Major depressive disorder (MDD) is a heterogeneous with underlying mechanisms that are insufficiently studied. We aimed to identify functional connectivity (FC)-based subtypes of MDD and investigate their biological mechanisms.

Consensus clustering of FC patterns was applied to a population of 829 MDD patients from the REST-Meta-MDD database, with validity assessed across multiple dimensions, including atlas replication, cross-validated classification, and drug-naïve subgroup analysis. Regression models were used to quantify FC alterations in each MDD subgroup compared with 770 healthy controls, and to analyze spatial associations between FC alterations and publicly available gene transcriptomic and neurotransmitter receptor/transporter density databases.

Two stable MDD subtypes emerged: hypoconnectivity (n = 527) and hyperconnectivity (n = 299), which had both shared and distinct regions with remarkable FC alterations (i.e. epicenters) in the default mode network.

There were several common enriched genes (e.g. axon/brain development, synaptic transmission/organization, etc.) related to FC alterations in both subtypes. However, glial cell and neuronal differentiation genes were specifically enriched in the hypoconnectivity and hyperconnectivity subtypes, respectively.

Both subtypes showed spatial associations between FC alterations and serotonin receptor/transporter density. In the hypoconnectivity subtype, FC alterations correlated with GABA and acetylcholine receptor densities, while norepinephrine transporter and glutamate receptor densities were linked to the hyperconnectivity subtype.

Our findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypoconnectivity or hyperconnectivity, demonstrating robust reproducibility. The two subtypes had both shared and distinct genetic mechanisms and neurotransmitter receptor/transporter profiles, suggesting potential clinical implications for this heterogeneous disorder.

The nosology of mania has long been a conundrum. Prior studies have alternately concluded that it is an internalizing disorder, a thought disorder, or a unique condition. Unfortunately, nearly all existing studies assessed symptoms cross-sectionally. This is problematic for syndromes that follow a more episodic course, such as mania. Here, we test whether including a history of episodes, not simply current symptoms, can help resolve the placement of mania in the meta-structure of psychopathology.

First-admission patients with psychosis from the Suffolk County Mental Health Project (N = 337) were followed across 20 years. Internalizing, thought disorder, and mania symptoms were assessed at year 20, whereas corresponding episodes (i.e. depressive, psychotic, and manic) were assessed across three intervals spanning the previous 20 years. We tested five models to determine whether mania (current and past) loaded onto the internalizing factor, the thought disorder factor, or an independent factor. A final model was validated against established markers of bipolar disorder.

For depression and psychosis, current and past markers were congruent in loading onto internalizing and thought disorder factors, respectively. However, current and past markers of mania diverged: current mania was most strongly related to the thought disorder dimension, whereas past mania formed an independent factor. Classic correlates of mania – including family history, genetic risk, and neuropsychological function – were associated only with the history of mania dimension.

Including illness course in structural models of psychopathology suggests that mania is distinguished from internalizing and thought disorder factors, whereas assessments of current symptoms place it with psychosis. These findings require independent validation, but if replicated, they would support a separate spectrum of mania defined by the occurrence of episodes across the lifetime.

Neuroticism, a personality trait linked to both cardiovascular and psychiatric disorders, has been associated with cognitive decline and increased dementia risk, though the underlying neural mechanisms remain unclear. Mapping its relationship with brain structure could provide valuable insights into neural pathways and targets for early intervention.

We examined brain-wide associations between neuroticism and structural neuroimaging metrics derived from T1-, T2-weighted, and diffusion MRI in 36,901 dementia-free UK Biobank participants. Bonferroni-significant associations underwent bidirectional two-sample Mendelian randomization to evaluate the evidence for a causal relationship. Given that neuroticism is generally stable across adulthood and challenging to modify, we assessed whether these associations were mediated by health conditions (depression, anxiety, hypertension, ischemic heart disease [IHD], and diabetes) that are both consequences of neuroticism and known risk factors for dementia, and also modifiable through widely available and efficacious therapeutic interventions.

Higher neuroticism was found to be associated with reduced grey matter volumes in the frontal and limbic regions, as well as widespread differences in white matter microstructure, particularly in thalamic radiations. Genetic analyses supported a potential causal effect of neuroticism on increased diffusivity in thalamic radiations. Hypertension mediated the associations between neuroticism and both grey and white matter measures, while depression and anxiety primarily mediated associations with white matter microstructure. Contributions from IHD and diabetes were minimal.

Neuroticism is linked to widespread structural brain differences that contribute to poorer brain health, and targeting vascular and mental health may help mitigate its impact.

Given substantial comorbidity among, and considerable heterogeneity within, psychiatric diagnoses, researchers have suggested alternative systems for classifying psychopathology. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a recently proposed framework for understanding mental disorders based on how symptoms and diagnoses tend to cluster across individuals. While the model is grounded in existing research and supported by recent meta-analytic evidence, its structure has not yet been directly tested using large, representative clinical datasets. In this study, we used electronic health record (EHR) data to examine the overall organization of mental disorders as proposed by HiTOP, with the goal of informing future research on biological and environmental risk factors as well as important life outcomes.

Data were drawn from the All of Us Research Program, a landmark nationwide US biobank initiative designed to advance population-scale health research, and included participants’ psychiatric diagnoses and sociodemographic correlates as documented in their EHRs. A total of 127,963 participants and 39 primary diagnoses were identified. We analyzed patterns of co-occurrence among psychiatric diagnoses to identify broader psychopathology dimensions, assess the overall structure of mental disorders, and clarify the placement of conditions that have been inconsistently categorized in past research. Several competing dimensional models were compared based on their statistical fit and complementary assessments of factor strength, specificity, and reproducibility.

A model identifying six broad and correlated dimensions – Fear, Distress, Externalizing, Substance Use, Thought Problems, and Neurodevelopmental Disorders – provided the best fit to the data. This structure was highly consistent across analyses and showed strong split-half replicability and meaningful associations with relevant clinical and demographic characteristics.

These findings support a 6-factor model of psychopathology that broadly resembles major dimensions in the HiTOP framework. By addressing key gaps in the literature, this study advances our understanding of the structure and correlates of mental disorders. The results offer a foundation for more nuanced investigations into the etiology, progression, and treatment of mental health conditions.

Psychotic-like experiences (PLEs) are considered a subclinical component of psychosis continuum. Studies indicate that PLEs arise from multimodal factors, yet research comprehensively examining these factors together remains scarce. Using a large youth sample, we present the first model that simultaneously examines multimodal factors related to PLEs. As a secondary aim, we evaluate the model’s ability to explain psychosis in an external validation cohort that included individuals experiencing psychosis.

After applying variable selection including generalized estimating equations, correlation filtering, Least Absolute Shrinkage and Selection Operator model to 741 variables (i.e., environmental factors, cognitive appraisals, clinical variables, cognitive functioning, and structural brain connectome measures), obtained PLEs predictors (N = 27) and covariates (i.e., age, sex, IQ) were included in the classification model based on Elastic Net algorithm for predicting high/low PLEs in 396 healthy participants aged 14–24 (Mage = 19.72 ± 2.5). We externally validated PLE-related predictors in a clinical sample comprising first-episode psychosis patients (n = 19), their siblings (n = 20), and healthy controls (n = 19).

Eleven factors, including environmental and cognitive appraisals, along with 16 structural network properties spanning frontal, temporal, occipital, and parietal regions, were identified as important predictors of PLEs. The model’s performance was moderate in predicting low versus high PLEs (accuracy = 75%, AUC = 0.750). Specificity was high (84.2%) in distinguishing siblings from patients.

Multimodal features, including environmental burden, cognitive schemas, and brain network alterations, predict PLEs and partially generalize to clinical psychosis. These variables may reflect intermediate phenotypes across the psychosis spectrum, offering insights into both vulnerability and resilience.

Anhedonia and depression symptoms have been linked to potential deficits in reward learning. However, how anhedonia impacts the ability to adjust and learn about the effort required to obtain rewards remains unclear.

We examined young people (N = 155, 16–25 years) with a range of depression and anhedonia symptoms using a probabilistic instrumental reward and effort learning task. Participants were asked to learn which options to choose to maximize reward or minimize effort for reward. We compared the exerted effort (button pressing speed) for high (puppy images) vs low (dog images) rewards and collected subjective reports of “liking,” “wanting,” and “willingness to exert effort.” Computational models were fit to the learning data and estimated parameter values were correlated with depression and anhedonia symptoms.

As depression symptoms and consummatory anhedonia increased, reward liking decreased, and as anticipatory anhedonia increased, liking, wanting, and willingness to exert effort for reward decreased.

Participants exerted more effort for high rewards than for low rewards, but anticipatory anhedonia diminished this difference.

Higher consummatory anhedonia was associated with poorer reward and effort learning, and with increased temperature parameter values for both learning types, indicating a higher tendency to make exploratory choices. Higher depression symptoms were associated with lower reward learning accuracy.

We provide novel evidence that anhedonia is associated with difficulties in modulating effort as a function of reward value and with the underexploitation of low effort and high reward options. We suggest that addressing these impairments could be a novel target for intervention in anhedonic young people.

Childbirth-related post-traumatic stress disorder (CB-PTSD) is an underrecognized condition with consequences for mothers and infants. This study aimed to determine risk factors for CB-PTSD symptoms across countries within a stress–diathesis framework, focusing on antenatal, birth-related, and postpartum predictors.

The INTERSECT cross-sectional survey (April 2021–January 2024) included 11,302 women at 6–12 weeks postpartum. The study was carried out across maternity services in 31 countries. Outcomes were CB-PTSD diagnosis, symptom severity, and perceived traumatic birth, assessed with the City Birth Trauma Scale. Multiple risk factors were assessed, including preexisting vulnerability, pregnancy, birth, and infant-related factors. All models were adjusted for country-level variation as a random effect.

Models explained substantial variance across all outcomes (conditional R2 = 0.53–0.58). Negative birth experience was the strongest predictor (e.g. odds ratio [OR] = 0.82, 95% confidence interval [CI] = 0.80–0.84 for diagnosis). Ongoing maternal complications predicted both CB-PTSD diagnosis and symptoms (e.g. OR = 1.61, 95% CI = 1.41–1.84), and major infant complications were associated with CB-PTSD diagnosis (OR = 1.63, 95% CI = 1.29–2.07). Reports of perceived danger to self or infant (criterion A) were linked to higher CB-PTSD symptoms and traumatic birth ratings (e.g., β =0.25, 95% CI = 0.21–0.29). Other predictors reached significance but showed small effects.

Findings support a stress–diathesis framework, showing that while pre-existing vulnerabilities contribute, birth-related stressors exert the strongest influence. Trauma-informed maternity care should prioritize these factors, with attention to women’s appraisals of birth.

Mitochondrial dysfunction has been implicated in the pathogenesis of major depressive disorder (MDD); however, the causal contributions of specific mitochondrial genes across regulatory layers remain unclear.

We integrated genome-wide association study summary statistics from the Psychiatric Genomics Consortium and FinnGen with quantitative-trait-locus (QTL) datasets for DNA methylation, gene expression (eQTL), and protein abundance. Mitochondrial genes were annotated using the MitoCarta3.0 database. Summary-based Mendelian randomization and Bayesian colocalization were applied to assess causal relationships, with colocalization determined by the posterior probability of a shared causal variant (PPH4), and the false discovery rate used for multiple-testing correction. Brain-specific effects were evaluated using Genotype-Tissue Expression eQTL data. Prioritized genes were ranked based on cross-omics consistency and replication evidence.

Five mitochondrial genes were prioritized. TDRKH showed consistent associations across methylation, transcription, and protein levels, with hypermethylation at cg24503712 linked to reduced expression and a lower risk of MDD (Tier 1). METAP1D (Tier 2) demonstrated protective effects at both the transcript and protein levels. LONP1, FIS1, and SCP2 (Tier 3) exhibited consistent but complex regulatory patterns. Several signals were replicated in brain tissues, including TDRKH in the caudate and METAP1D in the cortex.

This study provides multi-omics evidence for the causal involvement of mitochondrial genes in MDD. TDRKH and METAP1D emerged as key candidates, offering promising targets for future mechanistic research and therapeutic development.

Sexual minorities have continuously been found to experience poorer mental health compared to the general population, despite promising changes in attitudes and legislation throughout the 21st century in many Western countries. The present study is one of the first to assess group-level changes over time in mental health among sexual minorities compared to their heterosexual counterparts.

We used four waves of a Finnish population-based survey spanning 16 years (2006–2022) to compare heterosexual and sexual minority adults on depression and anxiety symptoms, alcohol use, and sexual distress.

Sexual minority individuals reported more depression and anxiety symptoms, sexual distress, and alcohol use relative to their heterosexual counterparts at all time points. There were no group differences in the direction or rate of change in group means from 2006 to 2022. Depression and anxiety symptoms showed equally large increases, and alcohol use showed equally large decreases among both heterosexual and sexual minority participants.

Contrary to our expectations based on minority stress theory, differences in mental health between sexual minority and heterosexual individuals persist despite changes in the sociolegal status of sexual minorities during the first two decades of the 21st century. Our findings align with the increasing general trend in anxiety and depression symptoms, which seems to affect the whole population regardless of sexual orientation. We conclude that the effect of legislative societal improvements seems to be small, and the mental health gap between sexual minority and heterosexual adults is likely maintained by factors not included in our study.

Major depressive episodes (MDEs) are highly recurrent in clinical samples. However, the course of MDEs and predictors of their endurance are unclear in the general youth population.

We investigated prospective factors associated with enduring MDE (the presence of 12-month DSM-IV MDE at baseline and 1 year using the Composite International Diagnostic Interview–Screening Scales) in 1,833 participants of a 1-year epidemiological youth cohort study in Hong Kong. Multivariable logistic regression models were used to examine the influences of a range of personal and environmental factors.

At baseline, 13.7% participants had MDEs, among whom 21.1% presented enduring MDEs. More severe symptoms of post-traumatic stress disorder (adjusted odds ratio [aOR] = 5.54, confidence interval [CI] = 2.14–14.38), depression (aOR = 3.92, CI = 1.79–8.62), and generalized anxiety (aOR = 2.27, CI = 1.21–4.25) at baseline were among the strongest associated factors for enduring MDE, with trends of associations observed for psychotic-like experiences (aOR = 1.98, CI = 0.98–4.02) and eating disorder symptoms (aOR = 1.88, CI = 0.90–3.95). Among various types of stressors, only dependent stressors at follow-up showed a clear association with enduring MDE (aOR = 4.22, CI = 1.81–9.83). Those with enduring MDE showed poorer functioning and mental health-related quality of life at follow-up, with only 35.6% having sought any psychiatric/psychological help during the past year.

Detecting comorbid symptoms in those with prior MDEs and reducing the impact of dependent stressors may help reduce their long-term implications. Enhancing the accessibility and acceptability of youth-targeted mental health services would also be crucial to improve help-seeking.

How psychotic symptoms, depressive symptoms, cognitive deficits, and functional impairment may interact with one another in schizophrenia or bipolar disorder is unclear.

This study explored these interactions in a discovery sample of 339 Chinese, of whom 146 had first-episode schizophrenia and 193 had bipolar disorder. Psychotic symptoms were assessed using the Positive and Negative Symptom Scale; depressive symptoms, using the Hamilton Depression Rating Scale; cognitive deficits, using tests of processing speed, executive function, and logical memory; and functional impairment, using clinical assessments. Network models connecting the four types of variables were developed and compared between men and women and between disorders. Potential causal relationships among the variables were explored through directed acyclic graphing. The results in the discovery sample were compared to those obtained for a validation sample of 235 Chinese, of whom 138 had chronic schizophrenia and 97 had bipolar disorder.

In the discovery and validation cohorts, schizophrenia and bipolar disorder showed similar networks of associations, in which the central hubs included ‘disorganized’ symptoms, depressive symptoms, and deficits in processing speed during the digital symbol substitution test. Directed acyclic graphing suggested that disorganized symptoms were upstream drivers of cognitive impairment and functional decline, while core depressive symptoms (e.g. low mood) drove somatic and anxiety symptoms.

Our study advocates for transdiagnostic, network-informed strategies prioritizing the mitigation of disorganization and depressive symptoms to disrupt symptom cascades and improve functional outcomes in schizophrenia and bipolar disorder.

Depression rates are higher in women, especially during periods of hormonal fluctuation. Reproductive system disorders (RSDs), which often disrupt hormonal balance, may contribute to this mental health burden. Despite their prevalence and significant health implications, the link between RSDs and depression remains underexplored, leaving a gap in understanding these women’s mental health risks.

Using Danish nationwide health registers (2005–2018), we conducted a cohort study of 2,295,824 women aged 15–49, examining depression outcomes in 265,891 women diagnosed with 24 RSDs, including endometriosis, polycystic ovary syndrome, and pain-related diagnoses. For each RSD, age-matched controls were selected. We calculated incidence rates, incidence rate ratios, and prevalence proportions of depression diagnoses or antidepressant use around RSD diagnosis.

Across all RSD subtypes, women demonstrated higher rates of depression both before and after diagnosis, with a peak within the year following diagnosis. Incidence rate ratios within 1 year of RSD diagnosis ranged from 1.15 (95% confidence interval [CI] 1.06–1.25) to 2.09 (95% CI 1.98–2.21), depending on RSD subtype. Elevated depression prevalence was observed 3 years before diagnosis, suggesting mental health impacts may have preceded clinical RSD identification.

This study reveals a striking association between RSDs and depression. Women with RSDs are more likely to suffer from depression, before and after RSD diagnosis, highlighting the need for integrated mental health screening and intervention. With over 10% of women affected by RSDs, addressing this overlooked mental health burden is imperative for improving well-being in a significant portion of the population.

Individuals with first-episode psychosis (FEP) face markedly increased excess mortality, yet the long-term trends and key contributing factors remain insufficiently characterized. This study aimed to examine long-term mortality patterns, standardized mortality ratios (SMRs), and associated factors in a FEP cohort.

This population-based cohort study included 1,389 individuals diagnosed with FEP, followed for up to 25 years. Mortality outcomes were obtained from Hong Kong’s centralized hospital database (CMS) and coroner’s court reports, with SMRs calculated. Baseline sociodemographic and clinical, as well as long-term treatment-related factors of all-cause, natural, and unnatural mortality were analyzed.

Among 1,389 participants, 137 deaths (9.86%) occurred during the follow-up period with the overall SMR of 6.56 (95% CI, 5.50–7.71). The cumulative incidence rate of unnatural mortality increased sharply over the first 10 years and that of the natural cause of death started to increase after the first decade of the illness. Male gender and poorer social functioning were associated with increased all-cause mortality risk, while male gender, lower education, and baseline hospitalization raised unnatural mortality risk. Greater monthly antipsychotic variability during the first 10 years increased all-cause mortality risk in the period after the initial 10 years.

This 25-year follow-up study of FEP highlighted the changes in the long-term mortality pattern of FEP and thus the phase-specific needs of individuals with FEP. Therefore, it is important to integrate physical care into mental health services, as well as stage-specific and individualized care for patients with psychotic disorders to reduce long-term excess mortality.

Recovery rates for panic disorder in NHS Talking Therapies (NHSTT) services in the United Kingdom do not match those in randomized trials. Previous research has found that training therapists in ‘focused cognitive behavioral therapy’ (CBT) improves outcomes. The primary aim was to examine whether focused CBT delivered by trained psychological well-being practitioners (PWPs) can improve treatment outcomes for panic disorder. An exploratory aim was to evaluate the potential impact of a novel component of focused CBT, which includes the use of ‘approach-supporting behaviors’ (ASBs) where safety-seeking behaviors (SSBs) are prominent.

We conducted a randomized parallel trial. Participants were randomly allocated to focused CBT or the current treatment at ‘Step Two’ (treatment as usual) in two NHSTT services (ISRCTN:11268881).

We found a significant group-timepoint interaction. Those in focused CBT had significantly greater reductions in the primary measure of panic severity relative to those in treatment as usual (TAU). The level of ASBs did not predict a change in panic severity; however, the level of SSBs at the end of treatment did predict a change in panic severity.

Focused CBT is effective for panic disorder and is superior to TAU, supporting the applicability of this lower-intensity and panic-specific version of CBT for panic disorder.

Ecological momentary assessment (EMA) is increasingly recognized as a vital tool for tracking the fluctuating nature of mental states and symptoms in psychiatric research. However, determining the optimal sampling rate – that is, deciding how often participants should be queried to report their symptoms – remains a significant challenge. To address this issue, our study utilizes the Nyquist–Shannon theorem from signal processing, which establishes that any sampling rate more than twice the highest frequency component of a signal is adequate.

We applied the Nyquist–Shannon theorem to analyze two EMA datasets on depressive symptoms, encompassing a combined total of 35,452 data points collected over periods ranging from 30 to 90 days per individual.

Our analysis of both datasets suggests that the most effective sampling strategy involves measurements at least every other week. We find that measurements at higher frequencies provide valuable and consistent information across both datasets, with significant peaks at weekly and daily intervals.

Ideal frequency for measurements remains largely consistent, regardless of the specific symptoms used to estimate depression severity. For conditions in which abrupt or transient symptom dynamics are expected, such as during treatment, more frequent data collection is recommended. However, for regular monitoring, weekly assessments of depressive symptoms may be sufficient. We discuss the implications of our findings for EMA study optimization, address our study’s limitations, and outline directions for future research.

As populations age rapidly, understanding the psychological benefits of sustained employment has become increasingly important. In South Korea, where the suicide rate among older adults is one of the highest among Organisation for Economic Co-operation and Development (OECD) countries, identifying modifiable social determinants, such as employment, may inform effective prevention strategies.

This retrospective cohort study used data from the Korean Welfare Panel Study (2009–2024), a nationally representative longitudinal survey. Individuals with depressive symptoms or suicidal ideation at baseline were excluded. The main exposure was participation in a government-led senior employment program. We employed discrete-time survival analysis using a generalized linear model with a complementary log–log link function, which appropriately handled the interval-censored structure of the panel data.

Older adults who participated in the employment program had a significantly lower risk of developing depressive symptoms (adjusted hazard ratio [HR] = 0.76, 95% confidence interval [CI]: 0.67–0.86) and suicidal ideation (adjusted HR = 0.60, 95% CI: 0.45–0.81) compared to those who did not participate. Subgroup analyses revealed that the strength of the association was particularly strong among individuals aged ≥80 years, those with chronic illness, poor self-rated health, and those who were previously or never married.

Structured government-supported employment may mitigate the risk of depressive symptoms and suicidal ideation in later life. These findings support the potential of senior employment programs as effective mental health promotion and suicide prevention strategies for aging populations.

Shared genetic risk has been shown across psychiatric disorders. In particular, anorexia nervosa (AN), obsessive-compulsive disorder (OCD), and schizophrenia (SCZ) show shared genetic risk that matches clinical evidence of shared illness and cognitive phenotypes. Given this evidence, we leveraged a large US-based population-based study to determine genetic associations of disorder-specific and shared psychiatric, cognitive, and brain markers and explore whether the latter might be state versus trait markers in eating disorders.

We used data from the population-based Philadelphia Neurodevelopmental Cohort (N = 4,729) and conducted sex-stratified analyses to test for associations between genetic risk for three disorders (AN, OCD, and SCZ) and mental health phenotypes, neurocognitive traits, and cortical features in a non-clinical population. Exploratory analyses on cortical features were run on a subset with neuroimaging data (N = 626).

Genetic risk for AN was significantly associated with body image distortion (pFDR = 0.02), and body image distortion was significantly related to a reduction in grey matter volume (pFDR = 0.05).

Genetic risk for AN associates with AN trait in a non-clinical sample of youth, particularly in females. Whilst genetic risk was not associated with cognitive or cortical markers, the AN phenotype was associated with cortical markers.