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

Validation and performance of the sleep inertia questionnaire in central disorders of hypersomnolence

BACKGROUND

Optimal measurement tools for problematic sleep inertia, common in some central disorders of hypersomnolence (CDH), have not yet been determined. We evaluated the performance of the Sleep Inertia Questionnaire (SIQ) in CDH, and how well it distinguished hypersomnolent groups from controls, and IH (idiopathic hypersomnia) from narcolepsy type 1 (NT1).

METHODS

This prospective, bi-centric study included 63 control, 84 IH, 16 NT1, 18 narcolepsy type 2 (NT2), and 88 subjective excessive daytime sleepiness (sEDS) participants, using ICSD-3 criteria. 126 (47.2 %) participants were on any medication at the time of SIQ completion. We assessed construct validity of SIQ scores, and sleep inertia duration (SID), and compared them across diagnoses, controlling for age and center. We derived cutpoints to distinguish hypersomnolent patients from controls and IH from NT1. Sensitivity analyses for depression, chronotype, and medication were performed.

RESULTS

The SIQ sum and composite score were significantly lower in controls than in other groups (p < 0.0001), demonstrating outstanding ability to distinguish patients from controls (AUCs 0.92), without differences among hypersomnolent groups. SID (AUC 0.76) was significantly shorter in controls than in all hypersomnolent groups except NT1, and was shorter in NT1 than in IH or sEDS. Optimal SIQ sum cutpoint was 42 (J = 0.71) for patients versus controls. Optimal SID cutpoint in distinguishing IH from NT1 was 25 min (J = 0.39).

CONCLUSION

The SIQ has excellent ability to distinguish hypersomnolent patients from healthy controls, after controlling for depression, eveningness, and medication. SID is best at distinguishing IH from NT1.

Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentime

Background

Mood and anxiety disorders are highly prevalent and comorbid worldwide, with variability in symptom severity that fluctuates over time. Digital phenotyping, a growing field that aims to characterize clinical, cognitive and behavioral features via personal digital devices, enables continuous quantification of symptom severity in the real world, and in real-time.

Methods

In this study, N=114 individuals with a mood or anxiety disorder (MA) or healthy controls (HC) were enrolled and completed 30-days of ecological momentary assessments (EMA) of symptom severity. Novel real-world measures of anxiety, distress and depression were developed based on the established Mood and Anxiety Symptom Questionnaire (MASQ). The full MASQ was also completed in the laboratory (in-lab). Additional EMA measures related to extrinsic and intrinsic motivation, and passive activity data were also collected over the same 30-days. Mixed-effects models adjusting for time and individual tested the association between real-world symptom severity EMA and the corresponding full MASQ sub-scores. A graph theory neural network model (D EP NA) was applied to all data to estimate symptom interactions.

Results

There was overall good adherence over 30-days (MA=69.5%, HC=71.2% completion), with no group difference (t (58) =0.874, p=0.386). Real-world measures of anxiety/distress/depression were associated with their corresponding MASQ measure within the MA group (t's > 2.33, p's < 0.024). Physical activity (steps) was negatively associated with real-world distress and depression (IRRs > 0.93, p's ≤ 0.05). Both intrinsic and extrinsic motivation were negatively associated with real-world distress/depression (IRR's > 0.82, p's < 0.001). D EP NA revealed that both extrinsic and intrinsic motivation significantly influenced other symptom severity measures to a greater extent in the MA group compared to the HC group (extrinsic/intrinsic motivation: t (46) = 2.62, p < 0.02, q FDR < 0.05, Cohen's d = 0.76; t (46) = 2.69, p < 0.01, q FDR < 0.05, Cohen's d = 0.78 respectively), and that intrinsic motivation significantly influenced steps (t (46) = 3.24, p < 0.003, q FDR < 0.05, Cohen's d = 0.94).

Conclusions

Novel real-world measures of anxiety, distress and depression significantly related to their corresponding established in-lab measures of these symptom domains in individuals with mood and anxiety disorders. Novel, exploratory measures of extrinsic and intrinsic motivation also significantly related to real-world mood and anxiety symptoms and had the greatest influencing degree on patients' overall symptom profile. This suggests that measures of cognitive constructs related to drive and activity may be useful in characterizing phenotypes in the real-world.

Understanding heterogeneity, comorbidity, and variability in depression: Idiographic models and depression outcomes

This study uses time-intensive, item-level assessment to examine individual depressive and co-occurring symptom dynamics. Participants experiencing moderate-severe depression (N = 31) completed ecological momentary assessment (EMA) four times per day for 20 days (total observations = 2480). We estimated idiographic networks using MDD, anxiety, and ED items. ED items were most frequently included in individual networks relative to depression and anxiety items. We built ridge and logistic regression ensembles to explore how idiographic network centrality metrics performed at predicting between-subject depression outcomes (PHQ-9 change score and clinical deterioration, respectively) at 6-months follow-up. For predicting PHQ-9 change score, R2 ranged between 0.13 and 0.28. Models predicting clinical deterioration ranged from no better than chance to 80 % accuracy. This pilot study shows how co-occurring anxiety and ED symptoms may contribute to the maintenance of depressive symptoms. Future work should assess the predictive utility of psychological networks to develop understanding of how idiographic models may inform clinical decisions.

Examining the influence of episode number and age of onset on individual depressive symptoms across episodes of major depression

Major depression is characterized by an episodic course with symptom manifestations differing across episodes. Previous work has found that symptom presentation differs across age. However, studies of symptom presentation have largely focused on symptoms in individual episodes, requiring further investigation of longitudinal symptom change. This study explored the impact of the initial age of onset, the number of episodes, and age of onset of each episode on individual depressive symptoms, while accounting for episode severity. We used data from the Oregon Adolescent Depression Project (N = 629) examining participants with at least one major depressive episode, assessed by diagnostic interview, across a 15-year follow-up. Multilevel logistic regression models revealed that approximately 20-25% of the main effects were significant and some were qualified by cross-level interactions. However, only a few associations remained robust after correcting for multiple comparisons. Specifically, older initial age of onset was associated with fatigue, younger initial age of onset for the first episode was associated with suicidal ideation, and a lower episode number was associated with weight loss. These findings highlight potential initial age of onset and scar effects influencing symptom manifestation, but require replication.

Individualized strategies for depression: narrative review of clinical profiles responsive to vortioxetine

BACKGROUND

Depression is a highly heterogeneous disorder, often resulting in suboptimal response and remission rates. This underscores the need for more nuanced clinical characterization of patients to tailor individualized treatment plans. Emerging evidence highlights the critical role of cognitive and emotional dysfunction in major depression, prompting the exploration of novel therapeutic interventions that target these specific symptom domains.

MAIN TEXT

Vortioxetine, a multimodal antidepressant, enhances serotonergic activity while also modulating several other neurotransmitter systems involved in depressive symptoms such as emotional blunting, anhedonia, and cognitive dysfunction. Numerous randomized, placebo-controlled trials have demonstrated vortioxetine's efficacy and safety in treating depression, particularly in specific subgroups of depressed patients, including those with cognitive deficits and comorbid anxiety symptoms or disorders. Although not randomized or placebo-controlled, studies have also shown vortioxetine's efficacy in depressed patients with emotional blunting or anhedonia. Vortioxetine's ability to effectively treat a range of depressive symptoms, including anhedonia, emotional blunting, anxiety, and cognitive dysfunction, provides an individualized treatment solution for depressed individuals suffering from these symptoms. The purpose of this paper is to identify clinical profiles of patients who may benefit from vortioxetine, with the goal of optimizing therapeutic outcomes.

CONCLUSION

Vortioxetine has been shown to be effective for patients with depression and symptoms such as anhedonia, emotional blunting, anxiety, and cognitive dysfunction. Tailoring treatment plans to individual needs and personalizing treatment choices based on the specific symptoms presented by depressed patients improve treatment outcomes.

Cognitive trajectories in older adults and the role of depressive symptoms: A 7-year follow-up study

OBJECTIVES

To examine different trajectories of cognitive changes in elderly adults and explore the mediating role of depressive symptoms.

DESIGN

A 7-year, community-based, prospective cohort study.

SETTING

The downtown neighborhood of Shanghai, China.

PARTICIPANTS

A cohort of 394 older adults, with an average age of 71.8 years, was recruited in 2015 and has been reassessed every two years until 2021.

METHODS

Latent Class Growth Analysis was used to model aging trajectories and Linear Mixed-Effect Models for Repeated Measures were used to estimate the least squares mean changes of cognition between subjects with depression (DEP+) and without (DEP-) across all visits.

RESULTS

Three cognitive trajectories were identified: the "successful aging" (SA) trajectory had the best and most consistent performance (n=229, 55.9%); the "normal aging" (NA) trajectory showed lower but stable cognition (n=141, 37.3%); while the "cognitive decline" (CD) trajectory displayed poor and declining cognition (n=24, 6.8%). Depressive symptoms were found to be influential across all trajectories. In the CD trajectory, the MoCA scores of the DEP+ group increased in within-group comparisons and were significantly higher than those of the DEP- group at visits 1 and 3 in between-group comparisons. A similar trend was observed in the NA trajectory, though it did not reach statistical significance.

CONCLUSIONS

Our research suggests that mild and decreasing depressive symptoms can be a reversible factor that might slow down the irreversible cognitive decline in the elderly. Therefore, we suggest that even mild depressive symptoms in the elderly should be monitored and detected.

Latent classes of symptom trajectories among major depressive disorder patients in China

OBJECTIVE

This study aimed to understand the long-term symptom trajectories of Chinese patients with major depressive disorder (MDD) using piecewise latent growth modeling and growth mixture modeling. The investigation also aimed to identify the baseline characteristics indicative of poorer treatment outcomes.

METHODS

A total of 558 outpatients with MDD were assessed using a sequence of surveys. The Hamilton Rating Scale for Depression (HRSD), Hamilton Anxiety Rating Scale (HAMA), and Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) were used to evaluate baseline depression, anxiety, and cognitive function. Depression symptom severity was subsequently measured at the 1-month, 2-month, 6-month, 1-year, and 2-year follow-ups.

RESULTS

Results indicated three depressive symptomology trajectories, including (a) severe, improving class (12.72 %), (b) partially responding, later deteriorating class (6.09 %), and (c) moderate, improving class (81.18 %). Logistic regression analyses showed that a history of cardiovascular disease (CVD) increased the odds of belonging to the partially responding, later deteriorating class, whereas higher baseline depression increased the odds of belonging to the severe, improving class compared to the moderate, improving class. Patients who experienced less depression relief during the first month of treatment had a lower probability of belonging to the moderate, improving class.

LIMITATIONS

Participant attrition in this study may have inflated the estimated rate of treatment-resistant patients.

CONCLUSIONS

The burden of CVD and poorer initial treatment response are plausible risk factors for poorer treatment outcomes, highlighting targets for intervention in Chinese MDD patients.

Disentangling between-person and within-person associations of physical symptoms of depression with self-perceived health and life satisfaction: A longitudinal study in Chilean adults

Depression is a major health problem in Chile. Evidence suggests that physical symptoms of depression (PSD) negatively impact self-perceived health and life satisfaction. The aim of this study was to determine the between-person and within-person associations of PSD with self-perceived health and life satisfaction in Chilean adults. The sample consisted of 1424 participants (64.54% female; Mage = 46.77, SD = 14.88) with data in five waves of the Social Longitudinal Study of Chile. Variables were measured through self-report questionnaires. Hypotheses were tested using multilevel analysis. At the within-person level, physical slowing, fatigue, and sleep problems were associated with poorer self-perceived health and lower life satisfaction. At the between-person level, physical slowing and fatigue were associated with poorer perceived health and lower life satisfaction. PSD are associated with self-perceived health and life satisfaction in Chilean adults longitudinally. The study highlights the importance of monitoring PSD changes in Chilean adults.

Current maternal depression associated with worsened children's social outcomes during middle childhood: Exploring the role of positive affect socialization

BACKGROUND

Maternal depression negatively predicts aspects of the mother-child relationship and social functioning in offspring. This study evaluated interrelations between mothers' depression history and current severity with dynamic indices of positive affect socialization and indices of offspring' social outcomes.

METHODS

N = 66 mother-child dyads in which approximately 50 % of mothers had a history of maternal depression were recruited. Children were 6-8 years old and 47.7 % male. Dyads completed a positive interaction task, which was coded for mother and child positive affect. Mothers and children reported on peer functioning and social problems and children reported on the quality of their best friendships at 1-year follow-up.

RESULTS

Current level of maternal depression, but not depression history, was related to more social problems and lower best friend relationship quality. Indices of positive affect socialization were not related to history or current levels of maternal depression, or social outcomes, with the exception of maternal depression history predicting greater likelihood of mothers joining their children in expressing positive affect. Exploratory, supplementary analysis revealed that this may be due to treatment history among these mothers.

LIMITATIONS

Conclusions should be tempered by the small sample size, which limited the types of analyses that were conducted.

CONCLUSION

Results suggest that the effect of maternal depression on aspects of child social outcomes could be specific to current levels. Our data also did not support previously found associations between maternal depression and positive affect socialization. Results suggest positive implications for the effect of treatment for maternal depression for mother-child dynamics.

Using digital phenotyping to capture depression symptom variability: detecting naturalistic variability in depression symptoms across one year using passively collected wearable movement and sleep data

Major Depressive Disorder (MDD) presents considerable challenges to diagnosis and management due to symptom variability across time. Only recent work has highlighted the clinical implications for interrogating depression symptom variability. Thus, the present work investigates how sociodemographic, comorbidity, movement, and sleep data is associated with long-term depression symptom variability. Participant information included (N = 939) baseline sociodemographic and comorbidity data, longitudinal, passively collected wearable data, and Patient Health Questionnaire-9 (PHQ-9) scores collected over 12 months. An ensemble machine learning approach was used to detect long-term depression symptom variability via: (i) a domain-driven feature selection approach and (ii) an exhaustive feature-inclusion approach. SHapley Additive exPlanations (SHAP) were used to interrogate variable importance and directionality. The composite domain-driven and exhaustive inclusion models were both capable of moderately detecting long-term depression symptom variability (r = 0.33 and r = 0.39, respectively). Our results indicate the incremental predictive validity of sociodemographic, comorbidity, and passively collected wearable movement and sleep data in detecting long-term depression symptom variability.

Electroconvulsive therapy improves somatic symptoms before mood in patients with depression: A directed network analysis

BACKGROUND

The recent network perspective of depression conceptualizes depression as a dynamic network of causally related symptoms, that contrasts with the traditional view of depression as a discrete latent entity that causes all symptoms. Electroconvulsive therapy (ECT) is an effective treatment for severe depression, but little is known about the temporal trajectories of symptom improvement during a course of ECT.

OBJECTIVE

To gain insight into the dynamics of depressive symptoms in individuals treated with ECT.

METHODS

The Quick Inventory of Depressive Symptomatology (QIDS) was used to assess symptoms twice a week in 68 participants with a unipolar or bipolar depression treated with ECT, with an average of 12 assessments per participant. Dynamic time warping (DTW) was used to analyze individual time series data, which were subsequently aggregated to calculate a directed symptom network and the in- and out-strength for each symptom.

RESULTS

Participants had a mean age of 49.6 (SD = 12.8) and 60% were female. Somatic symptoms (e.g., decreased weight) and suicidal ideation showed the highest out-strength values, indicating that their improvement tended to precede improvements in mood symptoms, which showed high in-strength. Sad mood had the highest in-strength, and thus appeared to be the last symptom to improve during ECT treatment (p < 0.001).

CONCLUSION

This study addresses a gap in the existing literature on ECT, by first analysing the temporal trajectories of symptoms within individual patients and subsequently aggregating them to the group level. The results show that somatic symptoms tend to improve before mood symptoms during ECT.

Response trajectories during escitalopram treatment of patients with major depressive disorder

Depression is a leading global cause of disability, yet about half of patients do not respond to initial antidepressant treatment. This treatment difficulty may be in part due to the heterogeneity of depression and corresponding response to treatment. Unsupervised machine learning allows underlying patterns to be uncovered, and can be used to understand this heterogeneity by finding groups of patients with similar response trajectories. Prior studies attempting this have clustered patients using a narrow range of data primarily from depression scales. In this work, we used unsupervised machine learning to cluster patients receiving escitalopram therapy using a wide variety of subjective and objective clinical features from the first eight weeks of the Canadian Biomarker Integration Network in Depression-1 trial. We investigated how these clusters responded to treatment by comparing changes in symptoms and symptom categories, and by using Principal Component Analysis (PCA). Our algorithm found three clusters, which broadly represented non-responders, responders, and remitters. Most categories of features followed this response pattern except for objective cognitive features. Using PCA with our clusters, we found that subjective mood state/anhedonia is the core feature of response with escitalopram, but there exists other distinct patterns of response around neurovegetative symptoms, activation, and cognition.

Association of depression phenotypes and antidepressant treatment with mortality due to cancer and other causes: a community-based cohort study

Objective

This study aimed to assess the association of somatic depressive symptoms (SDS), cognitive/emotional depressive symptoms (C-EDS), and antidepressant treatment on mortality due to cancer and other causes in a community cohort.

Methods

A community-based sample recruited in 1995, 2000, and 2005 aged between 35 and 75 years was examined in two waves and followed for a median of 6.7 years. SDS and C-EDS phenotypes were assessed using the Patient Health Questionnaire-9. Medication used by participants was collected. Deaths and their causes were registered during follow-up. Cox proportional hazard models stratified by sex were performed to determine the association between depressive phenotypes and mortality.

Results

The cohort consisted of 5,646 individuals (53.9% women) with a mean age of 64 years (SD = 11.89). During the follow-up, 392 deaths were recorded, of which 27.8% were due to cancer. C-EDS phenotype was associated with an increased risk of cancer mortality in both men (HR = 2.23; 95% CI = 1.11-4.44) and women (HR = 3.69; 95% CI = 1.69-8.09), and SDS was significantly associated with non-cancer mortality in men (HR = 2.16; 95 CI % = 1.46-3.18). Selective serotonin reuptake inhibitors (SSRIs) were significantly associated with both cancer (HR = 2.78; 95% CI = 1.10-6.98) and non-cancer mortality (HR = 2.94; 95% CI = 1.76-4.90) only in the male population.

Conclusion

C-EDS phenotype was related to an increased risk of cancer mortality at 6 years. In addition, the use of SSRIs in the male population was associated with cancer and all-cause mortality.

Characteristics and symptomatology of major depressive disorder with atypical features from symptom to syndromal level

OBJECTIVE

To explore clinical characteristics and symptomatology of major depressive disorder (MDD) with atypical features based on DSM criteria or only reversed vegetative symptoms.

METHOD

A total of 3187 patients who met DSM-IV TR criteria for MDD were enrolled. Demographics and symptomatology covering multiple symptom domains were assessed and compared between three groups of cases: those who met DSM criteria for atypical specifier (the DAD group), those who had at least one reversed vegetative symptoms (hypersomnia or hyperphagia) (the SAD group) without meeting DSM atypical specifier criteria, and those without any reversed vegetative symptoms (the NAD group).

RESULTS

The DAD and SAD group accounted for 4.4 % and 14.4 % of the participants, respectively. The DAD cases were characterized by a highest proportion of hospitalizations, longest duration of current episode and worst quality of life. The DAD and SAD cases were more likely to adopt unhealthy behaviors (smoking and alcohol drinking). Most depressive symptoms related to higher illness severity and treatment resistance were more frequent in the DAD cases, followed by the SAD cases, and least frequent in the NAD cases.

LIMITATIONS

A cross-sectional design and a non-validated questionnaire were used.

CONCLUSIONS

The findings support the role of DSM defined atypical depression as a valid MDD subtype and provide evidence for clinical utility of the simplified approach of defining atypical features based on only reversed vegetative symptoms. This has implications for illness screening, public health, suicide prevention and better treatment planning for depressed individuals with atypical features even below syndromal level.

Which residual symptoms predict relapse after successful electroconvulsive therapy for late-life depression?

The risk of relapse following successful acute-phase treatment of late-life depression (LLD), including electroconvulsive therapy (ECT), is substantial. In order to improve reliable prediction of individuals' risk of relapse, we assessed the association between individual residual symptoms following a successful acute course of ECT for LLD and relapse at six-month follow-up. This prospective cohort study was part of the MODECT study, which included 110 patients aged 55 years and older with major depressive disorder. Participants who showed response to the index ECT course were monitored for relapse for six months. We used multivariable stepwise logistic regression models to assess the association between the scores on the 10 individual Montgomery-Åsberg Depression Rating Scale (MADRS) items at the end of the acute ECT course and relapse at six-month follow-up. Of the 80 responders with available six-month follow-up data (58.75% of which had psychotic features at baseline), 36.25% had relapsed. Higher scores on the MADRS items 'reduced sleep' (odds ratio (OR) = 2.03, 95% confidence interval (CI) = 1.11-3.69, p = 0.0214) and 'lassitude' (OR = 1.62, 95% CI = 1.00-2.62, p = 0.0497) at the end of the acute ECT course were significantly associated with increased risk of relapse at six-month follow-up. In conclusion, some residual depressive symptoms, including sleep disturbance and lassitude, may help better identify patients vulnerable to relapse following a successful acute course of ECT for LLD. If these findings can be replicated, studies assessing interventions that target specific residual symptoms may further reduce post-ECT depressive relapse rates.

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.

Cognitive outcomes are differentially associated with depression severity trajectories during psychotherapy treatment for late life major depressive disorder

OBJECTIVES

Late Life Depression (LLD) is associated with persistent cognitive dysfunction even after depression symptoms improve. The present study was designed to examine cognitive outcomes associated with the pattern of depression severity change during psychotherapy intervention for LLD.

METHODS

96 community-dwelling adults ages 65-91 with major depressive disorder completed 12 sessions of Problem-Solving Therapy at the University of California, San Francisco. Nonlinear trajectories of depression severity ratings using the Hamilton Depression Rating Scale were computed from multiple time points collected throughout the weekly psychotherapy intervention. Performance on measures of cognition (information processing speed, executive functioning, verbal learning, memory) was assessed at baseline and post-treatment. Linear mixed-effects models examined associations between nonlinear depression severity trajectories and post-treatment change in cognitive performance.

RESULTS

Broadly, different patterns of depression change during treatment were associated with improved cognition post-treatment. Greater and more consistent interval improvements in depression ratings were differentially associated with improvements in aspects of verbal learning, memory, and executive function post-treatment, while no associations were found with information processing speed.

CONCLUSIONS

The heterogeneity of depression trajectories associated with improved cognitive outcomes suggests that the temporal pattern of depression response may impact specific cognitive processes distinctly. Results suggest that use of nonlinear depression severity trajectories may help to elucidate complex associations between the time course of depression response and cognitive outcomes of psychotherapy in LLD. These findings have important implications for identifying treatment targets to enhance clinical and cognitive outcomes of psychotherapy in LLD.

The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China

Background

Depression is a common psychiatric disorder in older adults that affects their health-related quality of life. Two percent of adults over the age of 55 suffer from major depression, and the prevalence of depression increases with age. Even in the absence of major depressive disorder, 10–15% of older adults have clinically significant depressive symptoms.

Objectives

Epidemiological studies on the association between different gender eating patterns and depression show inconsistent associations. Our study examined whether different gender eating patterns are related to depression. We consider eating patterns individually and as a joint exposure to predefined eating patterns.

Methods

Principal component analysis (PCA) was performed on the data of the 24-h diet recall dietary intake, and the dietary pattern was determined. Linear regression models are used to explore the relationship between different diets and depression of men and women; weighted quantile sum (WQS) regression, quantile g calculation (qgcomp) and Bayesian kernel machine regression (BKMR) are performed as Secondary analysis.

Results

In the dietary patterns model, we found that the vegetable and fruit-based diet has a significant inhibitory effect in women, and the egg-milk-based diet has a significant inhibitory effect in men. We found that when all dietary factors are above the 55th percentile, there is a significant positive correlation between multiple dietary patterns and depression risk. We also determined a positive correlation between meat and obesity risk and a negative correlation between egg and milk and vegetables and fruits.

Conclusions

In the study population, after controlling for other baseline indicators and predictors of dietary pattern exposure, a fruit and vegetable-based diet was associated with a slightly healthier and lower risk of depression, while a meat-based dietary pattern associated with a higher risk of depression, and this association effect varies between genders.

Toward personalized medicine in connectomic deep brain stimulation

At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.

Greater baseline connectivity of the salience and negative affect circuits are associated with natural improvements in anxiety over time in untreated participants

BACKGROUND

There is limited research examining the natural trajectories of depression and anxiety, how these trajectories relate to baseline neural circuit function, and how symptom trajectory-circuit relationships are impacted by engagement in lifestyle activities including exercise, hobbies, and social interactions. To address these gaps, we assessed these relations over three months in untreated participants.

METHODS

262 adults (59.5% female, mean age 35) with symptoms of anxiety and depression, untreated with pharmacotherapy or behavioral therapy, completed the DASS-42, WHOQOL, and custom surveys at baseline and follow-up to assess symptoms, psychosocial function, and lifestyle activity engagement. At baseline, participants underwent fMRI under task-free and task-evoked conditions. We quantified six circuits implicated in these symptoms: default mode, salience, negative and positive affect, attention, and cognitive control.

RESULTS

From baseline to 3 months, some participants demonstrated a natural improvement in anxiety (24%) and depression (26%) symptoms. Greater baseline salience circuit connectivity (pFDR=0.045), specifically between the left and right insula (pFDR=0.045), and greater negative affect circuit connectivity elicited by sad faces (pFDR=0.030) were associated with anxiety symptom improvement. While engagement in lifestyle activities were not associated with anxiety improvements, engagement in hobbies moderated the association between negative affect circuit connectivity and anxiety symptom improvement (p = 0.048).

LIMITATIONS

The observational design limits causal inference.

CONCLUSIONS

Our findings highlight the role of the salience and negative affect circuits as potential circuit markers of natural anxiety symptom improvements over time. Future studies that identify biomarkers associated with symptom improvements are critical for the development of personalized treatment targets.

Dynamic time warp analysis of individual symptom trajectories in depressed patients treated with electroconvulsive therapy

BACKGROUND

Although electroconvulsive therapy (ECT) effectively improves severity scores of depression, its effects on its individual symptoms has scarcely been studied. We aimed to study which depressive symptom trajectories dynamically cluster together in individuals as well as groups of patients during ECT using Dynamic Time Warp (DTW) analysis.

METHODS

We analysed the standardized weekly scores on the 25-item abbreviated version of the Comprehensive Psychopathological Rating Scale (CPRS) in depressed patients before and during their first six weeks of ECT treatment. DTW analysis was used to analyse the (dis)similarity of time series of items scores at the patient level (300 'DTW distances' per patient) as well as on the group level. Hierarchical cluster, network, and Distatis analyses yielded symptom dimensions.

RESULTS

We included 133 patients, 64.7% female, with an average age of 60.4 years (SD 15.1). Individual DTW distance matrices and networks revealed marked differences in hierarchical and network clusters among patients. Based on cluster analyses of the aggregated matrices, four symptom clusters emerged. In patients who reached remission, the average DTW distance between their symptoms was significantly smaller than non-remitters, reflecting denser symptom networks in remitters than non-remitters (p=0.04).

LIMITATIONS

The assessments were done only weekly during the first six weeks of ECT treatment. The use of individual items of the abbreviated CPRS may have led to measurement error as well as floor and ceiling effects.

CONCLUSION

DTW offers an efficient new approach to analyse symptom trajectories within individuals as well as groups of patients, aiding personalized medicine of psychopathology.

Age and sex-related variability in the presentation of generalized anxiety and depression symptoms

BACKGROUND

Generalized anxiety and depression are extremely prevalent and debilitating. There is evidence for age and sex variability in symptoms of depression, but despite comorbidity it is unclear whether this extends to anxiety symptomatology. Studies using questionnaire sum scores typically fail to address this phenotypic complexity.

METHOD

We conducted exploratory and confirmatory factor analyses on Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) items to identify latent factors of anxiety and depression in participants from the Genetic Links to Anxiety and Depression Study (N = 35,637; 16-93 years). We assessed age- and sex-related variability in latent factors and individual symptoms using multiple logistic regression.

RESULTS

Four factors of mood, worry, motor, and somatic symptoms were identified (comparative fit index [CFI] = 0.99, Tucker-Lewis Index [TLI] = 0.99, root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residuals [SRMR] = 0.04). Symptoms of irritability (odds ratio [OR] = 0.81) were most strongly associated with younger age, and sleep change (OR = 1.14) with older age. Males were more likely to report mood and motor symptoms (p < .001) and females to report somatic symptoms (p < .001).

CONCLUSION

Significant age and sex variability suggest that classic diagnostic criteria reflect the presentation most commonly seen in younger males. This study provides avenues for diagnostic adaptation and factor-specific interventions.

Highly variable suicidal ideation: a phenotypic marker for stress induced suicide risk

Suicidal behavior (SB) can be impulsive or methodical; violent or not; follow a stressor or no obvious precipitant. This study tested whether childhood trauma, affective lability, and aggressive and impulsive traits predicted greater SI variability. We also assessed whether affective lability, aggressive or impulsive traits explain childhood trauma's effects on SI variability and whether those with highly variable SI respond to stressful events with increases in SI. Finally, we assessed variable SI's trajectory over 2 years. Depressed participants (n = 51) had ecological momentary assessments (EMA) over 7 days at baseline, 3, 6, 12, 18, and 24 months. SI variability was assessed using the square Root of the Mean Square of Successive Deviations. Mixed Effects Models were fit as appropriate. Childhood trauma was associated with subsequent aggression. Physical abuse predicted both aggression and affective lability as well as SI variability, but not impulsivity. In two-predictor models, physical abuse's effect on SI variability was no longer significant, when controlling for the effect of higher aggression and impulsivity. Those with high SI variability exhibited greater increases in SI after stressors compared with those with less variability. We did not find that SI variability changed over time, suggesting it might be trait-like, at least over 2 years. Variable SI predisposes to marked SI increases after stressful events and may be a trait increasing risk for impulsive SB, at least over 2 years.

Socioeconomic inequalities in impairment associated with depressive symptoms: Evidence from the National Survey on Drug Use and Health

OBJECTIVE

Individuals with low socioeconomic status have higher rates of depression, but it is unknown whether the socioeconomically disadvantaged also have more disabling depressive symptoms. We examined (1) the associations of three indicators of socioeconomic status with depression-related severe role impairment, and (2) whether socioeconomic factors moderate the association between individual depression symptoms and depression-related severe role impairment.

METHODS

We used data from the National Survey on Drug Use and Health (NSDUH). Depressive symptoms, role impairment and socioeconomic indicators (poverty, participation in workforce, educational attainment) were self-reported by participants. The analytic sample consisted of participants who screened positive for a depressive episode during past 12 months (n = 32 661). We used survey-weighted logistic models to examine the associations of depressive symptoms with severe role impairment and the modifying effects of socioeconomic indicators.

RESULTS

The association between depression symptom count and severe role impairment was stronger among those not in workforce (OR = 1.12[1.02-1.23]). The association between specific depression symptoms and severe role impairment was stronger for conditions of poverty (fatigue, OR = 2.97 [1.54-5.73]; and anhedonia, OR = 1.93[1.13-3.30]), workforce non-participation (inability to concentrate/indecisiveness, OR = 1.54[1.12-2.12]), and lower educational attainment (anhedonia, OR = 0.77 [0.59-0.99]). Feelings of worthlessness was the only symptom with independent associations for all socioeconomic groups (adjusted OR = 1.91[1.35-2.70]).

CONCLUSION

Depression was more frequent and also more disabling for socioeconomically disadvantaged groups, especially when assessed with workforce participation. Additionally, some specific symptoms showed socioeconomic differences. Our findings highlight the need to prioritize population groups with more severe impairment associated with depressive symptoms.

Depression symptom profiles and long-term response to cognitive behavioral therapy plus contingency management for smoking cessation

BACKGROUND

Depression is heterogeneous in nature and using diagnostic categories limits insight into understanding psychopathology and its impact on treatment efficacy. This secondary analysis sought to: 1) identify distinct subpopulations of cigarette users with depression, and 2) examine their response to cognitive-behavioral treatment (CBT) + contingency management (CM) for smoking cessation at one year.

METHOD

The sample comprised 238 (74 % females) adults who smoke receiving CBT only or CBT + CM. A latent class analysis was conducted on baseline depressive symptoms measured using the Beck Depression Inventory-II. Generalized estimating equations assessed the main and interactive effects of class, time, treatment, and sex on smoking abstinence.

RESULTS

Three distinct classes were identified: C1 (n= 76/238), characterized by mild depression, loss of energy, pessimism, and criticism, C2 (n= 100/238) presenting moderate severity and decreased appetite, and C3 (n= 62/238) showing severe depression, increased appetite, and feelings of punishment. There was a significant cluster × treatment interaction, which indicated additive effects of CM over CBT alone for Class 1 and 2. Persons in Class 1 and 2 were 3.60 [95 % CI: 1.62, 7.97] and 2.65 [95 % CI: 1.19, 5.91] times more likely to be abstinent if CBT + CM was delivered rather than CBT only. No differential sex effects were observed on treatment response according to cluster.

CONCLUSIONS

Profiling depression symptom subtypes of cigarette users may be more informative to improve CM treatment response than merely focusing on total scores.

Individual and common patterns in the order of symptom improvement during outpatient treatment for major depression

BACKGROUND

Research so far provided few clues on the order in which depressive symptoms typically remit during treatment. This study examined which depressive symptoms improve first, and whether symptoms changed before, simultaneous with, or after the core symptoms of depression (i.e., sad mood, loss of pleasure, and loss of interest).

METHODS

Participants were 176 patients with Major Depressive Disorder (MDD) receiving outpatient treatment (a combination of pharmacotherapy and psychological interventions) for depression. Participants filled out the Inventory of Depressive Symptomatology - Self Report (IDS-SR) for 16 to 20 consecutive weeks. For each symptom, the timing of onset of a persistent improvement was determined for each single-subject separately.

RESULTS

Which symptoms improved first differed markedly across patients. The core depression symptoms improved 1.5 to 2 times more often before (48% - 60%) than after (19% -28%) depressive cognitions ('view of myself' and 'view of the future'), anxiety symptoms ('feeling irritable' and 'feeling anxious / tense') and vegetative symptoms ('loss of energy', 'slowed down', and 'physical energy'). Only improvements in suicidal thoughts were more likely to occur before (46% - 48%) than after (29%) improvements in the depression core symptoms.

LIMITATIONS

Not all 'core depression-non-core symptom' combinations could be tested because some symptoms did not improve in a sufficient number of patients.

CONCLUSIONS

Which improvements mark the start of symptom remission differed between patients. Improvements in the core depression symptoms 'sad mood', 'loss of interest', and 'loss of pleasure' were more likely to occur before than after improvements in non-core symptoms.

Prevalence, course, and determinants of suicide ideation and attempts in patients with a depressive and/or anxiety disorder: A review of NESDA findings

BACKGROUND

Depressive and anxiety disorders are often associated with suicide ideation (SI) and attempt (SA). However, analyses of prevalence, course, and more specific risk mechanisms are needed to improve knowledge and detection of high risk individuals with depressive and anxiety disorders. Previous studies often lacked statistical power, assessment of detailed determinants and follow-up measurements.

METHODS

The Netherlands Study of Depression and Anxiety (NESDA), a large cohort study, overcomes some earlier limitations. Scale for Suicide Ideation and Compositive Interview Diagnostic Instrument data were analyzed to report on prevalence of SI and SA. Additionally, important sociodemographic, clinical, psychological, environmental, and neurobiological determinants and course of SI and SA identified in depressive and/or anxiety disorder respondents in 16 NESDA articles were summarized.

RESULTS

Within respondents with 12-month diagnosis (n=1,783), SI and 12-month SA prevalence ranged from 17.1-20.1% and 0.8-3.0% respectively across 5 waves during 9-year follow-up and SI was highly recurrent. Both SI and SA were especially associated with comorbid depression and anxiety, higher clinical severity, sleep dysfunctions, higher aggression and hopelessness, and childhood trauma. In the (neuro)biological domain, SI was linked with immune dysregulation and SA with abnormal brain activity during emotion processing and genetic risk.

LIMITATIONS

Most articles were cross-sectional in nature, preventing causal inferences and no conclusions could be drawn about the overall magnitude of results.

CONCLUSION

SI and SA are multifactorial phenomena and especially prevalent amongst comorbid depressive and anxiety respondents. Considering many overlapping SI and SA determinants, more neurobiological determinants and use of innovative methodological techniques are desirable.

Longitudinal associations between specific symptoms of depression: Network analysis in a prospective cohort study

BACKGROUND

Network perspective to mental disorders suggests that depression develops due to interrelated associations between individual symptoms rather than due to a common cause. However, it is unclear whether long-term longitudinal associations between specific symptoms of depression demonstrate coherent patterns. We examined the temporal sequences and changes in depressive symptoms over time, and whether some symptoms are more central than others in inducing changes in the rest of the symptoms over time. We also compared the network structure of depressive symptoms between people who were and were not taking medication for depression or anxiety.

METHODS

Data were from the Survey of Health, Aging and Retirement in Europe, with five follow-ups conducted between 2004 and 2017. Participants who had data on depressive symptoms from at least two study waves were analyzed (n = 72,971). Depressive symptoms were self-reported using the 12-item EURO-D scale.

RESULTS

All individual symptoms were longitudinally associated with each other. Changes in sad or depressed mood, diminished interest, and suicidal ideation were the most strongly associated with changes in other symptoms. There were no consistent differences in symptom associations between individuals taking versus not taking psychotropic medication.

LIMITATIONS

Depressive symptoms were self-reported and measured every two years, which may dilute some short-term temporal sequences of the symptoms.

CONCLUSIONS

Our findings demonstrate differences between depressive symptoms in their long-term associations with other depressive symptoms in the general population. Changes in sad or depressed mood, diminished interest, and suicidal ideation have the strongest associations with changes in the rest of the symptoms.

Clinical traits of patients with major depressive disorder with comorbid borderline personality disorder based on propensity score matching

BACKGROUND

Major depressive disorder (MDD) with comorbid borderline personality disorder (BPD) makes the clinical symptoms of patients more complex and more difficult to treat, so more attention should be paid to the recognition of their clinical features. This study investigated the differences between patients with MDD with and without BPD in clinical traits.

METHODS

Propensity score matching was used to analyze the retrospective patients' data from August 2012 to September 2019. Altogether, 1381 patients with MDD were enrolled; 38 patients with MDD were matched to compare demographic data, and scores on the Hamilton Depression Scale, Hamilton Anxiety Scale (HAMA), Self-Rating Depression Scale (SDS), Modified Overt Aggression Scale (MOAS), and the frequency of nonsuicidal self-harm (NSSH).

RESULTS

Compared to patients with MDD without BPD, the age of onset of patients with MDD with comorbid BPD was significantly earlier (t = 3.25, p = .00). The scores of HAMA (t = -2.28, p = .03), SDS (t = 9.31, p = .00), MOAS (t = -13.67, p = .00), verbal aggression (t = -3.79, p = .00), aggression against objects (t = -2.84, p = .00), aggression against others (t = -6.70, p = .00), and aggression against self (t = -9.22, p = .00) were significantly higher in patients with MDD with comorbid BPD. Moreover, the frequency of NHSS in these patients was significantly higher (χ²  = 20.13, p = .00). MOAS was an independent influencing factor in these (odds ratio = 7.38, p = .00).

CONCLUSIONS

Patients with BPD showed early onset and increased complaints relative to symptoms, accompanied by obvious anxiety symptoms, impulsive behavior, and NSSH. Therefore, patients with MDD with impulsive behavior have comorbid BPD.

Basal and LPS-stimulated inflammatory markers and the course of individual symptoms of depression

Multiple studies show an association between inflammatory markers and major depressive disorder (MDD). People with chronic low-grade inflammation may be at an increased risk of MDD, often in the form of sickness behaviors. We hypothesized that inflammation is predictive of the severity and the course of a subset of MDD symptoms, especially symptoms that overlap with sickness behavior, such as anhedonia, anorexia, low concentration, low energy, loss of libido, psychomotor slowness, irritability, and malaise. We tested the association between basal and lipopolysaccharide (LPS)-induced inflammatory markers with individual MDD symptoms (measured using the Inventory of Depressive Symptomatology Self-Report) over a period of up to 9 years using multivariate-adjusted mixed models in 1147-2872 Netherlands Study of Depression and Anxiety (NESDA) participants. At baseline, participants were on average 42.2 years old, 66.5% were women and 53.9% had a current mood or anxiety disorder. We found that basal and LPS-stimulated inflammatory markers were more strongly associated with sickness behavior symptoms at up to 9-year follow-up compared with non-sickness behavior symptoms of depression. However, we also found significant associations with some symptoms that are not typical of sickness behavior (e.g., sympathetic arousal among others). Inflammation was not related to depression as a unified syndrome but rather to the presence and the course of specific MDD symptoms, of which the majority were related to sickness behavior. Anti-inflammatory strategies should be tested in the subgroup of MDD patients who report depressive symptoms related to sickness behavior.

White Matter Microstructure and Its Relation to Longitudinal Measures of Depressive Symptoms in Mid- and Late Life

BACKGROUND

Studies of white matter microstructure in depression typically show alterations in individuals with depression, but they are frequently limited by small sample sizes and the absence of longitudinal measures of depressive symptoms. Depressive symptoms are dynamic, however, and understanding the neurobiology of different trajectories could have important clinical implications.

METHODS

We examined associations between current and longitudinal measures of depressive symptoms and white matter microstructure (fractional anisotropy and mean diffusivity [MD]) in the UK Biobank Imaging Study. Depressive symptoms were assessed on two to four occasions over 5.9 to 10.7 years (n = 18,959 individuals on at least two occasions, n = 4444 on four occasions), from which we derived four measures of depressive symptomatology: cross-sectional measure at the time of scan and three longitudinal measures, namely trajectory and mean and intrasubject variance over time.

RESULTS

Decreased white matter microstructure in the anterior thalamic radiation demonstrated significant associations across all four measures of depressive symptoms (MD: βs = .020-.029, pcorr < .030). The greatest effect sizes were seen between white matter microstructure and longitudinal progression (MD: βs = .030-.040, pcorr < .049). Cross-sectional symptom severity was particularly associated with decreased white matter integrity in association fibers and thalamic radiations (MD: βs = .015-.039, pcorr < .041). Greater mean and within-subject variance were mainly associated with decreased white matter microstructure within projection fibers (MD: βs = .019-.029, pcorr < .044).

CONCLUSIONS

These findings indicate shared and differential neurobiological associations with severity, course, and intrasubject variability of depressive symptoms. This enriches our understanding of the neurobiology underlying dynamic features of the disorder.

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

BACKGROUND

Depression 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.

METHODS

Data 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.

RESULTS

The 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.

CONCLUSIONS

The 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.