The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods

Does healthy lifestyle attenuate the associations of phthalates with depression? A cross-sectional study

Phthalates have raised concerns on health outcomes including depression, due to its ubiquity. Knowledge is lacking on the role of modifiable lifestyle in attenuating phthalates' adverse effects. We aimed to evaluate the interaction effects of lifestyle with urinary phthalate metabolites (UPMs) on depression. A total of 3588 participants aged ≥ 20 from the National Health and Nutrition Examination Survey 2011-2018 were involved. We used multivariate logistic regression models and Bayesian Kernel Machine Regression models to evaluate the associations of UPMs (individual or mixture) and lifestyle with depression. Positive associations of individual UPMs and its mixture with depression were observed in total population and participants maintaining an unfavorable lifestyle. No such association was found in participants with a healthy lifestyle. Interactions between lifestyle category with MECPP (P for interaction = 0.028), and ΣDEHP (P for interaction = 0.087) on depression were observed. Additionally, smoking, alcohol consumption and physical activity in healthy levels showed the greatest effect against depression among the common lifestyle combinations. In conclusion, positive associations of UPMs with depression risk, and interaction effects of lifestyle and UPMs on depression were observed. Our findings indicate that healthy lifestyle might weaken the adverse effects of phthalate exposure on depression risk.

Estimating the Burden of Common Mental Disorders Attributable to Lifestyle Factors: Protocol for the Global Burden of Disease Lifestyle and Mental Disorder (GLAD) Project

BACKGROUND

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) collects and calculates risk-outcome data for modifiable lifestyle exposures (eg, dietary intake) and physical health outcomes (eg, cancers). These estimates form a critical digital resource tool, the GBD VizHub data visualization tool, for governments and policy makers to guide local, regional, and global health decisions. Despite evidence showing the contributions of lifestyle exposures to common mental disorders (CMDs), such as depression and anxiety, GBD does not currently generate these lifestyle exposure-mental disorder outcome pairings. This gap is due to a lack of uniformly collected and analyzed data about these exposures as they relate to CMDs. Such data are required to quantify whether, and to what degree, the global burden of CMDs could be reduced by targeting lifestyle factors at regional and global levels. We have established the Global burden of disease Lifestyle And mental Disorder (GLAD) Taskforce to address this gap.

OBJECTIVE

This study aims to generate the necessary estimates to afford the inclusion of lifestyle exposures as risk factors for CMDs in the GBD study and the GBD digital visualization tools, initially focusing on the relationship between dietary intake and CMDs.

METHODS

The GLAD project is a multicenter, collaborative effort to integrate lifestyle exposures as risk factors for CMDs in the GBD study. To achieve this aim, global epidemiological studies will be recruited to conduct harmonized data analyses estimating the risk, odds, or hazards of lifestyle exposures with CMD outcomes. Initially, these models will focus on the relationship between dietary intake, as defined by the GBD, and anxiety and depression.

RESULTS

As of August 2024, 18 longitudinal cohort studies from 9 countries (Australia: n=4; Brazil: n=1; France: n=1; Italy: n=3; The Netherlands: n=3; New Zealand: n=1; South Africa: n=1; Spain: n=1; and United Kingdom: n=3) have agreed to participate in the GLAD project.

CONCLUSIONS

Our comprehensive, collaborative approach allows for the concurrent execution of a harmonized statistical analysis protocol across multiple, internationally renowned epidemiological cohorts. These results will be used to inform the GBD study and incorporate lifestyle risk factors for CMD in the GBD digital platform. Consequently, given the worldwide influence of the GBD study, findings from the GLAD project can offer valuable insights to policy makers worldwide around lifestyle-based mental health care.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/65576.

Lifestyle behaviours do not moderate the association between childhood maltreatment and comorbid depression and cardiometabolic disease in older adults: a meta-analysis

BACKGROUND

Comorbidity between depression and cardiometabolic diseases is an emerging health concern, with childhood maltreatment as a major risk factor. These conditions are also linked to unhealthy lifestyle behaviours such as physical inactivity, smoking, and alcohol intake. However, the precise degree to which lifestyle behaviours moderate the risk between childhood maltreatment and comorbid depression and cardiometabolic disease is entirely unknown.

METHODS

We analysed clinical and self-reported data from four longitudinal studies (Npooled = 181,423; mean follow-up period of 5-18 years) to investigate the moderating effects of physical activity, smoking, and alcohol intake, on the association between retrospectively reported childhood maltreatment and i) depression, ii) cardiometabolic disease and iii) their comorbidity in older adults (mean age range of 47-66 years). Estimates of these moderation effects were derived using multinomial logistic regressions and then meta-analysed.

RESULTS

No meaningful moderation effects were detected for any of the lifestyle behaviours on the association between childhood maltreatment and each health outcome. Physical activity was linked to lower odds of depression (OR [95% CI] = 0.94 [0.92; 0.96]), while smoking was a risk factor for all three outcomes (OR [95% CI] = 1.16 [1.04; 1.31] or larger). Alcohol intake was associated with slightly lower odds of comorbidity (OR [95% CI] = 0.69 [0.66; 0.73]), although this association was not stable across all sensitivity analyses.

CONCLUSIONS

Lifestyle behaviours did not moderate the risk association between childhood maltreatment and depression, cardiometabolic disease, and their comorbidity in older adults. However, we confirmed that childhood maltreatment was associated with these conditions. Further research should address the limitations of this study to elucidate the most optimal targets for intervention.

Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder

BACKGROUND

Generalized Anxiety Disorder (GAD) is a chronic condition. Enabling the prediction of individual trajectories would facilitate tailored management approaches for these individuals. This study used machine learning techniques to predict the recovery of GAD at a nine-year follow-up.

METHOD

The study involved 126 participants with GAD. Various baseline predictors from psychological, social, biological, sociodemographic and health variables were used. Two machine learning models, gradient boosted trees, and elastic nets were compared to predict the clinical course in participants with GAD.

RESULTS

At nine-year follow-up, 95 participants (75.40 %) recovered. Elastic nets achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of .81 and a balanced accuracy of 72 % (sensitivity of .70 and specificity of .76). The elastic net algorithm revealed that the following factors were highly predictive of nonrecovery at follow-up: higher depressed affect, experiencing daily discrimination, more mental health professional visits, and more medical professional visits. The following variables predicted recovery: having some college education or higher, older age, more friend support, higher waist-to-hip ratio, and higher positive affect.

CONCLUSIONS

There was acceptable performance in predicting recovery or nonrecovery at a nine-year follow-up. This study advances research on GAD outcomes by understanding predictors associated with recovery or nonrecovery. Findings can potentially inform more targeted preventive interventions, ultimately improving care for individuals with GAD. This work is a critical first step toward developing reliable and feasible machine learning-based predictions for applications to GAD.

Insights from a methylome-wide association study of antidepressant exposure

This study tests the association of whole-blood DNA methylation and antidepressant exposure in 16,531 individuals from Generation Scotland (GS), using self-report and prescription-derived measures. We identify 8 associations and a high concordance of results between self-report and prescription-derived measures. Sex-stratified analyses observe nominally significant increased effect estimates in females for four CpGs. There is observed enrichment for genes expressed in the Amygdala and annotated to synaptic vesicle membrane ontology. Two CpGs (cg15071067; DGUOK-AS1 and cg26277237; KANK1) show correlation between DNA methylation with the time in treatment. There is a significant overlap in the top 1% of CpGs with another independent methylome-wide association study of antidepressant exposure. Finally, a methylation profile score trained on this sample shows a significant association with antidepressant exposure in a meta-analysis of eight independent external datasets. In this large investigation of antidepressant exposure and DNA methylation, we demonstrate robust associations which warrant further investigation to inform on the design of more effective and tolerated treatments for depression.

Increased ectodysplasin-A2-receptor EDA2R is a ubiquitous hallmark of aging and mediates parainflammatory responses

Intensive efforts have been made to identify features that could serve as biomarkers of aging. Yet, drug-based interventions aimed at lessening the detrimental effects of getting older are lacking. This is largely attributable to tissue-specificity, sex-related differences, and to the difficulty of identifying actionable targets, which continues to pose a significant challenge. Here, we implement a bioinformatics approach revealing that aging-associated increase of the transmembrane Ectodysplasin-A2-Receptor is a prominent tissue-independent alteration occurring in humans and other species, and is particularly pronounced in models of accelerated aging. We show that strengthening of the Ectodysplasin-A2-Receptor signalling axis in myogenic precursors and differentiated myotubes suffices to trigger potent parainflammatory responses, mirroring aspects of aging-driven sarcopenia. Intriguingly, obesity, insulin-resistance, and aging-related comorbidities, such as type-2-diabetes, result in heightened levels of the Ectodysplasin-A2 ligand. Our findings suggest that targeting the Ectodysplasin-A2 surface receptor represents a promising pharmacological strategy to mitigate the development of aging-associated phenotypes.

Interaction of chronic diseases and levels of mastery on the course of depression

BACKGROUND

Chronic diseases may negatively interfere with the course of depression. Our aim was to examine whether the association between chronic disease and course of depression is moderated by mastery.

METHOD

N = 1146 persons, aged 18-88, with depressive disorder according to DSM-IV criteria were followed for two years. Outcomes were change in depression severity (change in IDS-SR) (n = 945), chronic course (life chart interview) (n = 971), depression at follow-up (DSM-diagnosis) (n = 971), and time to remission (life chart interview) (n = 799). Predictors were number of chronic somatic diseases and mastery. Regression models (linear, logistic and Cox) were used, adjusted for depression severity, sociodemographics, loneliness, smoking and alcohol use. Next, an interaction term (chronic diseases*mastery) was added to the models.

RESULTS

We only found significant interaction between mastery and chronic diseases (p = 0.02), when outcome was defined as change in depression severity. In analyses, stratified for level of mastery, chronic diseases were significantly associated with chronic course in persons with moderate (B = 1.03; p = 0.03) and high (B = 1.10; p = 0.02) mastery levels. In unstratified analyses, mastery was associated with both chronic course (B = -0.18, p = 0.03) and time to remission (B = 1.03; p < 0.001). Chronic diseases did not reach significance in three outcomes.

CONCLUSION

While impact of chronic diseases on depression trajectories was less consistent than expected, when present, this association was moderated by mastery, suggesting that persons with higher levels of mastery may have difficulties coping with somatic illnesses. In clinical practice, attention to the impact of somatic diseases and coping strategies, in persons with higher levels of mastery, is warranted.

The Role of Psychopathology and Emotion Regulation in the Intergenerational Transmission of Childhood Abuse: A Family Study

Previous studies have shown that parents with a history of childhood abuse are at increased risk of perpetrating child abuse. To break the cycle of childhood abuse we need to better understand the mechanisms that play a role. In a cross-sectional extended family design including three generations (N = 250, 59% female), we examined the possible mediating role of parental psychopathology and emotion regulation in the association between a history of childhood abuse and perpetrating child abuse. Parents' own history of childhood abuse was associated with perpetrating abuse toward their children, and externalizing (but not internalizing) problems partially mediated this association statistically. Implicit and explicit emotion regulation were not associated with experienced or perpetrated abuse. Findings did not differ across fathers and mothers. Findings underline the importance of (early) treatment of externalizing problems in parents with a history of childhood abuse, to possibly prevent the transmission of child abuse.

Depression with immuno-metabolic dysregulation: Testing pragmatic criteria to stratify patients

INTRODUCTION

Inflammatory and metabolic processes are linked to depression, but only 25-30% of depressed patients show low-grade inflammation and metabolic dysregulation associated with atypical, energy-related symptoms (AES). Interventions targeting immuno-metabolic dysregulation could benefit depressed patients, but currently no consensus exists how to best select patients with immuno-metabolic dysregulations. Therefore, we investigated which combinations of circulating C-reactive protein (CRP) and AES could identify those depressed individuals with significant immuno-metabolic dysregulation.

METHODS

Data are from 1,077 persons with a current Major Depressive Disorder (MDD) of the Netherlands Study of Depression and Anxiety. Immuno-metabolic markers were Interleukin-6 (IL-6), Tumor Necrosis Factor alpha (TNF-α), glycoprotein acetyls, body mass index (BMI), waist circumference, triglycerides, high-density-lipoprotein cholesterol (HDL cholesterol), glucose and leptin. Strata for CRP (≤ 1, < 1 CRP ≤ 3, > 3 mg/L) and AES (score of ≤ 3, 4-5, ≥ 6) were compared on immuno-metabolic markers using analyses of covariance.

RESULTS

Across strata of CRP and AES, there was a dose-response pattern with all higher immuno-metabolic marker levels across higher strata of CRP and AES, with the exception for an association between AES and TNF-α. Persons with both elevated CRP (> 1 mg/L) and high AES (≥ 6) showed a more dysregulated inflammatory and metabolic profile compared to persons with lower CRP and/or AES (p < 0.001).

CONCLUSION

Our results show a dose-response relationship between both CRP levels and AES with immuno-metabolic risk biomarkers, indicating that CRP and AES combined can capture immuno-metabolic features of MDD. Combining these available and scalable indexes may be an effective strategy to select a patient sample with immuno-metabolic dysregulation who may benefit from treatments targeting inflammatory or metabolic pathways.

Metabolomics profiling of Type D personality traits

OBJECTIVE

Type D (Distressed) personality combines negative affectivity (NA) and social inhibition (SI) and is associated with an increased risk of cardiometabolic diseases. Here, we examined the association of Type D traits with 230 (predominantly) lipid metabolites and metabolite ratios.

METHODS

Four Dutch cohorts were included, comprising 10,834 individuals. Type D personality traits were measured by self-report questionnaires. A proton nuclear magnetic resonance (NMR) metabolomics platform provided 149 absolute measures (98 belonging to lipoprotein subclasses) and 81 derived ratios. For all, linear regression analyses were performed within each cohort, followed by random-effects meta-analyses. A per-measure FDR q-value<0.05 was set as a study-wise significant association.

RESULTS

SI was significantly associated with a lower omega-3 fatty acids to total fatty acids (FAw3.FA%) ratio, and a lower free cholesterol to total lipids ratio in very small VLDL (XS.VLDL.FC%). FAw3.FA% was also associated to NA (no study-wise significance though). NA showed a suggestive replication (p-value<.05) of the previous reported associations with depression for 5 out of 18 metabolites from the same metabolomics platform: triglycerides in HDL, serum total triglycerides, VLDL cholesterol, mean diameter for VLDL particles and VLDL triglycerides.

CONCLUSIONS

In this large meta-analysis, SI was associated with omega-3 fatty acids to total fatty acids ratio, which is suggestive of lower omega-3 fatty acid intake. Only some metabolite biomarkers showed tentative links to Type D and NA. In sum, it seems that there are no major alterations in lipid metabolism associated with Type D traits.

The metabolome-wide signature of major depressive disorder

Major Depressive Disorder (MDD) is a common, frequently chronic condition characterized by substantial molecular alterations and pathway dysregulations. Single metabolite and targeted metabolomics platforms have revealed several metabolic alterations in depression, including energy metabolism, neurotransmission, and lipid metabolism. More comprehensive coverage of the metabolome is needed to further specify metabolic dysregulations in depression and reveal previously untargeted mechanisms. Here, we measured 820 metabolites using the metabolome-wide Metabolon platform in 2770 subjects from a large Dutch clinical cohort with extensive clinical phenotyping (1101 current MDD, 868 remitted MDD, 801 healthy controls) at baseline, which were repeated in 1805 subjects at 6-year follow up (327 current MDD, 1045 remitted MDD, 433 healthy controls). MDD diagnosis was based on DSM-IV psychiatric interviews. Depression severity was measured with the Inventory of Depressive Symptomatology Self-report. Associations between metabolites and MDD status and depression severity were assessed at baseline and at 6-year follow-up. At baseline, 139 and 126 metabolites were associated with current MDD status and depression severity, respectively, with 79 overlapping metabolites. Adding body mass index and lipid-lowering medication to the models changed results only marginally. Among the overlapping metabolites, 34 were confirmed in internal replication analyses using 6-year follow-up data. Downregulated metabolites were enriched with long-chain monounsaturated (P = 6.7e-07) and saturated (P = 3.2e-05) fatty acids; upregulated metabolites were enriched with lysophospholipids (P = 3.4e-4). Mendelian randomization analyses using genetic instruments for metabolites (N = 14,000) and MDD (N = 800,000) showed that genetically predicted higher levels of the lysophospholipid 1-linoleoyl-GPE (18:2) were associated with greater risk of depression. The identified metabolome-wide profile of depression indicated altered lipid metabolism with downregulation of long-chain fatty acids and upregulation of lysophospholipids, for which causal involvement was suggested using genetic tools. This metabolomics signature offers a window on depression pathophysiology and a potential access point for the development of novel therapeutic approaches.

Clinical and sociodemographic features of the Texas resilience against depression (T-RAD) study: Findings from the initial cohort

OBJECTIVE

The burden of major depressive disorder is compounded by a limited understanding of its risk factors, the limited efficacy of treatments, and the lack of precision approaches to guide treatment selection. The Texas Resilience Against Depression (T-RAD) study was designed to explore the etiology of depression by collecting comprehensive socio-demographic, clinical, behavioral, neurophysiological/neuroimaging, and biological data from depressed individuals (D2K) and youth at risk for depression (RAD).

METHODS

This report details the baseline sociodemographic, clinical, and functional features from the initial cohort (D2K N = 1040, RAD N = 365).

RESULTS

Of the total T-RAD sample, n = 1078 (76.73 %) attended ≥2 in-person visits, and n = 845 (60.14 %) attended ≥4 in-person visits. Most D2K (84.82 %) had a primary diagnosis of any depressive disorder, with a bipolar disorder diagnosis being prevalent (13.49 %). RAD participants (75.89 %) did not have a psychiatric diagnosis, but other non-depressive diagnoses were present. D2K participants had 9-item Patient Health Questionnaire scores at or near the moderate range (10.58 ± 6.42 > 24 yrs.; 9.73 ± 6.12 10-24 yrs). RAD participants were in the non-depressed range (2.19 ± 2.65). While the age ranges in D2K and RAD differ, the potential to conduct analyses that compare at-risk and depressed youth is a strength of the study. The opportunity to examine the trajectory of depressive symptoms in the D2K cohort over the lifespan is unique.

LIMITATIONS

As a longitudinal study, missing data were common.

CONCLUSION

T-RAD will allow data to be collected from multiple modalities on a clinically well-characterized sample. These data will drive important discoveries on diagnosis, treatment, and prevention of depression.

Borderline personality features in relationship to childhood trauma in unipolar depressive and bipolar disorders

BACKGROUND

Childhood trauma, including emotional neglect, emotional abuse, physical abuse, and sexual abuse, may contribute to borderline personality features like affective instability, identity problems, negative relationships, and self-harm. This study aims to explore how different types of childhood trauma affect these features in bipolar versus unipolar depressive disorders.

METHODS

We included 839 participants of the Netherlands Study of Depression and Anxiety (NESDA) with a lifetime diagnosis of major depressive disorder single episode (MDDS; N = 443), recurrent major depressive disorder (MDD-R; N = 331), or bipolar disorder (BD; N = 65). Multivariate regression was used to analyze data from the Childhood Trauma Interview and borderline features (from the self-report Personality Assessment Inventory).

RESULTS

On average, participants were 48.6 years old (SD: 12.6), with 69.2 % being women, and 50.3 % of participants assessed positive for childhood trauma. Adjusted analyses revealed that participants diagnosed with BD, followed by MDD-R, exhibited the highest number of borderline personality features. Additionally, within the entire group, a strong association was found between childhood trauma, especially emotional neglect, and the presence of borderline personality features.

CONCLUSION

Given the high prevalence of childhood trauma and borderline personality features, screening for these factors in individuals with mood disorders is crucial. Identifying these elements can inform and enhance the management of the often fluctuating and complex nature of these comorbid conditions, leading to more effective and tailored treatment strategies.

Association between depressive symptoms and cardiovascular diseases in the Korean geriatric population: A nationwide retrospective cohort study

INTRODUCTION

Depression has emerged as a modifiable risk factor for cardiovascular disease (CVD). However, evidence on whether depressive symptoms measured using a self-report questionnaire are associated with CVD incidence is scarce. Therefore, we aimed to investigate the association between depressive symptoms and CVD risk using data from national health examinations and insurance claim records.

METHODS

This retrospective cohort study included participants who underwent the Korean National Screening Program for Transitional Ages at age 66 years between 2007 and 2017. The presence of depressive symptoms was defined as affirmative responses to any of three questions (loss of activities and interests, worthlessness, and hopelessness) selected from the Geriatric Depression Scale. Incident composite CVD event included myocardial infarction, stroke, heart failure, and CVD death. The association between depressive symptoms and CVD risk was evaluated using hazard ratios (HRs) and 95 % confidence intervals (CIs) estimated with Cox proportional hazards models.

RESULTS

Among 88,765 participants (48.5 % women) aged 66 years, 4036 incident CVD events occurred during a mean follow-up of 6.8 years. Participants with depressive symptoms had a significantly higher risk of CVD than those without depressive symptoms (adjusted HR = 1.16 [95 % CI: 1.07-1.24]). The three individual depressive symptoms showed similar associations with CVD risk (loss of activities and interests, adjusted HR = 1.17 [95 % CI: 1.08-1.26]; worthlessness, 1.15 [1.03-1.29]; hopelessness, 1.13 [1.01-1.26]).

LIMITATIONS

The study was limited to participants aged 66 years. Despite extensive adjustment for potential confounders and multiple sensitivity analyses, residual confounding and reverse causality could not be ruled out.

CONCLUSION

The presence of depressive symptoms was associated with an increased risk of CVD. Screening for depressive symptoms in the general population may effectively mitigate the burden of CVD.

Estimation of the Global Disease Burden of Depression and Anxiety between 1990 and 2044: An Analysis of the Global Burden of Disease Study 2019

(1) Background: Depression and anxiety are the most common and severe mental disorders. This research estimated the prevalence and disease burden of depression and anxiety from 1990 to 2044. (2) Methods: Data on disease burden, population, and risk factors were identified and gathered from the Global Health Data Exchange database. The time trends, sex and age differences, key factors, and regional variations in and predictions of depression and anxiety were analyzed based on the age-standardized incidence rate, prevalence rate, and DALY rate. (3) Results: Our findings revealed that the burden of depression and anxiety was heavy. Specifically, the age-standardized DALY rate of depression started to decrease compared with trends related to anxiety disorders. Meanwhile, females bear a heavier burden for both depression and anxiety. Seniors and the middle-aged population carry the highest burden regarding mental disorders. Both high- and low-socio-demographic-index countries were found to be high-risk regions for depressive disorders. The disease burden attributed to childhood sexual abuse, bullying victimization, and intimate partner violence has increased since 1990. Finally, projections regarding depression and anxiety revealed geographic and age variations. (4) Conclusions: Public health researchers, officers, and organizations should take effective age-, sex-, and location-oriented measures.

Chronotype variability in epilepsy and clinical significance: scoping review

PURPOSE

Chronotype, which captures a person's daily preferences for activity and sleep, is still a poorly researched area in epilepsy research. Finding common chronotype characteristics in people with epilepsy (PWE) and explaining possible effects on seizure management are the main goals.

METHODS

Eleven large-scale investigations from 2010 to 2023 were examined in this scoping review. These studies included 1.167 PWE and 4.657 control subjects.

RESULTS

PWE had intermediate chronotypes more often than not. Adult patients were more morning-oriented overall, while pediatric cohorts were variable. Relationships between chronotype and seizure control were limited since only two studies in adults reported this and those results conflicted. An evening-type chronotype was found to be more common in generalized epilepsy than focal. The relationship of chronotype and specific antiseizure medication (ASM) therapy was not investigated.

CONCLUSIONS

The majority of PWE displayed an intermediate chronotype, but analyses based on age showed more nuanced trends, with children displaying variable patterns, adults generally tending toward morningness, and generalized epilepsy being associated with eveningness. This review underscores the importance of more research on the complex connections between epilepsy outcomes and chronotype. It emphasizes the need to study larger samples of PWE with carefully documented seizure control and ASM therapy, including dose and timing of administration to better understand the role of chronotype on epilepsy outcomes.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis

BACKGROUND

Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).

METHODS

Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).

RESULTS

Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).

CONCLUSIONS

Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Long-term effects of experiencing childhood parental death on mental and physical health: A NESDA study

Experiencing parental death during childhood is an adverse, potentially traumatic experience that may have substantial long-term effects on mental and physical well-being. The current study was based on data of the Netherlands Study of Depression and Anxiety to investigate mental health (i.e., depressive symptoms, anxiety symptoms, and suicidal ideation) and physical health outcomes (i.e., metabolic syndrome, telomere length, and perceived physical health) as well as health behaviour (i.e., smoking status, alcohol use, and physical activity) to provide more insight into the long-term outcomes after experiencing childhood parental death (CPD). For individuals who experienced CPD, we also investigated the role of loss-related factors in these associations, namely the age of the child when their parent passed away and gender of the deceased parent. Interviews and questionnaires were completed by adults between 18 and 65 years; 177 participants experienced CPD (mean age = 45.19, 61.6% female) and 2463 did not (mean age = 41.38, 66.6% female). Results showed no overall association between the experience of CPD and mental and physical health indices and health behaviour. Within the CPD group, experiencing CPD at a younger age was related to a higher likelihood of suicidal ideation. These findings seem to illustrate a general positive adjustment with regard to long-term health functioning after experiencing such an impactful life event. Future research should focus on individual differences in terms of adaptation, especially elucidating on contextual factors after the loss, such as the kind of support that is or is not provided by the surviving parent and/or other important individuals.

Childhood abuse v. neglect and risk for major psychiatric disorders

BACKGROUND

Childhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood experiences. As first step toward a more refined analysis of the impact of CM, our objective is to revisit the relation of abuse and neglect, major subtypes of CM, with symptoms across disorders.

METHODS

Three longitudinal studies of major depressive disorder (MDD, N = 1240), bipolar disorder (BD, N = 1339), and schizophrenia (SCZ, N = 577), each including controls (N = 881), were analyzed. Multivariate regression models were used to examine the relation between exposure to abuse, neglect, or their combination to the odds for MDD, BD, SCZ, and symptoms across disorders. Bidirectional Mendelian randomization (MR) was used to probe causality, using genetic instruments of abuse and neglect derived from UK Biobank data (N = 143 473).

RESULTS

Abuse was the stronger risk factor for SCZ (OR 3.51, 95% CI 2.17-5.67) and neglect for BD (OR 2.69, 95% CI 2.09-3.46). Combined CM was related to increased risk exceeding additive effects of abuse and neglect for MDD (RERI = 1.4) and BD (RERI = 1.1). Across disorders, abuse was associated with hallucinations (OR 2.16, 95% CI 1.55-3.01) and suicide attempts (OR 2.16, 95% CI 1.55-3.01) whereas neglect was associated with agitation (OR 1.24, 95% CI 1.02-1.51) and reduced need for sleep (OR 1.64, 95% CI 1.08-2.48). MR analyses were consistent with a bidirectional causal effect of abuse with SCZ (IVWforward = 0.13, 95% CI 0.01-0.24).

CONCLUSIONS

Childhood abuse and neglect are associated with different risks to psychiatric symptoms and disorders. Unraveling the origin of these differences may advance understanding of disease etiology and ultimately facilitate development of improved personalized treatment strategies.

The role of explicit and implicit self-esteem in the relationship between childhood trauma and adult depression and anxiety

BACKGROUND

Self-esteem is an important psychological concept that can be measured explicitly (reflective processing) and implicitly (associative processing). The current study examined 1) the association between childhood trauma (CT) and both explicit and implicit self-esteem, and 2) whether self-esteem mediated the association between CT and depression/anxiety.

METHODS

In 1479 adult participants of the Netherlands Study of Depression and Anxiety, CT was assessed with a semi-structured interview, depression/anxiety symptoms with self-report questionnaires and explicit and implicit self-esteem with the Rosenberg Self-Esteem Scale and Implicit Association Test, respectively. ANOVAs and regression analyses determined the association between CT (no/mild/severe CT), its subtypes (abuse/neglect) and self-esteem. Finally, we examined whether self-esteem mediated the relationship between CT and depression/anxiety.

RESULTS

Participants with CT reported lower explicit (but not lower implicit) self-esteem compared to those without CT (p < .001, partial η2 = 0.06). All CT types were associated with lower explicit self-esteem (p = .05 for sexual abuse, p < .001 for other CT types), while only emotional neglect significantly associated with lower implicit self-esteem after adjusting for sociodemographic characteristics (p = .03). Explicit self-esteem mediated the relationship between CT and depression/anxiety symptoms (proportion mediated = 48-77 %).

LIMITATIONS

The cross-sectional design precludes from drawing firm conclusions about the direction of the proposed relationships.

CONCLUSIONS

Our results suggested that the relationship between CT and depression/anxiety symptoms can at least partly be explained by explicit self-esteem. This is of clinical relevance as it points to explicit self-esteem as a potential relevant treatment target for people with CT.

Depression, Anxiety and Poor Sleep Quality are Associated with Chronotype and Financial Wellness in University Students

Background: Evidence suggests the importance of a person's chronotype in predicting various aspects of an individual's physical and mental health. While the effect of depression on sleep is well established, the impact of a person's specific sleep timing and chronotype on the prevalence of both depression and anxiety has yet to be fully understood, especially among university students, vulnerable to mental health problems. In addition, other factors also seem to influence the occurrence of depression and anxiety among students as well as their quality of sleep, one of which being the students' financial wellness. The objective was to evaluate the association between chronotype and the severity and prevalence of depression among Lebanese university students, while also taking into account the possible connection between chronotype and financial wellness and both anxiety and sleep quality. Methods: This cross-sectional study was conducted between December 2021 and February 2022; 330 Lebanese university students was included (mean age 21.75 ± 2.43; 67.3% females). Results: The majority of the Lebanese university students in our sample were found to have an intermediate typology (63.0%), followed by the evening typology, which appeared to constitute 28.2% of the sample, while only 8.8% possessed a morning typology. In this study, having an intermediate or evening typology compared to a morning one was significantly associated with higher depression and worse sleep quality. In addition, having an evening chronotype compared to a morningness propensity was significantly associated with more anxiety. Conclusion: This study found a positive association between an evening typology (chronotype) and higher depression and anxiety and poorer quality of sleep. Although preliminary and based on cross-sectional data, this research could help provide a better understanding of the different chronotypes among university students, and of the possible increased susceptibility of some of these typologies (i.e., evening-type) to mental health problems.

Antidepressant Exposure and DNA Methylation: Insights from a Methylome-Wide Association Study

Importance

Understanding antidepressant mechanisms could help design more effective and tolerated treatments.

Objective

Identify DNA methylation (DNAm) changes associated with antidepressant exposure.

Design

Case-control methylome-wide association studies (MWAS) of antidepressant exposure were performed from blood samples collected between 2006-2011 in Generation Scotland (GS). The summary statistics were tested for enrichment in specific tissues, gene ontologies and an independent MWAS in the Netherlands Study of Depression and Anxiety (NESDA). A methylation profile score (MPS) was derived and tested for its association with antidepressant exposure in eight independent cohorts, alongside prospective data from GS.

Setting

Cohorts; GS, NESDA, FTC, SHIP-Trend, FOR2107, LBC1936, MARS-UniDep, ALSPAC, E-Risk, and NTR.

Participants

Participants with DNAm data and self-report/prescription derived antidepressant exposure.

Main Outcomes and Measures

Whole-blood DNAm levels were assayed by the EPIC/450K Illumina array (9 studies, N exposed = 661, N unexposed = 9,575) alongside MBD-Seq in NESDA (N exposed = 398, N unexposed = 414). Antidepressant exposure was measured by self- report and/or antidepressant prescriptions.

Results

The self-report MWAS (N = 16,536, N exposed = 1,508, mean age = 48, 59% female) and the prescription-derived MWAS (N = 7,951, N exposed = 861, mean age = 47, 59% female), found hypermethylation at seven and four DNAm sites (p < 9.42x10 -8 ), respectively. The top locus was cg26277237 ( KANK1, p self-report = 9.3x10 -13 , p prescription = 6.1x10 -3 ). The self-report MWAS found a differentially methylated region, mapping to DGUOK-AS1 ( p adj = 5.0x10 -3 ) alongside significant enrichment for genes expressed in the amygdala, the "synaptic vesicle membrane" gene ontology and the top 1% of CpGs from the NESDA MWAS (OR = 1.39, p < 0.042). The MPS was associated with antidepressant exposure in meta-analysed data from external cohorts (N studies = 9, N = 10,236, N exposed = 661, f3 = 0.196, p < 1x10 -4 ).

Conclusions and Relevance

Antidepressant exposure is associated with changes in DNAm across different cohorts. Further investigation into these changes could inform on new targets for antidepressant treatments.

3 Key Points

Question: Is antidepressant exposure associated with differential whole blood DNA methylation?Findings: In this methylome-wide association study of 16,536 adults across Scotland, antidepressant exposure was significantly associated with hypermethylation at CpGs mapping to KANK1 and DGUOK-AS1. A methylation profile score trained on this sample was significantly associated with antidepressant exposure (pooled f3 [95%CI]=0.196 [0.105, 0.288], p < 1x10 -4 ) in a meta-analysis of external datasets. Meaning: Antidepressant exposure is associated with hypermethylation at KANK1 and DGUOK-AS1 , which have roles in mitochondrial metabolism and neurite outgrowth. If replicated in future studies, targeting these genes could inform the design of more effective and better tolerated treatments for depression.

Dynamic reconfigurations of brain networks in depressive and anxiety disorders: The influence of antidepressants

Major Depressive Disorder (MDD) and anxiety disorders are highly comorbid recurrent psychiatric disorders. Reduced dynamic reconfiguration of brain regions across subnetworks may play a critical role underlying these deficits, with indications of normalization after treatment with antidepressants. This study investigated dynamic reconfigurations in controls and individuals with a current MDD and/or anxiety disorder including antidepressant users and non-users in a large sample (N = 207) of adults. We quantified the number of subnetworks a region switched to (promiscuity) as well as the total number of switches (flexibility). Average whole-brain (i.e., global) values and subnetwork-specific values were compared between diagnosis and antidepressant groups. No differences in reconfiguration dynamics were found between individuals with a current MDD (N = 49), anxiety disorder (N = 46), comorbid MDD and anxiety disorder (N = 55), or controls (N = 57). Global and sensorimotor network (SMN) promiscuity and flexibility were higher in antidepressant users (N = 49, regardless of diagnosis) compared to non-users (N = 101) and controls. Dynamic reconfigurations were considerably higher in antidepressant users relative to non-users and controls, but not significantly altered in individuals with a MDD and/or anxiety disorder. The increase in antidepressant users was apparent across the whole brain and in the SMN when investigating subnetworks. These findings help disentangle how antidepressants improve symptoms.

The Mood and Resilience in Offspring (MARIO) project: a longitudinal cohort study among offspring of parents with and without a mood disorder

BACKGROUND

One of the most robust risk factors for developing a mood disorder is having a parent with a mood disorder. Unfortunately, mechanisms explaining the transmission of mood disorders from one generation to the next remain largely elusive. Since timely intervention is associated with a better outcome and prognosis, early detection of intergenerational transmission of mood disorders is of paramount importance. Here, we describe the design of the Mood and Resilience in Offspring (MARIO) cohort study in which we investigate: 1. differences in clinical, biological and environmental (e.g., psychosocial factors, substance use or stressful life events) risk and resilience factors in children of parents with and without mood disorders, and 2. mechanisms of intergenerational transmission of mood disorders via clinical, biological and environmental risk and resilience factors.

METHODS

MARIO is an observational, longitudinal cohort study that aims to include 450 offspring of parents with a mood disorder (uni- or bipolar mood disorders) and 100-150 offspring of parents without a mood disorder aged 10-25 years. Power analyses indicate that this sample size is sufficient to detect small to medium sized effects. Offspring are recruited via existing Dutch studies involving patients with a mood disorder and healthy controls, for which detailed clinical, environmental and biological data of the index-parent (i.e., the initially identified parent with or without a mood disorder) is available. Over a period of three years, four assessments will take place, in which extensive clinical, biological and environmental data and data on risk and resilience are collected through e.g., blood sampling, face-to-face interviews, online questionnaires, actigraphy and Experience Sampling Method assessment. For co-parents, information on demographics, mental disorder status and a DNA-sample are collected.

DISCUSSION

The MARIO cohort study is a large longitudinal cohort study among offspring of parents with and without mood disorders. A unique aspect is the collection of granular data on clinical, biological and environmental risk and resilience factors in offspring, in addition to available parental data on many similar factors. We aim to investigate the mechanisms underlying intergenerational transmission of mood disorders, which will ultimately lead to better outcomes for offspring at high familial risk.

The role of emotion recognition in the intergenerational transmission of child maltreatment: A multigenerational family study

BACKGROUND

Understanding how child maltreatment is passed down from one generation to the next is crucial for the development of intervention and prevention strategies that may break the cycle of child maltreatment. Changes in emotion recognition due to childhood maltreatment have repeatedly been found, and may underly the intergenerational transmission of child maltreatment.

OBJECTIVE

In this study we, therefore, examined whether the ability to recognize emotions plays a role in the intergenerational transmission of child abuse and neglect.

PARTICIPANTS AND SETTING

A total of 250 parents (104 males, 146 females) were included that participated in a three-generation family study.

METHOD

Participants completed an emotion recognition task in which they were presented with series of photographs that depicted the unfolding of facial expressions from neutrality to the peak emotions anger, fear, happiness, and sadness. Multi-informant measures were used to examine experienced and perpetrated child maltreatment.

RESULTS

A history of abuse, but not neglect, predicted a shorter reaction time to identify fear and anger. In addition, parents who showed higher levels of neglectful behavior made more errors in identifying fear, whereas parents who showed higher levels of abusive behavior made more errors in identifying anger. Emotion recognition did not mediate the association between experienced and perpetrated child maltreatment.

CONCLUSIONS

Findings highlight the importance of distinguishing between abuse and neglect when investigating the precursors and sequalae of child maltreatment. In addition, the effectiveness of interventions that aim to break the cycle of abuse and neglect could be improved by better addressing the specific problems with emotion processing of abusive and neglectful parents.

Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we?

The question of whether immune dysfunction contributes to risk of psychiatric disorders has long been a subject of interest. To assert this hypothesis a plethora of correlative evidence has been accumulated from the past decades; however, a variety of technical and practical obstacles impeded on a cause-effect interpretation of these data. With the advent of large-scale omics technology and advanced statistical models, particularly Mendelian randomization, new studies testing this old hypothesis are accruing. Here we synthesize these new findings from genomics and genetic causal inference studies on the role of immune dysfunction in major psychiatric disorders and reconcile these new data with pre-omics findings. By reconciling these evidences, we aim to identify key gaps and propose directions for future studies in the field.

Multimodal Data Integration Advances Longitudinal Prediction of the Naturalistic Course of Depression and Reveals a Multimodal Signature of Remission During 2-Year Follow-up

BACKGROUND

The ability to predict the disease course of individuals with major depressive disorder (MDD) is essential for optimal treatment planning. Here, we used a data-driven machine learning approach to assess the predictive value of different sets of biological data (whole-blood proteomics, lipid metabolomics, transcriptomics, genetics), both separately and added to clinical baseline variables, for the longitudinal prediction of 2-year remission status in MDD at the individual-subject level.

METHODS

Prediction models were trained and cross-validated in a sample of 643 patients with current MDD (2-year remission n = 325) and subsequently tested for performance in 161 individuals with MDD (2-year remission n = 82).

RESULTS

Proteomics data showed the best unimodal data predictions (area under the receiver operating characteristic curve = 0.68). Adding proteomic to clinical data at baseline significantly improved 2-year MDD remission predictions (area under the receiver operating characteristic curve = 0.63 vs. 0.78, p = .013), while the addition of other omics data to clinical data did not yield significantly improved model performance. Feature importance and enrichment analysis revealed that proteomic analytes were involved in inflammatory response and lipid metabolism, with fibrinogen levels showing the highest variable importance, followed by symptom severity. Machine learning models outperformed psychiatrists' ability to predict 2-year remission status (balanced accuracy = 71% vs. 55%).

CONCLUSIONS

This study showed the added predictive value of combining proteomic data, but not other omics data, with clinical data for the prediction of 2-year remission status in MDD. Our results reveal a novel multimodal signature of 2-year MDD remission status that shows clinical potential for individual MDD disease course predictions from baseline measurements.

Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health's 1H-NMR Metabolomics Platform

1H-NMR metabolomics data is increasingly used to track health and disease. Nightingale Health, a major supplier of 1H-NMR metabolomics, has recently updated the quantification strategy to further align with clinical standards. Such updates, however, might influence backward replicability, particularly affecting studies with repeated measures. Using data from BBMRI-NL consortium (~28,000 samples from 28 cohorts), we compared Nightingale data, originally released in 2014 and 2016, with a re-quantified version released in 2020, of which both versions were based on the same NMR spectra. Apart from two discontinued and twenty-three new analytes, we generally observe a high concordance between quantification versions with 73 out of 222 (33%) analytes showing a mean ρ > 0.9 across all cohorts. Conversely, five analytes consistently showed lower Spearman's correlations (ρ < 0.7) between versions, namely acetoacetate, LDL-L, saturated fatty acids, S-HDL-C, and sphingomyelins. Furthermore, previously trained multi-analyte scores, such as MetaboAge or MetaboHealth, might be particularly sensitive to platform changes. Whereas MetaboHealth replicated well, the MetaboAge score had to be retrained due to use of discontinued analytes. Notably, both scores in the re-quantified data recapitulated mortality associations observed previously. Concluding, we urge caution in utilizing different platform versions to avoid mixing analytes, having different units, or simply being discontinued.

Suicidal ideation across depressive episodes: 9-year longitudinal cohort study

BACKGROUND

Depression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across episodes, some evidence indicates that suicidal ideation may be an exception. However, these findings warrant replication, especially over longer periods and across multiple episodes.

AIMS

To assess the relative stability of suicidal ideation in comparison with other non-core depressive symptoms across episodes.

METHOD

We examined 490 individuals with current major depressive disorder (MDD) at baseline and at least one subsequent episode during 9-year follow-up within the Netherlands Study of Depression and Anxiety (NESDA). The Inventory of Depressive Symptomatology (IDS) was used to assess DSM-5 non-core MDD symptoms (fatigue, appetite/weight change, sleep disturbance, psychomotor disturbance, concentration difficulties, worthlessness/guilt, suicidal ideation) at baseline and 2-, 4-, 6- and 9-year follow-up. We examined consistency in symptom presentation (i.e. whether the symptom met the diagnostic threshold, based on a binary categorisation of the IDS) using kappa (κ) and percentage agreement, and stability in symptom severity using Spearman correlation, based on the continuous IDS scores.

RESULTS

Out of all non-core depressive symptoms, insomnia appeared the most stable across episodes (r = 0.55-0.69, κ = 0.31-0.47) and weight decrease the least stable (r = 0.03-0.33, κ = 0.06-0.19). For suicidal ideation, correlations across episodes ranged from r = 0.36 to r = 0.55 and consistency ranged from κ = 0.28 to κ = 0.49.

CONCLUSIONS

Suicidal ideation is moderately stable in recurrent depression over 9 years. Contrary to prior reports, however, it does not exhibit substantially more stability than most other non-core symptoms of depression.

Functional MRI correlates of emotion regulation in major depressive disorder related to depressive disease load measured over nine years

Major Depressive Disorder (MDD) often is a recurrent and chronic disorder. We investigated the neurocognitive underpinnings of the incremental risk for poor disease course by exploring relations between enduring depression and brain functioning during regulation of negative and positive emotions using cognitive reappraisal. We used fMRI-data from the longitudinal Netherlands Study of Depression and Anxiety acquired during an emotion regulation task in 77 individuals with MDD. Task-related brain activity was related to disease load, calculated from presence and severity of depression in the preceding nine years. Additionally, we explored task related brain-connectivity. Brain functioning in individuals with MDD was further compared to 35 controls to explore overlap between load-effects and general effects related to MDD history/presence. Disease load was not associated with changes in affect or with brain activity, but with connectivity between areas essential for processing, integrating and regulating emotional information during downregulation of negative emotions. Results did not overlap with general MDD-effects. Instead, MDD was generally associated with lower parietal activity during downregulation of negative emotions. During upregulation of positive emotions, disease load was related to connectivity between limbic regions (although driven by symptomatic state), and connectivity between frontal, insular and thalamic regions was lower in MDD (vs controls). Results suggest that previous depressive load relates to brain connectivity in relevant networks during downregulation of negative emotions. These abnormalities do not overlap with disease-general abnormalities and could foster an incremental vulnerability to recurrence or chronicity of MDD. Therefore, optimizing emotion regulation is a promising therapeutic target for improving long-term MDD course.

A network analysis of depressive symptoms and metabolomics

BACKGROUND

Depression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models.

METHODS

We used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later.

RESULTS

The network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave.

CONCLUSIONS

The somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis

BACKGROUND

Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium.

METHODS

The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2).

RESULTS

No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23).

CONCLUSIONS

Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

The Metabolome-Wide Signature of Major Depressive Disorder

Major Depressive Disorder (MDD) is an often-chronic condition with substantial molecular alterations and pathway dysregulations involved. Single metabolite, pathway and targeted metabolomics platforms have indeed revealed several metabolic alterations in depression including energy metabolism, neurotransmission and lipid metabolism. More comprehensive coverage of the metabolome is needed to further specify metabolic dysregulation in depression and reveal previously untargeted mechanisms. Here we measured 820 metabolites using the metabolome-wide Metabolon platform in 2770 subjects from a large Dutch clinical cohort with extensive depression clinical phenotyping (1101 current MDD, 868 remitted MDD, 801 healthy controls) at baseline and 1805 subjects at 6-year follow up (327 current MDD, 1045 remitted MDD, 433 healthy controls). MDD diagnosis was based on DSM-IV psychiatric interviews. Depression severity was measured with the Inventory of Depressive Symptomatology self-report. Associations between metabolites and MDD status and depression severity were assessed at baseline and at the 6-year follow-up. Metabolites consistently associated with MDD status or depression severity on both occasions were examined in Mendelian randomization (MR) analysis using metabolite (N=14,000) and MDD (N=800,000) GWAS results. At baseline, 139 and 126 metabolites were associated with current MDD status and depression severity, respectively, with 79 overlapping metabolites. Six years later, 34 out of the 79 metabolite associations were subsequently replicated. Downregulated metabolites were enriched with long-chain monounsaturated (P=6.7e-07) and saturated (P=3.2e-05) fatty acids and upregulated metabolites with lysophospholipids (P=3.4e-4). Adding BMI to the models changed results only marginally. MR analyses showed that genetically-predicted higher levels of the lysophospholipid 1-linoleoyl-GPE (18:2) were associated with greater risk of depression. The identified metabolome-wide profile of depression (severity) indicated altered lipid metabolism with downregulation of long-chain fatty acids and upregulation of lysophospholipids, for which causal involvement was suggested using genetic tools. This metabolomics signature offers a window on depression pathophysiology and a potential access point for the development of novel therapeutic approaches.

Whole Person Modeling: a transdisciplinary approach to mental health research

The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.

Methylome-wide association study of anxiety disorders

Anxiety Disorders (ANX) such as panic disorder, generalized anxiety disorder, and phobias, are highly prevalent conditions that are moderately heritable. Evidence suggests that DNA methylation may play a role, as it is involved in critical adaptations to changing environments. Applying an enrichment-based sequencing approach covering nearly 28 million autosomal CpG sites, we conducted a methylome-wide association study (MWAS) of lifetime ANX in 1132 participants (618 cases/514 controls) from the Netherlands Study of Depression and Anxiety. Using epigenomic deconvolution, we performed MWAS for the main cell types in blood: granulocytes, T-cells, B-cells and monocytes. Cell-type specific analyses identified 280 and 82 methylome-wide significant associations (q-value < 0.1) in monocytes and granulocytes, respectively. Our top finding in monocytes was located in ZNF823 on chromosome 19 (p = 1.38 × 10-10) previously associated with schizophrenia. We observed significant overlap (p < 1 × 10-06) with the same direction of effect in monocytes (210 sites), T-cells (135 sites), and B-cells (727 sites) between this Discovery MWAS signal and a comparable replication dataset from the Great Smoky Mountains Study (N = 433). Overlapping Discovery-Replication MWAS signal was enriched for findings from published GWAS of ANX, major depression, and post-traumatic stress disorder. In monocytes, two specific sites in the FZR1 gene showed significant replication after Bonferroni correction with an additional 15 nominally replicated sites in monocytes and 4 in T-cells. FZR1 regulates neurogenesis in the hippocampus, and its knockout leads to impairments in associative fear memory and long-term potentiation in mice. In the largest and most extensive methylome-wide study of ANX, we identified replicable methylation sites located in genes of potential relevance for brain mechanisms of psychiatric conditions.

Lifestyle-related risk factors and their cumulative associations with hippocampal and total grey matter volume across the adult lifespan: A pooled analysis in the European Lifebrain consortium

BACKGROUND

Lifestyle-related risk factors, such as obesity, physical inactivity, short sleep, smoking and alcohol use, have been associated with low hippocampal and total grey matter volumes (GMV). However, these risk factors have mostly been assessed as separate factors, leaving it unknown if variance explained by these factors is overlapping or additive. We investigated associations of five lifestyle-related factors separately and cumulatively with hippocampal and total GMV, pooled across eight European cohorts.

METHODS

We included 3838 participants aged 18-90 years from eight cohorts of the European Lifebrain consortium. Using individual person data, we performed cross-sectional meta-analyses on associations of presence of lifestyle-related risk factors separately (overweight/obesity, physical inactivity, short sleep, smoking, high alcohol use) as well as a cumulative unhealthy lifestyle score (counting the number of present lifestyle-related risk factors) with FreeSurfer-derived hippocampal volume and total GMV. Lifestyle-related risk factors were defined according to public health guidelines.

RESULTS

High alcohol use was associated with lower hippocampal volume (r = -0.10, p = 0.021), and overweight/obesity with lower total GMV (r = -0.09, p = 0.001). Other lifestyle-related risk factors were not significantly associated with hippocampal volume or GMV. The cumulative unhealthy lifestyle score was negatively associated with total GMV (r = -0.08, p = 0.001), but not hippocampal volume (r = -0.01, p = 0.625).

CONCLUSIONS

This large pooled study confirmed the negative association of some lifestyle-related risk factors with hippocampal volume and GMV, although with small effect sizes. Lifestyle factors should not be seen in isolation as there is evidence that having multiple unhealthy lifestyle factors is associated with a linear reduction in overall brain volume.

Transdiagnostic factors predicting the 2-year disability outcome in patients with anxiety and depressive disorders

BACKGROUND

Both anxiety and depressive disorders are associated with significant long-term disability. Since experienced impairments vary between patients independent of diagnosis and disease severity, identifying transdiagnostic factors that predict the course of disability may provide new targets to reduce disability. This study examines transdiagnostic factors predicting the 2-year disability outcome in patients with anxiety and/or depressive disorders (ADD), focusing on potentially malleable factors.

METHODS

Six hundred fifteen participants with a current diagnosis of ADD from the Netherlands Study of Depression and Anxiety (NESDA) were included. Disability was assessed at baseline and after 2 years of follow-up, using the 32-item WHODAS II questionnaire. Transdiagnostic predictors of 2-year disability outcome were identified using linear regression analysis.

RESULTS

In univariable analyses, transdiagnostic factors associated with the 2-year disability outcome were locus of control (standardized β = -0.116, p = 0.011), extraversion (standardized β = -0.123 p = 0.004) and experiential avoidance (standardized β = 0.139, p = 0.001). In multivariable analysis, extraversion had a unique predictive value (standardized β = -0.143 p = 0.003). A combination of sociodemographic, clinical and transdiagnostic variables resulted in an explained variance (R2) of 0.090). The explained variance of a combination of transdiagnostic factors was 0.050.

CONCLUSION

The studied transdiagnostic variables explain a small but unique part of variability in the 2-year disability outcome. Extraversion is the only malleable transdiagnostic factor predictive of the course of disability independent of other variables. Due to the small contribution to the variance in the disability outcome, the clinical relevance of targeting extraversion seems limited. However, its predictive value is comparable to that of accepted disease severity measures, supporting the importance of looking beyond using disease severity measures as predictors. Furthermore, studies including extraversion in combination with other transdiagnostic and environmental factors may elucidate the unexplained part of variability of the course of disability in patients with ADD.

Depression among Turkish and Moroccan immigrant populations in Northwestern Europe: a systematic review of prevalence and correlates

BACKGROUND

This systematic review aimed to synthesize the prevalence and correlates of depressive disorders and symptoms of Turkish and Moroccan immigrant populations in Northwestern Europe, formulating evidence-informed recommendations for clinical practice.

METHODS

We conducted a systematic search in PsycINFO, MEDLINE, Science Direct, Web of Knowledge, and Cochrane databases for records up to March 2021. Peer-reviewed studies on adult populations that included instruments assessing prevalence and/or correlates of depression in Turkish and Moroccan immigrant populations met inclusion criteria and were assessed in terms of methodological quality. The review followed the relevant sections of the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting (PRISMA) guideline.

RESULTS

We identified 51 relevant studies of observational design. Prevalence of depression was consistently higher among people who had an immigrant background, compared to those who did not. This difference seemed to be more pronounced for Turkish immigrants (especially older adults, women, and outpatients with psychosomatic complaints). Ethnicity and ethnic discrimination were identified as salient, positive, independent correlates of depressive psychopathology. Acculturation strategy (high maintenance) was related to higher depressive psychopathology in Turkish groups, while religiousness appeared protective in Moroccan groups. Current research gaps concern psychological correlates, second- and third-generation populations, and sexual and gender minorities.

CONCLUSION

Compared to native-born populations, Turkish immigrants consistently showed the highest prevalence of depressive disorder, while Moroccan immigrants showed similar to rather moderately elevated rates. Ethnic discrimination and acculturation were more often related to depressive symptomatology than socio-demographic correlates. Ethnicity seems to be a salient, independent correlate of depression among Turkish and Moroccan immigrant populations in Northwestern Europe.

Cardiovascular risk indicators among depressed persons: A special case?

BACKGROUND

Traditional cardiovascular risk indicators only partially explain cardiovascular risks in depressed persons. Depressed persons may exhibit a profile of cardiovascular risk indicators that goes beyond traditional cardiovascular risk indicators, such as symptom severity, insomnia, loneliness and neuroticism, yet research on the added value of these depression-related characteristics in predicting cardiovascular risks of depressed persons is scarce.

METHODS

Data from N = 1028 depressed Dutch adults without prevalent CVD were derived from two longitudinal depression cohort studies. The outcome was medication-confirmed self-reported CVD. Fifteen depression-related clinical and psychological characteristics were included and tested against traditional cardiovascular risk indicators. Data were analysed using Cox regression models. Incremental values of these characteristics were calculated using c-statistics.

RESULTS

After a median follow-up of 65.3 months, 12.7% of the participants developed CVD. Only anxiety and depressive symptom severity were associated with incident CVD beyond traditional cardiovascular risk indicators. The c-statistic of the model with traditional cardiovascular risk indicators was 85.47%. This increased with 0.56 or 0.33 percentage points after inclusion of anxiety or depression severity, respectively.

LIMITATIONS

Other relevant depression-related characteristics were not available in the datasets used.

CONCLUSION

Anxiety and depressive symptom severity were indicative of an increased cardiovascular risk. Including these as additional risk indicators barely improved the ability to assess cardiovascular risks in depressed persons. Although traditional cardiovascular risk indicators performed well in depressed persons, existing risk prediction algorithms need to be validated in depressed persons.

Increased affective reactivity among depressed individuals can be explained by floor effects: An experience sampling study

Experience sampling studies into daily-life affective reactivity indicate that depressed individuals react more strongly to both positive and negative stimuli than non-depressed individuals, particularly on negative affect (NA). Given the different mean levels of both positive affect (PA) and NA between patients and controls, such findings may be influenced by floor/ceiling effects, leading to violations of the normality and homoscedasticity assumptions underlying the used statistical models. Affect distributions in prior studies suggest that this may have particularly influenced NA-reactivity findings. Here, we investigated the influence of floor/ceiling effects on the observed PA- and NA-reactivity to both positive and negative events. Data came from 346 depressed, non-depressed, and remitted participants from the Netherlands Study of Depression and Anxiety (NESDA). In PA-reactivity analyses, no floor/ceiling effects and assumption violations were observed, and PA-reactivity to positive events, but not negative events, was significantly increased in the depressed and remitted groups versus the non-depressed group. However, NA-scores exhibited a floor effect in the non-depressed group and naively estimated models violated model assumptions. When these violations were accounted for in subsequent analyses, group differences in NA-reactivity that had been present in the naive models were no longer observed. In conclusion, we found increased PA-reactivity to positive events but no evidence of increased NA-reactivity in depressed individuals when accounting for violations of assumptions. The results indicate that affective-reactivity results are very sensitive to modeling choices and that previously observed increased NA-reactivity in depressed individuals may (partially) reflect unaddressed assumption violations resulting from floor effects in NA.

Normal range CAG repeat size variations in the HTT gene are associated with an adverse lipoprotein profile partially mediated by body mass index

Tandem cytosine-adenine-guanine (CAG) repeat sizes of 36 or more in the huntingtin gene (HTT) cause Huntington's disease (HD). Apart from neuropsychiatric complications, the disease is also accompanied by metabolic dysregulation and weight loss, which contribute to a progressive functional decline. Recent studies also reported an association between repeats below the pathogenic threshold (<36) for HD and body mass index (BMI), suggesting that HTT repeat sizes in the non-pathogenic range are associated with metabolic dysregulation. In this study, we hypothesized that HTT repeat sizes < 36 are associated with metabolite levels, possibly mediated through reduced BMI. We pooled data from three European cohorts (n = 10 228) with genotyped HTT CAG repeat size and metabolomic measurements. All 145 metabolites were measured on the same targeted platform in all studies. Multilevel mixed-effects analysis using the CAG repeat size in HTT identified 67 repeat size metabolite associations. Overall, the metabolomic profile associated with larger CAG repeat sizes in HTT were unfavorable-similar to those of higher risk of coronary artery disease and type 2 diabetes-and included elevated levels of amino acids, fatty acids, low-density lipoprotein (LDL)-, very low-density lipoprotein- and intermediate density lipoprotein (IDL)-related metabolites while with decreased levels of very large high-density lipoprotein (HDL)-related metabolites. Furthermore, the associations of 50 metabolites, in particular, specific very large HDL-related metabolites, were mediated by lower BMI. However, no mediation effect was found for 17 metabolites related to LDL and IDL. In conclusion, our findings indicate that large non-pathogenic CAG repeat sizes in HTT are associated with an unfavorable metabolomic profile despite their association with a lower BMI.

Associations of emotional social support, depressive symptoms, chronic stress, and anxiety with hard cardiovascular disease events in the United States: the multi-ethnic study of atherosclerosis (MESA)

BACKGROUND

Cardiovascular diseases (CVDs) are a major cause of morbidity and mortality around the globe and psychosocial factors are not sufficiently understood.

AIM

In the current study, we aimed to evaluate the role of different psychosocial factors including depressive symptoms, chronic stress, anxiety, and emotional social support (ESS) on the incidence of hard CVD (HCVD).

METHODS

We examined the association of psychosocial factors and HCVD incidence amongst 6,779 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Using physician reviewers' adjudication of CVD events incident, depressive symptoms, chronic stress, anxiety, emotional social support scores were measured by validated scales. We used Cox proportional Hazards (PH) models with psychosocial factors in several of the following approaches: (1) Continuous; (2) categorical; and (3) spline approach. No violation of the PH was found. The model with the lowest AIC value was chosen.

RESULTS

Over an 8.46-year median follow-up period, 370 participants experienced HCVD. There was not a statistically significant association between anxiety and HCVD (95%CI) for the highest versus the lowest category [HR = 1.51 (0.80-2.86)]. Each one point higher score for chronic stress (HR, 1.18; 95% CI, 1.08-1.29) and depressive symptoms (HR, 1.02; 95% CI, 1.01-1.03) was associated with a higher risk of HCVD in separate models. In contrary, emotional social support (HR, 0.98; 95% CI, 0.96-0.99) was linked with a lower risk of HCVD.

CONCLUSIONS

Higher levels of chronic stress is associated with greater risk of incident HCVD whereas ESS has a protective association.

Dissection of depression heterogeneity using proteomic clusters

BACKGROUND

The search for relevant biomarkers of major depressive disorder (MDD) is challenged by heterogeneity; biological alterations may vary in patients expressing different symptom profiles. Moreover, most research considers a limited number of biomarkers, which may not be adequate for tagging complex network-level mechanisms. Here we studied clusters of proteins and examined their relation with MDD and individual depressive symptoms.

METHODS

The sample consisted of 1621 subjects from the Netherlands Study of Depression and Anxiety (NESDA). MDD diagnoses were based on DSM-IV criteria and the Inventory of Depressive Symptomatology questionnaire measured endorsement of 30 symptoms. Serum protein levels were detected using a multi-analyte platform (171 analytes, immunoassay, Myriad RBM DiscoveryMAP 250+). Proteomic clusters were computed using weighted correlation network analysis (WGCNA).

RESULTS

Six proteomic clusters were identified, of which one was nominally significantly associated with current MDD (p = 9.62E-03, Bonferroni adj. p = 0.057). This cluster contained 21 analytes and was enriched with pathways involved in inflammation and metabolism [including C-reactive protein (CRP), leptin and insulin]. At the individual symptom level, this proteomic cluster was associated with ten symptoms, among which were five atypical, energy-related symptoms. After correcting for several health and lifestyle covariates, hypersomnia, increased appetite, panic and weight gain remained significantly associated with the cluster.

CONCLUSIONS

Our findings support the idea that alterations in a network of proteins involved in inflammatory and metabolic processes are present in MDD, but these alterations map predominantly to clinical symptoms reflecting an imbalance between energy intake and expenditure.

Unhealthy lifestyle impacts on biological systems involved in stress response: hypothalamic-pituitary-adrenal axis, inflammation and autonomous nervous system

An unhealthy lifestyle has a critical role in the pathogenesis and course of several chronic disorders. It has been hypothesized that lifestyle may also impact biological systems involved in stress response. A global index of unhealthy lifestyle was calculated based on the cumulative presence of five self-reported lifestyle habits (smoking, excessive alcohol use, drug use, low physical activity and short sleep) in 2783 participants (18-65 years) from the Netherlands Study of Depression and Anxiety. The functioning of biological stress systems was based on multiple physiological measures of cortisol, inflammatory cytokines and autonomic cardiac activity. The unhealthy lifestyle index was associated with hyperactivity of hypothalamus-pituitary-adrenal axis and increased inflammation, indicating that with increasing unhealthy habits, the level of biological stress increases. No association with the autonomic nervous system activity was observed; however, the use of drugs increased parasympathetic cardiac activity and significantly impacted on ANS. Results were not impacted by a recent episode of depression or anxiety disorder. An unhealthy lifestyle may unfavorably impact on biological systems involved in stress response, which may underlie progression of several psychiatric as well as somatic chronic disorders.

Depression, cardiometabolic disease, and their co-occurrence after childhood maltreatment: an individual participant data meta-analysis including over 200,000 participants

BACKGROUND

Childhood maltreatment is associated with depression and cardiometabolic disease in adulthood. However, the relationships with these two diseases have so far only been evaluated in different samples and with different methodology. Thus, it remains unknown how the effect sizes magnitudes for depression and cardiometabolic disease compare with each other and whether childhood maltreatment is especially associated with the co-occurrence ("comorbidity") of depression and cardiometabolic disease. This pooled analysis examined the association of childhood maltreatment with depression, cardiometabolic disease, and their comorbidity in adulthood.

METHODS

We carried out an individual participant data meta-analysis on 13 international observational studies (N = 217,929). Childhood maltreatment comprised self-reports of physical, emotional, and/or sexual abuse before 18 years. Presence of depression was established with clinical interviews or validated symptom scales and presence of cardiometabolic disease with self-reported diagnoses. In included studies, binomial and multinomial logistic regressions estimated sociodemographic-adjusted associations of childhood maltreatment with depression, cardiometabolic disease, and their comorbidity. We then additionally adjusted these associations for lifestyle factors (smoking status, alcohol consumption, and physical activity). Finally, random-effects models were used to pool these estimates across studies and examined differences in associations across sex and maltreatment types.

RESULTS

Childhood maltreatment was associated with progressively higher odds of cardiometabolic disease without depression (OR [95% CI] = 1.27 [1.18; 1.37]), depression without cardiometabolic disease (OR [95% CI] = 2.68 [2.39; 3.00]), and comorbidity between both conditions (OR [95% CI] = 3.04 [2.51; 3.68]) in adulthood. Post hoc analyses showed that the association with comorbidity was stronger than with either disease alone, and the association with depression was stronger than with cardiometabolic disease. Associations remained significant after additionally adjusting for lifestyle factors, and were present in both males and females, and for all maltreatment types.

CONCLUSIONS

This meta-analysis revealed that adults with a history of childhood maltreatment suffer more often from depression and cardiometabolic disease than their non-exposed peers. These adults are also three times more likely to have comorbid depression and cardiometabolic disease. Childhood maltreatment may therefore be a clinically relevant indicator connecting poor mental and somatic health. Future research should investigate the potential benefits of early intervention in individuals with a history of maltreatment on their distal mental and somatic health (PROSPERO CRD42021239288).

The association between adiposity and atypical energy-related symptoms of depression: A role for metabolic dysregulations

BACKGROUND

Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations.

METHOD

Data were from NEO (n = 5734 individuals) and NESDA (n = 2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations.

RESULTS

We validated that both GRS-MUA and GRS-MHA were associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g., fasting glucose and HDL-cholesterol) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (β = 0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (β = -0.01, 95%CI: -0.03; 0.01).

CONCLUSION

These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions.

A prospective cohort study of depression (PROUD) in China: rationale and design

Background

Major depressive disorder (MDD) imposes a heavy global disease burden. However, current etiology, diagnosis and treatment remain unsatisfactory and no previous study has resolved this problem. Building on the strengths and limitations of previous cohort studies of MDD, the prospective cohort study of depression (PROUD) is a 3-year large-scale cohort study designed to collect multidimensional data with a flexible follow-up schedule and strategy. The goal is to establish a nationally representative, high-quality, standardized depression cohort to support precise diagnosis and treatment of MDD and address the gap in current research.

Methods

PROUD is a patient-based, nationally representative multicenter prospective cohort study with baseline and 3-year follow-up assessments. It will be carried out from January 2022 to December 2026 in 52 qualified tertiary hospitals in China. A total of 14,000 patients diagnosed with MDD, according to the DSM-5 criteria, and aged ≥ 16 years, will be recruited to PROUD. Participants aged 18-65 years who have not received any treatment during a depressive episode will be included in the precision medicine cohort (PMC) of PROUD (n=4,000). Patients who meet the general eligibility criteria but not the PMC criteria will be included in the naturalistic observation cohort (NOC) of PROUD (n=10,000). A multiple follow-up strategy, including scheduled, remote, telephone, external visits and patient self-reports, will be implemented to collect comprehensive sociodemographic, clinical information, biospecimens, neuroimaging, cognitive function and electrophysiology data and digital phenotypes according to strict standard operating procedures implemented across centers. Trial registration: ChiCTR2200059053, registered on 23 April 2022, http://www.chictr.org.cn/showproj.aspx?proj=165790.

Conclusions

PROUD is a prospective cohort study of MDD patients in China. It will provide a comprehensive database facilitating further analyses and aiding the development of homeostatic and precision medicine in China.

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk

BACKGROUND

A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations.

METHOD

Clustering data were from 1094 individuals with major depressive disorder in the last 6 months and measures of 149 metabolites from a ¹H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic diseases in an independent population-based cohort (n = 6572).

RESULTS

CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm² (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm² (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -0.01).

CONCLUSIONS

Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.

Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders

BACKGROUND

Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person-level. We examined bidirectional associations between PAL and affect in a 3-h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety.

METHODS

Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) Composite International Diagnostic Interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Positive affect (PA) and negative affect (NA) were assessed by EMA 5 times per day. Average PAL between EMA assessments were calculated from actigraphy data.

RESULTS

At the group-level, higher PAL was associated with subsequent higher PA (b = 0.109, p < .001) and lower NA (b = -0.043, p < .001), while higher PA (b = 0.066, p < .001) and lower NA (b = -0.053, p < .001) were associated with subsequent higher PAL. The association between higher PAL and subsequent lower NA was stronger for current depression/anxiety patients than controls (p = .01). At the person-level, analyses revealed heterogeneity in bidirectional associations.

CONCLUSIONS

Higher PAL may improve affect, especially among depression/anxiety patients. As the relationships vary at the person-level, ambulatory assessments may help identify who would benefit from behavioral interventions.

Childhood trauma and LPS-stimulated inflammation in adulthood: Results from the Netherlands Study of Depression and Anxiety

BACKGROUND

Childhood trauma (CT) is robustly associated with psychiatric disorders including major depressive and anxiety disorders across the life span. The innate immune system may play a role in the relation between CT and stress-related psychopathology. However, whether CT influences the innate production capacity of cytokine levels following ex vivo stimulation by lipopolysaccharide (LPS), is currently unknown.

METHODS

Using data from the Netherlands Study of Depression and Anxiety (NESDA, n=1237), we examined whether CT (emotional neglect, emotional, physical, and sexual abuse before the age of 16), assessed by the Childhood Trauma Interview, was associated with levels in supernatants of interferon (IFN)γ, interleukin-2 (IL-2), IL-4, IL-6, IL-8, IL-10, IL-18, monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein (MIP)-1α, MIP-1β, matrix metalloproteinase-2 (MMP-2), TNFα and TNFβ after ex vivo stimulation with LPS. Cytokines were analysed individually and cumulatively (overall inflammation index and number of cytokines in high-risk quartile (HRQ)) using linear regression analyses.

RESULTS

After adjustment for demographic, lifestyle, and health-related covariates, total CT severity was associated with the overall inflammation index (β = 0.085, P_FDR = 0.011), the number of cytokines in HRQ (β = 0.063, P_FDR = 0.036), and individual markers of IL-2 (β = 0.067, P_FDR = 0.036), IL-6 (β = 0.091 P_FDR = 0.011), IL-8 (β = 0.085 P_FDR = 0.011), IL-10 (β = 0.094 P_FDR = 0.011), MCP-1 (β = 0.081 P_FDR = 0.011), MIP-1α (β = 0.061 P_FDR = 0.047), MIP1-β (β = 0.077 P_FDR = 0.016), MMP-2 (β = 0.070 P_FDR = 0.027), and TNFβ (β = 0.078 P_FDR = 0.016). Associations were strongest for individuals with severe CT, reporting multiple types or higher frequencies of trauma. Half of the findings persisted after adjustment for psychiatric status. The findings were consistent across different CT types.

CONCLUSION

Childhood Trauma is associated with increased LPS-stimulated cytokine levels, with evidence for a dose-response relationship. Our results highlight a dysregulated innate immune system capacity in adults with CT, which could contribute to an increased vulnerability for psychopathology and somatic disorders across the lifespan.