Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

How sustainable is resilience? A mixed-methods study on the COVID-19-pandemic as a challenge to resilience resources of older adults who previously recovered from depression.

OBJECTIVES: Despite expanding knowledge about the internal and external resources that contribute to resilience among individuals who have experienced depression, the long-term accessibility and protectiveness of these resources across different stressors is unknown. We investigated whether and how the resilience resources of individuals who previously recovered from late-life depression remained protective during the COVID-19 pandemic. METHODS: We used a sequential explanatory mixed methods design. Quantitative data were derived from two psychiatric case-control cohorts and included twelve repeated measures during the COVID-19 pandemic (n = 465, aged ≥ 60). Qualitative data included two sequential interviews held in 2020 (n = 25) and 2021 (n = 19). We used thematic analysis to determine the protective resources after depression and during the COVID-19 pandemic and linear mixed models to examine the effect of these resources on change in depressive symptoms during the COVID-19 pandemic. RESULTS: While resources of 'Taking agency', 'Need for rest', 'Managing thought processes' and 'Learning from depression' remained accessible and protective during the pandemic, 'Social support' and 'Engaging in activities' did not. 'Negotiating with lockdown measures', 'changing social contact' and 'changing activities' were compensating strategies. Quantitative data confirmed the protectiveness of social contact, social cohesion, sense of mastery, physical activity, staying active and entertained and not following the media. CONCLUSION: Many of the resources that previously helped to recover from depression also helped to maintain good mental health during the COVID-19 pandemic. Where accessibility and protectiveness declined, compensatory strategies or new resources were used. Hence, the sustainability of resilience is enabled through adaptation and compensation processes.

Age-related subtypes of late life depression and mortality: A prospective clinical cohort study.

OBJECTIVES: Late Life Depression (LLD) is associated with increased mortality rates, but it remains unclear which depressed patients are at increased risk. This study examined the mortality risk of previously identified subgroups of depressed older patients based on age-related clinical features (the presence of physical and cognitive frailty). METHODS: A six-year follow-up of a clinical cohort study including 375 depressed older patients and 132 non-depressed persons (NESDO). Depressed patients were diagnosed with the Composite International Diagnostic Interview (CIDI) according to DSM-IV criteria and classified by latent profile analysis on depressive symptom severity, cognitive domains and physical frailty. We estimated the hazard rate of mortality for the four depressed subgroups compared to non-depressed persons by applying Cox-regression analyses. Models were adjusted for age, sex and education as confounders and for explanatory variables per pathway in separate models: somatic burden, lifestyle characteristics, vascular burden or inflammation markers. RESULTS: A total of 61/375 (16.3%) depressed patients and 8/132 (6.1%) non-depressed persons died during the 6-year follow-up. Two of the four subgroups (n = 186/375 (50%) of the depressed sample) had a higher hazard rate (HR) for mortality compared to non-depressed participants, that is, frail-depressed patients (HR = 5.25, [95%-CI: 2.13-13.0]) and pure mild depressed patients (HR = 3.32 [95%-CI: 1.46-7.58]) adjusted for confounders. Adding possible underlying pathways did not explain these associations. CONCLUSIONS: Age-related features (the presence of physical and cognitive frailty) contribute to the increased mortality risk in late-life depression. Future studies in depressed older patients should study the additional value of a clinical geriatric assessment and integrated treatment aimed to at reduce frailty and ameliorate their mortality risk.

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting. METHODS: Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier. RESULTS: Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC). CONCLUSIONS: These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

The Cortisol Awakening Response as a Biomarker for Cognitive Side-Effects of Electroconvulsive Therapy.

OBJECTIVE: To test whether the cortisol awakening response (CAR) could be a biomarker for cognitive decline during electroconvulsive therapy (ECT). METHODS: We studied 50 older patients with depression who were treated with ECT from the MODECT cohort. We used linear regression analyses to examine the association between CAR and cognitive change, assessed by the change in Mini Mental State Examination scores between baseline and 1 week after ECT course. CAR was assessed by the area under the curve of cortisol levels, according to Pruessner's-formula. Associations were adjusted for putative confounders, based on previous literature and availability. RESULTS: We found no significant associations between the CAR and cognitive change during the ECT course in (un)adjusted models. CONCLUSION: Our results indicate that the CAR is not usable as a biomarker for ECT-induced cognitive decline during ECT course. Further research in cohorts with larger samples is needed.

Association Between Personality Traits and Functional Limitations in Older Adults with Affective Disorders: A Cross Sectional Study.

OBJECTIVES: Personality traits and affective disorders are both related to functional limitations. It is unknown whether personality traits have an additional effect on functioning in older adults with affective disorders. We studied the association between personality traits and functioning within this group. METHODS: We performed a cross-sectional study of 180 older patients referred to outpatient specialized geriatric mental health care centers with a depressive, anxiety and/or somatic symptom disorder according to DSM-criteria. We studied the association between the Big Five personality traits and functional limitations assessed with the WHO-DAS II, adjusting for potential confounders, including the severity of various affective disorders. RESULTS: The 180 patients (57.1% female, mean age 69.2 years) had an average WHO-DAS II score of 31.3 (SD 15.1). Lower scores on Conscientiousness were associated with more overall functional limitations (p = .001), particularly limitations in self-care (p = .001) and household activities (p = .001). Lower Extraversion scores were associated with more limitations in getting along with others (p = .001). CONCLUSIONS: Personality traits are related to functional limitations independent of the severity of affective disorders in older adults. CLINICAL IMPLICATIONS: Personality traits may be used as predictive factors for functioning in older adults with affective disorders.

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy.

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. OBJECTIVE: We investigated whether there are consistent changes in effective resting-state connectivity. METHODS: This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. RESULTS: Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. CONCLUSIONS: A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.

Pharmacological prevention of postictal agitation after electroconvulsive therapy-A systematic review and meta-analysis.

Background: Postictal agitation (PIA) after electroconvulsive therapy (ECT) is a serious clinical problem estimated to occur in 7-36% of patients and recur in 19-54% of patients. PIA has the potential to cause dangerous situations for the patient and staff members aside from the financial impact. To date, it is unclear which pharmacological interventions should be used in the management of PIA. This study aimed to systematically review the (preventative) pharmacological treatment options for PIA after ECT. Method: A systematic search was done in PubMed, EMBASE, PsycINFO, and Web of Science from inception until 10 November 2022. We included randomized trials with any pharmacological intervention or comparison and a predefined outcome measure on PIA. Studies that solely included patients with neurodegenerative disorders or stroke were excluded. Data quality was assessed with the RoB2 and GRADE. Meta-analysis was performed if possible. This study was registered on PROSPERO under CRD42021262323. Results: We screened 2,204 articles and included 14 studies. Dexmedetomidine was investigated in 10 studies. Alfentanil, lignocaine, esmolol, midazolam, propofol, ketamine, haloperidol, and diazepam were each studied in only one study. Meta-analysis revealed an OR of 0.45 (0.32-0.63), a moderate effect size, in favor of dexmedetomidine than placebo to prevent PIA with very low heterogeneity (I2 = 0%). The certainty of the evidence was moderate. The other interventions studied were all found to have low certainty of evidence. Conclusion: For clinical practice, we believe that our results indicate that dexmedetomidine should be considered for the prevention of PIA in patients that have previously experienced PIA.

BrainAge of patients with severe late-life depression referred for electroconvulsive therapy.

BACKGROUND: Severe depression is associated with accelerated brain aging. BrainAge gap, the difference between predicted and observed BrainAge, was investigated in patients with late-life depression (LLD). We aimed to examine BrainAge gap in LLD and its associations with clinical characteristics indexing LLD chronicity, current severity, prior to electroconvulsive therapy (ECT) and ECT outcome. METHODS: Data was analyzed from the Mood Disorders in Elderly treated with Electroconvulsive Therapy (MODECT) study. A previously established BrainAge algorithm (BrainAge R by James Cole, (https://github.com/james-cole/brainageR)) was applied to pre-ECT T1-weighted structural MRI-scans of 42 patients who underwent ECT. RESULTS: A BrainAge gap of 1.8 years (SD = 5.5) was observed, Cohen's d = 0.3. No significant associations between BrainAge gap, number of previous episodes, current episode duration, age of onset, depression severity, psychotic symptoms or ECT outcome were observed. LIMITATIONS: Limited sample size. CONCLUSIONS: Our initial findings suggest an older BrainAge than chronological age in patients with severe LLD referred for ECT, however with high degree of variability and direction of the gap. No associations were found with clinical measures. Larger samples are needed to better understand brain aging and to evaluate the usability of BrainAge gap as potential biomarker of prognosis an treatment-response in LLD. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02667353.

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.

Heterogeneity in depressive and anxiety symptoms and loneliness during the COVID-19 pandemic: Results from three Dutch psychiatric case-control cohorts from April 2020 to February 2022.

OBJECTIVE: While research found heterogeneous changes in mental health during the COVID-19 pandemic, less is known about the long-term changes in mental health in psychiatric groups. Therefore, we applied a data-driven method to detect sub-groups with distinct trajectories across two years into the pandemic in psychiatric groups, and described their differences in socio-demographic and clinical characteristics. METHOD: We conducted sixteen rounds of questionnaires between April 2020 and February 2022 among participants (n = 1722) of three psychiatric case-control cohorts that started in the 2000's. We used Growth Mixture Modelling and (multinomial) logistic regression to identify characteristics associated with trajectory membership. RESULTS: We found low decreasing (1228 [72%] participants), intermediate (n = 348 [22%] participants) and high stable (106 [6%] participants) trajectories of depressive symptoms; decreasing low/intermediate (1507 [90%] participants) and high stable (161 [10%] participants) trajectories of anxiety symptoms; and stable low (1109 [61%] participants), stable high (315 [17%] participants), temporary lowered (123 [9%]) and temporary heightened (175 [13%] participants) trajectories of loneliness. Chronicity and severity of pre-pandemic mental disorders predicted unfavourable sub-group membership for all outcomes. Being female, having a low education and income level were associated with unfavourable trajectories of depression, being younger with unfavourable trajectories of anxiety and being female and living alone with unfavourable trajectories of loneliness. CONCLUSION: We found relatively stable trajectories of depression and anxiety symptoms over two years, suggesting low heterogeneity in outcomes during the pandemic. For loneliness, we found two specific sub-groups with temporary increase and decrease in loneliness during the pandemic.

The impact of personality traits on the course of frailty.

OBJECTIVES: Determinants of frailty are generally explored within context of somatic healthcare and/or lifestyle characteristics. To examine the impact of personality traits on change in frailty and the potential role of depression. METHODS: A 2-year follow-up study including 285 patients with a depressive disorder and 116 never-depressed controls. Multiple linear regression analyses were conducted to regress the Big Five personality traits (independent variables) on different frailty measures (dependent variables), including the Frailty Index, Frailty phenotype, gait speed, and handgrip strength. Analyses were adjusted for confounders (with and without depressive disorder) and baseline frailty severity. Interactions between personality traits and depressive disorder were examined. RESULTS: All personality traits were associated with change in at least one frailty marker over time. Over time, a higher level of neuroticism was associated with an accelerated increase of frailty, whereas a higher level of extraversion, agreeableness, conscientiousness and openness were associated with an attenuated increase of frailty. None of the associations were moderated by depression. Additional adjustment for depression decreased the strength of the association of neuroticism, extraversion and conscientiousness with frailty. CONCLUSIONS: Personality traits have impact on frailty trajectories in later life. CLINICAL IMPLICATIONS: Underlying pathways and potential modification by psychotherapy merit further study.

Cognitive functioning in late life affective disorders: Comparing older adults with bipolar disorder, late life depression and healthy controls.

INTRODUCTION: Both older age bipolar disorder (OABD) and late life depression (LLD) have been associated with cognitive dysfunction. It is unclear how cognitive functioning differs between these disorders and what the influence of current depressive symptoms is. METHODS: We compared OABD (n = 148), LLD (n = 378) and healthy controls (HC) (n = 132) on cognitive functioning. Cognitive functioning was measured by an extensive neuropsychological assessment, and divided into four domains: episodic memory, processing speed, interference inhibition and working memory. Separate linear regression analyses were conducted with OABD as reference category, controlling for age, gender, level of education and severity of depressive symptoms. RESULTS: Our findings show that OABD and LLD patients exhibit more cognitive dysfunction than HC, with OABD showing worst cognitive functioning on all cognitive domains, except for interference inhibition. These differences remained significant, even after controlling for the effect of depressive symptoms at the time of testing. DISCUSSION: Our findings suggest that cognitive dysfunction in OABD is more severe in magnitude albeit in the same domains as in LLD. This difference cannot be fully explained by the severity of depressive symptoms. Future research should focus on other disease characteristics and how these characteristics are associated with the complex concept of cognitive functioning in both OABD and LLD.

Rivastigmine for ECT-induced cognitive adverse effects in late life depression (RECALL study): A multicenter, randomized, double blind, placebo-controlled, cross-over trial in patients with depression aged 55 years or older: Rationale, objectives and methods.

Background: Cognitive side-effects are an important reason for the limited use of electroconvulsive therapy (ECT). Cognitive side-effects are heterogeneous and occur frequently in older persons. To date, insight into these side-effects is hampered due to inconsistencies in study designs and small sample sizes. Among all cognitive side-effects, confusion and delirious states are especially troublesome for patients, relatives and clinicians. In particular inter-ictal delirium-like states are worrisome, since they may lead to premature treatment discontinuation. Besides a need for further insight into determinants of cognitive side-effects of ECT, there is a great need for treatment options. Methods and design: The Rivastigmine for ECT-induced Cognitive Adverse effects in Late Life depression (RECALL) study combines a multicenter, prospective cohort study on older patients with depression, treated with ECT, with an embedded randomized, placebo-controlled cross-over trial to examine the effect of rivastigmine on inter-ictal delirium. Patients are recruited in four centers across the Netherlands and Belgium. We aim to include 150 patients into the cohort study, in order to be able to subsequently include 30 patients into the trial. Patients are included in the trial when inter-ictal delirium, assessed by the Confusion Assessment method (CAM), or a drop in Mini Mental State Examination (MMSE) score of ≥4 during ECT, develops. In the cohort study, comprehensive measurements of ECT-related cognitive side-effects-and their putative determinants-are done at baseline and during the ECT-course. The primary outcome of the clinical trial is the effectiveness of rivastigmine on inter-ictal delirium-severity, assessed with a change in the Delirium Rating Scale-Revised-98. Secondary outcomes of the clinical trial are several ECT-characteristics and side-effects of rivastigmine. Discussion: This study is the first clinical trial with a focus on ECT-induced, inter-ictal delirium. The cohort provides the basis for recruitment of patients for the cross-over trial and additionally provides an excellent opportunity to unravel cognitive side-effects of ECT and identify putative determinants. This paper describes the rationale and study protocol. Clinical trial registration: EudraCT 2014-003385-24.

Predictors of mental health deterioration from pre- to post-COVID-19 outbreak.

BACKGROUND: Mental health was only modestly affected in adults during the early months of the COVID-19 pandemic on the group level, but interpersonal variation was large. AIMS: We aim to investigate potential predictors of the differences in changes in mental health. METHOD: 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 online questionnaires at least once during lockdown in The Netherlands between 1 April and 15 May 2020. Sociodemographic, clinical (number of mental health disorders and personality factors) and COVID-19-related variables were analysed as predictors of relative changes in four mental health outcomes (depressive symptoms, anxiety and worry symptoms, and loneliness), using multivariate linear regression analyses. RESULTS: We included 1517 participants with (n = 1181) and without (n = 336) mental health disorders. Mean age was 56.1 years (s.d. 13.2), and 64.3% were women. Higher neuroticism predicted increases in all four mental health outcomes, especially for worry (ß = 0.172, P = 0.003). Living alone and female gender predicted increases in depressive symptoms and loneliness (ß = 0.05-0.08), whereas quarantine and strict adherence with COVID-19 restrictions predicted increases in anxiety and worry symptoms (ß = 0.07-0.11).Teleworking predicted a decrease in anxiety symptoms (ß = -0.07) and higher age predicted a decrease in anxiety (ß = -0.08) and worry symptoms (ß = -0.10). CONCLUSIONS: Our study showed neuroticism as a robust predictor of adverse changes in mental health, and identified additional sociodemographic and COVID-19-related predictors that explain longitudinal variability in mental health during the COVID-19 pandemic.

Remission Rates Following Electroconvulsive Therapy and Relation to Index Episode Duration in Patients With Psychotic Versus Nonpsychotic Late-Life Depression.

Objective: Electroconvulsive therapy (ECT) is a safe and effective treatment, especially in psychotic late-life depression (LLD). However, it is not yet clear whether the greater efficacy seen in psychotic LLD is because of a shorter index episode duration. The first aim of this study was to substantiate the superior ECT remission rates in patients with psychotic LLD, as compared to patients with nonpsychotic LLD, and a second aim was to investigate whether this association is independent of the index duration.Methods: 186 patients with LLD treated with ECT were included in the study: 76 from the Valerius cohort (data collection from 2001 to 2006) and 110 from the Mood Disorders Treated with Electroconvulsive Therapy (MODECT) cohort (data collection from 2011 to 2013). The Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate depression severity, with remission defined as 2 consecutive MADRS scores < 10. Diagnosis of depression was based on DSM-IV (Valerius) and DSM-IV-TR (MODECT) criteria. A stepwise logistic regression model was built to assess the association between psychotic symptoms, index duration, and remission.Results: Patients with psychotic LLD showed significantly higher remission rates compared to patients with nonpsychotic LLD (68.9% vs 51.0%), independent of index duration, additionally corrected for age, sex, and baseline depression severity (OR = 2.10 [95% CI, 1.07-4.10], P = .03).Conclusions: Patients with psychotic LLD treated with ECT show higher remission rates compared to patients with nonpsychotic LLD. The high remission rates in patients with psychotic LLD are not explained by a shorter index duration. Future studies focusing on neurobiological differences in psychotic versus nonpsychotic depression may indicate why this subtype of depression is very responsive to ECT.Trial Registration: ClinicalTrials.gov identifier: NCT02667353.

Network structure of time-varying depressive symptoms through dynamic time warp analysis in late-life depression.

OBJECTIVES: Late-life major depressive disorder (MDD) can be conceptualized as a complex dynamic system. However, it is not straightforward how to analyze the covarying depressive symptoms over time in case of sparse panel data. Dynamic time warping (DTW) analysis may yield symptom networks and dimensions both at the patient and group level. METHODS: In the Netherlands Study of Depression in Older People (NESDO) depressive symptoms were assessed every 6 months using the 30-item Inventory of Depressive Symptomatology (IDS) with up to 13 assessments per participant. Our sample consisted of 182 persons, aged ≥ 60 years, with an IDS total score of 26 or higher at baseline. Symptom networks dimensions, and centrality metrics were analyzed using DTW and Distatis analyses. RESULTS: The mean age was 69.8 years (SD 7.1), with 69.0% females, and a mean IDS score of 38.0 (SD = 8.7). DTW enabled visualization of an idiographic symptom network in a single NESDO participant. In the group-level nomothetic approach, four depressive symptom dimensions were identified: "core symptoms", "lethargy/somatic", "sleep", and "appetite/atypical". Items of the "internalizing symptoms" dimension had the highest centrality, whose symptom changes over time were most similar to those changes of other symptoms. CONCLUSIONS: DTW revealed symptom networks and dimensions based on the within-person symptom changes in older MDD patients. Its centrality metrics signal the most influential symptoms, which may aid personalized care.

Mental health and perceived impact during the first Covid-19 pandemic year: A longitudinal study in Dutch case-control cohorts of persons with and without depressive, anxiety, and obsessive-compulsive disorders.

BACKGROUND: Little is known about the longer-term impact of the Covid-19 pandemic beyond the first months of 2020, particularly for people with pre-existing mental health disorders. Studies including pre-pandemic data from large psychiatric cohorts are scarce. METHODS: Between April 2020 and February 2021, twelve successive online questionnaires were distributed among participants of the Netherlands Study of Depression and Anxiety, Netherlands Study of Depression in Older Persons, and Netherlands Obsessive Compulsive Disorder Association Study (N = 1714, response rate 62%). Outcomes were depressive symptoms, anxiety, worry, loneliness, perceived mental health impact of the pandemic, fear of Covid-19, positive coping, and happiness. Using linear mixed models we compared trajectories between subgroups with different pre-pandemic chronicity of disorders and healthy controls. RESULTS: Depressive, anxiety and worry symptoms were stable since April-May 2020 whereas happiness slightly decreased. Furthermore, positive coping steadily decreased and loneliness increased - exceeding pre-Covid and April-May 2020 levels. Perceived mental health impact and fear of Covid-19 fluctuated in accordance with national Covid-19 mortality rate changes. Absolute levels of all outcomes were poorer with higher chronicity of disorders, yet trajectories did not differ among subgroups. LIMITATIONS: The most vulnerable psychiatric groups may have been underrepresented and results may not be generalizable to lower income countries. CONCLUSIONS: After a year, levels of depressive and worry symptoms remained higher than before the pandemic in healthy control groups, yet not in psychiatric groups. Nevertheless, persistent high symptoms in psychiatric groups and increasing loneliness in all groups are specific points of concern for mental health care professionals.

The 5-year outcome of subjective quality of life in older schizophrenia patients.

PURPOSE: Subjective quality of life (SQOL) is increasingly valued as an important outcome in schizophrenia treatment. The current study aims to gain insight into changes in SQOL during 5-year follow-up in older persons with schizophrenia spectrum disorders (SSD). METHODS: The sample consisted of a catchment area-based group of 75 older Dutch patients (mean age 66.0 years) with schizophrenia or schizoaffective disorder. Factor analysis was used to identify subdomains of SQOL, measured with the Manchester Short Assessment of Quality of Life (MANSA). 5-Year course trajectories and putative predictors of changes in SQOL and subdomains were examined using multivariable regression analyses. RESULTS: 72% was stable in either a high or a low SQOL-status over time. When outcome was defined as change score, 36%, 20%, and 44% of participants, respectively, reported a clinically relevant improvement, deterioration, or no change of SQOL during follow-up. Three SQOL subdomains were identified with different course trajectories; 33% of participants reported an improvement in the subdomains satisfaction with 'daily life' and 'personal circumstances.' The largest number of declines (28%) was reported in the subdomain satisfaction with 'physical and mental health.' Predictors of positive total and subdomain SQOL-change scores were limited to a higher age of onset and higher baseline SQOL scores. CONCLUSION: In this cohort of older persons, it was demonstrated that SQOL might considerably change during 5-year follow-up. As course trajectories differed among subdomains, separate evaluation of these subdomains is clinically relevant. Improvement of SQOL is an attainable goal in older SSD patients despite deteriorating physical health.

Impact of Inflammation on Cognitive Functioning After Electroconvulsive Therapy in Older Patients with Depression with and Without White Matter Hyperintensities.

OBJECTIVE: Should we treat older, patients with depression with white matter hyperintensities (WMH) with electroconvulsive therapy (ECT)? WMH, inflammation, depression and cognitive functioning are suggested to be intertwined. Hence, this study investigates whether the association between inflammation and cognition is different in patients with depression with or without WMH. METHODS: Cognitive functioning was assessed using the Mini-Mental State Examination during and after a course of ECT in 77 older patients with depression. Serum samples (C-reactive protein [CRP], interleukin-6 [IL-6], interleukin-10 [IL-10] and tumour necrosis factor-alpha [TNF-α]) and 3T magnetic resonance imaging were obtained prior to ECT. RESULTS: An interaction effect was found for IL-10, but not for CRP, IL-6 or TNF-α. CONCLUSION: In general, the association between inflammatory markers and cognition in patients with depression treated with ECT is not different in patients with WMH compared to patients without WMH.