, P < 0.05).

Childhood adversity, particularly household mental illness, was significantly associated with sleep disturbances in older adults. The observed 2.1-fold prevalence difference suggests that older adults with high ACE exposure may benefit from targeted screening and early intervention.

The excitation–inhibition (E/I) imbalance is a major pathological characteristic of major depressive disorder (MDD). However, whether/how electroconvulsive therapy (ECT) modulates neuronal homeostasis or E/I balance in MDD and its molecular basis is still largely unknown.

In this study, longitudinal rs-fMRI data from 46 patients with MDD receiving ECT and 46 healthy controls were included. The Hurst index was used to characterize the E/I balance, and mixed-effects model was constructed to assess the interactive effects of ECT on the Hurst index and functional connectivity (FC). Moreover, spatial correlation analyses were conducted by integrating cortical myelination pattern, glucose metabolism distribution, neurotransmitter density maps, and transcriptomic data to reveal the underlying molecular basis.

ECT significantly reduces the Hurst index in the middle cingulate cortex (MCC) and induces functional decoupling between the MCC and the posterior cingulate cortex. Furthermore, changes in the Hurst index were closely associated with cortical myelination, glucose metabolism, and the distribution maps of dopamine and histamine. Spatial transcriptomic association analysis revealed that genes regulating the effects of ECT on Hurst index or FC are specifically enriched in cell types such as excitatory neurons, astrocytes, and oligodendrocytes, and are primarily involved in biological processes including synaptic signal transduction, neuronal projection regulation, and glutamatergic synapses.

These findings suggest that ECT may regulate the processes of myelin remodelling through neurons and glial cells by influencing the expression levels of relevant genes, thereby modulating the E/I balance and functional network activity in a synergistic manner to improve depressive symptoms.

Accelerated brain aging has been associated with several neuropsychiatric disorders; however, findings remain inconsistent due to limited lifespan modeling and inadequate age-bias correction. This study aimed to establish normative brain-aging trajectories across the lifespan and quantify disorder-specific deviations in brain-predicted age difference (brain-PAD) in a large, age-diverse sample.

Brain-age models were trained on structural MRI data from 25,425 healthy individuals (aged 2–95 years) and validated in 270 independent cross-sectional and 188 longitudinal participants from the Dallas Lifespan Brain Study. Clinical analyses included 1,737 patients with schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder (BD), attention-deficit/hyperactivity disorder (ADHD), chronic substance use disorder (CSUD), Alzheimer’s disease (AD), and frontotemporal dementia (FTD), compared with 1,793 age-matched controls. Brain-PAD was computed after age-bias correction, regional morphometric differences were assessed using ANCOVA, and model interpretability was evaluated using SHapley Additive exPlanations (SHAP).

The model achieved a mean absolute error of ~5–7 years across validation and independent cohorts. Healthy individuals showed median brain-PAD values near zero, and longitudinal analyses tracked within-person aging. Significantly elevated Δbrain-PAD values were observed in SZ (+7.64 years), FTD (+7.61 years), AD (+3.24 years), BD (+2.08 years), MDD (+2.76 years), and CSUD (+2.91 years), but not in ADHD. Regional analyses revealed shared and disorder-specific morphometric alterations, and SHAP highlighted key contributions from ventricular enlargement and fronto-parietal cortical features.

Brain-PAD captures biologically meaningful structural variation across disorders and provides a quantitative framework for investigating lifespan brain aging in psychiatric and neurodegenerative conditions.

Despite concerns over increasing adolescent loneliness and its lasting negative impact on mental and physical health, global trends and the gender and socioeconomic inequalities remain unclear. The study examined trends in adolescent school loneliness from 2000 to 2022 across 87 countries, analyzing disparities by gender, socioeconomic status, and country-income level.

We analyzed data from the Programme for International Student Assessment, a nationally representative survey of 15-year-olds conducted in 2000, 2003, 2012, 2015, 2018, and 2022. School loneliness was measured by a composite score from six self-reported questions. We used mixed-effects regression modeling and meta-regression to analyze trends by gender, socioeconomic status, and country-income level (low and lower-middle, upper-middle, or high).

Among the 2,155,046 students, 50.8% were girls (n = 1,095,010), and school loneliness increased over time. Although boys initially reported higher school loneliness, girls’ school loneliness increased more rapidly, surpassing boys’ levels around 2012 in high-income countries and around 2018 in upper-middle-income countries. This gender-based reversal was not evident in low- and lower-middle-income countries. Low socioeconomic status was consistently associated with greater school loneliness across genders and across all country-income groups.

Adolescent school loneliness has increased globally over the past two decades, becoming particularly pronounced among girls in wealthier nations, leading to a widening gender gap by 2022. Socioeconomic disadvantages are a common risk factor for higher levels of school loneliness across all income groups. Public health strategies aimed at mitigating global trends in adolescent school loneliness and addressing its socioeconomic and growing gender disparities are warranted.

Sleep disturbances are highly prevalent in individuals with severe mental illness (SMI) and are associated with functional impairment. This study examined the prevalence of sleep disturbances and their associations with psychiatric symptoms and functional outcomes in a transdiagnostic SMI sample.

In this cross-sectional study, SMI outpatients completed standardized assessments of sleep disturbances (PSQI, ISI, STOP-Bang, ESS, SQ-RLS, and SQ-RBD), psychiatric symptoms (HARS, MADRS, YMRS, PANSS-N, and CGI-S), and functioning (FAST). Bivariate analyses were followed by structural equation modeling (SEM), including latent constructs for insomnia and depressive/anxious symptoms to estimate direct and indirect associations with functional impairment.

A total of 229 participants were included, and 69% screened positive for at least one sleep measure, including poor sleep quality (55.5%). Among the specific sleep-related problems, high risk of obstructive sleep apnea (OSA) (45.8%) was the most prevalent. Sleep disturbances were associated with greater clinical severity and worse functional impairment. In the SEM, depressive/anxious symptoms (β = 0.45), negative symptoms (β = 0.38), manic symptoms (β = 0.17), and OSA risk (β = 0.41) were independently associated with functional impairment. Insomnia exhibited an inconsistent pattern, with a negative direct effect (β = −0.47) and a positive indirect effect on functional impairment through depressive/anxious symptoms (β = 0.22).

Sleep disturbances are highly prevalent in individuals with SMI and are associated with functional outcomes, particularly insomnia and OSA risk. Systematic screening for sleep disturbances in psychiatric care may help identify clinically relevant and potentially modifiable factors associated with functional impairment.