Subtypes of major depression: latent class analysis in depressed Han Chinese women

Clinical heterogeneity in major depressive disorder underlies comorbidity with functional disorders

The comorbidities between MDD and functional disorders (FDs), such as fibromyalgia (FM), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and irritable bowel syndrome (IBS) remain largely unexplored. We analyzed data from 10,563 lifetime MDD cases (mean age = 50.5 (SD = 11.9), 71.8% female) from the Lifelines Cohort Study. Lifetime MDD symptoms from DSM-5 criterion A were assessed in 2018. Current FDs were assessed according to diagnostic criteria between 2014 and 2017. First, we modeled the effect of 12 disaggregated MDD symptoms on FM, ME/CFS, and IBS diagnoses using multiple logistic regression. Most, but not all, MDD symptoms were associated with FD diagnoses, suggesting that some features of MDD are particularly important to the comorbidity between MDD and FDs. Next, we used Latent Class Analysis to classify MDD cases based on their symptoms to explore whether MDD - FD comorbidities were associated with specific symptom profiles. We found that a five-class solution provided the best balance of model fit and entropy. Two classes, termed severe typical and anhedonia/weight gain, associated with increased prevalence of all FDs. The severe typical class was equally associated with FM and ME/CFS, while the anhedonia/weight gain class was differentially associated with pairs of FDs suggesting that features of the anhedonia/weight gain class are uniquely related to different FDs with varying magnitudes of effect and, possibly, different mechanisms. The comorbidity between MDD and FDs does not appear to result from a single mechanism. Identification of the mechanisms that underlie the association between MDD and FDs is a priority for future work.

Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis

Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR). A secondary analysis of a two-year cohort study called Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD), which collected data every three months from patients with a history of recurrent MDD in the United Kingdom, the Netherlands, and Spain (N = 619). We used latent class and latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined transitions over time. We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. These same classes were identified at 6- and 12-month follow-ups, and participants tended to remain in the same class over time. We found no statistically significant differences between the two severe subtypes regarding baseline clinical and sociodemographic characteristics. Our findings emphasize severity differences over symptom types, suggesting that current subtyping methods provide insights akin to existing severity measures. When examining transitions, participants were most likely to remain in their respective classes over 1-year, indicating chronicity rather than oscillations in depression severity. Future work recommendations are made.

Latent class analysis of symptoms of depression and anxiety among older women

OBJECTIVES

This cross-sectional study aims to consider the potential classification of depression and anxiety symptoms among older women, and identify the influencing factors of this classification.

METHODS

This study examines Chinese women aged 65 years and older. Latent class analysis was used to explore the mental health subgroups of older women, and multivariate logistic regression was employed to examine the influencing factors based on the health ecological model among these subgroups.

RESULTS

The results helped classify this population under three subgroups: the coexistence of depression and anxiety group, dominated depression group, and the low symptoms group. Moreover, class differences in terms of age, residence, education, income, assessment of current life and health status, sleep duration, and health behaviors, such as alcohol use and exercise were noted.

CONCLUSIONS

These findings explain the heterogeneity among older women, and help illuminate their unique aspects of mental health. Accordingly, they are significant for scholars and policymakers to understand depression and anxiety among older women.

Relationship between eating problems and the risk of dementia: A retrospective study

BACKGROUND

Older adults and individuals with decreased cognition often experience appetite changes and weight loss. As weight loss can result in cognitive decline, change in appetite may be an important contributor to the onset of dementia. However, there is a lack of relevant studies on this topic. This study aimed to determine the relationship between appetite changes, weight loss, and dementia onset.

METHODS

A total of 135 patients with normal cognitive function, subjective cognitive impairment, and mild cognitive impairment who were assessed using the Neuropsychiatric Inventory 12 item version (NPI-12) and followed up for at least 1 month were enrolled in the study. All patients underwent a Mini-Mental State Examination (MMSE). Eating problems were assessed using the NPI Eating Problems Score. Appetite and weight loss were assessed at the first visit by caregivers. Kaplan-Meier survival analyses with a log-rank test were used to compare the time to the onset of dementia between the presence or absence of the NPI eating problems, appetite loss, weight loss, or NPI depression scores. Cox proportional hazards regression models using the forced entry method were employed to estimate the hazard ratio (HR) for dementia.

RESULTS

Weight loss was significantly related to dementia onset (P = 0.027) in the Kaplan-Meier survival analyses, while eating problems, appetite loss, and depression showed no significant association (P = 0.519, P = 0.326, and P = 0.317, respectively). In the Cox proportional hazards regression models, the MMSE score was found to be a significant factor (P = 0.021, HR = 0.871); moreover, weight loss tended to increase the risk of dementia onset (P = 0.057, HR = 1.694).

CONCLUSIONS

Weight loss experienced by older adults could contribute to an increased risk of developing dementia.

Depression Subtypes in Systolic Heart Failure: A Secondary Analysis From a Randomized Controlled Trial

BACKGROUND

Heart failure (HF) is associated with an elevated risk of morbidity, mortality, hospitalization, and impaired quality of life. One potential contributor to these poor outcomes is depression. Yet the effectiveness of treatments for depression in patients with HF is mixed, perhaps due to the heterogeneity of depression.

METHODS

This secondary analysis applied latent class analysis (LCA) to data from a clinical trial to classify patients with systolic HF and comorbid depression into LCA subtypes based on depression symptom severity, and then examined whether these subtypes predicted treatment response and mental and physical health outcomes at 12 months follow-up.

RESULTS

In LCA of 629 participants (mean age 63.6 ± 12.9; 43% females), we identified 4 depression subtypes: mild (prevalence 53%), moderate (30%), moderately severe (12%), and severe (5%). The mild subtype was characterized primarily by somatic symptoms of depression (e.g., energy loss, sleep disturbance, poor appetite), while the remaining LCA subtypes additionally included nonsomatic symptoms of depression (e.g., depressed mood, anhedonia, worthlessness). At 12 months, LCA subtypes with more severe depressive symptoms reported significantly greater improvements in mental quality of life and depressive symptoms compared to the LCA mild subtype, but the incidence of cardiovascular- and noncardiovascular-related readmissions, and mortality was similar among all subtypes.

CONCLUSIONS

In patients with depression and systolic heart failure those with the LCA mild depression subtype may not meet full criteria for major depressive disorder, given the overlap between HF and somatic symptoms of depression. We recommend requiring depressed mood or anhedonia as a necessary symptom for major depressive disorder in patients with HF.

Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys

Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).

Latent Class Analysis of Depressive Symptom Phenotypes Among Black/African American Mothers

BACKGROUND

Depression is a growing global problem with significant individual and societal costs. Despite their consequences, depressive symptoms are poorly recognized and undertreated because wide variation in symptom presentation limits clinical identification-particularly among African American (AA) women-an understudied population at an increased risk of health inequity.

OBJECTIVES

The aims of this study were to explore depressive symptom phenotypes among AA women and examine associations with epigenetic, cardiometabolic, and psychosocial factors.

METHODS

This cross-sectional, retrospective analysis included self-reported Black/AA mothers from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure study (data collected in 2015-2020). Clinical phenotypes were identified using latent class analysis. Bivariate logistic regression examined epigenetic age, cardiometabolic traits (i.e., body mass index ≥ 30 kg/m 2 , hypertension, or diabetes), and psychosocial variables as predictors of class membership.

RESULTS

All participants were Black/AA and predominantly non-Hispanic. Over half of the sample had one or more cardiometabolic traits. Two latent classes were identified (low vs. moderate depressive symptoms). Somatic and self-critical symptoms characterized the moderate symptom class. Higher stress overload scores significantly predicted moderate-symptom class membership.

DISCUSSION

In this sample of AA women with increased cardiometabolic burden, increased stress was associated with depressive symptoms that standard screening tools may not capture. Research examining the effect of specific stressors and the efficacy of tools to identify at-risk AA women are urgently needed to address disparities and mental health burdens.

Association between quality of life, sleep quality and mental disorders in Iranian older adults

Aging as a major challenge can affect the development and growth of countries all around the world. This study aimed to identify the subgroups of the elderly based on the quality of life (Qol), sleep quality, and common mental disorders and assess the role of demographic characteristics on the membership of participants in each latent class. This cross-sectional study was conducted on 1064 people over the age of 60 years. The sample was selected through cluster sampling in northern Iran. All participants completed six sets of checklists and questionnaires. Data analysis was performed using latent class analysis. Three latent classes were identified; namely, (1) healthy (66.8%), (2) anxious and with poor sleep quality (28.6%), and unhealthy (4.6%). Being Female significantly increased the odds of membership in classes 2 and 3 compared to class 1. Furthermore, living in urban areas increased the odds of belonging to class 2 and class 3 compared to class 1. Illiteracy was also shown to increase the odds of being in class 3 in comparison to class 1. Results from the present indicate that the co-occurrence of health problems in 33.2% of the elderly was observed in various forms. The results of this study can be used in prioritizing health programs for the elderly and emphasizing high-risk groups.

Subtyping late-life depression according to inflammatory and metabolic dysregulation: a prospective study

BACKGROUND

Inflammation and metabolic dysregulation are age-related physiological changes and are associated with depressive disorder. We tried to identify subgroups of depressed older patients based on their metabolic-inflammatory profile and examined the course of depression for these subgroups.

METHODS

This clinical cohort study was conducted in a sample of 364 depressed older (⩾60 years) patients according to DSM-IV criteria. Severity of depressive symptoms was monitored every 6 months and a formal diagnostic interview repeated at 2-year follow-up. Latent class analyses based on baseline metabolic and inflammatory biomarkers were performed. Adjusted for confounders, we compared remission of depression at 2-year follow-up between the metabolic-inflammatory subgroups with logistic regression and the course of depression severity over 2-years by linear mixed models.

RESULTS

We identified a 'healthy' subgroup (n = 181, 49.7%) and five subgroups characterized by different profiles of metabolic-inflammatory dysregulation. Compared to the healthy subgroup, patients in the subgroup with mild 'metabolic and inflammatory dysregulation' (n = 137, 37.6%) had higher depressive symptom scores, a lower rate of improvement in the first year, and were less likely to be remitted after 2-years [OR 0.49 (95% CI 0.26-0.91)]. The four smaller subgroups characterized by a more specific immune-inflammatory dysregulation profile did not differ from the two main subgroups regarding the course of depression.

CONCLUSIONS

Nearly half of the patients with late-life depressions suffer from metabolic-inflammatory dysregulation, which is also associated with more severe depression and a worse prognosis. Future studies should examine whether these depressed older patients benefit from a metabolic-inflammatory targeted treatment.

Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling

BACKGROUND

It is increasingly recognized that existing diagnostic approaches do not capture the underlying heterogeneity and complexity of psychiatric disorders such as depression. This study uses a data-driven approach to define fluid depressive states and explore how patients transition between these states in response to cognitive behavioural therapy (CBT).

METHODS

Item-level Patient Health Questionnaire (PHQ-9) data were collected from 9891 patients with a diagnosis of depression, at each CBT treatment session. Latent Markov modelling was used on these data to define depressive states and explore transition probabilities between states. Clinical outcomes and patient demographics were compared between patients starting at different depressive states.

RESULTS

A model with seven depressive states emerged as the best compromise between optimal fit and interpretability. States loading preferentially on cognitive/affective v. somatic symptoms of depression were identified. Analysis of transition probabilities revealed that patients in cognitive/affective states do not typically transition towards somatic states and vice-versa. Post-hoc analyses also showed that patients who start in a somatic depressive state are less likely to engage with or improve with therapy. These patients are also more likely to be female, suffer from a comorbid long-term physical condition and be taking psychotropic medication.

CONCLUSIONS

This study presents a novel approach for depression sub-typing, defining fluid depressive states and exploring transitions between states in response to CBT. Understanding how different symptom profiles respond to therapy will inform the development and delivery of stratified treatment protocols, improving clinical outcomes and cost-effectiveness of psychological therapies for patients with depression.

Symptom profiles of women at risk of mood disorders: A latent class analysis

BACKGROUND

Depression is the leading cause of disease burden among women worldwide. However, an understanding of symptom profiles among women at risk of mood disorders is limited. We determined distinct profiles of affective symptoms among high risk women, along with their distinguishing characteristics.

METHODS

Women were recruited from 17 clinical sites affiliated with the National Network of Depression Centers. They completed measures of depression (Patient Health Questionnaire - 9) and anxiety (Generalized Anxiety Disorder - 7) as well as questions regarding demographics, reproductive status, behavioral/mental health history, and life stress/adversity. Latent class analysis and multinomial logistic regression were used to identify and characterize symptom profiles.

RESULTS

5792 women participated, ages 18 to 90 (M = 38). Three latent classes were identified: generally asymptomatic (48%), elevated symptoms of comorbid anxiety and depression (16%), and somatic symptoms (36%). Financial security and greater social support were protective factors that distinguished asymptomatic women. The profile of the class with elevated anxiety/depressive symptoms constituted a complex mix of adverse social determinants and potentially heritable clinical features, including a diagnosis of Bipolar Disorder. Women in the 3rd latent class were characterized by menstrual irregularity and a stronger expression of neurovegetative symptoms, especially sleep disturbance and fatigue.

LIMITATIONS

Limitations included less than optimal racial diversity of our sample and reliance on self-report.

CONCLUSIONS

Different symptom profiles may reflect distinct subtypes of women at risk of mood disorders. Understanding the etiology and mechanisms underlying clinical and psychosocial features of these profiles can inform more precisely targeted interventions to address women's diverse needs.

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.

Cognitive Behavior Therapy for Depression From an Evolutionary Perspective

Evolutionary medicine attempts to solve a problem with which traditional medicine has struggled historically; how do we distinguish between diseased states and "healthy" responses to disease states? Fever and diarrhea represent classic examples of evolved adaptations that increase the likelihood of survival in response to the presence of pathogens in the body. Whereas, the severe mental disorders like psychotic mania or the schizophrenias may involve true "disease" states best treated pharmacologically, most non-psychotic "disorders" that revolve around negative affects like depression or anxiety are likely adaptations that evolved to serve a function that increased inclusive fitness in our ancestral past. What this likely means is that the proximal mechanisms underlying the non-psychotic "disorders" are "species typical" and neither diseases nor disorders. Rather, they are coordinated "whole body" responses that prepare the individual to respond in a maximally functional fashion to the variety of different challenges that our ancestors faced. A case can be made that depression evolved to facilitate a deliberate cognitive style (rumination) in response to complex (often social) problems. What this further suggests is that those interventions that best facilitate the functions that those adaptations evolved to serve (such as rumination) are likely to be preferred over those like medications that simply anesthetize the distress. We consider the mechanisms that evolved to generate depression and the processes utilized in cognitive behavior therapy to facilitate those functions from an adaptationist evolutionary perspective.

A distress-continuum, disorder-threshold model of depression: a mixed-methods, latent class analysis study of slum-dwelling young men in Bangladesh

BACKGROUND

Binary categorical approaches to diagnosing depression have been widely criticized due to clinical limitations and potential negative consequences. In place of such categorical models of depression, a 'staged model' has recently been proposed to classify populations into four tiers according to severity of symptoms: 'Wellness;' 'Distress;' 'Disorder;' and 'Refractory.' However, empirical approaches to deriving this model are limited, especially with populations in low- and middle-income countries.

METHODS

A mixed-methods study using latent class analysis (LCA) was conducted to empirically test non-binary models to determine the application of LCA to derive the 'staged model' of depression. The study population was 18 to 29-year-old men (n = 824) from an urban slum of Bangladesh, a low resource country in South Asia. Subsequently, qualitative interviews (n = 60) were conducted with members of each latent class to understand experiential differences among class members.

RESULTS

The LCA derived 3 latent classes: (1) Severely distressed (n = 211), (2) Distressed (n = 329), and (3) Wellness (n = 284). Across the classes, some symptoms followed a continuum of severity: 'levels of strain', 'difficulty making decisions', and 'inability to overcome difficulties.' However, more severe symptoms such as 'anhedonia', 'concentration issues', and 'inability to face problems' only emerged in the severely distressed class. Qualitatively, groups were distinguished by severity of tension, a local idiom of distress.

CONCLUSIONS

The results indicate that LCA can be a useful empirical tool to inform the 'staged model' of depression. In the findings, a subset of distress symptoms was continuously distributed, but other acute symptoms were only present in the class with the highest distress severity. This suggests a distress-continuum, disorder-threshold model of depression, wherein a constellation of impairing symptoms emerge together after exceeding a high level of distress, i.e., a tipping point of tension heralds a host of depression symptoms.

Associations between depression subtype and functional impairment and treatment utilization in a national sample of adolescents

BACKGROUND

Prior studies have characterized distinct major depressive episode (MDE) subtypes among adults, yet limited evidence exists regarding variation in MDE during adolescence.

METHODS

Using 2008-2016 National Survey of Drug Use and Health data, latent class analysis (LCA) was used to characterize depression subtypes (based on symptom presentation) among 9,896 youth ages 12-17 with recent first-onset MDE. Logistic regression was used to estimate associations of MDE subtype with functional outcomes and treatment utilization, adjusting for demographic characteristics and depression severity (i.e., number of MDE diagnostic criteria and recurrence status) RESULTS: A 5-class LCA model provided optimal fit. Three distinct categories of MDE symptoms generally clustered together, which we termed "somatic," "cognitive," and "self-worth;" classes were differentiated by distinct combinations of symptoms across these 3 categories. Subtypes were characterized as: Highly Symptomatic (39% of youth); Somatic & Cognitive (24%), Somatic (22%), Diffuse Symptoms (8%), and Somatic & Self-Worth (6%). The majority of youth reported at least moderate impairment across multiple domains; subtype was a significant predictor of functional impairment. Only 34% of youth received any past-year depression-related treatment; treatment utilization was significantly higher for MDE subtypes with the highest prevalences of suicidal ideation.

LIMITATIONS

Due to cross-sectional data, we cannot establish causal directionality.

CONCLUSIONS

Subtype was significantly predictive of functional impairment and treatment utilization, above and beyond number of MDE diagnostic criteria or recurrence status. Understanding distinct profiles of adolescent depression, as well as potential differential associations with impairment, can inform prevention, diagnosis, and treatment of depression among youth.

Latent Class Analysis in Depression, Including Clinical and Functional Variables: Evidence of a Complex Depressive Subtype in Primary Care in Chile

OBJECTIVE

To establish differentiated depressive subtypes using a latent class analysis (LCA), including clinical and functional indicators in a sample of depressed patients consulted in Chilean Primary Health Care.

METHODS

A LCA was performed on a sample of 297 depressed patients consulted in Chilean PHC. The Mini International Neuropsychiatric Interview, the Hamilton Depression Rating Scale, the Outcome Questionnaire -social role, and interpersonal subscales were as instruments. A regression analysis of the different subtypes with sociodemographic and adverse life experiences was performed.

RESULTS

In a sample characterized by 87.5% of women, two, three, and four latent class models were obtained. The three-class model likely represents the best clinical implications. In this model, the classes were labeled: "complex depression" (CD) (58% of the sample), "recurrent depression" (RD) (34%), and "single depression episode" (SD) (8%). Members of CD showed a higher probability of history of suicide attempts, interpersonal, and social dysfunction. Psychiatric comorbidities differentiated the RD from SD. According to a multinomial regression model, childhood trauma experiences, recent stressful life experiences, and intimate partner violence events were associated with the CD class (p < 0.01). Limitations. The vast majority of participants were females from Chile and the sample studied was not random. So, the results may not necessarily represent outpatient clinics.

CONCLUSIONS

This study can provide additional evidence that depression, specifically in female gender, could be better understood as a complex heterogeneous disorder when clinical and functional indicators are studied. Furthermore, adverse life experiences starting in childhood could lead to a differentiated complex depressive subtype.

Appetite changes reveal depression subgroups with distinct endocrine, metabolic, and immune states

There exists little human neuroscience research to explain why some individuals lose their appetite when they become depressed, while others eat more. Answering this question may reveal much about the various pathophysiologies underlying depression. The present study combined neuroimaging, salivary cortisol, and blood markers of inflammation and metabolism collected prior to scanning. We compared the relationships between peripheral endocrine, metabolic, and immune signaling and brain activity to food cues between depressed participants experiencing increased (N = 23) or decreased (N = 31) appetite and weight in their current depressive episode and healthy control participants (N = 42). The two depression subgroups were unmedicated and did not differ in depression severity, anxiety, anhedonia, or body mass index. Depressed participants experiencing decreased appetite had higher cortisol levels than subjects in the other two groups, and their cortisol values correlated inversely with the ventral striatal response to food cues. In contrast, depressed participants experiencing increased appetite exhibited marked immunometabolic dysregulation, with higher insulin, insulin resistance, leptin, CRP, IL-1RA, and IL-6, and lower ghrelin than subjects in other groups, and the magnitude of their insulin resistance correlated positively with the insula response to food cues. These findings provide novel evidence linking aberrations in homeostatic signaling pathways within depression subtypes to the activity of neural systems that respond to food cues and select when, what, and how much to eat. In conjunction with prior work, the present findings strongly support the existence of pathophysiologically distinct depression subtypes for which the direction of appetite change may be an easily measured behavioral marker.

Subtypes of Depression: Latent Class Analysis in Spanish Old People with Depressive Symptoms

Major depressive disorder (MDD) is one of the most disabling disorders and the one that most contributes to disability. When it occurs in older people, it is an additional burden to their potential physical and cognitive deficiencies, making MDD an important public health problem that supposes a large investment in health. There is a clear lack of consistency between the subtypes of depression found in the literature, ranging from two to seven classes, with three being the most commonly found non-melancholic, melancholic and psychotic, or putative psychotics. The aim of this research is to add knowledge to the profiles of depressive symptoms in a representative sample of older Spanish people, and to study the possible relationship of these symptom profiles with variables that have traditionally been related to depression. Spanish data from the sixth wave of SHARE were used, with 612 Spanish older adults living in Spain. A routine of several LCAs with a different number of classes was performed to answer this first aim to classify Spanish adults with depression symptoms. The results pointed out the presence of three different classes among the participants in the study: psychosomatic (11.12%), melancholic (14.21%), and anhedonic (74.67%). This work represents a step forward to understand the heterogeneity of major depressive disorder, facilitating the diagnosis, and subsequent treatment of older adults.

Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates

Depression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum, medial orbitofrontal cortex, insular cortex, anterior cingulate cortex amygdala and hippocampus). K-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15-25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Cortical surface area and thickness and subcortical volume were compared between the subtypes and 100 healthy controls using structural MRI. Three subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls. Our findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.

Suicidal Behavior in Adolescents: A Latent Class Analysis

The main goal of the present study was to identify and validate latent classes of suicidal behavior in a representative sample of adolescents. The sample comprised a total of 1506 students, including 667 males (44.3%), selected through a sample stratified by clusters. The mean age was 16.15 years (SD = 1.36). The instruments used evaluated suicidal behavior, positive and negative affect, emotional and behavioral problems, prosocial behavior, and subjective well-being. Using the Paykel Suicide Scale, the latent class analysis identified four homogeneous subgroups: “low risk”, “suicidal act”, “suicidal ideation”, and “high risk for suicide”. These subgroups presented a differential pattern in terms of their social-emotional adjustment. The subgroups with the highest theoretical risk showed lower scores on subjective well-being and positive affect as well as higher scores on emotional and behavioral problems and negative affect compared to the non-risk subgroups. This study contributes to an understanding of the typologies of suicidal behavior among adolescents and the relationship with psychopathological adjustment. Ultimately, these findings may promote the development or improvement of early detection and prevention strategies in the suicidal behavior field in order to reduce the socio-economic burdens associated with suicide in young populations.

Depression subtypes and obesity in adults: A systematic review and meta-analysis

Examining clinical features of depressive episodes may help elucidating the nature of association between depression and obesity, related to specific symptoms such as appetite and weight changes. This meta-analysis of observational studies evaluated whether subtypes of depression are associated with specific anthropometric profiles in adults. We searched MEDLINE, LILACS, PsycINFO, Scopus, Web of Science databases, and Grey Literature for articles published up to October 2016 that examined depressive subtypes and adiposity measures among adults. The pooled effect size was estimated with random effects models. The PRISMA guidelines were adopted to reporting results, and this review was registered in PROSPERO (CRD42016035685). A total of 22 articles were included in this systematic review, of which eight had data included in the meta-analysis, assessing 14 757 individuals with depression. Patients with atypical depression presented a 2.55 higher BMI score compared with those with melancholic depression. Subgroup analysis identified a differential distribution of anthropometric measures in studies conducted with Chinese populations. Among the remainder studies, only one reported discrepant results, possibly due to the exclusion of "weight change" in defining subtypes of depression. Atypical depression was significantly associated with elevated BMI compared with melancholic depression, deserving particular attention due to its clinical importance.

Toward a New Model of Understanding, Preventing, and Treating Adolescent Depression Focusing on Exhaustion and Stress

OBJECTIVE

Adolescent depression is a heterogeneous disorder, with a wide variety of symptoms and inconsistent treatment response, and is not completely understood. A dysregulated stress system is a consistent finding, however, and exhaustion is a consistent trait in adolescent patients. The aim of this paper is to critically assess current hypotheses in adolescent depression research and reframe causes and treatment approaches.

METHODS

A mixed-method approach involved a review based on publications from PubMed, Embase and PsycInfo, and two exemplary adolescent cases.

RESULTS

Both cases show a spiral of stress and exhaustion, but with a different profile of symptoms and coping mechanisms. Reframing both cases from the perspective of coping behavior, searching for the sources of experienced stress and exhaustion, showed coping similarities. This proved essential in the successful personalized treatment and recovery process. In combination with recent evidence, both cases support the functional reframing of depression as the outcome of a stress- and exhaustion-related spiralling mechanism.

CONCLUSIONS

We propose to open up a symptom-based, mood-centered view to a model in which adolescent depression is framed as a consecutive failure of stress coping mechanisms and chronic exhaustion. Addressing exhaustion and coping primarily as a treatment strategy in adolescents and young adults might work in synergy with existing treatments and improve overall outcomes. This perspective warrants further investigation.

Melancholia: An Attempt at Definition Based on a Review of Empirical Data

We sought to identify clinical features that best discriminate melancholia from nonmelancholic depressive conditions. An extensive review of studies using latent factor models that identified a melancholic depression dimension/factor was undertaken. Clinical variables extracted from these studies were analyzed in terms of their contribution to a diagnosis of melancholia and their consistency across studies. Psychomotor retardation and mood nonreactivity were the most relevant clinical features for the identification of melancholic depressions. Other clinical features commonly described as weighted to melancholia, such as anhedonia, psychomotor agitation, late insomnia, or appetite/weight loss, seemed less useful in distinguishing these subtypes of depression. Study results are considered in relation to the potential limitations of current operational definitions of melancholia, and how symptom sets could be modified.

The latent structure of depression symptoms and suicidal thoughts in Brazilian youths

BACKGROUND

Many studies have investigated the existence of discrete groups comprising the clinical concept of depression. Nevertheless, identifying true latent depression groups might require the inclusion of indicators of severe manifestations of depression, such as suicidal thoughts, in the analysis. Another issue is that relatively few studies have addressed the latent structure of depression in children and adolescents from Latin American cultures.

METHODS

In the present study, we combined latent profile and taxometric analysis to investigate the latent structure underlying depression symptoms (negative emotionality and low positive emotionality indicators) and suicidal thoughts in four aggregated Brazilian youth samples (total N = 2587; mean age = 12.86 years; SD = 2.60; 50.8% females).

RESULTS

Latent profile analysis indicated five classes that clearly represented distinct levels on a continuum of depression. However, taxometric results were ambiguous with regard to highlighting depression as a purely dimensional or categorical latent entity (mean CCFI = 0.497).

LIMITATIONS

The use of few indicators from a single instrument, the potential heterogeneity in the clinical group, and the non-random nature of the samples included in the study.

CONCLUSION

The mixed findings support the existence of a dimension of depression, as well as latent classes of individuals. Factor mixture models are discussed as a strategy for further exploring the nature of depression among young people.

Subtypes of treatment-resistant depression determined by a latent class analysis in a Chinese clinical population

BACKGROUND

This study aimed to explore subtypes of treatment-resistant depression (TRD).

METHODS

Latent class analysis (LCA) was performed on clinical and demographic data collected from 375 patients with TRD. Clinical variables were compared across subtypes. Treatment outcomes across subtypes of TRD were compared separately for those within each subtype with anxiety (those with a HRSD-17 anxiety/somatization factor score ≥ 7) and those without anxiety. LCA subtypes were compared using Cochran's and Mantel-Haenszel χ² test, respectively. Unordered multinomial logistic regression was used to assess clinical correlates of TRD subtypes.

RESULTS

Three categories were detected: severe depression (66%), moderate depression with anxiety (9%) and mild depression with anxiety/somatization (25%). Gender, age, age at first onset, family monthly income, number of hospitalizations, HRSD-17 and clinical global impression-severity (CGI) scores were significantly different across the three groups. Remission rates were significantly different among anxious cases with severe (43.75%), moderate (22.73%) and mild (26.25%) depression subtypes. Compared to cases in the mild depression group, those in the severe depression group had a greater likelihood of being male, having a later age of first onset, higher numbers of hospitalization, higher HRSD-17 and CGI total scores, and lower family income. Those in the moderate depression group were more likely to be male and have lower family income than those in the mild depression group.

LIMITATIONS

Representative bias, relatively small sample size, unbalanced group size and incomplete indicator variables might have a negative effect on the validity and generalization of the findings.

CONCLUSIONS

Depression severity could be a basis for subtype classification of patients with TRD. The classification of latent class of TRD observed in our study was similar to the structure found in MDD. Longitudinal research into the stability of the latent structure of TRD across illness course is merited as is research into treatment outcomes for TRD subtypes.

Prevalence and clinical features of atypical depression among patients with major depressive disorder in China

BACKGROUND

Little is known about the demographic and clinical features of the atypical subtype of major depressive disorder (MDD) patients in China. This study set out to investigate the prevalence of atypical depression in MDD patients in China, and identify its demographic and clinical features.

METHODS

The study was conducted in 13 major psychiatric hospitals or in the psychiatric units of general hospitals in China, and recruited a sample of 1172 patients diagnosed with MDD. The patients' demographic and clinical features and prescriptions of psychotropic drugs were collected using a standardized questionnaire designed for the study.

RESULTS

The prevalence of atypical depression was 15.3%. In multiple logistic regression analyses, compared to the non-atypical depression patients, the atypical depression patients were more likely to have depressive episodes with suicide ideation and attempts (OR = 1.49, 95% CI = 1.06, 2.10, P = 0.023), depressive episodes with psychotic features (OR = 2.15, 95% CI = 1.43, 3.22, P < 0.001), seasonal depressive episodes (OR = 1.77, 95% CI = 1.12, 2.78, P = 0.014), an earlier age of onset (OR = 0.98, 95% CI = 0.96, 0.99, P = 0.001), and lifetime depressive episodes (OR = 1.07, 95% CI = 1.01, 1.13, P = 0.020).

LIMITATIONS

The assessment of atypical features was not based on a validated rating scale.

CONCLUSION

Our results indicate that atypical depression is common in Chinese patients with MDD. MDD with atypical features may be more severe and debilitating than patients with non-atypical features.

The use of latent class analysis for identifying subtypes of depression: A systematic review

Depression is a significant public health problem but symptom remission is difficult to predict. This may be due to substantial heterogeneity underlying the disorder. Latent class analysis (LCA) is often used to elucidate clinically relevant depression subtypes but whether or not consistent subtypes emerge is unclear. We sought to critically examine the implementation and reporting of LCA in this context by performing a systematic review to identify articles detailing the use of LCA to explore subtypes of depression among samples of adults endorsing depression symptoms. PubMed, PsycINFO, CINAHL, Scopus, and Google Scholar were searched to identify eligible articles indexed prior to January 2016. Twenty-four articles reporting 28 LCA models were eligible for inclusion. Sample characteristics varied widely. The majority of articles used depression symptoms as the observed indicators of the latent depression subtypes. Details regarding model fit and selection were often lacking. No consistent set of depression subtypes was identified across studies. Differences in how models were constructed might partially explain the conflicting results. Standards for using, interpreting, and reporting LCA models could improve our understanding of the LCA results. Incorporating dimensions of depression other than symptoms, such as functioning, may be helpful in determining depression subtypes.

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

AIMS

Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals.

METHODS

Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity.

RESULTS

We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment.

CONCLUSIONS

First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

Cultural expressions of depression and the development of the Indonesian Depression Checklist

Depression may manifest differently across cultural settings, suggesting the value of an assessment tool that is sensitive enough to capture these variations. The study reported in this article aimed to develop a depression screening tool for Indonesians derived from ethnographic interviews with 20 people who had been diagnosed as having depression by clinical psychologists at primary health centers. The tool, which we have termed the Indonesian Depression Checklist (IDC), consists of 40 items. The tool was administered to 125 people assessed to have depression by 40 clinical psychologists in primary health centers. The data were analyzed with Confirmatory Factor Analysis (CFA) (IBM SPSS AMOS Software). CFA identified a five-factor hierarchical model ( χ ² = 168.157, p = .091; CFI = .963; TLI = .957; RMSEA = .036). A 19-item inventory of the IDC, with five factors - Physical Symptoms, Affect, Cognition, Social Engagement and Religiosity - was identified. There was a strong correlation between the total score of the IDC and total score of the Center for Epidemiological Studies-Depression scale (revised version CES-D), a standard tool for assessing symptoms of depression. The IDC accommodates culturally distinctive aspects of depression among Indonesians that are not included in the CES-D.

Number of illness episodes as predictor of residual symptoms in major depressive disorder

Notwithstanding major depressive disorder (MDD) is a recurring and chronic condition, relatively few variables have consistently been shown to predict its course. Residual depressive symptoms may be associated with disability and functional impairment but few studies evaluated clinical correlates associated with these symptoms and their impact on functioning after adjustment for potential confounders. Therefore, our study aimed to investigate factors associated with residual depressive symptoms and their impact on the course of MDD. The sample consisted of 210 consecutive MDD euthymic outpatients (67.6% females; mean age = 52.1 ± 15.5), admitted to the Section of Psychiatry, University of Genoa (Italy). Residuals depressive symptoms were significantly associated with female gender; use of short half-life benzodiazepines; longer duration of the current depressive episode; higher number of illness episodes; and higher duration of illness. Conversely, prior treatment with first-generation antipsychotics, later age of illness onset and first hospitalization were less frequently observed among patients with residual symptoms. After multivariate analyses, only duration of current illness episodes (ß = 0.003; p = <0.005) and substance abuse (ß = 0.042; p = <0.05) remained significantly associated with residual symptoms. Our findings indicate that residual depressive symptoms conferred a pernicious illness course in this specific cohort of MDD patients. Future trials mainly targeting these burdensome symptoms are warranted.

Suicidal ideation declines with improvement in the subjective symptoms of major depression

BACKGROUND

Suicidal ideation appears to be more strongly associated with subjective rather than neurovegetative symptoms of depression. Effective treatment, then, should produce reductions in suicidal ideation to the degree that these subjective symptoms are alleviated relative to treatment effects on other symptoms.

METHODS

In a randomized clinical trial comparing paroxetine and bupropion for treatment of depression in patients with either suicidal ideation or past attempt, depression severity and suicidal ideation were assessed weekly during the 8-week study. Depression rating scales - the 24-item Hamilton Depression Rating Scale [HDRS] and the Beck Depression Scale [BDI] - were decomposed into symptom clusters based on our published factor analyses, and their change over time compared to changes on the Beck Scale for Suicidal Ideation [SSI].

RESULTS

Improvement in factor scores associated with subjective symptoms of depression - HDRS Psychic Depression, BDI Subjective Depression, and BDI Self-Blame - were the best predictors of declining scores on the SSI regardless of type of drug treatment. BDI Subjective Depression was the best single predictor in the context of all other significant univariate predictors, accounting for 31.4% of the variance in the change in SSI. The three factors together accounted for 35.3%.

LIMITATIONS

This is a secondary analysis of clinical trial data, with fixed treatments.

CONCLUSIONS

Effective treatments to reduce suicidal ideation are associated with the reduction of the subjective symptoms of depression, which may not always decline in synchrony with improvement in neurovegetative symptoms. This asynchrony may result in a period of elevated risk after the initiation of therapy. Data indicate that subjective depression symptoms should be a primary target in the treatment of depressed suicidal patients.

Self-reported sleep problems among the elderly: A latent class analysis

The present study utilized a person-centered approach to examine the different profiles of problem sleepers in a community sample of elderly. In addition, this study also explores how demographic and psychiatric variables may be related to these different profiles of sleep problems. A total of 515 participants (Mean age = 67 years, SD = 5) were administered self-report measures of sleep problems, depression and anxiety. Among them, 230 who reported significant problems in any of five selected sleep components were entered into a latent class analysis. The remaining 285 participants were assigned to a comparison control group. The profiles of 'inadequate sleep', 'disturbed sleep', 'trouble falling asleep' and 'multiple problems' were identified. The 'multiple problems' group had significantly higher levels of depression and anxiety relative to the control group. Regression analyses indicated that these different profiles had contributed to a significant increase in variance explained in anxiety but not depression levels, on top of the severity of sleep problems and demographic variables. Although sleep problems occur among the elderly with considerable heterogeneity, they can generally be classified into four different profiles. Furthermore, the inclusion of sleep problem profiles can significantly enhance the prediction of anxiety symptoms.

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis

Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting latent class model on a sample of graduate students. Data were collected through the Interactive Screening Program deployed by the American Foundation for Suicide Prevention. LCA identified 6 subgroups from the undergraduate sample (N = 5654). In the group with the most students reporting current suicidal thoughts (N = 623, 66% suicidal), 22.5% reported a prior suicide attempt, and 97.6% endorsed moderately severe or worse depressive symptoms. Notably, LCA identified a second at-risk group (N = 662, 27% suicidal), in which only 1.5% of respondents noted moderately severe or worse depressive symptoms. When graduate students (N = 1138) were classified using the model, a similar frequency distribution of groups was found. Finding multiple replicable groups at-risk for suicidal behavior, each with a distinct prevalence of risk factors, including a group of students who would not be classified as high risk with depression-based screening, is consistent with previous studies that identified multiple potential etiologies of SB.

Partially distinct combinations of psychological, metabolic and inflammatory risk factors are prospectively associated with the onset of the subtypes of Major Depressive Disorder in midlife

BACKGROUND

Given the well known heterogeneity of Major Depressive Disorder (MDD), dividing this complex disorder into subtypes is likely to be a more promising approach to identify its determinants than to study it as a whole.

METHODS

In a prospective population-based cohort study (CoLaus|PsyCoLaus) with 5.5 years of follow-up, 1524 participants without MDD at baseline, aged 35-66 years (mean age 51.4 years, 43.4% females), participated in the physical and psychiatric baseline and the psychiatric follow-up evaluations.

RESULTS

The incidence of both atypical and melancholic MDD during the follow-up period were predicted by female sex, a lifetime history of minor depressive disorders and higher neuroticism scores. Higher baseline body mass index was associated with the onset of atypical MDD, whereas the absence of hypertension and younger age were associated with the development of melancholic MDD. Unspecified MDD was predicted by younger age, low concentrations of tumor necrosis factor-α and elevated life-event impact scores.

LIMITATIONS

The age range of our cohort restricts the identification of risk factors to MDD with onset in midlife and the recruitment in an urban area limits the generalizability of the findings.

CONCLUSIONS

Our data suggest that MDD subtypes are predicted by partially distinct combinations of baseline characteristics suggesting that these subtypes not only differ in their clinical manifestations but also in factors that contribute to their development. Subjects with minor depressive episodes, especially in combination with particular personality features, deserve close clinical attention to prevent the subsequent onset of atypical and melancholic major depression.

Clarifying the role of neuroticism in suicidal ideation and suicide attempt among women with major depressive disorder

BACKGROUND

Prior research consistently demonstrates that neuroticism increases risk for suicidal ideation, but the association between neuroticism and suicidal behavior has been inconsistent. Whereas neuroticism is recommended as an endophenotype for suicidality, the association of neuroticism with attempted suicide warrants clarification. In particular, prior research has not distinguished between correlates of attempted suicide, correlates of suicidal ideation, and correlates of comorbid psychopathology.

METHODS

The present study used the CONVERGE study, a sample of 5864 women with major depressive disorder (MD) and 5783 women without MD throughout China. Diagnoses, suicidal ideation, and attempted suicide were assessed with the Composite International Diagnostic Interview (CIDI). Neuroticism was assessed with the neuroticism portion of the Eysenck Personality Questionnaire.

RESULTS

Results replicate prior findings on the correlates of suicidal ideation, particularly elevated neuroticism among individuals who report prior suicidal ideation. Moreover, as compared with individuals who reported having experienced only suicidal ideation, neuroticism was associated with decreased likelihood of having attempted suicide.

CONCLUSIONS

The association of neuroticism with suicidality is more complicated than has been previously described. Whereas neuroticism increases risk for suicidal ideation, neuroticism may decrease risk for a suicide attempt among individuals with suicidal ideation. These results have implications for the assessment of risk for a suicide attempt among individuals who report suicidal ideation and addresses prior discordant findings by clarifying the association between neuroticism and attempted suicide.

Depressive subtypes in an elderly cohort identified using latent class analysis

BACKGROUND

Clinical findings indicate heterogeneity of depressive disorders, stressing the importance of subtyping depression for research and clinical care. Subtypes of the common late life depression are however seldom studied. Data-driven methods may help provide a more empirically-based classification of late-life depression.

METHODS

Data were used from the Netherlands Study of Depression in Older People (NESDO) derived from 359 persons, aged 60 years or older, with a current diagnosis of major depressive disorder. Latent class analysis (LCA) was used to identify subtypes of depression, using ten CIDI-based depression items. Classes were then characterized using various sociodemographic and clinical characteristics.

RESULTS

The most prevalent class, as identified by LCA, was a moderate-severe class (prevalence 46.5%), followed by a severe melancholic class (prevalence 38.4%), and a severe atypical class (prevalence 15.0%). The strongest distinguishing features between the three classes were appetite and weight and, to a lesser extent, psychomotor symptoms and loss of interest. Compared with the melancholic class, the severe atypical class had the highest prevalence of females, the lowest mean age, the highest BMI, and highest prevalence of both cardiovascular disease, and metabolic syndrome.

LIMITATIONS

The strongest distinguishing symptoms, appetite and weight, could be correlated. Further, only longitudinal studies could demonstrate whether the identified classes are stable on the long term.

DISCUSSION

In older persons with depressive disorders, three distinct subtypes were identified, similar to subtypes found in younger adults. The strongest distinguishing features were appetite and weight; moreover, classes differed strongly on prevalence of metabolic syndrome and cardiovascular disease. These findings suggest differences in the involvement of metabolic pathways across classes, which should be considered when investigating the pathogenesis and (eventually) treatment of depression in older persons.

Using a hybrid subtyping model to capture patterns and dimensionality of depressive and anxiety symptomatology in the general population

BACKGROUND

Researchers have tried to identify more homogeneous subtypes of major depressive disorder (MDD) with latent class analyses (LCA). However, this approach does no justice to the dimensional nature of psychopathology. In addition, anxiety and functioning-levels have seldom been integrated in subtyping efforts. Therefore, this study used a hybrid discrete-dimensional approach to identify subgroups with shared patterns of depressive and anxiety symptomatology, while accounting for functioning-levels.

METHODS

The Comprehensive International Diagnostic Interview (CIDI) 1.1 was used to assess previous-year depressive and anxiety symptoms in the Netherlands Mental Health Survey and Incidence Study-1 (NEMESIS-1; n=5583). The data were analyzed with factor analyses, LCA and hybrid mixed-measurement item response theory (MM-IRT) with and without functioning covariates. Finally, the classes' predictors (measured one year earlier) and outcomes (measured two years later) were investigated.

RESULTS

A 3-class MM-IRT model with functioning covariates best described the data and consisted of a 'healthy class' (74.2%) and two symptomatic classes ('sleep/energy' [13.4%]; 'mood/anhedonia' [12.4%]). Factors including older age, urbanicity, higher severity and presence of 1-year MDD predicted membership of either symptomatic class vs. the healthy class. Both symptomatic classes showed poorer 2-year outcomes (i.e. disorders, poor functioning) than the healthy class. The odds of MDD after two years were especially increased in the mood/anhedonia class.

LIMITATIONS

Symptoms were assessed for the past year whereas current functioning was assessed.

CONCLUSIONS

Heterogeneity of depression and anxiety symptomatology are optimally captured by a hybrid discrete-dimensional subtyping model. Importantly, accounting for functioning-levels helps to capture clinically relevant interpersonal differences.

Depressive symptom trajectories in late adolescence and early adulthood: A systematic review

OBJECTIVE

In adolescents and young adults, depressive symptoms are highly prevalent and dynamic. For clinicians, it is difficult to determine whether a young person reporting depressive symptoms is at risk of developing ongoing mood difficulties or whether symptoms form part of a transient maturational process. Trajectory analyses of longitudinally assessed symptoms in large cohorts have the potential to untangle clinical heterogeneity by determining subgroups or classes of symptom course and their risk factors, by interrogating the impact of known or suspected risk factors on trajectory slope and intercept and by tracing the interrelation between depressive symptoms and other clinical outcomes over time.

METHOD

We conducted a systematic review of trajectory studies conducted in cohorts including people aged between 15 and 25 years.

RESULTS

We retrieved 47 relevant articles. These studies suggest that young people fall into common mood trajectory classes and that class membership and symptom course are mediated by biological and environmental risk factors. Furthermore, studies provide evidence that high and persistent depressive symptoms are associated with a range of concurrent health and behavioral outcomes.

CONCLUSION

Findings could assist in the formulation of novel concepts of depressive disorders in young people and inform preventive strategies and predictive models for clinical practice.

Undertreatment of people with major depressive disorder in 21 countries

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide.

AIMS

To examine the: (a) 12-month prevalence of DSM-IV MDD; (b) proportion aware that they have a problem needing treatment and who want care; (c) proportion of the latter receiving treatment; and (d) proportion of such treatment meeting minimal standards.

METHOD

Representative community household surveys from 21 countries as part of the World Health Organization World Mental Health Surveys.

RESULTS

Of 51 547 respondents, 4.6% met 12-month criteria for DSM-IV MDD and of these 56.7% reported needing treatment. Among those who recognised their need for treatment, most (71.1%) made at least one visit to a service provider. Among those who received treatment, only 41.0% received treatment that met minimal standards. This resulted in only 16.5% of all individuals with 12-month MDD receiving minimally adequate treatment.

CONCLUSIONS

Only a minority of participants with MDD received minimally adequate treatment: 1 in 5 people in high-income and 1 in 27 in low-/lower-middle-income countries. Scaling up care for MDD requires fundamental transformations in community education and outreach, supply of treatment and quality of services.

CHRONICITY OF DEPRESSION AND MOLECULAR MARKERS IN A LARGE SAMPLE OF HAN CHINESE WOMEN

BACKGROUND

Major depressive disorder (MDD) has been associated with changes in mean telomere length and mitochondrial DNA (mtDNA) copy number. This study investigates if clinical features of MDD differentially impact these molecular markers.

METHODS

Data from a large, clinically ascertained sample of Han Chinese women with recurrent MDD were used to examine whether symptom presentation, severity, and comorbidity were related to salivary telomere length and/or mtDNA copy number (maximum N = 5,284 for both molecular and phenotypic data).

RESULTS

Structural equation modeling revealed that duration of longest episode was positively associated with mtDNA copy number, while earlier age of onset of most severe episode and a history of dysthymia were associated with shorter telomeres. Other factors, such as symptom presentation, family history of depression, and other comorbid internalizing disorders, were not associated with these molecular markers.

CONCLUSIONS

Chronicity of depressive symptoms is related to more pronounced telomere shortening and increased mtDNA copy number among individuals with a history of recurrent MDD. As these molecular markers have previously been implicated in physiological aging and morbidity, individuals who experience prolonged depressive symptoms are potentially at greater risk of adverse medical outcomes.

Depression-Related Increases and Decreases in Appetite: Dissociable Patterns of Aberrant Activity in Reward and Interoceptive Neurocircuitry

OBJECTIVE

Appetite and weight changes are common but variable diagnostic markers in major depressive disorder: some depressed individuals manifest increased appetite, while others lose their appetite. Many of the brain regions implicated in appetitive responses to food have also been implicated in depression. It is thus remarkable that there exists no published research comparing the neural responses to food stimuli of depressed patients with increased versus decreased appetites.

METHOD

Using functional MRI, brain activity was compared in unmedicated depressed patients with increased or decreased appetite and healthy control subjects while viewing photographs of food and nonfood objects. The authors also measured how resting-state functional connectivity related to subjects' food pleasantness ratings.

RESULTS

Within putative reward regions, depressed participants with increased appetites exhibited greater hemodynamic activity to food stimuli than both those reporting appetite decreases and healthy control subjects. In contrast, depressed subjects experiencing appetite loss exhibited hypoactivation within a region of the mid-insula implicated in interoception, with no difference observed in this region between healthy subjects and those with depression-related appetite increases. Mid-insula activity was negatively correlated with food pleasantness ratings of depressed participants with increased appetites, and its functional connectivity to reward circuitry was positively correlated with food pleasantness ratings.

CONCLUSIONS

Depression-related increases in appetite are associated with hyperactivation of putative mesocorticolimbic reward circuitry, while depression-related appetite loss is associated with hypoactivation of insular regions that support monitoring the body's physiological state. Importantly, the interactions among these regions also contribute to individual differences in the depression-related appetite changes.

The association between latent depression subtypes and remission after treatment with citalopram: A latent class analysis with distal outcome

BACKGROUND

The objectives were to characterize latent depression subtypes by symptoms, evaluate sex differences in and examine correlates of these subtypes, and examine the association between subtype and symptom remission after citalopram treatment.

METHODS

Latent class analysis was applied to baseline data from 2772 participants in the Sequenced Treatment Alternatives to Relieve Depression trial. Indicators were from the Quick Inventory of Depressive Symptomatology. Separate multinomial logistic models identified correlates of subtypes and the association between subtype and the distal outcome of remission.

RESULTS

Four latent subtypes were identified: Mild (men: 37%, women: 27%), Moderate (men: 24%, women: 21%), Severe with Increased Appetite (men: 13%, women: 22%), and Severe with Insomnia (men: 26%, women: 31%). Generalized anxiety disorder, bulimia, and social phobia were correlated with Severe with Increased Appetite and generalized anxiety disorder, post-traumatic stress disorder, and social phobia with Severe with Insomnia. Relative to those with the Mild subtype, those with Severe with Increased Appetite (odds ratiomen (OR): 0.48; 95% confidence interval (CI): 0.25-0.92; OR women: 0.59; 95% CI: 0.41-0.86) and those with Severe Depression with Insomnia (ORmen: 0.65; 95% CI: 0.41-1.02; ORwomen: 0.45; 95% CI: 0.32-0.64) were less likely to achieve remission.

LIMITATIONS

The sample size limited exploration of higher order interactions.

CONCLUSIONS

Insomnia and increased appetite distinguished latent subtypes. Sex and psychiatric comorbidities differed between the subtypes. Remission was less likely for those with the severe depression subtypes. Sleep disturbances, appetite changes, and other mental disorders may play a role in the etiology and treatment of depression.

Anxious and non-anxious major depressive disorder in the World Health Organization World Mental Health Surveys

BACKGROUND

To examine cross-national patterns and correlates of lifetime and 12-month comorbid DSM-IV anxiety disorders among people with lifetime and 12-month DSM-IV major depressive disorder (MDD).

METHOD

Nationally or regionally representative epidemiological interviews were administered to 74 045 adults in 27 surveys across 24 countries in the WHO World Mental Health (WMH) Surveys. DSM-IV MDD, a wide range of comorbid DSM-IV anxiety disorders, and a number of correlates were assessed with the WHO Composite International Diagnostic Interview (CIDI).

RESULTS

45.7% of respondents with lifetime MDD (32.0-46.5% inter-quartile range (IQR) across surveys) had one of more lifetime anxiety disorders. A slightly higher proportion of respondents with 12-month MDD had lifetime anxiety disorders (51.7%, 37.8-54.0% IQR) and only slightly lower proportions of respondents with 12-month MDD had 12-month anxiety disorders (41.6%, 29.9-47.2% IQR). Two-thirds (68%) of respondents with lifetime comorbid anxiety disorders and MDD reported an earlier age-of-onset (AOO) of their first anxiety disorder than their MDD, while 13.5% reported an earlier AOO of MDD and the remaining 18.5% reported the same AOO of both disorders. Women and previously married people had consistently elevated rates of lifetime and 12-month MDD as well as comorbid anxiety disorders. Consistently higher proportions of respondents with 12-month anxious than non-anxious MDD reported severe role impairment (64.4 v. 46.0%; χ 2 1 = 187.0, p < 0.001) and suicide ideation (19.5 v. 8.9%; χ 2 1 = 71.6, p < 0.001). Significantly more respondents with 12-month anxious than non-anxious MDD received treatment for their depression in the 12 months before interview, but this difference was more pronounced in high-income countries (68.8 v. 45.4%; χ 2 1 = 108.8, p < 0.001) than low/middle-income countries (30.3 v. 20.6%; χ 2 1 = 11.7, p < 0.001).

CONCLUSIONS

Patterns and correlates of comorbid DSM-IV anxiety disorders among people with DSM-IV MDD are similar across WMH countries. The narrow IQR of the proportion of respondents with temporally prior AOO of anxiety disorders than comorbid MDD (69.6-74.7%) is especially noteworthy. However, the fact that these proportions are not higher among respondents with 12-month than lifetime comorbidity means that temporal priority between lifetime anxiety disorders and MDD is not related to MDD persistence among people with anxious MDD. This, in turn, raises complex questions about the relative importance of temporally primary anxiety disorders as risk markers v. causal risk factors for subsequent MDD onset and persistence, including the possibility that anxiety disorders might primarily be risk markers for MDD onset and causal risk factors for MDD persistence.