Substantial evidence confirms a linear relationship between low-density lipoprotein and depression. However, findings on the association of abnormal high-density lipoprotein cholesterol (HDLc) with depression are inconclusive, with both low and high levels of HDLc implicated in severe symptoms and suicidality. Additionally, gender differences in this association remain underexplored.

This study evaluated the association between abnormal serum HDLc and depressive symptom severity and investigated whether the association varied by gender in a sample of multi-ethnic adults in Singapore.

Descriptive and multivariable analyses were conducted on data collected from participants of a longitudinal cohort - The PREDICT study. Participants were aged 18-75 years, of Chinese, Malay, or Indian ethnicity, with major depressive disorder (MDD) or general population without any psychiatric diagnosis. The primary outcome was depressive symptom score assessed with the Patient Health Questionnaire (PHQ)-9. Its association with abnormal serum HDLc levels (categorised into ordinal variable for abnormal low (AL), normal (N), and abnormal high (AH) HDL) and gender differences were investigated after adjusting for age, race, and known confounders of lipid abnormality (body mass index, mental health treatment, and history of chronic conditions).

The study sample comprised 212 participants with a mean age of 38.1 (SD 13) years. In all, 59.4% were women, 76.9% were Chinese, and 51.4% were diagnosed with MDD. Total PHQ-9 score ranged from 1- 34, with a mean score of 7.8 (SD 7); 19.8% met criteria for moderately severe to severe depression. The prevalence of abnormal HDLc was 58% with AL-HDLc and AH-HDLc observed in 11.8% and 46.2% of the sample, respectively. Compared to persons with N-HDLc, AL-HDLc was significantly and directly associated with symptom severity (β = 4.4, 95% CI:1.2 to 7.7, p = 0.008), while an inverse association was observed with AH-HDLc (β = −2.6, 95% CI:‒4.7 to −0.5, p = 0.015). The significant direct association between AL-HDLc and symptom severity was observed only among men, whereas AH-HDLc showed a significant inverse relationship only in women. The association between AL-HDLc remained significant after adjusting for confounders in the overall sample and among men.

Study results indicate that low HDLc is linked to more severe depressive symptoms, whereas high levels of HDLc have an inverse relationship. The latter contrasts with emerging literature on adverse outcomes of depression associated with high HDLc. Gender differences exist in these associations, which need to be investigated further and replicated in a larger sample. Nevertheless, these preliminary findings underscore the importance of maintaining healthy HDLc levels, which may lower morbidity in depressive disorders.

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Gambling disorder (GD) poses severe impacts on both individuals and society. Impairment in risky decision-making is a key behavioral characteristic of GD, but the underlying cognitive processes of these deficits remain unclear.

This study decomposed the risky decision-making processes of GD with cognitive computational modeling.

A total of 100 participants with GD and 59 healthy controls (HCs) were recruited to complete psychometric assessments and the Balloon Analog Risk Task. Since GD involved abnormal loss evaluation in decision-making, we developed a novel cognitive model incorporating diminishing loss sensitivity and revealed the processes underlying the risk-taking behaviors with hierarchical Bayesian analysis.

GD participants exhibited stronger loss aversion (p < 0.001) but faster-diminishing loss sensitivity (p < 0.001), regardless of severity, which drove the deficits in the overall performance of risky decision-making (p < 0.001) (Fig1). Overconfident prior belief (p = 0.002) and higher updating rate (p < 0.001) were observed among participants with GD (Fig3). Diminishing loss sensitivity was negatively correlated with impulsivity (p = 0.021), and loss aversion was negatively related to craving for gambling (p = 0.027) (Fig4).Table 1.

Demographic and clinical characteristics of participants

This research provides novel perspectives on the cognitive processes underlying the risky decision-making of GD patients, highlighting the role of diminishing loss sensitivity during loss evaluation and its clinical implications, which inspires future research on assessment and psychotherapy for GD.

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Treatment-resistant depression (TRD) presents a significant clinical challenge that demands innovative and rapid therapeutic approaches. Repetitive transcranial magnetic stimulation (rTMS), particularly its accelerated variant utilizing intermittent theta burst stimulation (aiTBS), has shown promising capacity to generate swift improvements in depressive symptomatology. Despite demonstrated effectiveness, substantial interindividual variability in treatment response persists.

The present investigation examined whether personality characteristics, measured via the Temperament and Character Inventory (TCI), could predict clinical outcomes in patients undergoing aiTBS protocols.

Individual participant data were aggregated from two randomized, sham-controlled aiTBS trials. Participants completed a two-week medication washout period before undergoing either active or sham aiTBS targeting the left dorsolateral prefrontal cortex across four consecutive days. Depression severity was quantified using the 17-item Hamilton Depression Rating Scale at baseline and one-week follow-up. Personality traits were assessed at baseline using the TCI questionnaire. Robust linear mixed-effects modeling was employed to evaluate associations between baseline TCI dimensions and symptomatic improvement trajectories.

The combined sample was of 104 individuals diagnosed with TRD (50 receiving active stimulation, 54 receiving sham). Findings revealed that elevated Novelty Seeking scores significantly moderated the rate of depressive symptom reduction across the treatment period (β = -1.70, SE = 0.73, p = 0.021). Notably, this accelerated therapeutic response manifested independently of whether participants received active or sham stimulation. Additionally, higher Novelty Seeking was associated with greater baseline depression severity (β = 2.91, SE = 1.00, p = 0.004). No additional TCI dimensions demonstrated significant predictive utility for clinical outcomes.

These findings highlight that temperamental characteristics, specifically Novelty Seeking, may influence the rate of symptom improvement in accelerated neuromodulation protocols, irrespective of active mechanism engagement. This phenomenon could involve dopaminergic sensitivity potentiated by intensive therapeutic contexts. Incorporating personality assessment into clinical neuromodulation frameworks may help identify TRD patients predisposed to demonstrate more rapid symptomatic improvement. Validation in larger, multi-site cohorts with extended longitudinal assessment is essential to establish whether sustained remission occurs and to verify the generalizability of these findings.

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Irritability is a common and impairing transdiagnostic symptom across multiple psychiatric disorders in children and adolescents, including ADHD, generalized anxiety disorder, and depression. It is often manifested as a stable, trait-like phenotype that significantly impacts daily functioning and long-term outcomes. Despite its clinical relevance, the underlying neural mechanisms—particularly those that generalize across diagnostic categories—remain poorly understood.

This study aimed to identify transdiagnostic neural markers of irritability in a large developmental sample using resting-state functional connectivity. Specifically, we sought to determine whether functional network connectivity patterns could predict irritability severity and to validate their generalizability across both internal subsamples and an external clinical cohort.

We analyzed resting-state fMRI data from 1143 children and adolescents (age = 11.65 ± 3.47 years) from the Healthy Brain Network project, encompassing diagnoses such as ADHD, depression, anxiety, and autism spectrum disorder. Irritability was measured using the Affective Reactivity Index. Connectome-based predictive modeling (CPM) was employed to identify functional networks associated with irritability. Internal validation was conducted using two random subsamples and an alternative brain atlas. Furthermore, an support vector machine (SVM) classifier was applied to an independent depression cohort (n = 129) to externally validate the robustness of the identified networks.

The positive predictive network for irritability primarily featured connections between the fronto-parietal network and other networks, whereas the negative network involved connections between the basal ganglia network and other networks. Internal validations confirmed that both the fronto-parietal network and the basal ganglia network consistently predicted irritability. External validation in the depression cohort further supported the role of these networks in irritability, successfully differentiating between high- and low-anger groups using SVM classification.

Our findings underscore the central roles of the fronto-parietal network—implicated in cognitive control—and the basal ganglia network—associated with motivational and emotional processes—in pediatric irritability across diagnostic boundaries. These networks may reflect a developmental imbalance between top-down regulation and bottom-up emotional responding, offering potential neural targets for early intervention and transdiagnostic treatment strategies.

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Southeast Asia is home to intra- and inter-regional migrant workers (MWs), with the Asia–Pacific region hosting approximately 14.2% of them—around 24 million individuals, with many engaging in low-wage, labour-intensive, and often precarious employment. Migrant workers (MWs) and migrant domestic workers (MDWs) in Asia are at heightened risk of mental health problems due to long working hours, abuse, and family separation. In Singapore, despite existing support systems, formal help-seeking for mental health conditions remains limited.

The aims of the current study were to understand the mental health help-seeking behaviors among MWs and MDWs in Singapore using a mixed methods approach. The study quantitatively explored the workers’ awareness of organisations or agencies that they could seek help from; the people, agencies or organisations that they had sought help from; and the ways in which they would like information on mental health to be conveyed to them. A deeper understanding of their perceived barriers and facilitators to accessing care and the ways in which they had sought help for their emotional problems were qualitatively examined through focus group discussions (FGDs).

A mixed-methods design was employed. Phase 1 was a quantitative survey involving 1,465 MWs and 1,462 MDWs from the six largest nationality groups in Singapore. Phase 2 comprised 14 focus group discussions with 48 MWs and 52 MDWs to explore their experiences in depth.

Most MWs (79.2%) and MDWs (91.4%) reported seeking help for emotional difficulties, mainly from informal sources such as family and friends. Awareness of formal services, including the Ministry of Manpower (MOM), was moderate (58.4% of MWs; 66.8% of MDWs). Both groups preferred face-to-face workshops for receiving mental health information. Help-seeking preferences diverged: 48.1% of MWs favored trained professionals, while 51.5% of MDWs preferred trained peers. Qualitative findings highlighted key barriers to be fear of job loss, financial constraints, limited awareness, and stigma, while facilitators included supportive family and friends, and positive, culturally sensitive healthcare encounters.

Although many migrant workers seek support for emotional distress, reliance on informal networks persists due to structural and cultural barriers to formal care. Integrated support models incorporating peer-led approaches, culturally and linguistically competent services, and clearer communication about accessible resources are needed to strengthen mental health support for this population.

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Non-suicidal self-injury (NSSI) is a common high-risk behavior in adolescents and it occurs in various psychiatric disorders, especially major depressive disorder (MDD). It remains largely unknown whether and which brain functional networks contribute to NSSI across youth psychiatric disorders.

This study aimed to identify common brain functional networks associated with NSSI across youth psychiatric disorders, and to examine their relationships with NSSI behavior, addiction, and its functions. Furthermore, we sought to validate the generalizability of these neural correlates in independent clinical cohorts.

This study analyzed functional brain imaging data acquired from 156 adolescents (MDD+NSSI group, n = 44, age = 15.32 ± 1.51; MDD-NSSI group, n = 32, age = 15.36 ± 1.96; healthy controls, n = 80, age = 15.92 ± 2.72). NSSI behavior, addiction and its four NSSI functions (internal and external emotion regulation, social influence and sensation seeking) were assessed using the Ottawa Self-injury Inventory. Using support vector machine recursive feature elimination classification and regression models, we investigated the brain functional networks that predicted NSSI. External validations were performed in an ADHD cohort (n = 40) and a transdiagnostic cohort (n = 40).

The brain networks related to NSSI behavior were mainly composed of inter-network connections between the fronto-parietal, motor, limbic, basal ganglia networks. These networks were also associated with NSSI addiction and its four functions. Notably, the fronto-parietal network was involved in all NSSI components. External validations in both the ADHD and the transdiagnostic cohorts validated the associations of these functional networks with NSSI severity.

Our results demonstrate roles of the fronto-parietal, motor, limbic and basal ganglia networks in NSSI across youth psychiatric disorders, which may serve as neural markers and potential targets for prevention and intervention.

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Depression is a major contributor to global disability, with profound personal, social, and economic costs. In Singapore, while cross-sectional studies have provided valuable insights into the prevalence of depression, data on the long-term trajectory, outcomes, and determinants of depression remain scarce.

This protocol describes the PREDICT study, which seeks to address this gap by launching the nation’s first longitudinal cohort dedicated to major depressive disorder (MDD) and subsyndromal depression (SD). The objectives include examining disease prognosis, relapse, comorbidity, suicidality, treatment response, healthcare utilization, and mortality, identifying biopsychosocial determinants, quantifying economic burden, and understanding progression from SD to MDD.

The study will recruit 3,201 participants aged 18–75 years, including those with first-episode depression, those with a longer history of depression, individuals with SD, and matched controls without psychiatric illness. Recruitment will be conducted at primary and tertiary care settings as well as from population cohorts. Participants will undergo comprehensive baseline and annual follow-up assessments for up to five years, capturing socio-demographic, psychosocial, physical, and biological data.

We hypothesize that sociocultural factors, such as accessible mental healthcare, social support, strong intergenerational relationships may confer protective effects leading to better outcomes compared with international cohorts, and that individuals with SD will incur higher resource use, poorer quality of life, and increased risk of progression to major depressive disorder as compared to controls.

Findings will provide the first comprehensive longitudinal evidence on depression trajectories in Singapore. Results will guide clinical protocols, inform national mental health strategies (including Singapore’s Healthier SG initiative), and strengthen early detection and management of depression at the population level.

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People with schizophrenia have poorer physical health than the general population due to poor diet, lack of physical activities, and high rates of obesity. This population has been reported to have lower quality of life across physical, psychological, and social health. Furthermore, these patients have a higher prevalence of smoking and lower quit rates when compared to general populations. Although smoking increases the risk of cardiovascular events, which are associated with an increased risk of premature death, limited research has compared cardiovascular risk and quality of life across different smoking statuses.

This study aimed to determine demographic and clinical differences in schizophrenia patients, including cardiovascular risks and health-related quality of life, by smoking status.

Baseline data were extracted from a longitudinal study. The primary objective of the study was to investigate the effects of different smoking cessation therapies using fMRI. Between 2022-2024, participants were recruited from local ICCMW centers and psychiatric outpatient clinics in Hong Kong. All participants were patients diagnosed with schizophrenia for more than one year and stable on medication. Smokers were required to agree to quit smoking and not have other substance use disorders. Participants were divided into two groups based on smoking status: never smokers and ever smokers (current and former). Information about cardiovascular risks (including BMI, body fat percentage, blood pressure, blood oxygen saturation, carbon monoxide level, clinical history) was collected. The EQ-5D5L was used to measure quality of life. To identify possible predictors for non-participation, a multivariate regression model was used.

There are 55 never smokers (57.9%) and 40 ever smokers (42.1%) included in the study (N = 95). Significant demographic difference was found in gender (p = 0.022), marital status (p = 0.020), education attainment (p = 0.002), and type of housing (p = 0.002). In terms of clinical differences, BMI and CO level were significantly different between the two groups, with p = 0.022 and p = 0.002 respectively. No significant correlation was found for other indicators, including body fat percentage, systolic blood pressure, diastolic blood pressure, blood oxygen saturation, history of high cholesterol, hypertension, diabetes, and quality of life. After regression analysis in participants and non-participants, the adjusted odds ratios for education level, employment status, and type of housing were 1.63 [95% CI: 0.747-3.559], 2904617146.5 [0], and 0.377 [0.178-0.802] respectively.

The results show that ever-smoking individuals with schizophrenia may have higher cardiovascular risks in some areas. These results should be interpreted with caution due to sampling and self-reporting biases.

None Declared