An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression

Bidirectional relationship between afternoon naps and depressive symptoms in Chinese middle-aged and older adults: Evidence from a nationally representative cohort study

BACKGROUND

Limited studies have investigated the association between depressive symptoms and napping habits. In this study, nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS) were employed to conduct cross-sectional and longitudinal analyses to investigate their associations among Chinese middle-aged and older adults.

METHODS

The study included 12,208 participants from the 2015 CHARLS. Depressive symptoms were measured using the Depression Scale. Napping duration was categorized into four groups: no napping (0 min), short (<30 min), moderate (30-89 min), and prolonged (≥90 min). Logistic regression analysis was used to assess bidirectional relationships, and dose-response patterns were analyzed via restricted cubic splines (RCS).

RESULTS

A total of 2487 participants (32.0 %) developed new-onset depressive symptoms, and moderate napping group exhibited the lowest incidence rate. Statistical analysis revealed that moderate napping was a protective factor for the depressive symptoms (OR, 95 % CI, 0.689, 0.567-0.843). A total of 1742 participants (42.3 %) newly experienced poor napping, and the incidence of poor napping gradually rose by the increase of the CES-D-10 score quartiles. Moreover, depressive symptoms were also found to be a risk factor for poor napping (OR, 95 % CI, 1.149, 1.004-1.314). The RCS model revealed that there was an approximately U-shaped association between nap duration and depressive symptoms, and there was a negative linear association between CES-D-10 scores and nap duration.

LIMITATION

The observational design limits ruling out unobserved confounding factors.

CONCLUSION

There was a significant bidirectional relationship and a dose-response association between napping and depressive symptoms in middle-aged and older adults.

The LvL UP trial: Protocol for a sequential, multiple assignment, randomised controlled trial to assess the effectiveness of a blended mobile lifestyle intervention

BACKGROUND

Blended mobile health (mHealth) interventions - combining self-guided and human support components - could play a major role in preventing non-communicable diseases (NCDs) and common mental disorders (CMDs). This protocol describes a sequential, multiple assignment, randomised trial aimed at (i) evaluating the effectiveness and cost-effectiveness of LvL UP, an mHealth lifestyle intervention for the prevention of NCDs and CMDs, and (ii) establishing the optimal blended approach in LvL UP that balances effective personalised lifestyle support with scalability.

METHODS

LvL UP is a 6-month mHealth holistic intervention targeting physical activity, diet, and emotional regulation. In this trial, young and middle-aged Singaporean adults at risk of developing NCDs or CMDs will be randomly allocated to one of two initial conditions ('LvL UP' or 'comparison'). After 4 weeks, participants categorised as non-responders from the LvL UP group will be re-randomised into second-stage conditions: (i) continuing with the initial intervention (LvL UP) or (ii) additional motivational interviewing (MI) support sessions by trained health coaches (LvL UP + adaptive MI). The primary outcome is mental well-being. Secondary outcomes include anthropometric measurements, resting blood pressure, blood metabolic profile, health status, and health behaviours (physical activity, diet). Outcomes will be measured at baseline, 6 months (post-intervention), and 12 months (follow-up).

DISCUSSION

In addition to evaluating the effectiveness of LvL UP, the proposed study design will contribute to increasing evidence on how to introduce human support in mHealth interventions to maximise their effectiveness while remaining scalable.

TRIAL REGISTRATION

The LvL UP Pilot trial was prospectively registered with ClinicalTrials.gov (NCT06360029).

Embracing complexity in psychiatry-from reductionistic to systems approaches

The understanding and treatment of psychiatric disorders present unique challenges due to these conditions' multifaceted nature, comprising dynamic interactions between biological, psychological, social, and environmental factors. Traditional reductionistic approaches often simplify these conditions into linear cause-and-effect relationships, overlooking the complexity and interconnectedness inherent in psychiatric disorders. Advances in complex systems approaches provide a comprehensive framework to capture and quantify the non-linear and emergent properties of psychiatric disorders. This Personal View emphasises the importance of identifying rules for generative models that govern brain and behaviour over time, which might contribute to personalised assessments and interventions for psychiatric disorders. For instance, mood fluctuations in bipolar disorder can be understood through dynamical systems modelling, which identifies modifiable parameters, such as circadian disruption, that can be addressed through targeted therapies such as light therapy. Similarly, recognition of depression as an emergent property arising from complex interactions highlights the need for integrated treatment strategies that enhance adaptive reactions in the individual. A framework for quantifying multilevel interactions and network dynamics can help researchers and clinicians to understand the interplay between neural circuits, behaviours, and social contexts. Probabilistic models and self-organisation concepts contribute to building concrete dynamical systems models of mental disorders, facilitating early identification of risk states and promoting resilience through adaptive interventions delivered with optimal timing. Embracing these complex systems approaches in psychiatry could capture the true nature of psychiatric disorders as properties of a dynamic complex system and not the manifestation of any lesion or insult. This line of thinking might improve diagnosis and treatment, offering new hope for individuals affected by psychiatric conditions and paving the way for more effective, personalised mental health care.

Advancing Mental Health Research Through Strategic Integration of Transdiagnostic Dimensions and Genomics

Genome-wide studies are yielding a growing catalog of common and rare variants that confer risk for psychopathology. However, despite representing unprecedented progress, emerging data also indicate that the full promise of psychiatric genetics-including understanding pathophysiology and improving personalized care-will not be fully realized by targeting traditional dichotomous diagnostic categories. The current article provides reflections on themes that emerged from a 2021 National Institute of Mental Health-sponsored conference convened to address strategies for the evolving field of psychiatric genetics. As anticipated by the National Institute of Mental Health's Research Domain Criteria framework, multilevel investigations of dimensional and transdiagnostic phenotypes, particularly when integrated with biobanks and big data, will be critical to advancing knowledge. The path forward will also require more diverse representation in source studies. Additionally, progress will be catalyzed by a range of converging approaches, including capitalizing on computational methods, pursuing biological insights, working within a developmental framework, and engaging health care systems and patient communities.

Exploring the Role of Language in Spiritual Health Consultations: Insights From an Ecological Model of Recovery on Depression and Anxiety

OBJECTIVE

Consultations conducted by spiritual health clinicians (SHC; also known as healthcare chaplains) offer a unique context for patients to express themselves and are associated with reduced stress and enhanced satisfaction. The language used during these consults may provide insights into emotions and recovery trajectories. This study aimed to characterize patient language in spiritual health consults and examine its relationship to mental health outcomes, evaluated within the Ecological Model of Recovery (EMR) framework.

METHODS

SHCs conducted consultations with 212 patients in five acute-care hospitals in the urban south. Pre-consult distress and post-consult anxiety and depression were measured. Consults were audio recorded, transcribed, and analyzed using Linguistic Inquiry and Word Count (LIWC-22). Linguistic indicators of emotion and EMR-related variables were examined. Spearman's rank-order correlation and Mann-Whitney U tests assessed the relationship between patient language and mental health outcomes.

RESULTS

Language reflecting confidence and discussions about lifestyle and religious topics were associated with lower post-consult anxiety and depression, highlighting the importance of positive self-perception and structured, meaningful activities in recovery. Language related to social connections was negatively associated with depression, while language indicative of differentiation or conflict correlated with higher depression levels.

CONCLUSION

This study underscores the relationship between patient language during spiritual health consultations and mental health outcomes, emphasizing the therapeutic value of expressive communication. Verbal expression plays a crucial role in emotional recovery, as linguistic patterns in healthcare settings can reflect and influence psychological well-being. Prospective research is needed to fully explore these effects.

Somatization and Body Composition: Findings from a Cross-Sectional Study on Non-Clinical Young Adults

BACKGROUND/OBJECTIVES

Lifestyle is a significant, common, and easily modifiable factor capable of increasing or reducing the risk of acquiring many diseases. Currently, there is a research gap as too little scientific attention has been focused on exploring the relationship between mental health and nutritional status in various populations. Moreover, the association between body composition and somatization has not been fully disclosed. Therefore, this study aimed to assess the associations of body composition with the symptomatology of somatization in an environmentally vulnerable sample of young adults.

METHODS

A single cross-sectional study included young non-clinical Lithuanian students (n = 1223) aged 21.7 ± 3.9. The body adiposity status of the study participants was estimated using both the body mass index (BMI) and the Body Adiposity Estimator (CUN-BAE) method. Fat-free mass was evaluated via the adjusted fat-free mass index equation (FFMIadj). The Patient Health Questionnaire (PHQ-15) was applied to assess the severity of the perceived symptoms of a somatic symptom disorder (SSD).

RESULTS

The CUN-BAE was considered to be a better predictor of adiposity than the BMI because 14.7% of females and 6.2% of males were interpreted as obese using the CUN-BAE, while the BMI equation identified participants as having a normal body weight. The highest rates of somatization were found in 18.6% of the cohort. Young adults with higher amounts of body fat mass (β: 0.050, 95% confidence interval (95% CI): 0.013; 0.084, p = 0.007) and lower FFMI are prone to a higher risk for developing somatization (β: -0.429, 95% CI: -0.597; -0.260, p < 0.001).

CONCLUSIONS

Our study revealed that body composition is significantly related to multiple somatic complaints throughout a range of measurements. However, in contrast to the CUN-BAE tool, the BMI equation underestimated the relationship between body fat and mental health outcomes in young adults. Even though nutritional status along with targeted physical load, as the mediators, are likely to play a significant role in the maintenance of optimal body composition and mental health outcomes, healthcare providers are recommended to advise individuals to lower their body fat percentage and increase fat-free mass in order to reduce the risk of somatization.

A systematic exposure-wide framework leveraging machine learning to identify multidomain exposure factors and their joint influence on cognitive function: Evidence from a neurological cohort

INTRODUCTION

Cognitive decline has become a growing public concern, yet large-scale exposure data identifying the contributing factors remain limited.

METHODS

We conducted an exposure-wide association study involving 1142 participants and 207 exposures, using machine learning to assess the relative contribution and joint effects of key factors. Cluster analysis and intervention simulation trials helped identify high-risk subpopulations and the potential benefits of targeted interventions.

RESULTS

In adjusted mixed models, the socioeconomic status domain emerged as the strongest predictor of longitudinal global cognitive score (β = 2.91, p < 0.0001, q < 0.0001), while the dietary domain also played an important role in memory function. The cluster analysis found that the "unfavorable lifestyle" dominated phenotype was associated with the poorest cognitive outcomes. Simulation trials indicated that cognitive scores could improve by shifting individuals from unfavorable to favorable phenotypes.

DISCUSSION

Cognitive health requires multidomain interventions, particularly in the socioeconomic and dietary fields, and necessitates collaboration between government and individuals.

HIGHLIGHTS

The exposure-wide association study design, which assesses a broad range of exposures, is used to identify novel variables and understand their contributions to cognitive function. The findings from the multidomain analysis indicate that socioeconomic status is the most significant contributor to global cognitive function, while diet plays the largest role in memory function. Increasing the proportion of favorable phenotypes through multidomain interventions can significantly enhance public cognitive health.

Causal effects of circulating immune cells on coronary atherosclerosis: Evidence from Mendelian randomization

The role of circulating immune cells in coronary atherosclerosis remains unclear. This study aimed to assess the causal effects of various immune cells on coronary atherosclerosis using Mendelian randomization (MR). Circulating immune cell datasets were obtained from genome-wide association studies, and coronary atherosclerosis datasets were obtained from FinnGen. Single-nucleotide polymorphisms satisfying the assumptions of association, independence, and exclusivity were screened in the datasets and analyzed using MR, with inverse-variance weighted as the main method. Horizontal pleiotropy, heterogeneity, and sensitivity analyses were performed using the MR-Egger, Cochran Q, and leave-one-out analyses, respectively. The MR analysis showed that effector memory double negative (DN) (cluster of differentiation [CD]4-CD8-) %DN (odds ratio [OR]: 1.042, 95% confidence interval [CI]: 1.008-1.077, P = .014), CD4 on CD39+ CD4+ (OR: 1.027, 95% CI: 1.001-1.054, P = .040), C-X3-C motif chemokine receptor 1 on CD14+ CD16- monocytes (OR: 1.035, 95% CI: 1.010-1.060, P = .006), C-C chemokine receptor 7 on naive CD4+ (OR: 1.035, 95% CI: 1.006-1.076, P = .023), and immunoglobulin D- CD38- %lymphocytes (OR: 1.098, 95% CI: 1.016-1.187, P = .019) were associated with an increased genetic susceptibility to coronary atherosclerosis, with no horizontal pleiotropy (P ≥ .05). Cochran Q showed no heterogeneity (P ≥ .05), and the sensitivity analysis indicated that the results were robust. The MR analysis revealed various markers and immune cell subsets, including effector memory DN (CD4-CD8-) %DN, CD4 on CD39+ CD4+, C-X3-C motif chemokine receptor on CD14+ CD16- monocytes, C-C chemokine receptor 7 on naive CD4+, and IgD- CD38- %lymphocytes, associated with increased genetic susceptibility to coronary atherosclerosis. This provides a genetic explanation for the role of specific immune cells in inducing and exacerbating coronary artery disease and offers new ideas for the exploration of immune markers and immune-targeted drugs.

Joint effect of modifiable risk factors on Parkinson's disease: a large-scale longitudinal study

Introduction

Previous researches have often underestimated the diversity and combined effects of risk factors for Parkinson's disease (PD). This study aimed to identify how multiple modifiable risk factors collectively impact PD.

Methods

The study included 452,492 participants from the UK Biobank, utilizing genetic data and 255 phenotypic variables. A broad exposure association study was conducted across seven domains: socioeconomic status, medical history, psychosocial factors, physical measures, early life, local environment, and lifestyle. Risk scores of each domain for each participant were generated. The joint effects of modifiable and genetic risks assessed using Cox proportional hazards model. Population attributable fraction (PAF) was estimated to quantify contribution ratio of risk factors in different domains to the occurrence of PD.

Results

Multiple risk factors significantly (p < 1.96 × 10-4) associated with PD was observed. The top 5 factors were hand grip strength (hazard ratio (HR) = 0.98, p = 1.59 × 10-24), long-standing illness (HR = 1.38, p = 3.63 × 10-20), self-reported nervousness (HR = 1.56, p = 5.9 × 10-20), ever suffered from mental health concerns (HR = 1.42, p = 5.48 × 10-18) and chest pain (HR = 1.42, p = 1.43 × 10-18). Individuals with unfavorable medical history, psychosocial factors, physical measures, and lifestyle had an increased risk of PD by 33 to 51% compared to those with favorable factors (p < 0.001).

Discussion

Results indicated that addressing modifiable risk factors, especially in physical measures and psychological factors, could potentially prevent up to 33.87% of PD cases. In formulating prevention strategies, it is recommended to prioritize domains such as physical measures, psychosocial factors, lifestyle, and medical history.

Impact of accelerated biological aging and genetic variation on esophageal adenocarcinoma: Joint and interaction effect in a prospective cohort

Accelerated biological aging may be associated with increased risk of esophageal adenocarcinoma (EAC). However, its relationship with genetic variation, and its effect on improving risk population stratification, remains unknown. We performed an exposome association study to determine potential associated factors associated with EAC. To quantify biological age and its difference from chronological age, we calculated the BioAge10 and Biological Age Acceleration (BioAgeAccel) based on chronological age and nine biomarkers. Multivariable Cox regression models for 362,310 participants from the UK Biobank with a median follow-up of 13.70 years were performed. We established a weighted polygenic risk score (wPRS) associated with EAC, to assess joint and interaction effects with BioAgeAccel. Four indicators were used to evaluate their interaction effects, and we fitted curves to evaluate the risk stratification ability of BioAgeAccel. Compared with biologically younger participants, those older had higher risk of EAC, with adjusted HR of 1.79 (95%CI: 1.52-2.10). Compared with low wPRS and biologically younger group, the high wPRS and biologically older group had a 4.30-fold increase in HR (95% CI: 2.78-6.66), at meanwhile, 1.15-fold relative excess risk was detected (95% CI: 0.30-2.75), and 22% of the overall EAC risk was attributable to the interactive effects (95% CI: 12%-31%). The 10-year absolute incidence risk indicates that biologically older individuals should begin screening procedures 4.18 years in advance, while youngers can postpone screening by 4.96 years, compared with general population. BioAgeAccel interacted positively with genetic variation and increased risk of EAC, it could serve as a novel indicator for predicting incidence.

Variables associated with cognitive function: an exposome-wide and mendelian randomization analysis

BACKGROUND

Evidence indicates that cognitive function is influenced by potential environmental factors. We aimed to determine the variables influencing cognitive function.

METHODS

Our study included 164,463 non-demented adults (89,644 [54.51%] female; mean [SD] age, 56.69 [8.14] years) from the UK Biobank who completed four cognitive assessments at baseline. 364 variables were finally extracted for analysis through a rigorous screening process. We performed univariate analyses to identify variables significantly associated with each cognitive function in two equal-sized split discovery and replication datasets. Subsequently, the identified variables in univariate analyses were further assessed in a multivariable model. Additionally, for the variables identified in multivariable model, we explored the associations with longitudinal cognitive decline. Moreover, one- and two- sample Mendelian randomization (MR) analyses were conducted to confirm the genetic associations. Finally, the quality of the pooled evidence for the associations between variables and cognitive function was evaluated.

RESULTS

252 variables (69%) exhibited significant associations with at least one cognitive function in the discovery dataset. Of these, 231 (92%) were successfully replicated. Subsequently, our multivariable analyses identified 41 variables that were significantly associated with at least one cognitive function, spanning categories such as education, socioeconomic status, lifestyle factors, body measurements, mental health, medical conditions, early life factors, and household characteristics. Among these 41 variables, 12 were associated with more than one cognitive domain, and were further identified in all subgroup analyses. And LASSO, rigde, and principal component analysis indicated the robustness of the primary results. Moreover, among these 41 variables, 12 were significantly associated with a longitudinal cognitive decline. Furthermore, 22 were supported by one-sample MR analysis, and 5 were further confirmed by two-sample MR analysis. Additionally, the quality of the pooled evidence for the associations between 10 variables and cognitive function was rated as high. Based on these 10 identified variables, adopting a more favorable lifestyle was significantly associated with 38% and 34% decreased risks of dementia and Alzheimer's disease (AD).

CONCLUSION

Overall, our study constructed an evidence database of variables associated with cognitive function, which could contribute to the prevention of cognitive impairment and dementia.

Connecting genomic results for psychiatric disorders to human brain cell types and regions reveals convergence with functional connectivity

Identifying cell types and brain regions critical for psychiatric disorders and brain traits is essential for targeted neurobiological research. By integrating genomic insights from genome-wide association studies with a comprehensive single-cell transcriptomic atlas of the adult human brain, we prioritized specific neuronal clusters significantly enriched for the SNP-heritabilities for schizophrenia, bipolar disorder, and major depressive disorder along with intelligence, education, and neuroticism. Extrapolation of cell-type results to brain regions reveals the whole-brain impact of schizophrenia genetic risk, with subregions in the hippocampus and amygdala exhibiting the most significant enrichment of SNP-heritability. Using functional MRI connectivity, we further confirmed the significance of the central and lateral amygdala, hippocampal body, and prefrontal cortex in distinguishing schizophrenia cases from controls. Our findings underscore the value of single-cell transcriptomics in understanding the polygenicity of psychiatric disorders and suggest a promising alignment of genomic, transcriptomic, and brain imaging modalities for identifying common biological targets.

Associations of Polygenic Risk for Depression, Traditional Chinese Medicine Constitution, and Depression: A Population-Based Study in Taiwan

To comprehensively investigate the risk factors associated with depression, traditional Chinese medicine constitution (TCMC) has been found to be related to depression. However, the underlying mechanism remains unclear. This study examined the association between the concept of unbalanced TCMCs and major depressive disorder (MDD), investigated the overlapping polygenic risks between unbalanced TCMC and MDD, and performed a mediation test to establish potential pathways. In total, 11,030 individuals were recruited from the Taiwan Biobank, and the polygenic risk score (PRS) for MDD for each participant was calculated using the data from the Psychiatric Genomics Consortium. Unbalanced TCMC were classified as yang-deficiency, yin-deficiency, and stasis. The MDD PRS was associated with yang-deficiency odds ratio [OR] per standard deviation increase in standardized (PRS = 1.07, p = 0.0080), yin-deficiency (OR = 1.07, p = 0.0030), and stasis constitution (OR = 1.06, p = 0.0331). Yang-deficiency (OR = 2.07, p < 0.0001) and stasis constitutions (OR = 1.65, p = 0.0015) were associated with an increased risk of MDD. A higher number of unbalanced constitutions was associated with MDD (p < 0.0001). The effect of MDD PRS on MDD was partly mediated by yang-deficiency (10.21%) and stasis (8.41%) constitutions. This study provides evidence for the shared polygenic risk mechanism underlying depression and TCMC and the potential mediating role of TCMC in the polygenic liability for MDD.

The Effects of Confiding on Shift Work Nurses' Emotion Regulation and Self-Perceived Well-Being: An Online Randomized Controlled Trial

Shift work nurses suffered great stress and emotion dysregulation during the COVID-19 pandemic. Interpersonal emotion regulation has emerged as a promising therapeutic approach, often facilitated through confiding. It has been suggested that medical staff benefit from confiding, with the act of reflecting on the social support gained from confiding being associated with higher well-being. Consequently, we hypothesized that thinking about the social support derived from confiding about work-related hassles could enhance emotion regulation and well-being in shift work nurses. This study aimed to evaluate the effects of the intervention "thinking about the social support obtained from confiding about work-related hassles" on shift work nurses' emotion regulation and self-perceived well-being. An online randomized controlled trial was conducted with 66 shift work nurses, including 34 in the experimental group and 32 in the control group, to assess the impact of an 8-week confiding intervention focused on thinking about the social support obtained from confiding. The results indicated that the intervention significantly improved the interpersonal emotion regulation of shift work nurses in the experimental group compared to the control group. In terms of intrapersonal emotion regulation, the intervention appeared to reduce the cognitive reappraisal in the intervention group; however, there was no significant difference in cognitive reappraisal or expressive inhibition between the intervention group and control group. Furthermore, self-rated general health and sleep quality showed significant improvement in the intervention group compared to pre-test levels, but no significant differences were observed between the experimental and control groups. In conclusion, the online confiding intervention effectively enhanced interpersonal emotion regulation among shift work nurses. However, its effects on intrapersonal emotion regulation were not significant. Similarly, while participants in the intervention group reported improved self-rated general health and sleep quality, these improvements did not significantly differ from those in the control group.

How do immune cells shape type 1 diabetes? Insights from Mendelian randomization

Objective

The role of immune cells in type 1 diabetes (T1D) is unclear. The aim of this study was to assess the causal effect of different immune cells on T1D using Mendelian randomization (MR).

Methods

A dataset of immune cell phenotypes (numbered from GCST0001391 to GCST0002121) was obtained from the European Bioinformatics Institute, while a T1D dataset (numbered finngen_R10_T1D) was obtained from FinnGen. Single nucleotide polymorphisms meeting the conditions were screened stepwise according to the assumptions of association, independence, and exclusivity. Inverse variance weighted was used as the main method for the MR analysis. MR-Egger was used to assess the horizontal pleiotropy of the results. Cochran's Q and the leave-one-out method were respectively used for the heterogeneity analysis and the sensitivity analysis of the results.

Results

MR analysis showed that effector memory (EM) double-negative (DN) (CD4-CD8-) %T cells [odds ratio (OR) = 1.157, 95% confidence interval (95% CI) = 1.016-1.318, p = 0.028, false discovery rate (FDR) = 0.899], EM CD8br %T cells (OR = 1.049, 95% CI = 1.003-1.098, p = 0.037, FDR = 0.902), CD28 on CD28+CD45RA+CD8br (OR = 1.334, 95% CI = 1.132-1.571, p = 0.001, FDR = 0.044), IgD+CD38dim %lymphocytes (OR = 1.045, 95% CI = 1.002-1.089, p = 0.039, FDR = 0.902), CD80 on monocytes (OR = 1.084, 95% CI = 1.013-1.161, p = 0.020, FDR = 0.834), SSC-A on plasmacytoid dendritic cells (pDCs) (OR = 1.174, 95% CI = 1.004-1.372, p = 0.044, FDR = 0.902), and FSC-A on pDCs (OR = 1.182, 95% CI = 1.011-1.382, p = 0.036, FDR = 0.902) were associated with an increased genetic susceptibility to T1D. Cochran's Q showed that there was heterogeneity for CD28 on the CD28+CD45RA+CD8br results (p = 0.043), whereas there was no heterogeneity for the other results (p ≥ 0.05). The sensitivity analysis showed that the MR analysis results were robust.

Conclusion

The MR analysis demonstrated that seven immune cell phenotypes were associated with an increased genetic susceptibility to T1D. These findings provide a new direction for the pathogenesis of and the drug development for T1D.

Association between physical activity and sedentary behavior and depression in US adults with cardiovascular disease: NHANES 2007-2016

BACKGROUND

Previous studies reported the effect of physical activity (PA) or sedentary behavior (SB) on increasing occurrence of depression in patients with cardiovascular disease, leading to a higher risk of adverse clinical outcomes. However, the association between the combination of PA and SB and depression in patients with cardiovascular disease remained unstudied.

METHODS

Patients with cardiovascular disease (aged ≥18 years) who participated in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2016. Multivariable logistic regression was used to investigate the association between PA, SB, and depression.

RESULTS

Among the 2585 patients (mean age 64.43 years; 54.65 % male) in this study, the prevalence of depression was 16.40 %. After adjustment for age, gender, race, education level, marital status, poverty income ratio, employment status, smoking, alcohol use, BMI, hypertension, and number of cardiovascular diseases, depression was negatively associated with higher PA (adjusted OR = 0.567, 95 % CI 0.403, 0.799) and positively associated with higher SB (adjusted OR = 1.472, 95 % CI 1.089, 1.990), respectively. The risk of depression associated with higher PA and lower SB was significantly lower (adjusted OR = 0.464, 95 % CI 0.307, 0.702) compared to those with lower PA but higher SB.

LIMITATIONS

This was a cross-sectional study with limited ability to make causal inferences.

CONCLUSIONS

Our findings indicate that patients with higher PA and lower SB have a lower risk of depression than those with low PA levels and high SB levels. Moving more and sitting less is a potential preventive measure against depression in patients with cardiovascular disease.

Daytime napping and depressive symptoms in bipolar disorder: A cross-sectional analysis of the APPLE cohort

BACKGROUND

The relationship between daytime napping and depression remains debatable. Thus, we investigated whether daytime napping is associated with depressive symptoms in patients with bipolar disorder.

METHODS

In a cross-sectional study, we enrolled 204 outpatients with bipolar disorder who were participants in the Association between Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study. Each participant's daytime napping was measured using an actigraph over 7 consecutive days. Depressive symptoms were evaluated using the Montgomery-Åsberg Depression Rating Scale, and scores of ≥8 points were considered indicative of a depressed state.

RESULTS

One-hundred and ten (53.9 %) participants were depressed. In multivariable logistic regression analysis, as the number of nap days, number of naps per day, and nap duration increased, the odds ratio (OR) for depressed state significantly increased. Additionally, compared to the participants who did not nap, the participants who napped on five or more days a week or who had an average nap duration over 60 min had more than three times higher ORs in the depressed state (number of nap days: OR, 3.66; 95 % confidence interval [CI], 1.32-10.17; nap duration: OR, 3.14; 95 % CI, 1.12-8.81).

CONCLUSIONS

We found a significant and independent association between daytime napping and depressive symptoms in patients with bipolar disorder. Further studies are warranted to identify the effect of short napping on depressive symptoms in patients with bipolar disorder.

Association of physical activity and sedentary behaviour with depressive symptoms in Chinese adults

This study aims to examine the independent and joint associations of physical activity (PA) and sedentary behaviour with depressive symptoms. A population-based cross-sectional study conducted in China included 17,861 adults. PA and sedentary behaviour were assessed using the International Physical Activity Questionnaire. Depressive symptoms were determined by the 9-item Patient Health Questionnaire score ≥10. Logistic regression models were used to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs). The prevalence of depressive symptoms among all participants was 20.6% (3679/17861). Higher levels of PA were inversely associated with depressive symptoms, whereas prolonged sedentary behaviour was associated with increased odds of depressive symptoms. The positive associations between sedentary behaviour and depressive symptoms remained significant, regardless of PA levels. In joint analyses, the depressive symptoms OR comparing adults who reported low level of PA with the highest tertile of sedentary behaviour to those reporting high level of PA with the lowest tertile of sedentary behaviour was 1.99 (95% CI 1.64 to 2.40). This study indicated that high level of PA may not offset the increased risk of depressive symptoms associated with high amounts of sedentary behaviour, and therefore these behaviours should be considered jointly to obtain optimal prevention effects.

The association among multiple-site chronic pain, sedentary behavior, and major depressive disorders: a mendelian randomization study

OBJECTIVE

Observational studies have reported that major depressive disorder (MDD) is associated with sedentary behavior (SB) and multiple chronic pain (MCP), but their associations remain unclear. Mendelian randomization analysis was used to assess the association.

METHODS

Single nucleotide polymorphisms (SNPs) associated with MCP, SB [time spent watching television (Tel), using a computer (Com), or driving (Dri)], and MDD were collected from genome-wide association studies and screened as instrumental variants with a threshold of 1 × 10 -5 . Mendelian randomization was performed to examine their associations. Sensitivity analyses were conducted to evaluate robustness.

RESULTS

MCP was associated with a higher risk of MDD [odds ratio (OR) inverse variance weighting (IVW)  = 1.88; 95% confidence interval (CI), 1.64-2.15; P  = 4.26 × 10 -8 ), and causally related to SB (Tel: OR IVW  = 1.23; 95% CI, 1.19-1.26; P  = 6.02 × 10 -38 ) (Dri: OR IVW  = 1.05; 95% CI, 1.03-1.08; P  = 3.92 × 10 -5 ). Causality of SB on MCP was detected for Tel (OR IVW  = 1.46; 95% CI, 1.39-1.53; P  = 1.40 × 10 -54 ) and Com (OR IVW  = 0.88; 95% CI, 0.83-0.93; P  = 2.50 × 10 -6 ). No association was observed for SB on MDD. There is currently insufficient evidence to support that leisure activities are a mediating factor in MCP-induced MDD.

CONCLUSION

There are complex relationships among MCP, SB, and MDD. More research and learning about potential relationships and mechanisms among these phenotypes should be supplied.

Spontaneous miscarriage and social support in predicting risks of depression and anxiety: a cohort study in UK Biobank

BACKGROUND

It is still unclear whether social support can moderate the high risk of depression and anxiety due to spontaneous miscarriage.

OBJECTIVE

This study prospectively investigated the associations of spontaneous miscarriage with risks of depression and anxiety, and evaluated the interactions between spontaneous miscarriage and the degree of social support in relation to depression and anxiety risks.

STUDY DESIGN

A total of 179,000 participants from the UK Biobank with pregnancy experience and without depression or anxiety at baseline were included. Spontaneous miscarriage was defined by self-report from participants at enrollment or by International Classification of Diseases codes. The degree of social support was defined as the number of social support factors including living with a spouse or partner, participation in social activities, and confiding. Cox proportional hazards models were used to evaluate the joint association of spontaneous miscarriage and social support with the risks of depression and anxiety.

RESULTS

During a median follow-up of 12.3 years, 4939 depression incidents and 5742 anxiety incidents were documented. For participants with 1, 2, and ≥3 spontaneous miscarriages, hazard ratios (95% confidence intervals) for depression were 1.10 (1.02-1.19), 1.31 (1.14-1.50), and 1.40 (1.18-1.67), respectively (P trend <.001), compared with participants without a history of spontaneous miscarriage, after adjustment for covariates. For anxiety, the hazard ratios (95% confidence intervals) were 1.07 (1.00-1.15), 1.04 (0.90-1.19), and 1.21 (1.02-1.44), respectively (P trend=.01). Moreover, we found that the risk of depression associated with a combination of spontaneous miscarriage and low degree of social support in later life was greater than the sum of the risks associated with each individual factor, indicating significant interactions on an additive scale (P interaction=.03).

CONCLUSION

Spontaneous miscarriage is associated with higher risks of depression and anxiety, and the risk of depression is further increased when there is also low degree of social support.

Correlations between alterations in global brain functional connectivity in patients with major depressive disorder and their genetic characteristics

This study aims to elucidate the neuroimaging changes associated with major depressive disorder (MDD) and their relationship with genetic characteristics. We conducted a global-brain functional connectivity (GFC) and genetic-neuroimaging correlation analysis on 42 MDD patients and 42 healthy controls (HCs), exploring the correlation between GFC abnormalities and clinical variables. Results showed that compared to HCs, MDD patients had significantly decreased GFC values in the bilateral posterior cingulate cortex/precuneus and increased GFC values in the left and right cerebellum Crus I/II. Additionally, a negative correlation was observed between the GFC values of the left cerebellum Crus I/II and subjective support scores, as well as social support revalued scale total scores. We identified genes associated with GFC changes in MDD, which are enriched in biological processes such as synaptic transmission and ion transport. Our findings indicate the presence of abnormal GFC values in severe depression, complementing the pathological research on the condition. Furthermore, this study provides preliminary evidence for the correlation between social support levels and brain functional connectivity, offering insights into the potential association between GFC changes and gene expression in MDD patients.

Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method

OBJECTIVE

This paper aims to investigate the key factors, including demographics, socioeconomics, physical well-being, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention.

PARTICIPANTS

For our cross-sectional study, we recruited a total of 976 volunteers, with a specific focus on individuals aged 50 and above. Each participant was requested to provide their demographic, socioeconomic information and undergo several physical health tests. Additionally, they were asked to respond to questionnaires that assessed their mental well-being. Furthermore, participants were requested to maintain an activity log for a continuous 14-day period, starting from the day after they signed up. They had the option to use either a provided mobile application or paper to record their activities.

METHODS

We evaluated multiple machine learning models to find the best-performing one. Subsequently, we conducted post-hoc analysis to extract the variable significance from the selected model to gain deeper insights into the factors influencing depression.

RESULTS

Logistic Regression was chosen as it exhibited superior performance across other models, with AUC of 0.807 ± 0.038, accuracy of 0.798 ± 0.048, specificity of 0.795 ± 0.061, sensitivity of 0.819 ± 0.097, NPV of 0.972 ± 0.013 and PPV of 0.359 ± 0.064. The top influential predictors identified in the model included loneliness, health indicator (i.e. frailty, eyesight, functional mobility), time spent on activities (i.e. staying home, doing exercises and visiting friends) and perceived income adequacy.

CONCLUSION

These findings have the potential to identify individuals at risk of depression and prioritize interventions based on the influential factors. The amount of time dedicated to daily activities emerges as a significant indicator of depression risk among middle-aged and elderly individuals, along with loneliness, physical health indicators and perceived income adequacy.

The effects of a teacher-led online mental health literacy program for high school students: a pilot cluster randomized controlled trial

BACKGROUND

Adolescents are vulnerable to mental health problems, and this vulnerability may be enhanced in situations such as the present COVID-19 pandemic. Online mental health literacy (MHL) education may help adolescents maintain/improve their mental health, especially in situations where face-to-face education is difficult.

AIMS

To evaluate the effects of a teacher-led "online Short MHL Program (o-SMHLP)" delivered online to grade 10 students in their classrooms.

METHODS

Students (age 15-16) were randomly assigned to an o-SMHLP group (n = 115 (3 classes)) or a control group (n = 155 (4 classes)) at the class level. The program consisted of a 20-minute session which included an animated video. The students completed a self-report questionnaire pre- and post-intervention assessing outcomes including: "Knowledge about mental health/illnesses", "Recognition of necessity to seek help", "Intention to seek help", and "Unwillingness to socialize with people having mental illness". Mixed effects modeling was employed for analyses.

RESULTS

All outcomes were significantly improved in the intervention group compared to the control group post-intervention, except for "intention to seek help".

CONCLUSIONS

The present study shows the effectiveness of an online MHL intervention while identifying the need for the development of effective online programs targeting adolescents' "intention to seek help".

The association between dietary quality, sleep duration, and depression symptoms in the general population: findings from cross-sectional NHANES study

BACKGROUND

Unhealthy lifestyles, which include unhealthy diet and unhealthy sleep duration, have been widely recognized as modifiable risk factors for depressive symptoms. This study aims to explore the associations between dietary quality, sleep duration, and depression symptoms, as well as their combined effects.

METHODS

The NHANES 2007 to 2014 cycles provided the data for this study, in which 19,134 adults aged 20 years and older were included. Unhealthy diet, measured using an average Healthy Eating Index (HEI)-2015 score below the 60th percentile, and unhealthy sleep duration, measured as sleep duration at night less than 7 h or greater than/equal to 9 h, were the primary exposures. Then participants were divided into four different lifestyles. A weighted-multivariable logistic regression was employed, controlling for relevant variables. Furthermore, stratified analyses were conducted to assess the robustness of the findings and identify potential high-risk groups.

RESULTS

The overall prevalence of depressive symptoms among all participants was 8.44%. Among the participants, 56.58% met the criteria for healthy sleep duration, and 24.83% scored at or above the 60th percentile on the HEI-2015. Unhealthy diet (OR: 1.40, 95% CI: 1.18-1.67, p < 0.001) and unhealthy sleep duration (OR: 1.94, 95% CI: 1.63-2.31, p < 0.001) exhibited positive associations with depression symptoms. Individuals who maintained an unhealthy diet but healthy sleep duration (OR: 1.60, 95% CI: 1.20-2.13, p = 0.002), healthy diet but unhealthy sleep duration (OR: 2.50, 95% CI: 1.64-3.80, p < 0.001), or an unhealthy diet and unhealthy sleep duration (OR: 2.91, 95% CI: 2.16-3.92, p < 0.001) were significantly associated with depressive symptoms compared to those with a healthy diet and healthy sleep duration, respectively. In stratified analyses, females, middle-aged individuals, those with a college degree or higher education, and individuals who do not meet the recommended level of physical activity exhibit heightened susceptibility to depressive symptoms when exposed to unhealthy diet and unhealthy sleep duration.

CONCLUSION

In summary, our study suggests that individuals affected by the individual and synergistic effect of an unhealthy diet and unhealthy sleep duration are more susceptible to experiencing depressive symptoms.

Association of cardiometabolic multimorbidity with risk of late-life depression: a nationwide twin study

BACKGROUND

Cardiometabolic diseases (CMDs) including heart disease, stroke, and type 2 diabetes have been individually linked to depression. However, their combined impact on depression risk is unclear. We aimed to examine the association between cardiometabolic multimorbidity and depression and explore the role of genetic background in this association.

METHODS

Within the Swedish Twin Registry, 40,080 depression-free individuals (mean age 60 years) were followed for 18 years. Cardiometabolic multimorbidity was defined as having ≥2 CMDs. CMDs and depression were ascertained based on the National Patient Register. Cox regression was used to estimate the CMD-depression association in a classical cohort study design and a matched co-twin design involving 176 twin pairs. By comparing the associations between monozygotic and dizygotic co-twins, the contribution of genetic background was estimated.

RESULTS

At baseline, 4809 (12.0%) participants had one CMD and 969 (2.4%) had ≥2 CMDs. Over the follow-up period, 1361 participants developed depression. In the classical cohort design, the multi-adjusted hazard ratios (95% confidence interval [CIs]) of depression were 1.52 (1.31-1.76) for those with one CMD and 1.83 (1.29-2.58) for those with ≥2 CMDs. CMDs had a greater risk effect on depression if they developed in mid-life (<60 years) as opposed to late life (≥60 years). In matched co-twin analysis, the CMD-depression association was significant among dizygotic twins (HR = 1.63, 95% CI, 1.02-2.59) but not monozygotic twins (HR = 0.90, 95% CI, 0.32-2.51).

CONCLUSIONS

Cardiometabolic multimorbidity is associated with an elevated risk of depression. Genetic factors may contribute to the association between CMDs and depression.

The Mediating Roles of Lung Function Traits and Inflammatory Factors on the Associations between Measures of Obesity and Risk of Lower Respiratory Tract Infections: A Mendelian Randomization Study

BACKGROUND

Identifying mediators between obesity-related traits and lower respiratory tract infections (LRTIs) would inform preventive and therapeutic strategies to reduce the burden of LRITs. We aimed to recognize whether lung function and inflammatory factors mediate their associations.

METHODS

We conducted a two-step, two-sample Mendelian randomization (MR) analysis. Two-sample MR was performed on (1) obesity-related traits (i.e., body mass index [BMI], waist circumference [WC], and waist-to-hip ratio [WHR]) and LRTIs (i.e., acute bronchitis, acute bronchiolitis, bronchiectasis, influenza, and pneumonia), (2) obesity-related traits and potential mediators, and (3) potential mediators and LRTIs. Next, two-step MR was applied to infer whether the mediation effects exist.

RESULTS

We found that C-reactive protein (CRP), interleukin-6 (IL-6), and forced expiratory volume in the first second (FEV1) mediated 32.59% (95% CI: 17.90%, 47.27%), 7.96% (95% CI: 1.79%, 14.14%), and 4.04% (95% CI: 0.34%, 7.74%) of the effect of BMI on pneumonia, and they mediated 26.90% (95% CI: 13.98%, 39.83%), 10.23% (95% CI: 2.72%, 17.73%), and 4.67% (95% CI: 0.25%, 9.09%) of the effect of WC on pneumonia, respectively. Additionally, CRP, forced vital capacity (FVC), and FEV1 mediated 18.66% (95% CI: 8.70%, 28.62%), 8.72% (95% CI: 1.86%, 15.58%), and 8.41% (95% CI: 2.77%, 14.06%) of the effect of BMI on acute bronchitis, and they mediated 19.96% (95% CI: 7.44%, 32.48%), 12.19% (95% CI: 2.00%, 22.39%), and 12.61% (95% CI: 2.94%, 22.29%) of the effect of WC on acute bronchitis, respectively.

CONCLUSIONS

Health interventions linked to reducing inflammation and maintaining normal lung function could help mitigate the risk of obesity-related LRTIs.

Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank

Suicide is a global public health challenge, yet considerable uncertainty remains regarding the associations of both behaviour-related and physiological factors with suicide attempts (SA). Here we first estimated polygenic risk scores (PRS) for SA in 334,706 UK Biobank participants and conducted phenome-wide association analyses considering 2,291 factors. We identified 246 (63.07%) behaviour-related and 200 (10.41%, encompassing neuroimaging, blood and metabolic biomarkers, and proteins) physiological factors significantly associated with SA-PRS, with robust associations observed in lifestyle factors and mental health. Further case-control analyses involving 3,558 SA cases and 149,976 controls mirrored behaviour-related associations observed with SA-PRS. Moreover, Mendelian randomization analyses supported a potential causal effect of liability to 58 factors on SA, such as age at first intercourse, neuroticism, smoking, overall health rating and depression. Notably, machine-learning classification models based on behaviour-related factors exhibited high discriminative accuracy in distinguishing those with and without SA (area under the receiver operating characteristic curve 0.909 ± 0.006). This study provides comprehensive insights into diverse risk factors for SA, shedding light on potential avenues for targeted prevention and intervention strategies.

Multisystemic factors predicting street migration of children in Kenya: A multilevel longitudinal study of families and villages

BACKGROUND

Street-migration of children is a global problem with sparse multi-level or longitudinal data. Such data are required to inform robust street-migration prevention efforts.

OBJECTIVE

This study analyzes longitudinal cohort data to identify factors predicting street-migration of children - at caregiver- and village-levels.

PARTICIPANTS AND SETTING

Kenyan adult respondents (n = 575; 20 villages) actively participated in a community-based intervention, seeking to improve factors previously identified as contributing to street-migration by children.

METHODS

At two time points, respondents reported street-migration of children, and variables across economic, social, psychological, mental, parenting, and childhood experience domains. Primary study outcome was newly reported street-migration of children at T2 "incident street-migration", compared to households that reported no street-migration at T1 or T2. For caregiver-level analyses, we assessed bivariate significance between variables (T1) and incident street-migration. Variables with significant bivariate associations were included in a hierarchical logistical regression model. For community-level analyses, we calculated the average values of variables at the village-level, after excluding values from respondents who indicated an incident street-migration case to reduce potential outlier influence. We then compared variables between the 5 villages with the highest incidence to the 15 villages with fewer incident cases.

RESULTS

In regression analyses, caregiver childhood experiences, psychological factors and parenting behaviors predicted future street-migration. Lower village-aggregated depression and higher village-aggregated collective efficacy and social curiosity appeared significantly protective.

CONCLUSIONS

While parenting and economic strengthening approaches may be helpful, efforts to prevent street migration by children should also strengthen community-level mental health, collective efficacy, and communal harmony.

Association between trajectories of the neighborhood social exposome and mental health in late adolescence: A FinnTwin12 cohort study

BACKGROUND

Adolescent mental health problems impose a significant burden. Exploring evolving social environments could enhance comprehension of their impact on mental health. We aimed to depict the trajectories of the neighborhood social exposome from middle to late adolescence and assess the intricate relationship between them and late adolescent mental health.

METHODS

Participants (n = 3965) from the FinnTwin12 cohort with completed questionnaires at age 17 were used. Nine mental health measures were assessed. The social exposome comprised 28 neighborhood social indicators. Trajectories of these indicators from ages 12 to 17 were summarized via latent growth curve modeling into growth factors, including baseline intercept. Mixture effects of all growth factors were assessed through quantile-based g-computation. Repeated generalized linear regressions identified significant growth factors. Sex stratification was performed.

RESULTS

The linear-quadratic model was the most optimal trajectory model. No mixture effect was detected. Regression models showed some growth factors saliently linked to the p-factor, internalizing problems, anxiety, hyperactivity, and aggression. The majority of them were baseline intercepts. Quadratic growth factors about mother tongues correlated with anxiety among sex-combined participants and males. The linear growth factor in the proportion of households of couples without children was associated with internalizing problems in females.

LIMITATIONS

We were limited to including only neighborhood-level social exposures, and the multilevel contextual exposome situation interfered with our assessment.

CONCLUSIONS

Trajectories of the social neighborhood exposome modestly influenced late adolescent mental health. Tackling root causes of social inequalities through targeted programs for living conditions could improve adolescent mental health.

Environmental Toxicant Exposure and Depressive Symptoms

Importance

Recognizing associations between exposure to common environmental toxicants and mental disorders such as depression is crucial for guiding targeted mechanism research and the initiation of disease prevention efforts.

Objectives

To comprehensively screen and assess the associations between potential environmental toxicants and depressive symptoms and to assess whether systemic inflammation serves as a mediator.

Design, Setting, and Participants

A total of 3427 participants from the 2013-2014 and 2015-2016 waves of the National Health and Nutrition Examination and Survey who had information on blood or urine concentrations of environmental toxicants and depression scores assessed by the 9-item Patient Health Questionnaire (PHQ-9) were included. Statistical analysis was performed from July 1, 2023, to January 31, 2024.

Exposures

Sixty-two toxicants in 10 categories included acrylamide, arsenic, ethylene oxide, formaldehyde, iodine, metals, nicotine metabolites, polycyclic aromatic hydrocarbons, volatile organic compound (VOC) metabolites; and perchlorate, nitrate, and thiocyanate.

Main Outcomes and Measures

An exposome-wide association study and the deletion-substitution-addition algorithm were used to assess associations with depression scores (PHQ-9 ≥5) adjusted for other important covariates. A mediation analysis framework was used to evaluate the mediating role of systemic inflammation assessed by the peripheral white blood cell count.

Results

Among the 3427 adults included, 1735 (50.6%) were women, 2683 (78.3%) were younger than 65 years, and 744 (21.7%) were 65 years or older, with 839 (24.5%) having depressive symptoms. In terms of race and ethnicity, 570 participants (16.6%) were Mexican American, 679 (19.8%) were non-Hispanic Black, and 1314 (38.3%) were non-Hispanic White. We identified associations between 27 chemical compounds or metals in 6 of 10 categories of environmental toxicants and the prevalence of depressive symptoms, including the VOC metabolites N-acetyl-S-(2-hydroxy-3-butenyl)-l-cysteine (odds ratio [OR], 1.74 [95% CI, 1.38, 2.18]) and total nicotine equivalent-2 (OR, 1.42 [95% CI, 1.26-1.59]). Men and younger individuals appear more vulnerable to environmental toxicants than women and older individuals. Peripheral white blood cell count mediated 5% to 19% of the associations.

Conclusions and Relevance

In this representative cross-sectional study of adults with environmental toxicant exposures, 6 categories of environmental toxicants were associated with depressive symptoms with mediation by systemic inflammation. This research provides insight into selecting environmental targets for mechanistic research into the causes of depression and facilitating efforts to reduce environmental exposures.

A prospective cohort study in depression and anxiety among Vietnamese migrants in Japan during the early to mid-COVID-19 pandemic

INTRODUCTION

The enduring COVID-19 pandemic has had persistent, intermittent socioeconomic impacts on migrants. This raises the concern that many Vietnamese migrants in Japan may have developed mental health issues due to the socioeconomic impact. The study aimed to examine changes in the socio-economic and mental health status of Vietnamese migrants in Japan and factors affecting mental health status during the early to mid-COVID-19 period.

METHODS

We conducted a prospective cohort study among Vietnamese migrants in Japan from September to October 2021 (baseline) and from May to June 2022 (follow-up) using an online questionnaire. Multiple linear regression analyses were conducted to examine the association between changes in socioeconomic status and alterations in symptoms of depression and anxiety within this demographic.

RESULTS

The mean age of the 159 participants was 26.1 ± 4.9 years, with a mean length of residency in Japan of 4.0 ± 4.1 years. The mean PHQ-9 score exhibited a significant decrease from 7.89 (SD = 6.34) to 6.62 (SD = 5.87) (p = 0.01). Variables associated with changes in depression and anxiety included subjective socioeconomic status (unstandardized partial regression coefficient (UPRC): 1.901, 95% confidence interval (CI) 0.30 to 3.50, p = 0.02) and (UPRC: 2.060, 95% CI 0.80 to 3.32, p = 0.002), as well as changes in having someone with whom to discuss one's health (UPRC: 2.689, 95% CI 0.89 to 4.49, p = 0.004) and (UPRC: 1.955, 95% CI 0.54 to 3.38, p = 0.007).

CONCLUSIONS

In this prospective cohort study of depression and anxiety, depressive symptoms among Vietnamese migrants decreased from 2021 to 2022. Key findings underscore the importance of socioeconomic status improvement and having someone to discuss to about their health as protective factors against mental health challenges. Employment and social support have emerged as crucial determinants of mental health among Vietnamese migrants in Japan, emphasizing the necessity for comprehensive support strategies addressing both economic vulnerabilities and social connectedness.

Decoding depression by exploring the exposome-genome edge amidst COVID-19 lockdown

Risk of depression increased in the general population after the COVID-19 pandemic outbreak. By examining the interplay between genetics and individual environmental exposures during the COVID-19 lockdown, we have been able to gain an insight as to why some individuals are more vulnerable to depression, while others are more resilient. This study, conducted on a Spanish cohort of 9218 individuals (COVICAT), includes a comprehensive non-genetic risk analysis, the exposome, complemented by a genomics analysis in a subset of 2442 participants. Depression levels were evaluated using the Hospital Anxiety and Depression Scale. Together with Polygenic Risk Scores (PRS), we introduced a novel score; Poly-Environmental Risk Scores (PERS) for non-genetic risks to estimate the effect of each cumulative score and gene-environment interaction. We found significant positive associations for PERSSoc (Social and Household), PERSLife (Lifestyle and Behaviour), and PERSEnv (Wider Environment and Health) scores across all levels of depression severity, and for PRSB (Broad depression) only for moderate depression (OR 1.2, 95% CI 1.03-1.40). On average OR increased 1.2-fold for PERSEnv and 1.6-fold for PERLife and PERSoc from mild to severe depression level. The complete adjusted model explained 16.9% of the variance. We further observed an interaction between PERSEnv and PRSB showing a potential mitigating effect. In summary, stressors within the social and behavioral domains emerged as the primary drivers of depression risk in this population, unveiling a mitigating interaction effect that should be interpreted with caution.

Influence of cognitive reserve on risk of depression and subsequent dementia: A large community-based longitudinal study

BACKGROUND

Cognitive reserve (CR) has been linked to dementia, yet its influence on the risk of depression and related outcomes remains unknown. We aimed to examine the association of CR with depression and subsequent dementia or death, and to assess the extent to which CR is related to depression-free survival.

METHODS

Within the UK Biobank, 436,232 participants free of depression and dementia were followed. A comprehensive CR indicator (low, moderate, and high) was created using latent class analysis based on information on education, occupation, mentally passive sedentary behavior, social connection, confiding with others, and leisure activities. Depression, dementia, and survival status were ascertained through self-reported medical history and/or linkages to medical records. Data were analyzed using multi-state Markov model and Laplace regression.

RESULTS

Over a median follow-up of 12.96 years, 16,560 individuals developed depression (including 617 with subsequent dementia) and 28,655 died. In multivariable multi-state models, compared with low CR, high CR was associated with lower risk of depression (hazard ratio 0.53 [95% confidence interval 0.51-0.56]) and lower risk of post-depression dementia (0.55 [0.34-0.88]) or death (0.69 [0.55-0.88]) in middle-aged adults (aged <60 years). In Laplace regression, the depression-free survival time was prolonged by 2.77 (2.58-2.96) years in participants with high compared to low CR.

CONCLUSIONS

High CR is associated with lower risks of depression and subsequent transitions to dementia and death, particularly in middle age. High CR may prolong depression-free survival. Our findings highlight the importance of enhancing CR in the prevention and prognosis of depression.

Optimising the use of electronic medical records for large scale research in psychiatry

The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.

The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression

Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective studies is limited. Here, we analyze data of 352,277 participants from UK Biobank with 12.25-year follow-up. Compared with non-frail individuals, pre-frail and frail individuals have increased risk for incident depression independent of many putative confounds. Altogether, pre-frail and frail individuals account for 20.58% and 13.16% of depression cases by population attributable fraction analyses. Higher risks are observed in males and individuals younger than 65 years than their counterparts. Mendelian randomization analyses support a potential causal effect of frailty on depression. Associations are also observed between inflammatory markers, brain volumes, and incident depression. Moreover, these regional brain volumes and three inflammatory markers-C-reactive protein, neutrophils, and leukocytes-significantly mediate associations between frailty and depression. Given the scarcity of curative treatment for depression and the high disease burden, identifying potential modifiable risk factors of depression, such as frailty, is needed.

The role of lifestyle factors in the association between early-life stress and adolescent psycho-physical health: Moderation analysis in two European birth cohorts

OBJECTIVE

Early-life stress (ELS) is an established risk factor for a host of adult mental and physical health problems, including both depression and obesity. Recent studies additionally showed that ELS was associated with an increased risk of comorbidity between mental and physical health problems, already in adolescence. Healthy lifestyle factors, including physical activity, sleep and diet have also been robustly linked to both emotional and physical wellbeing. However, it is yet unclear whether these lifestyle factors may moderate the association between ELS and psycho-physical comorbidity.

METHODS

We investigated whether (a) participation in physical activity, (b) sleep duration, and (c) adherence to a Mediterranean diet, moderated the relationship between cumulative ELS exposure over the first 10 years of life and psycho-physical comorbidity at the age of 13.5 years. Analyses were conducted in 2022-2023, using data from two large adolescent samples based in the UK (ALSPAC; n = 8428) and The Netherlands (Generation R; n = 4268).

RESULTS

Exposure to ELS was significantly associated with a higher risk of developing comorbidity, however this association was not modified by any of the three lifestyle factors investigated. Only physical activity was significantly associated with a reduced risk of comorbidity in one cohort (ORALSPAC [95%CI] = 0.73 [0.59;0.89]).

CONCLUSIONS

In conclusion, while we found some evidence that more frequent physical activity may be associated with a reduction in psycho-physical comorbidity, we did not find evidence in support of the hypothesised moderation effects. However, more research is warranted to examine how these associations may evolve over time.

Subjective evaluation of home environment and levels of self-reported depression in middle to old age: Results from the HCHS study

OBJECTIVES

The immediate living environment might, like other lifestyle factors, be significantly related to mental well-being. The current study addresses the question whether five relevant subjective home environment variables (i.e., protection from disturbing nightlight, daylight entering the home, safety at home, quality of window views, and noise disturbance) are associated with levels of self-reported depression over and above well-known sociodemographic and common lifestyle variables.

METHODS

Data from the Hamburg City Health Study (HCHS) were analyzed. In N = 8757 with available PHQ-9 depression data, multiple linear regression models were computed, with demographic data, lifestyle variables, and variables describing the subjective evaluation of the home environment.

RESULTS

The model explained 15% of variance in depression levels, with ratings for the subjective evaluation of home environment accounting for 6%. Better protection from disturbing light at night, more daylight entering the home, feeling safer, and perceived quality of the window views, were all significantly associated with lower, while more annoyance by noise was associated with higher levels of self-reported depression. Results did not differ if examining a sample of the youngest (middle-aged participants: 46-50 years) versus oldest (70-78 years) participants within HCHS.

CONCLUSION

Beyond studying the role of lifestyle factors related to self-reported depression, people's homes may be important for subclinical levels of depression in middle and older age, albeit the direction of effects or causality cannot be inferred from the present study. The development of a consensus and tools for a standardized home environment assessment is needed.

Associations between joint lifestyle behaviors and depression among children and adolescents: A large cross-sectional study in China

BACKGROUND

Lifestyles in children and adolescents are associated with mental health, yet the combined effects of diet-related joint lifestyles on depression are unclear.

METHODS

A cross-sectional study was conducted in January 2020 in primary and secondary schools in Shanghai, China, with 6478 participants in the analysis. Lifestyle behaviors (physical activity, sleep duration, screen time, and diet quality) and depressive symptoms were measured using validated questionnaires. A series of multivariable logistic regressions were performed to examine the associations between lifestyle behaviors and their combinations and depression.

RESULTS

The prevalence of depressive symptoms 12.2 % (n = 788). Compared to those considered physically active, physically inactive individuals showed higher odds of depression (adjusted odds ratio [aOR] = 1.206). Similarly, insufficient sleep duration (aOR = 1.449), long screen time (aOR = 1.457) and poor diet quality (aOR = 1.892) were all associated with higher odds of depression. Compared to participants with behaviors meeting all guidelines, the odds of depression increased as the number of behaviors not meeting guidelines increased in a dose-response relationship, with an average increase in depression odds of 49 % on average for each additional unhealthy behavior. Moreover, different combinations of behaviors not meeting guidelines showed varied odds of depression.

CONCLUSIONS

Our research suggests that lifestyle behaviors not meeting guidelines in children and adolescents are associated with poorer mental health, and the risk varies with the number and specific combination of behaviors not meeting guidelines. Diet-related joint behaviors may be overlooked, and practical measures targeting joint lifestyles are needed to prevent and alleviate mental health problems among children and adolescents.

Why do Middle-Aged Adults Report Worse Mental Health and Wellbeing than Younger Adults? An Exploratory Network Analysis of the Swiss Household Panel Data

Despite the growing consensus that midlife appears to be a particularly vulnerable life phase for lower mental health and wellbeing, little is known about the potential reasons for this phenomenon or who the individuals at higher risk are. Our study used six waves (2013-2018) of the Swiss Household Panel (n = 5,315), to compare the distribution of mental health and wellbeing, as well as their key correlates, between midlife (40-55 years) and younger adults (25-39 years) in Switzerland. Moreover, using network analysis to investigate interrelationships across life domains, we describe the complex interrelations between multiple domain-specific correlates and indicators of both mental health and wellbeing across the two age groups. Middle-aged (age 40-55) individuals reported lower life satisfaction and joy, as well as higher anger, sadness, and worry than young adults (age 25-39), with the effect sizes reaching up to 0.20 Cohen's d. They also reported lower social support, relationships satisfaction, health satisfaction, and higher job demands and job insecurity. Relationships satisfaction and social support were the most consistent correlates across all three indicators of wellbeing in both age groups. Health satisfaction was more strongly, and directly, interrelated with energy and optimism in midlife compared with young adulthood (0.21 vs 0.12, p = 0.007). Job demands were more strongly linked with anger and sadness in midlife. The network model helped us to identify correlates or their clusters with direct and strong links to mental health and wellbeing. We hypothesised that health satisfaction, relationships satisfaction, social support, and job demands may help to explain worse mental health and wellbeing in midlife.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11482-024-10274-4.

Modifiable factors associated with cognitive performance in Chinese adolescents: a national environment-wide association study

Growing evidence exists about the candidate factors of childhood cognitive performance, but mainly limited to single-exposure studies. We sought to systematically and simultaneously identify and validate a wide range of potential modifiable factors for childhood cognitive performance. We used data from five waves of data from the China Family Panel Studies (CFPS-2010, 2012, 2014, 2016 and 2018). Our analytical sample was restricted to those children aged 2-5 at baseline with valid exposure information. A total of 80 modifiable factors were identified. Childhood cognitive performance was assessed using vocabulary and mathematics test at wave 5. We used an environment-wide association study (EnWAS) to screen all exposure-outcome associations independently and used the least absolute shrinkage and selection operator (LASSO) variable selection algorithm to identify factors associated with cognitive performance. Multivariable linear model was then used to evaluate causal relationships between identified factors and cognitive performance. Of the 1305 participants included in the study (mean ± SD, 3.5 ± 1.1 years age at baseline, 45.1% girls). Eight factors were retained in the LASSO regression analysis. Six factors across community characteristics (percentage of poverty in the community; percentage of children in the community), household characteristics (family size), child health and behaviors (mobile internet access), parenting behaviors and cognitive enrichment (parental involvement in child' s education), and parental wellbeing (paternal happiness) domains were significantly associated with childhood cognition. Using a three-stage approach, this study validates several actionable targets for improving childhood cognitive performance.

Modifiable lifestyle factors influencing psychiatric disorders mediated by plasma proteins: A systemic Mendelian randomization study

BACKGROUND

Psychiatric disorders are emerging as a serious public health hazard, influencing an increasing number of individuals worldwide. However, the effect of modifiable lifestyle factors on psychiatric disorders remains unclear.

METHODS

Genome-wide association studies (GWAS) summary statistics were obtained mainly from Psychiatric Genomics Consortium and UK Biobank, with sample sizes varying between 10,000 and 1,200,000. The two-sample Mendelian randomization (MR) method was applied to investigate the causal associations between 45 lifestyle factors and 13 psychiatric disorders, and screen potential mediator proteins from 2992 candidate plasma proteins. We implemented a four-step framework with step-by-step screening incorporating two-step, univariable, and multivariable MR.

RESULTS

We found causal effects of strenuous sports or other exercise on Tourette's syndrome (OR [95%CI]: 0.0047 [5.24E-04-0.042]); lifelong smoking index on attention-deficit hyperactivity disorder (10.53 [6.96-15.93]), anxiety disorders (3.44 [1.95-6.05]), bipolar disorder (BD) (2.25 [1.64-3.09]), BD II (2.89 [1.81-4.62]), and major depressive disorder (MDD) (2.47 [1.90-3.20]); and educational years on anorexia nervosa (AN) (1.47 [1.22-1.76]), and MDD (0.74 [0.66-0.83]). Five proteins were found to have causal associations with psychiatric disorders, namely ADH1B, GHDC, STOM, CD226, and TP63. STOM, a membrane protein deficient in the erythrocytes of hereditary stomatocytosis patients, may mediate the effect of educational attainment on AN.

LIMITATIONS

The mechanisms underlying the effects of lifestyle factors on psychiatric disorders require further investigation.

CONCLUSIONS

These findings could help assess the risk of psychiatric disorders based on lifestyle factors and also support lifestyle interventions as a prevention strategy for mental illness.

Depression and hepatobiliary diseases: a bidirectional Mendelian randomization study

Background

More and more evidence suggests a close association between depression and hepatobiliary diseases, but its causal relationship is not yet clear.

Method

Using genome-wide association studies (GWAS) to summarize data, independent genetic variations associated with depression were selected as instrumental variables. Firstly, we designed a univariate Mendelian randomization (UVMR) analysis with two samples and simultaneously conducted reverse validation to evaluate the potential bidirectional causal relationship between depression and various hepatobiliary diseases. Secondly, we conducted a multivariate Mendelian randomization (MVMR) analysis on diseases closely related to depression, exploring the mediating effects of waist to hip ratio, hypertension, and daytime nap. The mediating effects were obtained through MVMR. For UVMR and MVMR, inverse variance weighted method (IVW) is considered the most important analytical method. Sensitivity analysis was conducted using Cochran'Q, MR Egger, and Leave-one-out methods.

Results

UVMR analysis showed that depression may increase the risk of non-alcoholic fatty liver disease (OR, 1.22; 95% CI, 1.03-1.46; p=0.0248) in liver diseases, while depression does not increase the risk of other liver diseases; In biliary and pancreatic related diseases, depression may increase the risk of cholelithiasis (OR, 1.26; 95% CI, 1.05-1.50; p=0.0120), chronic pancreatitis (OR, 1.61; 95% CI, 1.10-2.35; p=0.0140), and cholecystitis (OR, 1.23; 95% CI, 1.03-1.48; p=0.0250). In addition, through reverse validation, we found that non-alcoholic fatty liver disease, cholelithiasis, chronic pancreatitis, cholecystitis, or the inability to increase the risk of depression (p>0.05). The waist to hip ratio, hypertension, and daytime nap play a certain role in the process of depression leading to non-alcoholic fatty liver disease, with a mediating effect of 35.8%.

Conclusion

Depression is a susceptibility factor for non-alcoholic fatty liver disease, and the causal effect of genetic susceptibility to depression on non-alcoholic fatty liver disease is mediated by waist-hip ratio, hypertension, and daytime nap.

A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis

BACKGROUND

'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056).

RESULTS

We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null.

CONCLUSION

Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.

Body composition, lifestyle, and depression: a prospective study in the UK biobank

BACKGROUND

Obesity has been related to depression and adhering healthy lifestyle was beneficial to lower the risk of depression; however, little is known about the relationship between body composition and fat distribution with depression risk and the influence of body composition and fat distribution on the association of lifestyle and depression. Therefore, we aimed to investigate whether body composition and fat distribution were associated with the adverse events of depression and the relationship between lifestyle and depression.

METHODS

We included 330,131 participants without depression at baseline in the UK Biobank (mean age, 56.9 years; 53.83% females). The assessment of depression was sourced from health outcomes across self-report, primary care, hospital inpatient data, and death data. Body composition was determined by bioelectrical impedance. Seven lifestyles (no current smoking, moderate alcohol consumption, regular physical activity, healthy diet, less sedentary behavior, healthy sleep pattern, and appropriate social connection) were used to generate a lifestyle score.

RESULTS

During a median of 11.7 years of follow-up, 7576 incident depression occurred. All the body composition measures were positively associated with depression risk, with the Hazard ratios (HR) for the uppermost tertile (T3) versus the lowest tertile (T1) ranging from 1.26 (95% CI: 1.15-1.39) for trunk fat-free mass (TFFM) to 1.78 (1.62-1.97) for leg fat percentage (LFP). In addition, we found significant interactions between fat mass-related indices, especially leg fat mass (LFM) (p = 1.65 × 10-9), and lifestyle score on the risk of depression, for which the beneficial associations of a healthy lifestyle with the risk of depression were more evident among participants with low body fat measurement.

CONCLUSIONS

High levels of body composition measures were associated with an increased depression risk. Adverse body composition measures may weaken the link between a healthy lifestyle and a reduced risk of depression.

Physical and mental health in adolescence: novel insights from a transdiagnostic examination of FitBit data in the ABCD study

Adolescence is among the most vulnerable period for the emergence of serious mental illnesses. Addressing this vulnerability has generated interest in identifying markers of risk for symptoms and opportunities for early intervention. Physical fitness has been linked to psychopathology and may be a useful risk marker and target for early intervention. New wearable technology has made assessing fitness behavior more practical while avoiding recall and self-report bias. Still, questions remain regarding the clinical utility of physical fitness metrics for mental health, both transdiagnostically and along specific symptom dimensions. The current study includes 5007 adolescents (ages 10-13) who participated in the Adolescent Brain Cognitive Development (ABCD) study and additional sub-study that collected fitness data from wearable technology and clinical symptom measures. Physical fitness metrics included resting heart rate (RHR- an index of cardiovascular health), time spent sedentary (associated with increased inflammation and cardiovascular disease), and time spent in moderate physical activity (associated with increased neurogenesis, neuroplasticity, and healthy neurodevelopment). Self-report clinical symptoms included measures of psychosis-like experiences (PLE), internalizing symptoms, and externalizing symptoms. Increased RHR- lower cardiovascular fitness- related only to greater internalizing symptoms (t = 3.63). More sedentary behavior related to elevated PLE severity (t = 5.49). More moderate activity related to lower PLE (t = -2.69) and internalizing (t = -6.29) symptom severity. Wearable technology fitness metrics linked physical health to specific mental health dimensions, which emphasizes the utility of detailed digital health data as a marker for risk and the need for precision in targeting physical health behaviors to benefit symptoms of psychopathology.

[New advances in exposomics-analysis methods and research paradigms based on chromatography-mass spectrometry]

The occurrence and development of human diseases are influenced by both genetic and environmental factors. Research models that describe disease occurrence only from the perspective of genetics present certain limitations. In recent years, effects of environment factors on the occurrence and development of diseases have attracted extensive attentions. Exposomics focuses on the measurement of all exposure factors in an individual's life and how these factors are related to disease development. Exposomics provides new ideas to promote studies on the relationship between human health and environmental factors. Environmental exposures are characterized with different physical and chemical properties, as well as very low concentrations in vivo, which contribute great challenges in the comprehensive measurement of chemical residues in the human body. Chromatography-mass spectrometry-based technologies combine the high-efficiency separation ability of chromatography with the high resolution and sensitive detection characteristics of mass spectrometry; the combination of these techniques can achieve the high-coverage, high-throughput, and sensitive detection of environmental exposures, thus providing a powerful tool for measuring chemical exposures. Exposomics-analysis methods based on chromatography-mass spectrometry mainly include targeted quantitative analysis, suspect screening, and non-targeted screening. To explore the relationship between environmental exposure and the occurrence and development of diseases, researchers have developed research paradigms, including exposome wide association study, mixed-exposure study, exposomics and multi-omics (genome, transcriptome, proteome, metabolome)-association study, and so on. The emergence of these methods has brought about unprecedented developments in exposomics studies. In this manuscript, analytical methods based on chromatography-mass spectrometry, exposomics research paradigms, and their relevant prospects are reviewed.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

The influence of social participation and depressive symptoms on cognition among middle-aged and older adults

Background

The global aging phenomenon has raised concerns about the cognitive abilities of older individuals. This study aimed to explore the relationship between social participation, depressive symptoms, and cognitive function among middle-aged and older adults.

Methods

This study utilized data from the China Longitudinal Study of Health and Retirement (CHARLS) from wave 1 to wave 4. We used linear regression and generalized estimation equations to investigate the correlation between social participation, depressive symptoms, and cognitive function. Moreover, three models were constructed by adjusting covariates, and we used the sobel test and bootstrap method to analyze the mediating effects of depressive symptoms on social activities and cognitive function.

Results

The results of both linear regression and generalized estimation equation showed that social participation had a positive correlation with cognitive function (P < 0.05), and the impact of social participation on cognition increased with the number of social activity types. Meanwhile, depressive symptoms had a negative association with cognitive function (P < 0.05). Furthermore, there was no interaction between social participation and depressive symptoms on cognitive function. Finally, after adjusting the model, social participation could affect cognitive function by affecting depressive symptoms (P < 0.05).

Conclusion

The study emphasizes the mediating role of depressive symptoms in the relationship between social participation and cognitive function. Notably, no interaction was observed between social participation and depressive symptoms. These findings highlight the potential of active social participation in reducing depressive symptoms and enhancing cognitive function in middle-aged and older adults.

Staying connected: An umbrella review of meta-analyses on the push-and-pull of social connection in depression

BACKGROUND

Depression affects approximately 4 % of the global population and has huge social and economic implications. Social factors, including support, engagement, and stigma, play a crucial role in the development and severity of depression.

METHODS

We provide a synthesis of the consistency and magnitude of the association between measures of social connection and depression. We searched PubMed, PsycINFO, Cochrane Library, and EMBASE and 47 meta-analyses were included in the umbrella review. The strength of the associations was extracted and compared among different populations. The quality/certainty of evidence was assessed using AMSTAR-2 and GRADE tool.

RESULTS

Results indicate that social support serves as a protective factor against depression, particularly in peripartum populations, while its impact is weaker in clinical populations. No association was found between social support and depression in post-disaster populations. Stigma and discrimination favour the development and maintenance of depressive symptoms in clinical populations, but have a weaker effect in ethnic minorities.

LIMITATIONS

The quality and certainty of evidence should be taken into account when interpreting our findings. Further research with more rigorous methodology and higher-quality evidence is needed to better understand the complex relationship between depression and social connection across various populations and contexts.

CONCLUSIONS

Our findings confirm the role of social determinants in the emergence and severity of depression, particularly in the case of vulnerable populations. Efforts to counteract disconnection at the societal and individual levels and to reduce stigma should be central to an effective depression prevention agenda.

The clustering of lifestyle behaviors in U.S. college students: a network approach

Objective: College student mental health has been decreasing and lifestyle factors may be an important factor in improving mental health. These behaviors may cluster together in complex ways, which could impact the success of lifestyle interventions. Participants: Two samples of U.S. undergraduate college students were drawn from the American College Health Association's National College Health Assessment (NCHA). The data were collected in Fall of 2019 (N = 30,075) and Spring of 2021 (N = 70,059). Methods: Students responded to various health and well-being related questions. Network models were used to examine how lifestyle behaviors cluster together and additional models contained both lifestyle behaviors and health and well-being outcomes. Results: Lifestyle clustering was found, and some similar patterns were seen across time periods and across levels of psychological distress. Conclusions: Individual lifestyle behaviors exist within a complex lifestyle network, which may need to be accounted for in lifestyle interventions.