Netherlands Study Of Depression And Anxiety Research Articles

Bidirectional longitudinal associations of omega-3 polyunsaturated fatty acid plasma levels with depressive disorders

BackgroundTemporality of the association of low omega-3 polyunsaturated fatty acid (n-3 PUFA) plasma levels with depression remains questionable. To determine the underlying nature of these associations, this study examined the bidirectional longitudinal associations of n-3 PUFA plasma levels with (presence, onset and course of) depressive disorders and symptoms. MethodsBaseline (n = 2912, 28.6% with current depressive disorder) and 6-year follow-up data (n = 1966, 13.0% with current depressive disorder) of the Netherlands Study of Depression and Anxiety (NESDA) were used. Depression diagnoses and symptoms were based on psychiatric interviews and self-report questionnaires. N-3 PUFA levels (ratio of total fatty acids (mmol%)), were assessed using nuclear magnetic resonance. ResultsUsing two waves of data, n-3 PUFA levels were lower among depressed persons, as compared to healthy controls (Beta = −0.047, SE = 0.011, p < .001). Nevertheless, baseline n-3 PUFA levels were not consistently associated with subsequent change in depressive symptoms, onset or remission of depressive disorders over 6 years. Furthermore, the difference in n-3 PUFA levels detected at baseline between depressed and non-depressed participants tended to dissipate over 6 years (depression-by-time estimate: p = .011). Finally, subjects depressed both at baseline and at 6-year follow up had consistently lower n-3 PUFA levels over the entire follow-up as compared to those who had never been depressed. Change in depressive disorders across waves was not consistently accompanied by change in n-3 PUFA levels over time. LimitationsNo data on intermediate time points and EPA levels were available. ConclusionsDespite significant cross-sectional associations between n-3 PUFA plasma levels and depressive disorders and severity, this 6-year longitudinal study could not confirm an uni- or bidirectional association over time. The association between depression and n-3 PUFA plasma levels is unlikely to be causal.

Predicting individual clinical trajectories of depression with generative embedding.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy - generative embedding (GE) - which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.

Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates.

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.

Involvement of inflammatory gene expression pathways in depressed patients with hyperphagia

The pathophysiology of major depressive disorder (MDD) is highly heterogeneous. Previous evidence at the DNA level as well as on the serum protein level suggests that the role of inflammation in MDD pathology is stronger in patients with hyperphagia during an active episode. Which inflammatory pathways differ in MDD patients with hyperphagia inflammatory pathways in terms of gene expression is unknown. We analyzed whole-blood gene expression profiles of 881 current MDD cases and 331 controls from the Netherlands Study of Depression and Anxiety (NESDA). The MDD patients were stratified according to patients with hyperphagia (characterized by increased appetite and/or weight, N = 246) or hypophagia (characterized by decreased appetite and/or weight, N = 342). Using results of differential gene expression analysis between controls and the MDD subgroups, enrichment of curated inflammatory pathways was estimated. The majority of the pathways were significantly (FDR < 0.1) enriched in the expression profiles of MDD cases with hyperphagia, including top pathways related to factors responsible for the onset of inflammatory response (‘caspase’, ‘GATA3’, ‘NFAT’, and ‘inflammasomes’ pathways). Only two pathways (‘adaptive immune system’ and ‘IL-8- and CXCR2-mediated signaling’) were enriched in the MDD with hypophagia subgroup, these were also enriched in the total current MDD group and the group with hyperphagia. This confirms the importance of inflammation in MDD pathology of patients with hyperphagia, and suggests that distinguishing more uniform MDD phenotypes can help in finding their pathophysiological basis.

Trait anger and anger attacks in relation to depressive and anxiety disorders

BackgroundPatients with various psychiatric disorders may suffer from feelings of anger, sometimes leading to maladaptive (e.g., aggressive) behaviors. We examined to what extent depressive and anxiety disorders, relevant clinical correlates, and sociodemographics determined the level of trait anger and the prevalence of recent anger attacks. MethodsIn the Netherlands Study of Depression and Anxiety (NESDA), the Spielberger Trait Anger Subscale and the Anger Attacks Questionnaire were analyzed in patients with depressive (n = 204), anxiety (n = 288), comorbid (n = 222), and remitted disorders (n = 1,107), as well as in healthy controls (n = 470) based on DSM-IV criteria. ResultsOn average, participants were 46.2 years old (SD = 13.1) and 66.3% were female. Trait anger and anger attacks were most prevalent in the comorbid group (M = 18.5, SD = 5.9, and prevalence 22.1%), followed by anxiety disorder, depressive disorder, remitted disorder, and controls (M = 12.7; SD = 2.9, and prevalence 1.3%). Major depressive disorder, social phobia, panic disorder, and generalized anxiety disorder were most strongly associated to trait anger and anger attacks. LimitationsDue to a cross-sectional design, it was not possible to provide evidence for temporal or causal relationships between anger and depressive and anxiety disorders. ConclusionsTrait anger and anger attacks are linked to depressive and anxiety disorders, although the strength of the relationship differed among both anger constructs.

Long-term disability in major depressive disorder: a 6-year follow-up study.

Major depressive disorder (MDD) represents a leading cause of disability. This study examines the course of disability in patients with chronic, recurrent and remitting MDD compared to healthy controls and identifies predictors of disability in remitting MDD. We included 914 participants from the Netherlands Study of Depression and Anxiety (NESDA). DSM-IV MDD and WHO DAS II disability were assessed at baseline and at 2, 4 and 6 years. Six-year total and domain-specific disability were analysed and compared in participants with chronic (n = 57), recurrent (n = 120), remitting (n = 127) MDD and in healthy controls (n = 430). Predictors of residual disability were identified using linear regression analysis. At baseline, most disability was found in chronic MDD, followed by recurrent MDD, remitting MDD and healthy controls. Across diagnostic groups, most disability was found in household activities, interpersonal functioning, participation in society and cognition. A chronic course was associated with chronic disability. Symptom remission was associated with a decrease in disability, but some disability remained. In remitting MDD, higher residual disability was predicted by older age, more severe avoidance symptoms, higher disability at baseline and late symptom remission. Severity of residual disability correlated with the severity of residual depressive symptoms. Symptomatic remission is a prerequisite for improvements in disability. However, disability persists despite symptom remission. Therefore, treatment of MDD should include an explicit focus on disability, especially on the more complex domains. To this end, treatments should promote behavioural activation and address subthreshold depressive symptoms in patients with remitted MDD.

Longitudinal course of suicidal ideation and predictors of its persistence – A NESDA study

BackgroundPrior research indicates that the factors that trigger suicidal ideation may differ from those that maintain it, but studies into the maintenance of suicidal ideation remain scarce. Our aim was to assess the longitudinal course of suicidal ideation, and to identify predictors of persistent suicidal ideation. MethodsWe used data from the Netherlands Study of Depression and Anxiety (NESDA). We performed a linear mixed-effects growth model analysis (n = 230 with current suicidal ideation at baseline) to assess the course of suicidal ideation over time (baseline through 2-, 4-, 6- and 9-year follow-up). We used logistic regression analysis (n = 195) to test whether factors previously associated with the incidence of suicidal ideation in the literature (insomnia, hopelessness, loneliness, borderline personality traits, childhood trauma, negative life events) also predict persistence of suicidal ideation (i.e., reporting ideation at two consecutive assessment points, 6- and 9-years). We controlled for socio-demographics, clinical diagnosis and severity, medication use, and suicide attempt history. ResultsSuicidal ideation decreased over time, and this decrease became slower with increasing time, with the majority of symptom reductions occurring in the first two years of follow-up. More severe insomnia and hopelessness were associated with increased odds of persistent suicidal ideation, and hopelessness was a significant mediator of the relationship between insomnia and persistent suicidal ideation. LimitationsFindings may not generalize to those with more severe suicidal ideation due to dropout of those with the worst clinical profile. ConclusionsTargeting insomnia and hopelessness in treatment may be particularly important to prevent the persistence of suicidal ideation.

Predictive value of attentional bias for the recurrence of depression: A 4-year prospective study in remitted depressed individuals

Previous research showed that individuals who were remitted from a depressive disorder displayed heightened attention towards negative adjectives (e.g., worthless). We tested if this attentional bias (AB) is predictive of future recurrence of depressive episodes and/or having depressive symptoms at 2- and 4-year follow-up. We used a longitudinal approach within the Netherlands Study of Depression and Anxiety (NESDA) and selected participants who were remitted from Major Depressive Disorder (MDD) (n = 918). AB was measured with a verbal Exogenous Cueing Task; using 2 presentation times (500 and 1250 ms) and 3 stimulus types (negative, positive, neutral). Over 4 years, we prospectively assessed recurrence of depressive episodes and depressive symptomatology after participants completed the ECT. Diagnosis of depressive disorder was measured with clinical rating-scales and self-report questionnaires. A heightened probability of recurrence was neither associated with (heightened) AB for negative nor with (lowered) AB for positive adjectives. Thus, the findings do not support the view that an AB toward negative stimuli or away from positive stimuli plays a critical role in the recurrence of depression.

24 - PREDICTING THE FUTURE DISEASE STATUS OF DEPRESSED PATIENTS FROM DNA METHYLATION PATTERNS IN BLOOD

Background Major Depressive Disorder (MDD) is a severe disorder with a lifetime prevalence of 15%. Recurrent or chronic MDD, which typically requires long-term treatment, occurs in the majority of patients. As previous efforts to predict recurrence/chronicity have met with limited success, novel avenues are required. In this study, we aimed to predict the future disease status of MDD patients from DNA methylation patterns in blood. Methods We assayed 28 million methylation sites in 581 MDD patients from the Netherlands Study of Depression and Anxiety (NESDA). A Machine Learning algorithm condensed all information into a single predictor labeled methylation risk score (MRS). The outcome was MDD disease status six years later. To evaluate the predictive power of our MRS, we obtained an unbiased estimate of the area under the curve (AUC) using k-fold cross validation. Results The AUC of the MRS was 0.724. We compared our MRS with predictions based on a set of five putative MDD biomarkers (e.g., assaying neurotrophic factors or inflammation), genome-wide genetic variant data, and 27 clinical, demographic or lifestyle variables (e.g., MDD symptom severity, childhood trauma, alcohol use). The MRS not only outperformed all these predictors but also seemed to capture their predictive power as the inclusion of any of these sets did not significantly increase the AUC of the MRS. Discussion The current study suggests a novel avenue for predicting future MDD status using DNA methylation patterns in blood. The predictive power of the MRS is comparable to the AUC of the Framingham Risk Score, one of the most widely used clinical tools to predict coronary heart disease. This AUC level can potentially support clinical decisions about treatment strategies by providing empirical information about the likelihood MDD is chronic or will recur in the future.

Decreased functional connectivity of the insula within the salience network as an indicator for prospective insufficient response to antidepressants.

Insufficient response to treatment is the main cause of prolonged suffering from major depressive disorder (MDD). Early identification of insufficient response could result in faster and more targeted treatment strategies to reduce suffering. We therefore explored whether baseline alterations within and between resting state functional connectivity networks could serve as markers of insufficient response to antidepressant treatment in two years of follow-up. We selected MDD patients (N = 17) from the NEtherlands Study of Depression and Anxiety (NESDA), who received ≥ two antidepressants, indicative for insufficient response, during the two year follow-up, a group of MDD patients who received only one antidepressant (N = 32) and a healthy control group (N = 19) matched on clinical characteristics and demographics. An independent component analysis (ICA) of baseline resting-state scans was conducted after which functional connectivity within the components was compared between groups. We observed lower connectivity of the right insula within the salience network in the group with ≥ two antidepressants compared to the group with one antidepressant. No difference in connectivity was found between the patient groups and healthy control group. Given the suggested role of the right insula in switching between task-positive mode (activation during attention-demanding tasks) and task-negative mode (activation during the absence of any task), we explored whether right insula activation differed during switching between these two modes. We observed that in the ≥2 antidepressant group, the right insula was less active compared to the group with one antidepressant, when switching from task-positive to task-negative mode than the other way around. These findings imply that lower right insula connectivity within the salience network may serve as an indicator for prospective insufficient response to antidepressants. This result, supplemented by the diminished insula activation when switching between task and rest related networks, could indicate an underlying mechanism that, if not sufficiently targeted by current antidepressants, could lead to insufficient response. When replicated, these findings may contribute to the identification of biomarkers for early detection of insufficient response.

Severity, course trajectory, and within‐person variability of individual symptoms in patients with major depressive disorder

BackgroundDepression shows a large heterogeneity of symptoms between and within persons over time. However, most outcome studies have assessed depression as a single underlying latent construct, using the sum score on psychometric scales as an indicator for severity. This study assesses longitudinal symptom‐specific trajectories and within‐person variability of major depressive disorder over a 9‐year period.MethodsData were derived from the Netherlands Study of Depression and Anxiety (NESDA). This study included 783 participants with a current major depressive disorder at baseline. The Inventory Depressive Symptomatology‐Self‐Report (IDS‐SR) was used to analyze 28 depressive symptoms at up to six time points during the 9‐year follow‐up.ResultsThe highest baseline severity scores were found for the items regarding energy and mood states. The core symptoms depressed mood and anhedonia had the most favorable course, whereas sleeping problems and (psycho‐)somatic symptoms were more persistent over 9‐year follow‐up. Within‐person variability was highest for symptoms related to energy and lowest for suicidal ideation.ConclusionsThe severity, course, and within‐person variability differed markedly between depressive symptoms. Our findings strengthen the idea that employing a symptom‐focused approach in both clinical care and research is of value.

Unraveling the association between depression and telomere length using genomics

ObjectiveWhile there is robust evidence for a cross-sectional association between depression and shorter telomere length, suggestive of advanced biological aging, the nature of this association remains unclear. Here, we tested whether both traits share a common genetic liability with novel methods using genomics. MethodsData were from 2032 participants of the Netherlands Study of Depression and Anxiety (NESDA) with genome-wide genetic information and multiple waves of data on DSM-IV lifetime depression diagnosis, depression severity, neuroticism and telomere length. Polygenic risk scores (PRS) for both traits were built using summary results from the largest genome-wide association studies (GWAS) on depression (59,851 cases and 113,154 controls) and telomere length (37,684 samples). Additionally, a PRS for neuroticism was built (337,000 samples). Genetic overlap between the traits was tested using PRS for same- and cross-trait associations. Furthermore, GWAS summary statistics were used to estimate the genome-wide genetic correlation between traits. ResultsIn NESDA data, the PRS for depression was associated with lifetime depression (odds ratio = 1.36; p = 6.49e-7) and depression severity level (β = 0.13; p = 1.24e-8), but not with telomere length. Similar results were found for the PRS for neuroticism. Conversely, the PRS for telomere length was associated with telomere length (β = 0.07; p = 8.42e-4) and 6-year telomere length attrition rate (β = 0.04; p = 2.15e-2), but not with depression variables. In summary-level analyses, the genetic correlation between the traits was small and not significant (rg=-0.08; p = .300). ConclusionThe use of genetic methods in this paper indicated that the established phenotypic association between telomere length and depression is unlikely due to shared underlying genetic vulnerability. Our findings suggest that short telomeres in depressed patients may simply represent a generic marker of disease or may originate from non-genetic environmental factors.

Long-term glucocorticoid levels measured in hair in patients with depressive and anxiety disorders

BackgroundDepressive and anxiety disorders have been linked to a dysregulated hypothalamus-pituitary-adrenal (HPA)-axis. Hair cortisol levels (HairF) reflect integrated long-term cortisol regulation and are therefore promising endocrine markers of chronic (psychological and physical) stress.Our aim was to assess hair cortisol levels in persons with a depressive and/or anxiety disorder and to compare their levels with that of persons in remission and healthy controls. MethodsData from 1166 participants of the Netherlands Study of Depression and Anxiety (NESDA) were used, including 266 participants with a recent (1-month) diagnosis of a depressive and/or anxiety disorder, 655 participants with a diagnosis in remission, and 245 healthy controls. HairF was measured in the proximal three cm of scalp hair, using LC–MS/MS. ResultsCompared to the healthy controls no differences on HairF or HairE levels were found for depressive and anxiety disorders alone. However the presence of a comorbid depressive and anxiety disorder was significantly associated with increased HairF levels (β = 0.07; p = .031), as was the severity of depressive symptoms (β = 0.06; p = .029), but no differences were found on HairE nor the HairF:HairE ratio. ConclusionsPersons with current diagnosis of comorbid depression and anxiety show moderately higher levels of cortisol than patients with only depression or anxiety, or patients in remission and healthy controls, which may be indicative of a chronic state of hyperactivation of the HPA axis.

Local fast-food environment, diet and blood pressure: the moderating role of mastery

PurposeTo examine the moderating role of mastery in the association of local fast-food restaurants (FFR) with diet quality and systolic blood pressure (SBP).MethodsWe used cross-sectional data from 1543 adults participating in wave six of the Netherlands Study of Depression and Anxiety (NESDA). Data were collected between 2013 and 2016. Diet quality was defined by adherence with the dietary approaches to stop hypertension (DASH) diet. Individuals reported on their food consumption through a food frequency questionnaire and SBP was measured. Density of FFR in 1600 m, 800 m and 400 m circular buffers around the home postal code was calculated using Geographic Information Systems. We assessed the association between density of FFR, diet and SBP using linear regression analyses, testing for moderation by mastery.ResultsMean age was 52 years and 32.2% of the sample were men. Exposure to FFR ranged from 0 to 35 FFR per km2. Density of FFR was not significantly associated with DASH adherence or SBP. Only one out of the six interaction terms was significant, suggesting that for individuals with lower levels of mastery, higher density of FFR in an 800-m buffer was negatively associated with DASH adherence, while for individuals with higher levels of mastery, this association was positive.ConclusionsExposure to FFR was not associated with diet quality and SBP, and we observed little evidence for moderation by level of mastery. This research question should be further explored in a large sample of healthy adults.

Comparing factor structures of depressed patients with and without suicidal ideation, a measurement invariance analysis

BackgroundSuicidality could be associated with specific combinations of biological, social and psychological factors. Therefore, depressive episodes with suicidal ideation could be different from depressive episodes without suicidal ideation in terms of latent variable structures. MethodsIn this study we compared latent variable structures between suicidal and non-suicidal depressed patients using confirmatory factor analysis (CFA), following a measurement invariance test procedure. Patients (N = 919) suffering from major depressive disorder were selected from the Netherlands Study of Depression and Anxiety (NESDA) and split into a group that showed no symptoms of suicidal ideation (non-SI; N = 691) and a suicidal ideation (SI) group that had one or more symptoms of suicidal ideation (N = 228). Depression and anxiety symptoms were measured using the short form of the Mood and Anxiety Symptoms Questionnaire (MASQ-D30). ResultsCFA implied a difference in latent variable structures between the non-SI sample (CFI 0.957; RMSEA 0.041) and the SI sample (CFI 0.900; RMSEA 0.056). Subsequent multiple-group CFA showed violations of measurement invariance. The General distress and Anhedonic depression subscales were best indicated by hopelessness and lack of optimism in the SI sample and by dissatisfaction and not feeling lively in the non-SI sample. Overall, the SI sample had higher scores and lower inter-item correlations on the Anhedonic depression items. LimitationsWe have included very mild cases of suicidal ideation in our SI sample. ConclusionsOn a latent variable level, depression with suicidal ideation differs from depression without suicidal ideation. Results encourage further research into the symptom structure of depression among suicidal patients.

Can chronotype function as predictor of a persistent course of depressive and anxiety disorder?

BackgroundThe role of chronotype, the individual timing of sleep/activity, has been studied in relation to depressive and anxiety disorders. A cross-sectional association between a depressive episode and evening-type has been identified. However, until now the predicting capacity of chronotype concerning persistence of psychiatric disorders remains unclear. Our aim is to examine whether a later chronotype in patients with a depressive and/or anxiety disorder can serve as a predictor of a persistent course. MethodsA subsample of patients with a depressive and/or anxiety disorder diagnosis and chronotype data of the longitudinal Netherlands Study of Depression and Anxiety (NESDA) was used. Diagnosis of depressive and anxiety disorders (1-month DSM-IV based diagnosis) were determined at baseline (n = 505). From this group persistence was determined at 2-year (FU2) (persistent course: n = 248, non-persistent course: n = 208) and 4-year follow-up (FU4) (persistent course: n = 151, non-persistent course: n = 264). Chronotype was assessed at baseline with the Munich Chronotype Questionnaire. ResultsA later chronotype did not predict a persistent course of depressive and/or anxiety disorder at FU2 (OR (95% CI) = 0.99 (0.83–1.19), P = 0.92) or at FU4 (OR (95% CI) = 0.94 (0.77–1.15), P = 0.57). LimitationsPersistence was defined as having a diagnosis of depressive and/or anxiety disorder at the two-year and four-year follow-up, patients may have remitted and relapsed between assessments. ConclusionChronotype, measured as actual sleep timing, of patients with a depressive or anxiety disorder did not predict a persistent course which suggests it might be unsuitable as predictive tool in clinical settings.

Six-year healthcare trajectories of adults with anxiety and depressive disorders: Determinants of transition to specialised mental healthcare

BackgroundTo investigate potential facilitators and barriers for patients receiving specialised mental healthcare using a longitudinal design. MethodsLongitudinal data on 701 adult participants with a depressive and/or anxiety disorder were derived from the Netherlands Study of Depression and Anxiety (NESDA). Demographic, clinical and treatment determinants at baseline were assessed with self-report questionnaires and the Composite International Diagnostic Interview (CIDI 2.1). Transition to specialised mental healthcare was assessed at one, two, four, and six-year follow-up with a self-report resource use questionnaire (TiC-P). Results28.3% of patients with a depressive and/or anxiety disorder transitioned from receiving no care or primary mental healthcare to specialised mental health services during six-year follow-up. The multivariate Cox regression model identified suicidal ideation, younger age, higher education level, openness to experience, pharmacological treatment, prior treatment in primary mental healthcare and perceived unmet need for help as determinants of transition, explaining 8–18% of variance. LimitationsThis study focused on baseline determinants of future transition to specialised mental healthcare. Recovery and remittance of depression and anxiety in relation to transition were not studied. ConclusionsNot all key clinical guideline characteristics such as severity of symptoms and comorbidity were predictive of a transition to specialised mental healthcare, while non-clinical factors, such as age and perceived unmet need for help, did influence the process.

Associations between age and the course of major depressive disorder: a 2-year longitudinal cohort study

Although there is some evidence that older people might have a poorer course of major depressive disorder (MDD) than younger or middle-aged people, and that age-related course differences might affect the optimisation of MDD treatment, large-scale studies with a broad age range, including consistent course assessments, are needed to properly address this issue. Therefore, we aimed to longitudinally examine whether older age was associated with a poorer naturalistic course trajectory of MDD than that of younger ages and to establish which prognostic-clinical, social, and health-factors could explain this potentially poorer course. For this longitudinal cohort study, we used baseline and 2-year follow-up data from the Netherlands Study of Depression and Anxiety (NESDA) and the Netherlands Study of Depression in Older Persons (NESDO) cohorts. People aged between 18 and 88 years, with an MDD diagnosis at baseline, and a valid clinical assessment at 2-year follow-up were included. The primary outcome was the 2-year course of MDD, which was assessed by use of four indicators: having a depression diagnosis (MDD or dysthymia) after 2 years, having a chronic symptom course (depressive symptoms present during 80% or more of the 2-year follow-up period), time to remission, and depression severity change. We used multivariate analyses to examine associations between continuous age and these MDD course indicators. We also examined whether prognostic clinical (eg, comorbid anxiety), social (loneliness and social support), and health (body-mass index, pain, and chronic diseases) factors contributed to the differences in the course of MDD between age groups. Between 2004-2012, baseline and 2-year follow-up data were obtained for 1042 participants from the NESDA and NESDO cohorts, of whom 690 (66%) were women. Older age was significantly associated with a worse 2-year MDD course for all four indicators (MDD diagnosis: odds ratio [OR] 1·08, 95% CI 1·00-1·17; chronic symptom course: OR 1·24, 1·13-1·35; time to remission: hazard ratio [HR] 0·91, 0·87-0·96; and depression severity change: regression coefficient 1·06, p<0·0001; all per 10-year increase). The course of MDD worsened linearly with age, and people aged 70 years or older had the worst outcomes compared with those of the reference group of people aged 18-29 years (MDD diagnosis: OR 2·02, 95% CI 1·18-3·45; chronic symptom course: OR 3·19, 1·74-5·84; time to remission: HR 0·60, 0·44-0·83; and depression severity change: -12·64 [SD 10·85] in those aged 18-29 years and -5·57 [11·14] in those aged 70 years or older). These results were slightly reduced, but remained mostly significant when adjusting for prognostic clinical, social, and health factors. Older age was found to be a consistent and important risk factor for a poorer MDD course, which could not be explained by a range of well established risk factors. Further investigation of potential underlying mechanisms-including the effect of cognitive impairment, for example-is needed to prevent the negative consequences of a long-term MDD burden in older people. Netherlands Organisation for Health Research and Development, Fonds NutsOhra, Stichting tot Steun VCVGZ, NARSAD The Brain and Behaviour Research Fund, and European Union's 7th Framework Programme.

41. Telomere Length, Epigenetic Aging and Depression in the Netherlands Study of Depression and Anxiety (NESDA)

41. Telomere Length, Epigenetic Aging and Depression in the Netherlands Study of Depression and Anxiety (NESDA)

Development and external validation of a prediction rule for an unfavorable course of late-life depression: A multicenter cohort study

BackgroundGiven the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. MethodsFor development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60–90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50–66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. Results111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). LimitationsThe model was developed and validated in The Netherlands, which could affect the cross-country generalizability. ConclusionsBased on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome.