Characteristics, comorbidities, and correlates of atypical depression: evidence from the UK Biobank Mental Health Survey

Depressive disorder subtypes, depressive symptom clusters, and risk of obesity and diabetes: A systematic review

BACKGROUND

Overlapping but divided literatures suggest certain depression facets may pose greater obesity and diabetes risk than others. Our objectives were to integrate the major depressive disorder (MDD) subtype and depressive symptom cluster literatures and to clarify which facets are associated with the greatest cardiometabolic disease risk.

METHODS

We conducted a systematic review of published studies examining associations of ≥2 MDD subtypes or symptom clusters with obesity or diabetes risk outcomes. We report which facets the literature is "in favor" of (i.e., having the strongest or most consistent results).

RESULTS

Forty-five articles were included. Of the MDD subtype-obesity risk studies, 14 were in favor of atypical MDD, and 8 showed similar or null associations across subtypes. Of the symptom cluster-obesity risk studies, 5 were in favor of the somatic cluster, 1 was in favor of other clusters, and 5 were similar or null. Of the MDD subtype-diabetes risk studies, 7 were in favor of atypical MDD, 3 were in favor of other subtypes, and 5 were similar or null. Of the symptom cluster-diabetes risk studies, 7 were in favor of the somatic cluster, and 5 were similar or null.

LIMITATIONS

Limitations in study design, sample selection, variable measurement, and analytic approach in these literatures apply to this review.

CONCLUSIONS

Atypical MDD and the somatic cluster are most consistently associated with obesity and diabetes risk. Future research is needed to establish directionality and causality. Identifying the depression facets conferring the greatest risk could improve cardiometabolic disease risk stratification and prevention programs.

Characterization of depression subtypes and their relationships to stressor profiles among middle-aged and older adults: An analysis of the canadian longitudinal study on aging (CLSA)

The current diagnostic criteria for depression do not sufficiently reflect its heterogeneous clinical presentations. Associations between adverse childhood experiences (ACEs), allostatic load (AL), and depression subtypes have not been extensively studied. Depression subtypes were determined based on clinical presentations, and their relationships to AL biomarkers and ACEs were elucidated in a sample of middle-aged and older adults. Participants from the Canadian Longitudinal Study on Aging who screened positive for depression were included (n = 3966). Depression subtypes, AL profiles and ACE profiles were determined with latent profile analyses, and associations between them were determined using multinomial logistic regression. Four depression subtypes were identified: positive affect, melancholic, typical, and atypical. Distinct associations between depression subtypes, stressor profiles and covariates were observed. Among the subtypes compared to positive affect, atypical subtype had the most numerous significant associations, and the subtypes had unique relationships to stressor profiles. Age, sex, smoking status, chronic conditions, marital status, and physical activity were significant covariates. The present study describes distinct associations between depression subtypes and measures of stress (objective and self-reported), as well as related factors that differentiate subtypes. The findings may inform more targeted and integrated clinical management strategies for depression in individuals exposed to multiple stressors.

Dysregulated cerebral blood flow, rather than gray matter Volume, exhibits stronger correlations with blood inflammatory and lipid markers in depression

Arterial spin labeling (ASL) can be used to detect differences in perfusion for multiple brain regions thought to be important in major depressive disorder (MDD). However, the potential of cerebral blood flow (CBF) to predict MDD and its correlations between the blood lipid levels and immune markers, which are closely related to MDD and brain function change, remain unclear. The 451 individuals - 298 with MDD and 133 healthy controls who underwent MRI at a single time point with arterial spin labelling and a high resolution T1-weighted structural scan. A proportion of MDD also provided blood samples for analysis of lipid and immune markers. We performed CBF case-control comparisons, random forest model construction, and exploratory correlation analyses. Moreover, we investigated the relationship between gray matter volume (GMV), blood lipids, and the immune system within the same sample to assess the differences in CBF and GMV. We found that the left inferior parietal but supramarginal and angular gyrus were significantly different between the MDD patients and HCs (voxel-wise P < 0.001, cluster-wise FWE correction). And bilateral inferior temporal (ITG), right middle temporal gyrus and left precentral gyrus CBF predict MDD (the area under the receiver operating characteristic curve of the random forest model is 0.717) and that CBF is a more sensitive predictor of MDD than GMV. The left ITG showed a positive correlation trend with immunoglobulin G (r = 0.260) and CD4 counts (r = 0.283). The right ITG showed a correlation trend with Total Cholesterol (r = -0.249) and tumour necrosis factor-alpha (r = -0.295). Immunity and lipids were closely related to CBF change, with the immunity relationship potentially playing a greater role. The interactions between CBF, plasma lipids and immune index could therefore represent an MDD pathophysiological mechanism. The current findings provide evidence for targeted regulation of CBF or immune properties in MDD.

Investigating the role of the relaxin-3/RXFP3 system in neuropsychiatric disorders and metabolic phenotypes: A candidate gene approach

The relaxin-3/RXFP3 system has been implicated in the modulation of depressive- and anxiety-like behaviour in the animal literature; however, there is a lack of human studies investigating this signalling system. We seek to bridge this gap by leveraging the large UK Biobank study to retrospectively assess genetic risk variants linked with this neuropeptidergic system. Specifically, we conducted a candidate gene study in the UK Biobank to test for potential associations between a set of functional, candidate single nucleotide polymorphisms (SNPs) pertinent to relaxin-3 signalling, determined using in silico tools, and several outcomes, including depression, atypical depression, anxiety and metabolic syndrome. For each outcome, we used several rigorously defined phenotypes, culminating in subsample sizes ranging from 85,881 to 386,769 participants. Across all outcomes, there were no associations between any candidate SNP and any outcome phenotype, following corrections for multiple testing burden. Regression models comprising several SNPs per relevant candidate gene as exploratory variables further exhibited no prediction of outcome. Our findings corroborate conclusions from previous literature about the limitations of candidate gene approaches, even when based on firm biological hypotheses, in the domain of genetic research for neuropsychiatric disorders.

Trustworthy Data and AI Environments for Clinical Prediction: Application to Crisis-Risk in People With Depression

Depression is a common mental health condition that often occurs in association with other chronic illnesses, and varies considerably in severity. Electronic Health Records (EHRs) contain rich information about a patient's medical history and can be used to train, test and maintain predictive models to support and improve patient care. This work evaluated the feasibility of implementing an environment for predicting mental health crisis among people living with depression based on both structured and unstructured EHRs. A large EHR from a mental health provider, Mersey Care, was pseudonymised and ingested into the Natural Language Processing (NLP) platform CogStack, allowing text content in binary clinical notes to be extracted. All unstructured clinical notes and summaries were semantically annotated by MedCAT and BioYODIE NLP services. Cases of crisis in patients with depression were then identified. Random forest models, gradient boosting trees, and Long Short-Term Memory (LSTM) networks, with varying feature arrangement, were trained to predict the occurrence of crisis. The results showed that all the prediction models can use a combination of structured and unstructured EHR information to predict crisis in patients with depression with good and useful accuracy. The LSTM network that was trained on a modified dataset with only 1000 most-important features from the random forest model with temporality showed the best performance with a mean AUC of 0.901 and a standard deviation of 0.006 using a training dataset and a mean AUC of 0.810 and 0.01 using a hold-out test dataset. Comparing the results from the technical evaluation with the views of psychiatrists shows that there are now opportunities to refine and integrate such prediction models into pragmatic point-of-care clinical decision support tools for supporting mental healthcare delivery.

Screening, Genetic Variants, and Bipolar Disorders: Can Useful Hypotheses Arise from the Sum of Partial Failures?

Bipolar disorder (BD) is a relevant public health issue, therefore accurate screening tools could be useful. The objective of this study is to verify the accuracy of the Mood Disorder Questionnaire (MDQ) and genetic risk as screeners, and their comparison in terms of reliability. Older adults (N = 61, ≥60 years) received a clinical psychiatric evaluation, the MDQ, and were evaluated according to the presence of the genetic variant RS1006737 of CACNA1C. MDQ+ versus the diagnosis of BD as a gold standard shows a sensitivity of 0.286 (Cl 95% 0.14-0.39); a specificity of 0.925 (Cl 95% 0.85-0.08); a predictive positive value (PPV) of 0.667 (Cl 95% 0.33-0.91); and a predictive negative value (PNV) of 0.702 (Cl 95% 0.65-0.75). The positivity for the variant RS1006737 of the CACNA1C against the diagnosis of BD as a gold standard shows a sensitivity of 0.750 (Cl 95% 0.55-0.90); a specificity of 0.375 (Cl 95% 0.28-0.45); a PPV of 0.375 (Cl 95% 0.28-0.45); and a PNV of 0.750 (Cl 95% 0.55-0.90). The reliability between the MDQ+ and positivity for the variant RS1006737 of the CACNA1C was very low (K = -0.048, Cl 95% -0.20-0.09). The study found that both the genetic and the paper and pencil test were quite accurate, but were not reliable in case finding. In fact, despite some validity, albeit specular (in the case of a positive genetic test, the probability of having the disorder is very high, whereas in the case of a negative score on the paper and pencil test, the probability of not having the disorder is very high), the unreliability of the two tests (i.e., they certainly do not measure the same underlying dimension) opens the door to the need for an interpretation and the possibility of a synergistic use for screening. From a heuristic perspective, which obviously requires all of the necessary verifications, this study seems to suggest the hypothesis that a condition of hyperactivation common to disorders and stress conditions, and identified by a positive score on the MDQ (which is common to BD, post-traumatic stress disorder (PTSD), and anxiety disorders and whose genetic basis has not yet been clarified) can trigger BD in people with a predisposition to hyperactivity (i.e., in people with the condition identified by the analyzed genetic variant).

Exploring the Heart-Mind Connection: Unraveling the Shared Pathways between Depression and Cardiovascular Diseases

Civilization diseases are defined as non-communicable diseases that affect a large part of the population. Examples of such diseases are depression and cardiovascular disease. Importantly, the World Health Organization warns against an increase in both of these. This narrative review aims to summarize the available information on measurable risk factors for CVD and depression based on the existing literature. The paper reviews the epidemiology and main risk factors for the coexistence of depression and cardiovascular disease. The authors emphasize that there is evidence of a link between depression and cardiovascular disease. Here, we highlight common risk factors for depression and cardiovascular disease, including obesity, diabetes, and physical inactivity, as well as the importance of the prevention and treatment of CVD in preventing depression and other mental disorders. Conversely, effective treatment of CVD can also help prevent depression and improve mental health outcomes. It seems advisable to introduce screening tests for depression in patients treated for cardiac reasons. Importantly, in patients treated for mood disorders, it is worth controlling CVD risk factors, for example, by checking blood pressure and pulse during routine visits. It is also worth paying attention to the mental condition of patients with CVD. This study underlines the importance of interdisciplinary co-operation.

Determinants of socioeconomic factors for quality of life and depressive symptoms in community-dwelling older people: A cross-sectional study in Brazil and Portugal

Our aim was to analyze the association between socioeconomic status and quality of life (QoL) among older people with depressive symptoms treated through the Primary Health Care (PHC) system in Brazil and Portugal. This was a comparative cross-sectional study with a nonprobability sample of older people in the PHC in Brazil and Portugal conducted between 2017 and 2018. To evaluate the variables of interest, the socioeconomic data questionnaire, the Geriatric Depression Scale and the Medical Outcomes Short-Form Health Survey were used. Descriptive and multivariate analyses were performed to test the study hypothesis. The sample consisted of n = 150 participants (Brazil n = 100 and Portugal n = 50). There was a predominance of woman (76.0%, p = 0.224) and individuals between 65 and 80 years (88.0%, p = 0.594). The multivariate association analysis showed that in the presence of depressive symptoms, the QoL mental health domain was most associated with the socioeconomic variables. Among the prominent variables, woman group (p = 0.027), age group 65-80 years (p = 0.042), marital status "without a partner" (p = 0.029), education up to 5 years (p = 0.011) and earning up to 1 minimum wage (p = 0.037) exhibited higher scores among brazilian participants. The portuguese participants showed an association between the general health status domain and woman group (p = 0.042) and education up to 5 years (p = 0.045). The physical functioning domain was associated with income of up to 1 minimum wage (p = 0.037). In these domains, the portuguese participants exhibited higher scores than the brazilian participants. We verified the association between socioeconomic profile and QoL in the presence of depressive symptoms, which occurred mainly among woman, participants with low levels of education and low income, with QoL aspects related to mental, physical and social health and self-perceived health. The group from Brazil had higher QoL scores than the group from Portugal.

Microbiome and immuno-metabolic dysregulation in patients with major depressive disorder with atypical clinical presentation

Depression is highly prevalent (6% 1-year prevalence) and is the second leading cause of disability worldwide. Available treatment options for depression are far from optimal, with response rates only around 50%. This is most likely related to a heterogeneous clinical presentation of major depression disorder (MDD), suggesting different manifestations of underlying pathophysiological mechanisms. Poorer treatment outcomes to first-line antidepressants were reported in MDD patients endorsing an "atypical" symptom profile that is characterized by preserved reactivity in mood, increased appetite, hypersomnia, a heavy sensation in the limbs, and interpersonal rejection sensitivity. In recent years, evidence has emerged that immunometabolic biological dysregulation is an important underlying pathophysiological mechanism in depression, which maps more consistently to atypical features. In the last few years human microbial residents have emerged as a key influencing variable associated with immunometabolic dysregulations in depression. The microbiome plays a critical role in the training and development of key components of the host's innate and adaptive immune systems, while the immune system orchestrates the maintenance of key features of the host-microbe symbiosis. Moreover, by being a metabolically active ecosystem commensal microbes may have a huge impact on signaling pathways, involved in underlying mechanisms leading to atypical depressive symptoms. In this review, we discuss the interplay between the microbiome and immunometabolic imbalance in the context of atypical depressive symptoms. Although research in this field is in its infancy, targeting biological determinants in more homogeneous clinical presentations of MDD may offer new avenues for the development of novel therapeutic strategies for treatment-resistant depression.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

BACKGROUND

Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes.

METHODS

Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC).

RESULTS

For MD vs. controls (n_(MD) = 24,229; n_(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n_(atypical) = 958; n_(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes.

LIMITATIONS

Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary.

DISCUSSION

Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Depressive symptoms and neuroticism-related traits are the main factors associated with wellbeing independent of the history of lifetime depression in the UK Biobank

BACKGROUND

Wellbeing has a fundamental role in determining life expectancy and major depressive disorder (MDD) is one of the main modulating factors of wellbeing. This study evaluated the modulators of wellbeing in individuals with lifetime recurrent MDD (RMDD), single-episode MDD (SMDD) and no MDD in the UK Biobank.

METHODS

Scores of happiness, meaningful life and satisfaction about functioning were condensed in a functioning-wellbeing score (FWS). We evaluated depression and anxiety characteristics, neuroticism-related traits, physical diseases, lifestyle and polygenic risk scores (PRSs) of psychiatric disorders. Other than individual predictors, we estimated the cumulative contribution to FWS of each group of predictors. We tested the indirect role of neuroticism on FWS through the modulation of depression manifestations using a mediation analysis.

RESULTS

We identified 47 966, 21 117 and 207 423 individuals with lifetime RMDD, SMDD and no MDD, respectively. Depression symptoms and personality showed the largest impact on FWS (variance explained ~20%), particularly self-harm, worthlessness feelings during the worst depression, chronic depression, loneliness and neuroticism. Personality played a stronger role in SMDD. Anxiety characteristics showed a higher effect in SMDD and no MDD groups. Neuroticism played indirect effects through specific depressive symptoms that modulated FWS. Physical diseases and lifestyle explained only 4-5% of FWS variance. The PRS of MDD showed the largest effect on FWS compared to other PRSs.

CONCLUSIONS

This was the first study to comprehensively evaluate the predictors of wellbeing in relation to the history of MDD. The identified variables are important to identify individuals at risk and promote wellbeing.

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.

Bangpungtongsung-san for patients with major depressive disorder: study protocol for a randomized controlled phase II clinical trial

BACKGROUND

Bangpungtongsung-san (BTS) is a representative herbal medicine that has been widely used for patients with obesity in east Asian countries. Various preclinical studies have demonstrated the anti-depressive effect of BTS granules in various animal models of depression. This phase II trial aimed to explore the efficacy and safety of BTS in human patients with depression.

METHODS

A total of 126 patients diagnosed with major depressive disorder and who are not underweight (body mass index ≥ 18.5 kg/m²) will be enrolled in this study. Eligible participants will be randomly allocated into three groups: the high-dose BTS, low-dose BTS, and placebo groups in a 1:1:1 ratio. BTS or placebo granules will be orally administered twice a day for 8 weeks. The BTS and placebo granules will be made to have identical color, scent, and shape, and participants and investigators will be blinded to the allocation. The primary efficacy endpoint is the change from baseline of the 17-item Hamilton Depression Rating Scale total score at 8 weeks. The superiority of the high- and low-dose BTS granules to the placebo granules will be tested.

DISCUSSION

The results of this clinical trial will provide evidence on the efficacy and safety of BTS for patients with major depressive disorder. This study will be conducted in accordance with ethical and regulatory guidelines, and the results will be submitted and published in international peer-reviewed journals.

TRIAL REGISTRATION

CRIS registration Number: KCT0007571; registered on 2022/07/26 ( https://cris.nih.go.kr/cris/search/detailSearch.do/23192 ).

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.

Metabolic syndrome among young adults at high and low familial risk for depression

BACKGROUND

Our study examined whether the early-onset depression phenotype among young adults (probands) is associated with the metabolic syndrome (MetS) and its components, and if MetS characterizes unaffected but high-risk siblings of probands.

METHODS

We studied three groups of young adults (Mage = 25 years, s.d. = 3.84 years): probands with histories of childhood onset depression - i.e. early-onset phenotype - (n = 293), their unaffected siblings (high-risk siblings, n = 273), and healthy controls (n = 171). Participants completed a full psychiatric interview, physical and laboratory assessments, and self-rating scales. MetS was defined using the criteria of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults ().

RESULTS

Early-onset depression phenotype and being a high-risk sibling were associated with higher MetS composite scores relative to that of controls, but did not differ from one another. With regard to MetS components: Probands and siblings had similarly larger waist circumference and lower HDL than did controls, while siblings and controls had lower triglyceride levels than did probands but did not differ from one another. Groups did not differ on glucose levels and SBP.

CONCLUSIONS

Our study extends the literature on the association between MetS and depression and underscores the importance of depression phenotypes: failure to account for the clinical heterogeneity of depression may partly underlie the inconsistent findings regarding its relation to MetS. The results also suggest that, in depression-prone populations, MetS may predate and possibly function as a risk factor for eventual depression.

The association between trauma exposure, polygenic risk and individual depression symptoms

BACKGROUND

Traumatic experiences are associated with increased risk for major depressive disorder (MDD). This study sought to determine the extent that trauma exposure, depression polygenic risk scores (PRS), and their interaction are associated with MDD and individual depression symptoms.

METHODS

Data from 102,182 individuals from the large-scale UK Biobank population cohort was analysed. A series of regression analyses were conducted to estimate the association between trauma, depression PRS and 1) current depression, 2) lifetime MDD case-control status, 3) nine individual current depressive symptoms, and 4) thirteen individual symptoms experienced during a major depressive episode. Additive and multiplicative PRS-by-trauma interactions were also assessed.

RESULTS

Trauma and depression PRS were significantly associated with both current depression and lifetime MDD. A positive, additive interaction effect was observed on depression, but multiplicative interactions were not significant. Trauma exposure and depression PRS were associated with specific patterns of depression symptoms; Trauma was associated with low self-esteem, suicidal ideation, and atypical (but not typical) neurovegetative symptoms. Additive interaction effects were observed on six out of nine current depressive symptoms.

CONCLUSIONS

Trauma exposure and genetic predisposition to depression may lead to particular symptomatology, which may contribute to the extreme clinical heterogeneity observed in individuals with major depression.

A viewpoint on aldosterone and BMI related brain morphology in relation to treatment outcome in patients with major depression

An abundance of knowledge has been collected describing the involvement of neuroendocrine parameters in major depression. The hypothalamic-pituitary-adrenocortical (HPA) axis regulating cortisol release has been extensively studied; however, attempts to target the HPA axis pharmacologically to treat major depression have failed. This review focuses on the importance of the adrenocortical stress hormone aldosterone, which is released by adrenocorticotropic hormone and angiotensin, and the mineralocorticoid receptor (MR) in depression. Depressed patients, in particular those with atypical depression, have signs of central hyperactivation of the aldosterone sensitive MR, potentially as a consequence of a reactive aldosterone release induced by low blood pressure and as a result of low sensitivity of peripheral MR. This is reflected in reduced heart rate variability, increased salt appetite and sleep changes in this group of patients. In addition, enlarged brain ventricles, compressed corpus callosum and changes of the choroid plexus are associated with increased aldosterone (in relation to cortisol). Furthermore, subjects with these features often show obesity. These characteristics are related to a worse antidepressant treatment outcome. Alterations in choroid plexus function as a consequence of increased aldosterone levels, autonomic dysregulation, metabolic changes and/or inflammation may be involved. The characterization of this regulatory system is in its early days but may identify new targets for therapeutic interventions.

Melancholic features and typical neurovegetative symptoms of major depressive disorder show specific polygenic patterns

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric condition characterised by a heterogeneous clinical presentation and an estimated twin-based heritability of ~40-50 %. Different clinical MDD subtypes might partly reflect distinctive underlying genetics. This study aims to investigate if polygenic risk scores (PRSs) for different psychiatric disorders, personality traits, and substance use-related traits may be associated with different clinical subtypes of MDD (i.e., MDD with melancholic or psychotic features), higher symptom severity, or different clusters of depressive symptoms (i.e., sadness symptoms, typical neurovegetative symptoms, detachment symptoms, and negative thoughts).

METHODS

The target sample included 1149 patients with MDD, recruited by the European Group for the Study of Resistant Depression. PRSs for 25 psychiatric disorders and traits were computed based on the most recent publicly available summary statistics of the largest genome-wide association studies. PRSs were then used as predictors in regression models, adjusting for age, sex, population stratification, and recruitment sites.

RESULTS

Patients with MDD having higher PRS for MDD and loneliness were more likely to exhibit melancholic features of MDD (p = 0.0009 and p = 0.005, respectively). Moreover, patients with higher PRS for alcohol intake and post-traumatic stress disorder were more likely to experience greater typical neurovegetative symptoms (p = 0.0012 and p = 0.0045, respectively).

LIMITATIONS

The proportion of phenotypic variance explained by the PRSs was limited.

CONCLUSIONS

This study suggests that melancholic features and typical neurovegetative symptoms of MDD may show distinctive underlying genetics. Our findings provide a new contribution to the understanding of the genetic heterogeneity of MDD.

Symptom dimensions of major depression in a large community-based cohort

BACKGROUND

Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community.

METHODS

This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or 'symptom dimensions' via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records.

RESULTS

Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations.

CONCLUSIONS

An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

A Survey of Living Conditions and Psychological Distress in Japanese University Freshmen during the COVID-19 Pandemic

Since the novel coronavirus disease 2019 (COVID-19) pandemic, educational institutions have implemented measures such as school closures, raising concerns regarding the increase in psychological distress among university students. The purpose of this study is to identify factors that have influenced psychological distress among college freshmen during the COVID-19 pandemic. A questionnaire survey was conducted at the conclusion of the sixth wave of COVID-19 in Japan. Psychological distress was measured using the six-item Kessler Psychological Distress Scale (K6). Factors affecting psychological distress were calculated using regression analysis. Of the 2536 participants, 1841 (72.6%) reported having no psychological distress, while 695 (27.4%) reported having psychological distress. Factors that were identified to contribute to psychological distress were lack of sleep, weight gain or loss, worsening of interpersonal relationships, and physical symptoms and illnesses. A willingness to join an athletic club and having an environment in which it is easy to discuss worries and anxieties with others were factors that were identified to hinder psychological distress. It is necessary for universities to offer enhanced supports for physical and interpersonal activities. Additionally, it is imperative to encourage students to look after their physical health and to actively utilize university-based consultation systems.

Stratification of individuals with lifetime depression and low wellbeing in the UK Biobank

BACKGROUND

Previous studies stratified patients with major depressive disorder (MDD) based on their clinical characteristics. This study used this approach in individuals with lifetime MDD who reported low wellbeing, a group of high clinical relevance.

METHODS

We selected participants in the UK Biobank (UKB) with lifetime MDD and a wellbeing score in the lowest 25 %. A wellbeing score was previously created considering happiness, belief that own life is meaningful, health satisfaction and functioning in relevant areas. In the selected group, we applied latent class analysis using mood-spectrum symptoms and personality traits as input variables, then we compared the clinical-demographic and genetic (polygenic risk scores, PRSs) characteristics of the identified classes.

RESULTS

A total of 13,896 individuals were included and a model with five classes showed the best performance. The most common class (31.25 %) was characterised by periods of irritable mood and trait irritability with high neuroticism. A rarer class (16.49 %) showed depressive-manic mood fluctuations and risk-taking personality, higher percentage of males, atypical depressive symptoms, lower socio-economic status, higher PRS for attention-deficit hyperactivity disorder and lower PRS for education. The second most common class (29.79 %) showed worry as main personality trait with low risk of manic/irritable manifestations. The remaining classes showed an anxious-irritable personality profile and a purely depressive profile (4.92 % and 17.55 %, respectively).

LIMITATIONS

Our results may reflect the characteristics of UKB participants.

CONCLUSIONS

Subthreshold manic/irritable mood fluctuations and personality traits irritability and neuroticism may distinguish the most common groups with poor wellbeing in lifetime MDD.

Overweight, obesity, and individual symptoms of depression: A multicohort study with replication in UK Biobank

OBJECTIVES

Obesity is associated with increased risk of depression, but the extent to which this association is symptom-specific is unknown. We examined the associations of overweight and obesity with individual depressive symptoms.

METHODS

We pooled data from 15 population-based cohorts comprising 57,532 individuals aged 18 to 100 years at study entry. Primary analyses were replicated in an independent cohort, the UK Biobank study (n = 122,341, age range 38 to 72). Height and weight were assessed at baseline and body mass index (BMI) was computed. Using validated self-report measures, 24 depressive symptoms were ascertained once in 16 cross-sectional, and twice in 7 prospective cohort studies (mean follow-up 3.2 years).

RESULTS

In the pooled analysis of the primary cohorts, 22,045 (38.3 %) participants were overweight (BMI between 25 and 29.9 kg/m2), 12,025 (20.9 %) class I obese (BMI between 30 and 34.9 kg/m2), 7,467 (13.0 %) class II-III obese (BMI ≥ 35 kg/m2); and 7,046 (12.3 %) were classified as depressed. After multivariable adjustment, obesity class I was cross-sectionally associated with 1.11-fold (95 % confidence interval 1.01-1.22), and obesity class II-III with 1.31-fold (1.16-1.49) higher odds of overall depression. In symptom-specific analyses, robust associations were apparent for 4 of the 24 depressive symptoms ('could not get going/lack of energy', 'little interest in doing things', 'feeling bad about yourself, and 'feeling depressed'), with confounder-adjusted odds ratios of having 3 or 4 of these symptoms being 1.32 (1.10-1.57) for individuals with obesity class I, and 1.70 (1.34-2.14) for those with obesity class II-III. Elevated C-reactive protein and 21 obesity-related diseases explained 23 %-31 % of these associations. Symptom-specific associations were confirmed in longitudinal analyses where obesity preceded symptom onset, were stronger in women compared with men, and were replicated in UK Biobank.

CONCLUSIONS

Obesity is associated with a distinct set of depressive symptoms. These associations are partially explained by systemic inflammation and obesity-related morbidity. Awareness of this obesity-related symptom profile and its underlying biological correlates may inform better targeted treatments for comorbid obesity and depression.

A population-based retrospective study of the modifying effect of urban blue space on the impact of socioeconomic deprivation on mental health, 2009-2018

The incidence of mental health disorders in urban areas is increasing and there is a growing interest in using urban blue spaces (urban waterways, canals, lakes, ponds, coasts, etc.) as a tool to manage and mitigate mental health inequalities in the population. However, there is a dearth of longitudinal evidence of the mechanisms and impact of blue spaces on clinical markers of mental health to support and inform such interventions. We conducted a 10-year retrospective study, following STROBE guidelines, using routinely collected population primary care health data within the National Health Service (NHS) administrative area of Greater Glasgow and Clyde for the North of Glasgow city area. We explored whether living near blue space modifies the negative effect of socio-economic deprivation on mental health during the regeneration of an urban blue space (canal) from complete dereliction and closure. A total of 132,788 people (65,351 female) fulfilling the inclusion criteria were entered in the analysis. We established a base model estimating the effect of deprivation on the risk of mental health disorders using a Cox proportional hazards model, adjusted for age, sex and pre-existing comorbidities. We then investigated the modifying effect of living near blue space by computing a second model which included distance to blue space as an additional predicting variable and compared the results to the base model. Living near blue space modified the risk of mental health disorders deriving from socio-economic deprivation by 6% (hazard ratio 2.48, 95% confidence interval 2.39–2.57) for those living in the most deprived tertile (T1) and by 4% (hazard ratio 1.66, 95% confidence interval 1.60–1.72) for those in the medium deprivation tertile (T2). Our findings support the notion that living near blue space could play an important role in reducing the burden of mental health inequalities in urban populations.

Dietary diversity and depression: cross-sectional and longitudinal analyses in Spanish adult population with metabolic syndrome. Findings from PREDIMED-Plus trial

OBJECTIVE

To examine the cross-sectional and longitudinal (2-year follow-up) associations between dietary diversity (DD) and depressive symptoms.

DESIGN

An energy-adjusted dietary diversity score (DDS) was assessed using a validated FFQ and was categorised into quartiles (Q). The variety in each food group was classified into four categories of diversity (C). Depressive symptoms were assessed with Beck Depression Inventory-II (Beck II) questionnaire and depression cases defined as physician-diagnosed or Beck II >= 18. Linear and logistic regression models were used.

SETTING

Spanish older adults with metabolic syndrome (MetS).

PARTICIPANTS

A total of 6625 adults aged 55-75 years from the PREDIMED-Plus study with overweight or obesity and MetS.

RESULTS

Total DDS was inversely and statistically significantly associated with depression in the cross-sectional analysis conducted; OR Q4 v. Q1 = 0·76 (95 % CI (0·64, 0·90)). This was driven by high diversity compared to low diversity (C3 v. C1) of vegetables (OR = 0·75, 95 % CI (0·57, 0·93)), cereals (OR = 0·72 (95 % CI (0·56, 0·94)) and proteins (OR = 0·27, 95 % CI (0·11, 0·62)). In the longitudinal analysis, there was no significant association between the baseline DDS and changes in depressive symptoms after 2 years of follow-up, except for DD in vegetables C4 v. C1 = (β = 0·70, 95 % CI (0·05, 1·35)).

CONCLUSIONS

According to our results, DD is inversely associated with depressive symptoms, but eating more diverse does not seem to reduce the risk of future depression. Additional longitudinal studies (with longer follow-up) are needed to confirm these findings.

Genome-wide association studies in non-anxiety individuals identified novel risk loci for depression

BACKGROUND

Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).

METHODS

The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.

RESULTS

Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10^-8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10^-8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (p_{replication GWAS1} = 0.02, p_{replication GWAS2} = 2.71 × 10^-3) in CFAP61, and rs11661122 (p_{replication GWAS1} = 8.16 × 10^-3, p_{replication GWAS2} = 8.08 × 10^-3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).

CONCLUSIONS

Our findings provide novel clues for understanding of the complex genetic architecture of depression.

Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas

Contemporarily, depression has become a common psychiatric disorder that influences people's life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understanding the hot spots, evolutionary trends, and future related research directions and offers further guidance for practice. This investigation contributes to knowledge by combining robust methodological software for analysis, including Citespace, Ucinet, and Pajek. This paper employed the bibliometric methodology to analyze 5,000 research articles concerning depression. This current research also employed the BibExcel software to bibliometrically measure the keywords of the selected articles and further conducted a co-word matrix analysis. Additionally, Pajek software was used to conduct a co-word network analysis to obtain a co-word network diagram of depression. Further, Ucinet software was utilized to calculate K-core values, degree centrality, and mediated centrality to better present the research hotspots, sort out the current status and reveal the research characteristics in the field of depression with valuable information and support for subsequent research. This research indicates that major depressive disorder, anxiety, and mental health had a high occurrence among adolescents and the aged. This present study provides policy recommendations for the government, non-governmental organizations and other philanthropic agencies to help furnish resources for treating and controlling depression orders.

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study

Background

In 2017, an estimated 17.3 million adults in the United States experienced at least one major depressive episode, with 35% of them not receiving any treatment. Underdiagnosis of depression has been attributed to many reasons, including stigma surrounding mental health, limited access to medical care, and barriers due to cost.

Objective

This study aimed to determine if low-burden personal health solutions, leveraging person-generated health data (PGHD), could represent a possible way to increase engagement and improve outcomes.

Methods

Here, we present the development of PSYCHE-D (Prediction of Severity Change-Depression), a predictive model developed using PGHD from more than 4000 individuals, which forecasts the long-term increase in depression severity. PSYCHE-D uses a 2-phase approach. The first phase supplements self-reports with intermediate generated labels, and the second phase predicts changing status over a 3-month period, up to 2 months in advance. The 2 phases are implemented as a single pipeline in order to eliminate data leakage and ensure results are generalizable.

Results

PSYCHE-D is composed of 2 Light Gradient Boosting Machine (LightGBM) algorithm–based classifiers that use a range of PGHD input features, including objective activity and sleep, self-reported changes in lifestyle and medication, and generated intermediate observations of depression status. The approach generalizes to previously unseen participants to detect an increase in depression severity over a 3-month interval, with a sensitivity of 55.4% and a specificity of 65.3%, nearly tripling sensitivity while maintaining specificity when compared with a random model.

Conclusions

These results demonstrate that low-burden PGHD can be the basis of accurate and timely warnings that an individual’s mental health may be deteriorating. We hope this work will serve as a basis for improved engagement and treatment of individuals experiencing depression.

Depression with atypical neurovegetative symptoms shares genetic predisposition with immuno-metabolic traits and alcohol consumption

BACKGROUND

Depression is a highly prevalent and heterogeneous disorder. This study aims to determine whether depression with atypical features shows different heritability and different degree of overlap with polygenic risk for psychiatric and immuno-metabolic traits than other depression subgroups.

METHODS

Data included 30 069 European ancestry individuals from the UK Biobank who met criteria for lifetime major depression. Participants reporting both weight gain and hypersomnia were classified as ↑WS depression (N = 1854) and the others as non-↑WS depression (N = 28 215). Cases with non-↑WS depression were further classified as ↓WS depression (i.e. weight loss and insomnia; N = 10 142). Polygenic risk scores (PRS) for 22 traits were generated using genome-wide summary statistics (Bonferroni corrected p = 2.1 × 10-4). Single-nucleotide polymorphism (SNP)-based heritability of depression subgroups was estimated.

RESULTS

↑WS depression had a higher polygenic risk for BMI [OR = 1.20 (1.15-1.26), p = 2.37 × 10-14] and C-reactive protein [OR = 1.11 (1.06-1.17), p = 8.86 × 10-06] v. non-↑WS depression and ↓WS depression. Leptin PRS was close to the significance threshold (p = 2.99 × 10-04), but the effect disappeared when considering GWAS summary statistics of leptin adjusted for BMI. PRS for daily alcohol use was inversely associated with ↑WS depression [OR = 0.88 (0.83-0.93), p = 1.04 × 10-05] v. non-↑WS depression. SNP-based heritability was not significantly different between ↑WS depression and ↓WS depression (14.3% and 12.2%, respectively).

CONCLUSIONS

↑WS depression shows evidence of distinct genetic predisposition to immune-metabolic traits and alcohol consumption. These genetic signals suggest that biological targets including immune-cardio-metabolic pathways may be relevant to therapies in individuals with ↑WS depression.

Associations between the Willingness to Donate Samples to Biobanks and Selected Psychological Variables

Over the past few decades, there has been a dynamic development of biobanks collecting human biological material and data. Advances in biomedical research based on biobanks, however, are highly dependent on the successful enrolment and participation of human subjects. Therefore, it is crucial to recognise those factors affecting the willingness of individuals to participate in biomedical research. There are very few studies pointing to the role of trust, preferred values and specific psychological factors. The aim of our study was the analysis of the most significant relationships between selected moral and psychological variables (i.e., preferred values, types of trust and personality) and willingness to donate biological material to biobanks. The research was carried out on a Polish representative national sample of 1100 people over 18 years of age. Statistical methods with regression models were used during the analyses. The willingness to donate samples to a biobank was associated with different types of trust and specific values. Based on regression analysis, the most important factors related to the willingness to donate material to biobanks seemed to be (1) trust towards scientists and doctors and (2) selected preferred values such as knowledge, self-development and tradition. Other values or personality traits did not seem to be as important in this context. The obtained results can be useful in building the social responsibility of biobankers and scientists, issuing more appropriate opinions by research ethics committees and planning better communication strategies between participants and biobanks.

Mood and anxiety profiles differentially associate with physical conditions in US adolescents

BACKGROUND

Mood and anxiety are widely associated with physical conditions, but research and treatment are complicated by their overlap, clinical heterogeneity, and manifestation on a spectrum rather than as discrete disorders. In contrast to previous work relying on threshold-level disorders, we examined the association between empirically-derived profiles of mood and anxiety syndromes with physical conditions in a nationally-representative sample of US adolescents.

METHODS

Participants were 2,911 adolescents (aged 13-18) from the National Comorbidity Survey-Adolescent Supplement who provided information on physical conditions and reported at least one lifetime mood-anxiety 'syndrome' based on direct interviews with the Composite International Diagnostic Interview Version 3.0. Mood-anxiety syndromes reflected 3-level ratings from subthreshold to severe distress/impairment, and subtyped mood episodes. Stepwise latent profile analysis identified mood-anxiety profiles and tested associations with physical conditions.

RESULTS

Three mood-anxiety profiles were identified: "Mood-GAD" (25.6%)-non-atypical depression, mania, generalized anxiety; "Atypical-Panic" (11.3%)-atypical depression, panic; and "Reference" (63.1%)-lower mood and anxiety except specific phobia. Headaches were more prevalent in Mood-GAD and Atypical-Panic than Reference (47.9%, 50.1%, and 37.7%, respectively; p=0.011). Heart problems were more common in Mood-GAD than Atypical-Panic (7.4% v 2.2%, p=0.004) and Reference, with back/neck pain more prevalent in Mood-GAD than Reference (22.5% v 15.3%, p=0.016).

LIMITATIONS

Broad categories of physical conditions without information on specific diagnoses; replication regarding specificity is recommended.

CONCLUSIONS

Heart problems and pain-related conditions were differentially associated with specific mood-anxiety profiles. Subtyping depression and anxiety-inclusive of subthreshold syndromes-and their patterns of clustering may facilitate etiologic and intervention work in multimorbidity.

Insulin resistance as a marker for the immune-metabolic subtype of depression

OBJECTIVE

Insulin resistance (IR), a marker of metabolic dysregulation and pro-inflammatory state, moderates the antidepressant treatment effect in patients with type 2 diabetes (T2D) and is therefore a potential marker for personalized treatment. Based on data from a light therapy trial (NTR4942), we aimed to evaluate whether 1) depression symptoms differ according to the level of IR, and 2) improvement of specific depression symptoms drive the positive effects of light therapy in those with higher IR.

METHODS

This secondary analysis in 59 individuals with depression and T2D explored differences in depressive symptom profile (30-item Inventory of Depressive Symptomatology (IDS)) at baseline and in response to light therapy (versus placebo), between lower and higher IR individuals, using Likelihood Ratio tests and Linear-by-linear association. IR was measured using the gold standard, a hyperinsulinemic-euglycaemic clamp.

RESULTS

At baseline, higher IR individuals reported more symptoms of irritability (p=0.024) anhedonia (no interest in people and activities: p=0.011; absence of pleasure and enjoyment: p=0.021), fatigue (fatigue: p=0.036; physical fatigue: p=0.035) and hypersomnia (p=0.029) relative to persons with lower IR, who reported more insomnia (nightly awakening: p=0.041; early morning awakening: p=0.012). Light therapy led to an improvement across IDS symptoms in higher IR individuals, while in lower IR individuals, light therapy improved early morning awakening (p=0.005) and interest in people and activities (p=0.015), but worsened mood (feeling sad: p=0.001; feeling irritable: p=0.002; interpersonal sensitivity: p=0.014).

CONCLUSIONS

Results add to the hypothesis of an immune-metabolic subtype of depression, and suggest that IR might be a promising focus for precision medicine.

Higher adiposity and mental health: causal inference using Mendelian randomization

Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one- and two- sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß: -0.15, 95%CI: -0.26, -0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being.

Vitamin D and the risk of treatment-resistant and atypical depression: A Mendelian randomization study

Observational evidence has implicated vitamin D levels as a risk factor in major depressive disorder (MDD). Confounding or reverse causation may be driving these observed associations, with studies using genetics indicating little evidence of an effect. However, genetic studies have relied on broad definitions of depression. The genetic architecture of different depression subtypes may vary since MDD is a highly heterogenous condition, implying potentially diverging requirements in therapeutic approaches. We explored the associations between vitamin D and two subtypes of MDD, for which evidence of a causal link could have the greatest clinical benefits: treatment-resistant depression (TRD) and atypical depression (AD). We used a dual approach, combining observational data with genetic evidence from polygenic risk scores (PRS) and two-sample Mendelian randomization (MR), in the UK Biobank. There was some evidence of a weak association between vitamin D and both incident TRD (Ncases = 830) and AD (Ncases = 2366) in observational analyses, which largely attenuated when adjusting for confounders. Genetic evidence from PRS and two-sample MR, did not support a causal link between vitamin D and either TRD (Ncases = 1891, OR = 1.01 [95%CI 0.78, 1.31]) or AD (Ncases = 2101, OR = 1.04 [95%CI 0.80, 1.36]). Our comprehensive investigations indicated some evidence of an association between vitamin D and TRD/AD observationally, but little evidence of association when using PRS and MR, mirroring findings of genetic studies of vitamin D on broad depression phenotypes. Results do not support further clinical trials of vitamin D in these MDD subtypes but do not rule out that small effects may exist that require larger samples to detect.

Identification of risk groups for mental disorders, headache and oral behaviors in adults during the COVID-19 pandemic

The dramatically changing situation during COVID-19 pandemic, is anticipated to provoke psycho-emotional disturbances and somatization arising from the current epidemiological situation that will become a significant problem for global and regional healthcare systems. The aim of this study was to identify the predictors, risk factors and factors associated with mental disorders, headache and potentially stress-modulated parafunctional oral behaviors among the adult residents of North America and Europe as indirect health effects of the COVID-19 pandemic. This may help limit the long-term effects of this and future global pandemic crises. The data were collected from 1642 respondents using an online survey. The results demonstrated increased levels of anxiety, depression, headache and parafunctional oral behaviors during the COVID-19 pandemic in both North American and European residents. The results of this study facilitated the definition of the group most predicted to experience the aforementioned secondary effects of the pandemic. This group included females younger than 28.5 years old, especially those who were single, less well educated and living in Europe. In case of this and other global crises this will allow faster defining the most vulnerable groups and providing rapid and more targeted intervention.

Sexual and physical abuse and depressive symptoms in the UK Biobank

BACKGROUND

The association between sexual and physical abuse and subsequent depression is well-established, but the associations with specific depressive symptoms and sex differences remain relatively understudied. We investigated the associations of sexual and physical abuse with depressive symptoms in men and women in a large population cohort.

METHODS

Observational study based on 151,396 UK Biobank participants. Exposures included self-reported experiences of childhood physical abuse and sexual abuse. Mid-life outcomes included current depressive symptoms score, individual depressive symptoms, and lifetime depression. We used logistic regression to test associations of childhood sexual/physical abuse with depressive outcomes.

RESULTS

Recalled childhood sexual and physical abuse were both associated with current depressive symptoms score in adults. Results for individual symptoms-based analyses suggest that sexual and physical abuse are associated with all depressive symptoms, particularly suicidal behaviours. The associations between lifetime depression and sexual/physical abuse were not fully explained by current depressive symptoms score, indicating that these findings may not be fully attributable to recall bias. There was no indication of differential risk for specific depressive symptoms among men and women.

CONCLUSIONS

Sexual and physical abuse are robust risk factors for depression/depressive symptoms regardless of sex. Higher risk of suicidal behaviours associated with childhood sexual/physical abuse are of particular concern. Longitudinal research into sex-specific associations for individual depressive symptoms is required.

Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study

BACKGROUND

Sleep problems tend to vary according to the course of the disorder in individuals with mental health problems. Research in mental health has associated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography (PSG), is not suitable for long-term, continuous monitoring of daily sleep, and methods such as sleep diaries rely on subjective recall, which is qualitative and inaccurate. Wearable devices, on the other hand, provide a low-cost and convenient means to monitor sleep in home settings.

OBJECTIVE

The main aim of this study was to devise and extract sleep features from data collected using a wearable device and analyze their associations with depressive symptom severity and sleep quality as measured by the self-assessed Patient Health Questionnaire 8-item (PHQ-8).

METHODS

Daily sleep data were collected passively by Fitbit wristband devices, and depressive symptom severity was self-reported every 2 weeks by the PHQ-8. The data used in this paper included 2812 PHQ-8 records from 368 participants recruited from 3 study sites in the Netherlands, Spain, and the United Kingdom. We extracted 18 sleep features from Fitbit data that describe participant sleep in the following 5 aspects: sleep architecture, sleep stability, sleep quality, insomnia, and hypersomnia. Linear mixed regression models were used to explore associations between sleep features and depressive symptom severity. The z score was used to evaluate the significance of the coefficient of each feature.

RESULTS

We tested our models on the entire dataset and separately on the data of 3 different study sites. We identified 14 sleep features that were significantly (P<.05) associated with the PHQ-8 score on the entire dataset, among them awake time percentage (z=5.45, P<.001), awakening times (z=5.53, P<.001), insomnia (z=4.55, P<.001), mean sleep offset time (z=6.19, P<.001), and hypersomnia (z=5.30, P<.001) were the top 5 features ranked by z score statistics. Associations between sleep features and PHQ-8 scores varied across different sites, possibly due to differences in the populations. We observed that many of our findings were consistent with previous studies, which used other measurements to assess sleep, such as PSG and sleep questionnaires.

CONCLUSIONS

We demonstrated that several derived sleep features extracted from consumer wearable devices show potential for the remote measurement of sleep as biomarkers of depression in real-world settings. These findings may provide the basis for the development of clinical tools to passively monitor disease state and trajectory, with minimal burden on the participant.

The role of monoamine oxidase enzymes in the pathophysiology of neurological disorders

Monoamine oxidase enzymes are responsible for the degredation of serotonin, dopamine, and norepinephrine in the central neurvous system. Although it has been nearly 100 years since they were first described, we are still learning about their role in the healthy brain and how they are altered in various disease states. The present review provides a survey of our current understanding of monoamine oxidases, with a focus on their contributions to neuropsychiatric, neurodevelopmental, and neurodegenerative disease. Important species differences in monoamine oxidase function and development in the brain are highlighted. Sex-specific monoamine oxidase regulatory mechanisms and their implications for various neurological disorders are also discussed. While our understanding of these critical enzymes has expanded over the last century, gaps exist in our understanding of sex and species differences and the roles monoamine oxidases may play in conditions often comorbid with neurological disorders.

How to Utilize Clinical and Genetic Information for Personalized Treatment of Major Depressive Disorder: Step by Step Strategic Approach

Depression is the single largest contributor to non-fatal health loss and affects 322 million people globally. The clinical heterogeneity of this disorder shows biological correlates and it makes the personalization of antidepressant prescription an important pillar of treatment. There is increasing evidence of genetic overlap between depression, other psychiatric and non-psychiatric disorders, which varies across depression subtypes. Therefore, the first step of clinical evaluation should include a careful assessment of psychopathology and physical health, not limited to previously diagnosed disorders. In part of the patients indeed the pathogenesis of depression may be strictly linked to inflammatory and metabolic abnormalities, and the treatment should target these as much as the depressive symptoms themselves. When the evaluation of the symptom and drug tolerability profile, the concomitant biochemical abnormalities and physical conditions is not enough and at least one pharmacotherapy failed, the genotyping of variants in CYP2D6/CYP2C19 (cytochromes responsible for antidepressant metabolism) should be considered. Individuals with altered metabolism through one of these enzymes may benefit from some antidepressants rather than others or need dose adjustments. Finally, if available, the polygenic predisposition towards cardio-metabolic disorders can be integrated with non-genetic risk factors to tune the identification of patients who should avoid medications associated with this type of side effects. A sufficient knowledge of the polygenic risk of complex medical and psychiatric conditions is becoming relevant as this information can be obtained through direct-to-consumer genetic tests and in the future it may provided by national health care systems.

Depression Heterogeneity and Its Biological Underpinnings: Toward Immunometabolic Depression

Epidemiological evidence indicates the presence of dysregulated homeostatic biological pathways in depressed patients, such as increased inflammation and disrupted energy-regulating neuroendocrine signaling (e.g., leptin, insulin). Alterations in these biological pathways may explain the considerable comorbidity between depression and cardiometabolic conditions (e.g., obesity, metabolic syndrome, diabetes) and represent a promising target for intervention. This review describes how immunometabolic dysregulations vary as a function of depression heterogeneity by illustrating that such biological dysregulations map more consistently to atypical behavioral symptoms reflecting altered energy intake/expenditure balance (hyperphagia, weight gain, hypersomnia, fatigue, and leaden paralysis) and may moderate the antidepressant effects of standard or novel (e.g., anti-inflammatory) therapeutic approaches. These lines of evidence are integrated in a conceptual model of immunometabolic depression emerging from the clustering of immunometabolic biological dysregulations and specific behavioral symptoms. The review finally elicits questions to be answered by future research and describes how the immunometabolic depression dimension could be used to dissect the heterogeneity of depression and potentially to match subgroups of patients to specific treatments with higher likelihood of clinical success.

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.

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.

Mental health in UK Biobank - development, implementation and results from an online questionnaire completed by 157 366 participants: a reanalysis

BACKGROUND

UK Biobank is a well-characterised cohort of over 500 000 participants including genetics, environmental data and imaging. An online mental health questionnaire was designed for UK Biobank participants to expand its potential.

AIMS

Describe the development, implementation and results of this questionnaire.

METHOD

An expert working group designed the questionnaire, using established measures where possible, and consulting a patient group. Operational criteria were agreed for defining likely disorder and risk states, including lifetime depression, mania/hypomania, generalised anxiety disorder, unusual experiences and self-harm, and current post-traumatic stress and hazardous/harmful alcohol use.

RESULTS

A total of 157 366 completed online questionnaires were available by August 2017. Participants were aged 45-82 (53% were ≥65 years) and 57% women. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status. Lifetime depression was a common finding, with 24% (37 434) of participants meeting criteria and current hazardous/harmful alcohol use criteria were met by 21% (32 602), whereas other criteria were met by less than 8% of the participants. There was extensive comorbidity among the syndromes. Mental disorders were associated with a high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation.

CONCLUSIONS

The UK Biobank questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed because of selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.

Non-melancholic depressive symptoms increase risk for incident cardiovascular disease: A prospective study in a primary care population at risk for cardiovascular disease and type 2 diabetes

OBJECTIVE

To assess subtypes of depressive symptoms and their relationship with cardiovascular disease (CVD) morbidity among CVD risk persons.

METHODS

A prospective study of 2522 CVD risk persons was conducted. Non-melancholic and melancholic depressive symptoms were assessed by Beck's Depression Inventory. Data on incident CVD was gathered from a national register, after 8 years of follow-up.

RESULTS

At baseline, the prevalence of non-melancholic and melancholic depressive symptoms was 14.9% and 5.2%, respectively. A total of 18,413 person-years was followed up, and the incidence of CVD was 9.6% in non-depressive, 14.1% in non-melancholically depressive, and 13.0% in melancholically depressive subjects. When adjusted for age, gender, education, smoking, alcohol use, leisure-time physical activity, hypertension, and dyslipidemia, the incidence rate ratios (IRR) for CVD in subjects with non-melancholic and melancholic depressive symptoms compared to non-depressiveness were IRR 1.69 (95% CI: 1.23-2.31) and IRR 1.31 (95% CI: 0.75-2.26).

CONCLUSION

Non-melancholic depressive symptoms seem to increase risk for incident CVD among CVD risk subjects. Considering non-melancholic depressive symptoms might be useful when treating subjects with other CVD risk factors.

Gender Differences in Dysfunctional Attitudes in Major Depressive Disorder

BACKGROUND

Dysfunctional attitudes play a key role in the development and prognosis of depression. Gender also plays an important role in many clinical features of major depressive disorder (MDD). This study is aimed at investigating the gender differences in dysfunctional attitudes in patients with MDD.

METHODS

One hundred and seventy-two patients with MDD and 159 healthy controls (HCs) were enrolled in this study. Dysfunctional attitudes were assessed by the Chinese version of the dysfunctional attitude scale-form A (C-DAS-A) and depression severity was assessed by the 24-item Hamilton rating scale for depression (HAMD₂₄). The 14-item Hamilton Anxiety Rating Scale (HAMA₁₄) was used to measure anxiety. Factorial analysis of variance (ANOVA) of gender and diagnosis on C-DAS-A total and factor scores was adopted with age, education, and body mass index (BMI) controlled. Multiple linear regression analyses of DAS were performed in the MDD group.

RESULTS

First, the C-DAS-A score in the MDD group was increased significantly than HCs. Second, female patients with MDD showed significantly higher scores in C-DAS-A total and three-factor scores (seeking applause, dependence, and self-determination attitude), while no significant difference between female HCs and male HCs was detected. Third, five variables (age, gender, smoking history, HAMD₂₄, and HAMA₁₄) had predictive effects on and gender showed the greatest contributions to C-DAS-A total and three-factor scores (seeking applause, dependence, and self-determination attitude).

CONCLUSION

Females with MDD may be linked to more severe cognitive distortion than their male counterparts in seeking applause, dependence, and self-determination attitude, supporting the reasonableness for gender-specific psychosocial interventions.