Contributions of specific causes of death by age to the shorter life expectancy in depression: a register-based observational study from Denmark, Finland, Sweden and Italy

Integrating brain imaging features and genomic profiles for the subtyping of major depression

BACKGROUND

Precise stratification of patients into homogeneous disease subgroups could address the heterogeneity of phenotypes and enhance understanding of the pathophysiology underlying specific subtypes. Existing literature on subtyping patients with major depressive disorder (MDD) mainly utilized clinical features only. Genomic and imaging data may improve subtyping, but advanced methods are required due to the high dimensionality of features.

METHODS

We propose a novel disease subtyping framework for MDD by integrating brain structural features, genotype-predicted expression levels in brain tissues, and clinical features. Using a multi-view biclustering approach, we classify patients into clinically and biologically homogeneous subgroups. Additionally, we propose approaches to identify causally relevant genes for clustering.

RESULTS

We verified the reliability of the subtyping model by internal and external validation. High prediction strengths (PS) (average PS: 0.896, minimum: 0.854), a measure of generalizability of the derived clusters in independent datasets, support the validity of our approach. External validation using patient outcome variables (treatment response and hospitalization risks) confirmed the clinical relevance of the identified subgroups. Furthermore, subtype-defining genes overlapped with known susceptibility genes for MDD and were involved in relevant biological pathways. In addition, drug repositioning analysis based on these genes prioritized promising candidates for subtype-specific treatments.

CONCLUSIONS

Our approach successfully stratified MDD patients into subgroups with distinct clinical prognoses. The identification of biologically and clinically meaningful subtypes may enable more personalized treatment strategies. This study also provides a framework for disease subtyping that can be extended to other complex disorders.

Gut microbiome in atypical depression

BACKGROUND

Recent studies showed that immunometabolic dysregulation is related to unipolar major depressive disorder (MDD) and that it more consistently maps to MDD patients endorsing an atypical symptom profile, characterized by energy-related symptoms including increased appetite, weight gain, and hypersomnia. Despite the documented influence of the microbiome on immune regulation and energy homeostasis, studies have not yet investigated microbiome differences among clinical groups in individuals with MDD.

METHODS

Fifteen MDD patients with atypical features according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5)-5, forty-four MDD patients not fulfilling the DSM-5 criteria for the atypical subtype, and nineteen healthy controls were included in the study. Participants completed detailed clinical assessment and stool samples were collected. Samples were sequenced for the prokaryotic 16S rRNA gene, in the V3-V4 variable regions. Only samples with no antibiotic exposure in the previous 12 months and a minimum of >2000 quality-filtered reads were included in the analyses.

RESULTS

There were no statistically significant differences in alpha- and beta-diversity between the MDD groups and healthy controls. However, within the atypical MDD group, there was an increase in the Verrucomicrobiota phylum, with Akkermansia as the predominant bacterial genus.

LIMITATIONS

Cross-sectional data, modest sample size, and significantly increased body mass index in the atypical MDD group.

CONCLUSIONS

There were no overall differences among the investigated groups. However, differences were found at several taxonomic levels. Studies in larger longitudinal samples with relevant confounders are needed to advance the understanding of the microbial influences on the clinical heterogeneity of depression.

Severe depression and all-cause and cause-specific mortality in Scotland: 20 year national cohort study

BACKGROUND

Understanding cause of death in people with depression could inform approaches to reducing premature mortality.

AIM

To describe all-cause and cause-specific mortality for people with severe depression in Scotland, by sex, relative to the general population.

METHOD

We performed a retrospective cohort study, using psychiatric hospital admission data linked to death data, to identify adults (≥18 years old) with severe depression and ascertain cause-specific deaths, during 2000-2019. We estimated relative all-cause and cause-specific mortality for people with severe depression using standardised mortality ratios (SMRs), stratified by sex using the whole Scottish population as the standard.

RESULTS

Of 28 808 people with severe depression, 7903 (27.4%) died during a median follow-up of 8.7 years. All-cause relative mortality was over three times higher than expected (SMR, both sexes combined: 3.26, 95% CI 3.19-3.34). Circulatory disease was the leading cause of death, and, among natural causes of death, excess relative mortality was highest for circulatory diseases (SMR 2.51, 2.40-2.66), respiratory diseases (SMR 3.79, 3.56-4.01) and 'other' causes (SMR 4.10, 3.89-4.30). Among circulatory disease subtypes, excess death was highest for cerebrovascular disease. Both males and females with severe depression had higher all-cause and cause-specific mortality than the general population. Suicide had the highest SMR among both males (SMR 12.44, 95% CI 11.33-13.54) and females (22.86, 95% CI 20.35-25.36).

CONCLUSION

People with severe depression have markedly higher all-cause mortality than the general population in Scotland, with relative mortality varying by cause of death. Effective interventions are needed to reduce premature mortality for people with severe depression.

Life expectancy and years of potential life lost in people with mental disorders: a systematic review and meta-analysis

Background

Mental disorders are associated with premature mortality. There is increasing research examining life expectancy and years-of-potential-life-lost (YPLL) to quantify the disease impact on survival in people with mental disorders. We aimed to systematically synthesize studies to estimate life expectancy and YPLL in people with any and specific mental disorders across a broad spectrum of diagnoses.

Methods

In this systematic review and meta-analysis, we searched Embase, MEDLINE, PsychINFO, WOS from inception to July 31, 2023, for published studies reporting life expectancy and/or YPLL for mental disorders. Criteria for study inclusion were: patients of all ages with any mental disorders; reported data on life expectancy and/or YPLL of a mental-disorder cohort relative to the general population or a comparison group without mental disorders; and cohort studies. We excluded non-cohort studies, publications containing non-peer-reviewed data or those restricted to population subgroups. Survival estimates, i.e., life expectancy and YPLL, were pooled (based on summary data extracted from the included studies) using random-effects models. Subgroup analyses and random-effects meta-regression analyses were performed to explore sources of heterogeneity. Risk-of-bias assessment was evaluated using the Newcastle-Ottawa Scale. This study is registered with PROSPERO (CRD42022321190).

Findings

Of 35,865 studies identified in our research, 109 studies from 24 countries or regions including 12,171,909 patients with mental disorders were eligible for analysis (54 for life expectancy and 109 for YPLL). Pooled life expectancy for mental disorders was 63.85 years (95% CI 62.63-65.06; I2 = 100.0%), and pooled YPLL was 14.66 years (95% CI 13.88-15.98; I2 = 100.0%). Disorder-stratified analyses revealed that substance-use disorders had the shortest life expectancy (57.07 years [95% CI 54.47-59.67]), while neurotic disorders had the longest lifespan (69.51 years [95% CI 67.26-71.76]). Substance-use disorders exhibited the greatest YPLL (20.38 years [95% CI 18.65-22.11]), followed by eating disorders (16.64 years [95% CI 7.45-25.82]), schizophrenia-spectrum disorders (15.37 years [95% CI 14.18-16.55]), and personality disorders (15.35 years [95% CI 12.80-17.89]). YPLLs attributable to natural and unnatural deaths in mental disorders were 4.38 years (95% CI 3.15-5.61) and 8.11 years (95% CI 6.10-10.13; suicide: 8.31 years [95% CI 6.43-10.19]), respectively. Stratified analyses by study period suggested that the longevity gap persisted over time. Significant cross-study heterogeneity was observed.

Interpretation

Mental disorders are associated with substantially reduced life expectancy, which is transdiagnostic in nature, encompassing a wide range of diagnoses. Implementation of comprehensive and multilevel intervention approaches is urgently needed to rectify lifespan inequalities for people with mental disorders.

Funding

None.

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.

Relationship between citizens' perspective on digital health and underlying health risks

Objective

Digital health has been gaining widespread attention but has not been fully integrated into the existing healthcare system. However, it remains unclear whether the new digital health solutions align with users' needs and wants. This study examines how citizens perceive the functionalities of digital health and how different health risks influence their perception.

Methods

Using an online survey, data are collected from over 4000 Danish citizens. The data are analysed using linear regression models.

Results

The results show how users' perceptions of digital health differ significantly. Users are highly interested in data sharing across different healthcare stakeholders but less interested in online health communities. The results also show that the support for digital health is correlated with various health risks, including age, smoking and social network. However, health risks do not have uniform relationship with the perceived value of digital health.

Conclusions

While developing and implementing new digital health solutions, it is important to consider the perceptions of people who are expected to benefit from such solutions. This study contributes to the literature by deepening the knowledge of how citizens with different risk profiles perceive the multitude of digital health tools being introduced in the healthcare sector.

Depression is associated with increased disease activity in patients with ulcerative colitis: A propensity score-matched analysis using a nationwide database in Japan

Background and Aim

The incidence and prevalence of psychiatric disorders are elevated in patients with inflammatory bowel disease (IBD). Whether psychiatric disorders could affect the clinical course of IBD is uncertain and controversial. We aimed to evaluate the impact of psychiatric disorders, particularly depression, on the clinical course of IBD using a nationwide database in Japan.

Methods

We collected data on admissions with IBD using the Diagnosis Procedure Combination database system introduced in Japan. We divided eligible admissions into IBD with and without depression groups using propensity score matching and compared the rates of surgery, use of molecular targeted drugs and biologics, systemic steroid administrations, and in-hospital death. We also conducted a logistic regression analysis to identify clinical factors affecting surgery, the use of molecular targeted drugs and biologics, and systemic steroid administrations.

Results

The rates of surgery, use of two or more molecular targeted drugs, systemic steroid administrations, and in-hospital deaths in the ulcerative colitis (UC) with depression group were higher than in the UC without depression group. Multivariate analysis of UC showed that depression increased the odds of systemic steroid administrations, use of two or more molecular targeted drugs, and surgery. However, analysis of Crohn's disease showed that only steroid administrations were associated with depression.

Conclusion

Our study demonstrated an association between a worse clinical course of UC and depression. Although this result indicates that depression might be associated with increased disease activity in patients with UC, the causal relationship is still unclear. Further prospective studies are warranted.

Association of depression with mortality in nationwide twins: The mediating role of dementia

BACKGROUND

The differential impact of depression across different periods in life on mortality remains inconclusive. We aimed to examine the association of depression that occurs at different age with all-cause mortality, and to explore the roles of dementia, as well as genetic and early-life environmental factors, in this association.

METHODS

From the Swedish Twin Registry, 44,919 twin individuals were followed for up to 18 years. Depression was ascertained using the National Patient Registry and categorized as early-life (<45 years), midlife (45-64 years), and late-life (≥65 years) depression according to the age of the first diagnosis. Deaths were identified through the Cause of Death Register. Generalized estimating equation, generalized structural equation, and conditional logistic regression were used for unmatched, mediation, and co-twin matched analyses, respectively.

RESULTS

In unmatched analyses, the multivariate-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of mortality were 1.71 (1.46-2.00) for depression at any age, 1.72 (1.36-2.17) for early-life, 1.51 (1.19-1.90) for midlife, and 4.10 (2.02-8.34) for late-life depression. Mortality was significantly higher in individuals with late-life depression than those with earlier-life depression (p < 0.05). The mediation analysis showed that 59.83% of the depression-mortality association was mediated by dementia. No significant difference in ORs between the unmatched and co-twin matched analyses was observed (p = 0.09).

CONCLUSIONS

Depression is associated with an increased risk of all-cause mortality, and dementia mediates approximately 60% of the impact of depression on mortality in late life. Genetic and early-life environmental factors may not play a significant role in the depression-mortality association.