Associations between systemic inflammation and somatic depressive symptoms: Findings from the Moli-sani study

Association of perceived mental health with mortality, and analysis of potential pathways in Italian men and women: Prospective results from the Moli-sani Study cohort

BACKGROUND

Perceived mental health (PMH) was reportedly associated with mortality in general populations worldwide. However, little is known about sex differences and pathways potentially linking PMH to mortality. We explored the relationship between PMH and mortality in Italian men and women, and analysed potential explanatory factors.

METHODS

We performed longitudinal analyses on 9045 men and 9467 women (population mean age 53.8 ± 11.2 years) from the Moli-sani Study. Baseline PMH was assessed through a self-administered Short Form 36-item questionnaire. Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95 % confidence intervals (95%CI) of death across sex-specific quartiles of PMH, controlling for age, chronic health conditions, and perceived physical health. Socioeconomic, behavioural, and physiological factors were examined as potential explanatory factors of the association between PMH and mortality.

RESULTS

In women, HRs for the highest (Q4) vs. bottom quartile (Q1) of PMH were 0.75 (95%CI 0.60-0.96) for all-cause mortality and 0.59 (0.40-0.88) for cardiovascular mortality. Part of these associations (25.8 % and 15.7 %, for all-cause and cardiovascular mortality, respectively) was explained by physiological factors. In men, higher PMH was associated with higher survival (HR = 0.82; 0.69-0.98, for Q4 vs. Q1) and reduced hazard of other cause mortality (HR = 0.67; 0.48-0.95). More than half of the association with all-cause mortality was explained by physiological factors.

LIMITATIONS

PMH was measured at baseline only.

CONCLUSIONS

PMH was independently associated with mortality in men and women. Public health policies aimed at reducing the burden of chronic diseases should prioritize perceived mental health assessment along with other interventions.

Chronic Low-Grade Inflammation and Brain Structure in the Middle-Aged and Elderly Adults

Low-grade inflammation (LGI) mainly acted as the mediator of the association of obesity and inflammatory diet with numerous chronic diseases, including neuropsychiatric diseases. However, the evidence about the effect of LGI on brain structure is limited but important, especially in the context of accelerating aging. This study was then designed to close the gap, and we leveraged a total of 37,699 participants from the UK Biobank and utilized inflammation score (INFLA-score) to measure LGI. We built the longitudinal relationships of INFLA-score with brain imaging phenotypes using multiple linear regression models. We further analyzed the interactive effects of specific covariates. The results showed high level inflammation reduced the volumes of the subcortex and cortex, especially the globus pallidus (β [95% confidence interval] = -0.062 [-0.083, -0.041]), thalamus (-0.053 [-0.073, -0.033]), insula (-0.052 [-0.072, -0.032]), superior temporal gyrus (-0.049 [-0.069, -0.028]), lateral orbitofrontal cortex (-0.047 [-0.068, -0.027]), and others. Most significant effects were observed among urban residents. Furthermore, males and individuals with physical frailty were susceptive to the associations. The study provided potential insights into pathological changes during disease progression and might aid in the development of preventive and control targets in an age-friendly city to promote great health and well-being for sustainable development goals.

The association of circulating systemic inflammation with premature death and the protective role of the Mediterranean diet: a large prospective cohort study of UK biobank

BACKGROUND

Although previous studies have identified specific circulating inflammatory markers associated with the risk of mortality, they have often overlooked the broader impact of a comprehensive inflammatory response on health outcomes. This study aims to assess the association between circulating systemic inflammation and age-related hospitalization and premature death, as well as explore the potential mediating effects of various dietary patterns on these associations.

METHODS

A total of 448,574 participants enrolled in the UK Biobank study were included. Circulating C-reactive protein(CRP), white blood cell count(WBC), platelet count(Plt), and neutrophil/lymphocyte ratio(NLR) were measured, which were used to establish a weighted systemic inflammatory index of inflammation index(INFLA-Score). Dietary intake information was documented through 24-hour dietary recalls, and dietary pattern scores including Dietary Approaches to Stop Hypertension(DASH), Mediterranean(MED), and Healthy Eating Index-2020(HEI-2020) were calculated. Cox proportional hazards regression models were performed to assess the associations between INFLA-Score and age-related disease hospitalization, cause-specific and all-cause premature death.

RESULTS

During a median follow-up of 12.65 years, 23,784 premature deaths were documented. After adjusting for multiple covariates, higher levels of CRP, WBC, NLR, and INFLA-Score were significantly associated with increased risks of age-related disease hospitalization(HRCRP=1.19; 95%:1.17-1.21; HRWBC=1.17; 95%:1.15-1.19; HRNLR=1.18; 95%:1.16-1.20; HRINFLA-Score=1.19; 95%:1.17-1.21) and premature death(HRCRP=1.68; 95%:1.61-1.75; HRWBC=1.23; 95%:1.18-1.27; HRNLR=1.45; 95%:1.40-1.50; HRINFLA-Score=1.58; 95%:1.52-1.64). Compared to the lowest INFLA-Score group, the highest INFLA-Score group was associated with increased values of whole-body and organ-specific biological age, and had a shortened life expectancy of 2.96 (95% CI 2.53-3.41) and 4.14 (95% CI 3.75-4.56) years at the age of 60 years in women and men, respectively. Additionally, we observed no significant association of the INFLA-Score with aging-related hospitalization and premature death among participants who were more adhering to the Mediterranean (MED) dietary pattern(HRAging-related hospitalization=1.07; 95%:0.99-1.16;HRPremature death=1.19; 95%:0.96-1.47).

CONCLUSION

A higher INFLA-Score was correlated with an increased risk of age-related hospitalization and premature death. Nevertheless, adherence to a Mediterranean (MED) diet may mitigate these associations.

The novel subtype of major depressive disorder characterized by somatic symptoms is associated with poor treatment efficacy and prognosis: A data-driven cluster analysis of a prospective cohort in China

BACKGROUND

There is not yet a valid and evidence-based system to classify patients with MDD into more homogeneous subtypes based on their clinical features. This study aims to identify symptom-based subtypes of MDD and investigate whether the treatment outcomes of those subtypes would be different.

METHOD

The cohort was established at 12 densely populated cities of China. A total of 1487 patients were enrolled. All participants were 18-65 years old and diagnosed with MDD. Participants were followed up at baseline, weeks 4, 8, and 12, and months 4 and 6. K-means algorithm was used to cluster patients with MDD according to clinical symptoms. The network analysis was adopted to characterize and compare the symptom patterns in the clusters. We also examined the associations between the clusters and the clinical outcomes.

RESULTS

The optimal number of the clusters was determined to be 2. Each cluster's maximum Jaccard Co-efficient was calculated to be >0.5 (cluster1 = 0.53, cluster 2 = 0.67). The symptom "depressed mood" and some other affective symptoms were the most prominent in cluster 1. Somatic symptoms, such as weight loss and general somatic symptoms, had the greatest expected influence in cluster 2. Compared with the response rates of the patients in the "somatic cluster", those of the patients in the "affective cluster" were significantly higher (P < 0.05).

CONCLUSIONS

Patients with MDD might be classified into two symptom-based subtypes featured with affective symptoms or somatic symptoms. The treatment efficacy and prognosis of the subtype featured with somatic symptoms may be worse.

Exploring the multiverse: the impact of researchers' analytic decisions on relationships between depression and inflammatory markers

In recent years, a replication crisis in psychiatry has led to a growing focus on the impact of researchers' analytic decisions on the results from studies. Multiverse analyses involve examining results across a wide array of possible analytic decisions (e.g., log-transforming variables, number of covariates, or treatment of outliers) and identifying if study results are robust to researchers' analytic decisions. Studies have begun to use multiverse analysis for well-studied relationships that have some heterogeneity in results/conclusions across studies.We examine the well-studied relationship between peripheral inflammatory markers (PIMs; e.g., white blood cell count (WBC) and C-reactive protein (CRP)) and depression severity in the large NHANES dataset (n = 25,962). Specification curve analyses tested the impact of 9 common analytic decisions (comprising of 58,000+ possible combinations) on the association of PIMs and depression severity. Relationships of PIMs and total depression severity are robust to analytic decisions (based on tests of inference jointly examining effect sizes and p-values). However, moderate/large differences are noted in effect sizes based on analytic decisions and the majority of analyses do not result in significant findings, with the percentage of analyses with statistically significant results being 46.1% for WBC and 43.8% for CRP. For associations of PIMs with specific symptoms of depression, some associations (e.g., sleep, appetite) in males (but not females) were robust to analytic decisions. We discuss how multiverse analyses can be used to guide research and also the need for authors, reviewers, and editors to incorporate multiverse analyses to enhance replicability of research findings.

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

BACKGROUND

Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis.

METHODS

Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve.

RESULTS

From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients.

CONCLUSIONS

This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

Associations of white blood cell and platelet counts with specific depressive symptom dimensions in patients with bipolar disorder: Analysis of data from the FACE-BD cohort

Evidences suggest that inflammation is increased in a subgroup of patients with depression. Moreover, increased peripheral inflammatory markers (cells and proteins) are associated with some, but not all depressive symptoms. On the other hand, similar studies on bipolar disorders mainly focused on blood cytokines. Here, we analysed data from a large (N = 3440), well-characterized cohort of individuals with bipolar disorder using Kendall partial rank correlation, multivariate linear regression, and network analyses to determine whether peripheral blood cell counts are associated with depression severity, its symptoms, and dimensions. Based on the self-reported 16-Item Quick Inventory of Depressive Symptomatology questionnaire scores, we preselected symptom dimensions based on literature and data-driven principal component analysis. We found that the counts of all blood cell types were only marginally associated with depression severity. Conversely, white blood cell count was significantly associated with the sickness dimension and its four components (anhedonia, slowing down, fatigue, and appetite loss). Platelet count was associated with the insomnia/restlessness dimension and its components (initial, middle, late insomnia and restlessness). Principal component analyses corroborated these results. Platelet count was also associated with suicidal ideation. In analyses stratified by sex, the white blood cell count-sickness dimension association remained significant only in men, and the platelet count-insomnia/restlessness dimension association only in women. Without implying causation, these results suggest that peripheral blood cell counts might be associated with different depressive symptoms in individuals with bipolar disorder, and that white blood cells might be implicated in sickness symptoms and platelets in insomnia/agitation and suicidal ideation.

Role of leukocytes, gender, and symptom domains in the influence of depression on hospitalization and mortality risk: Findings from the Moli-sani study

Background

Major depressive disorder is a mental illness associated with chronic conditions like cardiovascular disease (CVD). Circulating inflammation has been proposed as a potential mechanism underlying this link, although the role of specific biomarkers, gender, and symptom domains is not well elucidated.

Methods

We performed multivariable Cox regressions of first hospitalization/all-cause mortality and CVD, ischemic heart (IHD), and cerebrovascular disease (CeVD) causes vs. depression severity in an Italian population cohort (N = 13,191; age ≥ 35 years; 49.3% men; 4,856 hospitalizations and 471 deaths, median follow-up 7.28 and 8.24 years, respectively). In models adjusted for age, sex, and socioeconomic status, we estimated the proportion of association explained by C-reactive protein (CRP), platelet count, granulocyte-to-lymphocyte ratio (GLR), and white blood cell count (WBC). Gender-by-depression interaction and gender-stratified analyses were performed. Associations of polychoric factors tagging somatic and cognitive symptoms with incident clinical risks were also tested, as well as the proportion explained by a composite index of circulating inflammation (INFLA score).

Results

Significant proportions of the influence of depression on clinical risks were explained by CRP (4.8% on IHD hospitalizations), GLR (11% on all-cause mortality), and WBC (24% on IHD/CeVD hospitalizations). Gender-by-depression interaction was significantly associated only with all-cause mortality (p = 0.03), with moderate depression showing a + 60% increased risk in women, but not in men. Stable associations of somatic, but not of cognitive, symptoms with increased hospitalization risk were observed (+ 16% for all causes, + 14% for CVD causes), with INFLA score explaining small but significant proportions of these associations (2.5% for all causes, 8.6% for IHD causes).

Conclusions

These findings highlight the importance of cellular components of inflammation, gender, and somatic depressive symptoms in the link between depression and clinical (especially CVD) risks, pointing to the existence of additional pathways through which depression may play a detrimental effect on the cardiovascular system.

Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles

Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inflammatory profiles (C-reactive protein (CRP), Interleukin (IL)-6, and tumor necrosis factor (TNF) - α) could be used to differentiate symptom clusters. Six distinct clusters were identified that differed significantly on symptom dimensions including somatic anxiety, general anxiety, anhedonia, and neurovegetative depression. Moreover, the neurovegetative depression cluster displayed significantly elevated CRP levels compared to other clusters. In fact, inflammation was not strongly associated with overall depression scores or severity, but rather related to specific features of depression marked by eating, appetite, and tiredness. This study emphasizes the importance of characterizing the biological underpinnings of symptom dimensions and subtypes to better understand the etiology of complex mental health disorders such as depression.

Identifying the Subtypes of Major Depressive Disorder Based on Somatic Symptoms: A Longitudinal Study Using Latent Profile Analysis

BACKGROUND

Two-thirds of major depressive disorder (MDD) patients initially present with somatic symptoms, yet no study has used approaches based on somatic symptoms to subtype MDD. This study aimed to classify MDD via somatic symptoms and tracked the prognosis of each subtype.

METHODS

Data were obtained from the study of Algorithm Guided Treatment Strategies for Major Depressive Disorder (AGTs-MDD). We recruited 395 subjects who received monotherapy of mirtazapine or escitalopram and conducted 2-, 4-, 6-, 8-, and 12-week follow-up assessments (n = 311, 278, 251, 199, and 178, respectively). Latent profile analysis (LPA) was performed on somatic symptom items of the depression and somatic symptoms scale (DSSS). Generalized linear mixed models (GLMM) were used to study the longitudinal prognosis of the subtypes classed by LPA. Primary outcome measures were the Hamilton Depression Rating Scale (HAMD), HAMD score reduction rate, as well as somatic and depressive items of DSSS.

RESULTS

Three subtypes of MDD were found, namely, depression with mild somatic symptoms (68.9%), depression with moderate somatic symptoms (19.2%), and depression with severe somatic symptoms (11.9%). Scores of HAMD (F = 3.175, p = 0.001), somatic (F = 23.594, p < 0.001), and depressive (F = 4.163, p < 0.001) DSSS items throughout the 12-week follow-up showed statistical difference among the three subtypes. The moderate group displayed a higher HAMD-17 score and a lower reduction rate at the 6th week, and more severe depressive symptoms both at the 4th and 6th weeks.

CONCLUSION

The results indicate that somatic symptoms should be emphasized in patients with MDD, and more attention is needed for those with moderate somatic symptoms, which may be relevant to a worse prognosis.

Circulating Inflammation Markers Partly Explain the Link Between the Dietary Inflammatory Index and Depressive Symptoms

BACKGROUND

Depression is a mood disorder characterized by a high rate of resistance to pharmacological treatments, which has often been linked to chronic inflammation. This can be influenced by different environmental factors, in particular pro-inflammatory diets. However, a mediating role of circulating inflammation has never been observed.

AIM

To test the association between a dietary inflammatory index (DII®) and continuous depressive symptoms (adapted version of PHQ9) in an Italian population cohort (N=13,301), along with potential explanatory effect of a composite index (INFLA-score) based on four circulating inflammatory biomarkers: C-reactive protein, granulocyte-to-lymphocyte ratio, platelet and white blood cell counts.

RESULTS

Significant positive associations were observed between DII and total depressive symptoms (standardized β (SE) = 0.038 (0.005), p < 0.001), and with two factors tagging somatic (0.012 (0.003), p < 0.001) and cognitive symptoms (0.012 (0.003), p < 0.001), after adjustment for different potential confounders (socioeconomic status, chronic health conditions and lifestyles). These associations were about twice as strong in women than in men. INFLA-score explained a small but significant proportion of the association with total depressive symptoms (0.90-2.30%, p < 0.05), which was mainly driven by granulocyte-to-lymphocyte ratio (1.18-1.65%). This effect was even stronger for the somatic (2.66-4.66%) but not for the cognitive factor (0%).

CONCLUSION

These findings support a strong link between inflammatory diet and depression, especially with somatic symptoms and within women. Moreover, they provide novel evidence for a potential explanatory role of circulating inflammation in this association, suggesting new paths for prevention and treatment of major and atypical depression.