Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Major Depressive Disorder (MDD) is a complex mental health condition characterized by a wide spectrum of symptoms. According to the Diagnostic Statistical Manual 5 (DSM-5) criteria, patients can present with up to 1,497 different symptom combinations, yet all receive the same MDD diagnosis. This diversity in symptom presentation poses a significant challenge to understanding the disorder in the wider population. Subtyping offers a way to unpick this phenotypic diversity and enable improved characterization of the disorder. According to reviews, MDD subtyping work to date has lacked consistency in results due to inadequate statistics, non-transparent reporting, or inappropriate sample choice. By addressing these limitations, the current study aims to extend past phenotypic subtyping studies in MDD.

(1) To investigate phenotypic subtypes at baseline in a sample of people with MDD;

(2) To determine if subtypes are consistent between baseline 6- and 12-month follow-ups; and

(3) To examine how participants move between subtypes over time.

This was a secondary analysis of a one-year longitudinal observational cohort study. We collected data from individuals with a history of recurrent MDD in the United Kingdom, the Netherlands and Spain (N=619). The presence or absence of symptoms was tracked at three-month intervals through the Inventory of Depressive Symptomatology: Self-Report (IDS-SR) assessment. We used latent class and three-step latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined participants’ transitions over time.

We identified a 4-class solution based on model fit and interpretability, including (Class 1) severe with appetite increase, (Class 2), severe with appetite decrease, (Class 3) moderate, and (Class 4) low severity. The classes mainly differed in terms of severity (the varying likelihood of symptom endorsement) and, for the two more severe classes, the type of neurovegetative symptoms reported (Figure 1). The four classes were stable over time (measurement invariant) and participants tended to remain in the same class over baseline and follow-up (Figure 2).

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We identified four stable subtypes of depression, with individuals most likely to remain in their same class over 1-year follow-up. This suggests a chronic nature of depression, with (for example) individuals in severe classes more likely to remain in the same class throughout follow-up. Despite the vast heterogeneous symptom combinations possible in MDD, our results emphasize differences across severity rather than symptom type. This raises questions about the meaningfulness of these subtypes beyond established measures of depression severity. Implications of these findings and recommendations for future research are made.

C. Oetzmann Grant / Research support from: C.O. is supported by the UK Medical Research Council (MR/N013700/1) and King’s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences., N. Cummins: None Declared, F. Lamers: None Declared, F. Matcham: None Declared, K. White: None Declared, J. Haro: None Declared, S. Siddi: None Declared, S. Vairavan Employee of: S.V is an employee of Janssen Research & Development, LLC and hold company stocks/stock options., B. Penninx : None Declared, V. Narayan: None Declared, M. Hotopf Grant / Research support from: M.H. is the principal investigator of the RADAR-CNS programme, a precompetitive public–private partnership funded by the Innovative Medicines Initiative and the European Federation of Pharmaceutical Industries and Associations. The programme received support from Janssen, Biogen, MSD, UCB and Lundbeck., E. Carr: None Declared

Little is known about touch hunger (longing for physical contact) during the COVID-19 pandemic, particularly for people with pre-existing mental health disorders.

We aim to investigate the dynamics of touch hunger in people with and without depressive, anxiety, or obsessive-compulsive disorders during the COVID-19 pandemic, and the potential predictors for touch hunger during lockdown.

Data were aggregated from three Dutch ongoing prospective cohorts with similar methodology for data collection. We included participants with pre-pandemic data gathered during 2006–2016, and who completed up to 9 online questionnaires between October 2020 and February 2022. We compared trajectories between subgroups with different pre-pandemic chronicity of disorders and healthy controls using linear mixed models. Sociodemographic, clinical (number and type of mental health disorders, personality traits) and COVID-19-related variables were analysed as predictors of touch hunger using multivariate linear regression analyses.

We included 1061 participants with (n = 811) and without (n = 250) mental health disorders. In all groups, touch hunger increased during lockdown (Fig. 1). Extraversion (β = 0.256, P <0.001), social distancing due to COVID-19 anxiety (β = 0.122, P = 0.001) and death of a close contact from COVID-19 (β = 0.073, P = 0.02) predicted higher touch hunger, while living with a partner (β = -0.109, P = 0.004) or with a partner and children (β = -0.147, P <0.001) were protective factors for touch hunger. Remarkably, pre-pandemic mental disorders did not predict touch hunger during lockdown.

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Social distancing measures have important psychological and emotional implications, as our study showed an increase in touch hunger during lockdown, which did not differ between people with and without mental health disorders. Extroverted individuals may benefit most from interventions aimed at addressing their need for physical contact during times of crisis.

None Declared

Profiling patients on a proposed ‘immunometabolic depression’ (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment.

To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants.

Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses.

Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, βpooled = 0.06, P = 0.049, 95% CI 0.0001–0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, βpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01–0.22, I2 = 23.91%), with a higher – but still small – effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (βpooled = 0.16) and the IMD index (βpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission.

Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

In recent research, psychological disorders have been increasingly defined as complex dynamic systems in which symptoms are interconnected and influence each other, thereby forming symptom networks. This paradigm shift calls for the analysis and interpretation of relationships between symptoms that are complex, potentially non-linear, and dynamic. Dynamic Time Warping (DTW) is used to measure similarity in temporal sequences, and has recently been found effective in modelling psychopathology symptom networks.

We aim to demonstrate that DTW could also be used to model the network structure in Ecological Momentary Assessment (EMA) data.

355 participants of the Netherlands Study of Depression and Anxiety (NESDA), of which 100 with and 255 without current disorder, completed EMA assessments of 20 symptoms (e.g., feeling sad, tired, satisfied) five times a day for two weeks. DTW analysis was performed on the group level, comparing participants suffering from mood disorders to healthy controls. DTW distances were visualized as an undirected symptom network, in which we adjusted for the average symptom severity per item per person.

DTW analysis of close to half a million symptom scores yielded six symptom dimensions based on their aggregated similarity of changes over time within the participants. Surprisingly, negative affect symptom networks were found to be less strongly connected in those currently suffering from mood disorders than in controls, whereas the network density of (reverse-coded) positive affect symptoms was more closely connected in this group. This is contrary to the results of previous studies, where negative affect-related symptom networks of those with mood disorders were found to be more strongly interconnected.

DTW is a promising new technique for analyzing EMA data and modeling dynamic symptom networks at both the individual and group levels. Using EMA data, symptom networks and dimensions can be modeled with great structural and temporal detail. Incorporating the temporal symptom dynamics may highlight the importance of the independent trajectories of negative mood symptoms.

None Declared

The role of the interaction between the serotonin-transporter-linked promoter region (5HTTLPR) and stressful condition in determining the vulnerability to depression has been widely investigated. Nevertheless, empirical research provides contrasting findings. Recently, the differential susceptibility to environment model proposed a conceptual shift respect to the classical interpretation of 5-HTTLPR: viewing the short (s) and the long (l) allele not as associated to different traits of vulnerability (respectively vulnerable or not), but determining different plasticity levels (respectively, more and less plasticity) and, thus, different susceptibilities to the environment (respectively, high and low susceptibility).

As 5-HTTLPR is involved in plasticity, the main goal of the present study is to demonstrate that the interaction between the polymorphism and stress emerges when assessing its effects according to temporal factors in a dynamic process perspective.

We explored our hypothesis, exploiting a meta analytic approach. We searched PubMed, PsychoINFO, Scopus and EMBASE databases and 1096 studies were identified and screened, resulting in 22 studies to be included in the meta-analyses. We applied the DerSimonian and Laird random-effects model to estimate crude odds ratios for risk of depression according to 5HTTLPR and we assessed heterogeneity using the I² and Cochran’s Q statistic. We stratified the staties according to (i) stress duration (i.e., chronic vs. acute stress) and (ii) time elapsed between the end of the stressful condition and the assessment of depression (i.e., within one year vs. more than one year).

When stratifying for the duration of stress, the effect of the 5-HTTLPR x stress interaction emerged only in the case of chronic stress (OR 1.43, 95%IC 1.16-1.77, I²= 52%, Q=25.25; Figure 1), with a significant subgroup difference (p=0.004). The stratification according to time interval revealed a significant interaction only for intervals within one year (OR 1.23, 95%IC 1.03-1-46, I²= 67%, Q=39.35), though no difference between subgroups was found. The critical role of time interval clearly emerged when considering only chronic stress: a significant effect of the 5-HTTLPR and stress interaction was confirmed exclusively within one year (OR 1.53, 95%IC 1.17-2.02, I²= 45%, Q=10.94; Figure 2) and a significant subgroup difference was found (p=0.01).

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Our results show that the 5-HTTLPR x stress interaction is a dynamic process, producing different effects at different time-points, and indirectly confirm that s-allele carriers are both at higher risk and more capable to recover from depression. Overall, these findings expand the current view of the interplay between 5-HTTLPR and stress adding the temporal dimension, resulting in a three-way interaction: gene x environment x time.

None Declared

Childhood trauma (CT) is associated with severe sequelae, including personality disorders and stress-related mental health disorders that can perpetuate long into adulthood.

We aimed to investigate (1) whether childhood trauma is associated with anger in adulthood, and, if so, (2) to explore which types of childhood trauma predominate in the prediction of anger, and (3) to explore whether the association is independent of psychopathology in a cohort that included participants without lifetime psychiatric disorders, with current or remitted depressive and anxiety disorders, or comorbid depressive and anxiety disorders.

In the Netherlands Study of Depression and Anxiety (NESDA), childhood trauma was assessed with a semi-structured Childhood Trauma Interview (CTI) at baseline, and analyzed in relation to anger as measured at 4-year follow-up with the Spielberger Trait Anger Subscale (STAS), the Anger Attacks Questionnaire, and cluster B personality traits (i.e., borderline, antisocial) of the Personality Disorder Questionnaire 4 (PDQ-4), using analysis of covariance (ANCOVA) and multivariable logistic regression analyses. Post-hoc analyses comprised cross-sectional regression analyses, using the Childhood Trauma Questionnaire – Short Form (CTQ-SF) obtained at 4-year follow-up.

Participants (n = 2,276) were on average 42.1 years (SD = 13.1), and 66.3% were female. Childhood trauma showed a dose-response association with all anger constructs. Zooming in, all types of childhood trauma except for sexual abuse were associated with higher levels of trait anger, and a higher prevalence of anger attacks and antisocial personality traits in adulthood, independently of depression and anxiety. Additionally, all types of childhood trauma were significantly associated with borderline personality traits. Cross-sectionally, the effect sizes were larger compared to the analyses with the childhood trauma measured four years prior to the anger measures.

Childhood trauma is linked with anger in adulthood, most strongly for trait anger and borderline personality traits. It is of clinical importance to explore childhood traumatic experience and start trauma-focused interventions when appropriate.

None Declared

Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.

Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions.

Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms.

Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.

Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes.

This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; N = 623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every 3 months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up.

508 individuals (81.5%) provided data (mean age: 46.6, s.d.: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (<25% of timepoints), those with high persistence (>75% of timepoints) reported significantly higher levels of depression (B = 5.17, s.e. = 2.21, p = 0.019) and functional impairment (B = 4.82, s.e. = 1.79, p = 0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms.

We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input.

There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders.

Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels.

Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant.

Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation.

Studies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the specific inflammatory markers studied and covariates accounted for. Second, specific depressive symptoms may be differentially related to inflammation. We address both challenges using network psychometrics.

We estimated seven regularized Mixed Graphical Models in the Netherlands Study of Depression and Anxiety (NESDA) data (N = 2321) to explore shared variances among (1) depression severity, modeled via depression sum-score, nine DSM-5 symptoms, or 28 individual depressive symptoms; (2) inflammatory markers C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); (3) before and after adjusting for sex, age, body mass index (BMI), exercise, smoking, alcohol, and chronic diseases.

The depression sum-score was related to both IL-6 and CRP before, and only to IL-6 after covariate adjustment. When modeling the DSM-5 symptoms and CRP in a conceptual replication of Jokela et al., CRP was associated with ‘sleep problems’, ‘energy level’, and ‘weight/appetite changes’; only the first two links survived covariate adjustment. In a conservative model with all 38 variables, symptoms and markers were unrelated. Following recent psychometric work, we re-estimated the full model without regularization: the depressive symptoms ‘insomnia’, ‘hypersomnia’, and ‘aches and pain’ showed unique positive relations to all inflammatory markers.

We found evidence for differential relations between markers, depressive symptoms, and covariates. Associations between symptoms and markers were attenuated after covariate adjustment; BMI and sex consistently showed strong relations with inflammatory markers.

Studies on neighbourhood characteristics and depression show equivocal results.

This large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression.

Cross-sectional design including data are from eight Dutch cohort studies (n= 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis.

The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01–1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87–0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06–1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02–1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01–1.12), less green space (OR = 0.94, 95% CI 0.88–0.99) and less social safety (OR = 0.92, 95% CI 0.88–0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores.

This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.

None.

Literature has shown that obesity, metabolic syndrome and inflammation are associated with depression, however, evidence suggests that these associations are specific to atypical depression. Which of the atypical symptoms are driving associations with obesity-related outcomes and inflammation is unknown. We evaluated associations between individual symptoms of depression (both atypical and non-atypical) and body mass index (BMI), metabolic syndrome components and inflammatory markers.

We included 808 persons with a current diagnosis of depression participating in the Netherlands Study of Depression and Anxiety (67% female, mean age 41.6 years). Depressive symptoms were derived from the Composite International Diagnostic Interview and the Inventory of Depressive Symptomatology. Univariable and multivariable regression analyses adjusting for sex, age, educational level, depression severity, current smoking, physical activity, anti-inflammatory medication use, and statin use were performed.

Increased appetite was positively associated with BMI, number of metabolic syndrome components, waist circumference, C-reactive protein and tumor necrosis factor-α. Decreased appetite was negatively associated with BMI and waist circumference. Psychomotor retardation was positively associated with BMI, high-density lipoprotein cholesterol and triglycerides, and insomnia with number of metabolic syndrome components.

Increased appetite – in the context of a depressive episode – was the only symptom that was associated with both metabolic as well as inflammatory markers, and could be a key feature of an immuno-metabolic form of depression. This immuno-metabolic depression should be considered in clinical trials evaluating effectiveness of compounds targeting metabolic and inflammatory pathways or lifestyle interventions.

Accelerated cellular ageing, which can be examined by telomere length (TL), may be an overarching mechanism underlying the association between personality and adverse health outcomes. This 6-year longitudinal study examined the relation between personality and leukocyte telomere length (LTL) across time among adults with a wide age-range.

Data from the Netherlands Study of Depression and Anxiety were used and included patients with a depression and/or anxiety disorder and healthy controls. Overall, 2936 persons (18–65 years, 66% female) had data on LTL at baseline and 1883 persons had LTL at 6-year follow-up. The Big Five personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) and Type D personality were assessed.

Neuroticism was negatively (B = −2.11, p = 0.03) and agreeableness was positively (B = 3.84, p = 0.03) related to LTL measured across two time points, which became just non-significant after adjusting for somatic health, lifestyle factors, and recent life stress (B = −1.99, p = 0.06; and B = 3.01, p = 0.10). Type D personality was negatively (B = −50.16, p < 0.01) related to LTL across two time points, which still remained statistically significant after full adjustment (B = −47.37, p = 0.01). Associations did not differ by age, gender, and current psychiatric status.

The Big Five traits high neuroticism and low agreeableness, and Type D personality were associated with shorter LTL measured across a 6-year period. Associations with the Big Five traits became non-significant after controlling for somatic health, lifestyle factors, and recent life stress, yet similar trends were observed. Type D personality remained independently associated with shorter LTL after full adjustment.

Poor recovery from depressive disorder has been shown to be related to low perceived social support and loneliness, but not to social network size or frequency of social interactions. Some studies suggest that the significance of social relationships for depression course may be greater in younger than in older patients, and may differ between men and women. None of the studies examined to what extent the different aspects of social relationships have unique or overlapping predictive values for depression course. It is the aim of the present study to examine the differential predictive values of social network characteristics, social support and loneliness for the course of depressive disorder, and to test whether these predictive associations are modified by gender or age.

Two naturalistic cohort studies with the same design and overlapping instruments were combined to obtain a study sample of 1474 patients with a major depressive disorder, of whom 1181 (80.1%) could be studied over a 2-year period. Social relational variables were assessed at baseline. Two aspects of depression course were studied: remission at 2-year follow-up and change in depression severity over the follow-up period. By means of logistic regression and random coefficient analysis, the individual and combined predictive values of the different social relational variables for depression course were studied, controlling for potential confounders and checking for effect modification by age (below 60 v. 60 years or older) and gender.

Multiple aspects of the social network, social support and loneliness were related to depression course, independent of potential confounders – including depression severity – but when combined, their predictive values were found to overlap to a large extent. Only the social network characteristic of living in a larger household, the social support characteristic of few negative experiences with the support from a partner or close friend, and limited feelings of loneliness proved to have unique predictive value for a favourable course of depression. Little evidence was found for effect modification by gender or age.

If depressed persons experience difficulties in their social relationships, this may impede their recovery. Special attention for interpersonal problems, social isolation and feelings of loneliness seems warranted in depression treatment and relapse prevention. It will be of great interest to test whether social relational interventions can contribute to better recovery and relapse prevention of depressive disorder.

Physical inactivity has been identified as a risk factor for depression and, less often, as a long-term consequence of depression. Underexplored is whether similar bi-directional longitudinal relationships are observed for anxiety disorders, particularly in relation to three distinct indicators of activity levels – sports participation, general physical activity and sedentary behavior.

Participants were from the Netherlands Study of Depression and Anxiety (NESDA; N = 2932, 18–65 years old; 57% current anxiety or depressive disorder, 21% remitted disorder, 22% healthy controls). At baseline, 2, 4, and 6 years, participants completed a diagnostic interview and self-report questionnaires assessing psychopathology symptom severity, physical activity indicators, and sociodemographic and health covariates.

Consistently across assessment waves, people with anxiety and/or depressive disorders had lower sports participation and general physical activity compared to healthy controls. Greater anxiety or depressive symptoms were associated with lower activity according to all three indicators. Over time, a diagnosis or greater symptom severity at one assessment was associated with poorer sports participation and general physical activity 2 years later. In the opposite direction, only low sports participation was associated with greater symptom severity and increased odds of disorder onset 2 years later. Stronger effects were observed for chronicity, with lower activity according to all indicators increasing the odds of disorder chronicity after 2 years.

Over time, there seems to a mutually reinforcing, bidirectional relationship between psychopathology and lower physical activity, particularly low sports participation. People with anxiety are as adversely affected as those with depression.

Oxidative stress has been implicated in the pathophysiology of major depressive disorder (MDD) and anxiety disorders and may be influenced by antidepressant use. This study investigated the association of oxidative stress, measured by plasma levels of F2-isoprostanes and 8-hydroxy-2′-deoxyguanosine (8-OHdG) reflecting oxidative lipid and DNA damage respectively, with MDD, anxiety disorders and antidepressant use in a large cohort.

Data was derived from the Netherlands Study of Depression and Anxiety including patients with current (N = 1619) or remitted (N = 610) MDD and/or anxiety disorder(s) (of which N = 704 antidepressant users) and 612 controls. Diagnoses were established with the Composite International Diagnostic Interview. Plasma 8-OHdG and F2-isoprostanes were measured using LC-MS/MS. ANCOVA was performed adjusted for sampling, sociodemographic, health and lifestyle variables.

F2-isoprostanes did not differ between controls and patients, or by antidepressant use. Patients with current disorders had lower 8-OHdG (mean 42.1 pmol/l, 95% CI 40.4–43.8) compared to controls (45.0 pmol/l, 95% CI 42.9–47.2; p < 0.001) after adjustment for sampling, sociodemographics and lifestyle, but these differences disappeared after further adjustment for antidepressant use (p = 0.562). Antidepressant users had lower 8-OHdG levels (38.2 pmol/l, 95% CI 36.5–39.9) compared to controls (44.9 pmol/l, 95% CI 43.2–46.6; Cohen's d = 0.21, p < 0.001). Results for 8-OHdG were comparable across disorders (MDD and/or anxiety disorders), and all antidepressant types (SSRIs, TCAs, other antidepressants).

Contrary to previous findings this large-scale study found no increased oxidative stress in MDD and anxiety disorders. Antidepressant use was associated with lower oxidative DNA damage, suggesting antidepressants may have antioxidant effects.

Universal screening for postpartum depression is recommended in many countries. Knowledge of whether the disclosure of depressive symptoms in the postpartum period differs across cultures could improve detection and provide new insights into the pathogenesis. Moreover, it is a necessary step to evaluate the universal use of screening instruments in research and clinical practice. In the current study we sought to assess whether the Edinburgh Postnatal Depression Scale (EPDS), the most widely used screening tool for postpartum depression, measures the same underlying construct across cultural groups in a large international dataset.

Ordinal regression and measurement invariance were used to explore the association between culture, operationalized as education, ethnicity/race and continent, and endorsement of depressive symptoms using the EPDS on 8209 new mothers from Europe and the USA.

Education, but not ethnicity/race, influenced the reporting of postpartum depression [difference between robust comparative fit indexes (∆*CFI) < 0.01]. The structure of EPDS responses significantly differed between Europe and the USA (∆*CFI > 0.01), but not between European countries (∆*CFI < 0.01).

Investigators and clinicians should be aware of the potential differences in expression of phenotype of postpartum depression that women of different educational backgrounds may manifest. The increasing cultural heterogeneity of societies together with the tendency towards globalization requires a culturally sensitive approach to patients, research and policies, that takes into account, beyond rhetoric, the context of a person's experiences and the context in which the research is conducted.