Major depression disorder may causally associate with the increased breast cancer risk: Evidence from two-sample mendelian randomization analyses

Association between sleep duration, depression and breast cancer in the United States: a national health and nutrition examination survey analysis 2009-2018

OBJECTIVE

Breast cancer is the most common cancer in women, threatening both physical and mental health. The epidemiological evidence for association between sleep duration, depression and breast cancer is inconsistent. The aim of this study was to determine the association between them and build machine-learning algorithms to predict breast cancer.

METHODS

A total of 1,789 participants from the National Health and Nutrition Examination Survey (NHANES) were included in the study, and 263 breast cancer patients were identified. Sleep duration was collected using a standardized questionnaire, and the Nine-item Patient Health Questionnaire (PHQ-9) was used to assess depression. Logistic regression yielded multivariable-adjusted breast cancer odds ratios (OR) and 95% confidence intervals (CI) for sleep duration and depression. Then, six machine learning algorithms, including AdaBoost, random forest, Boost tree, artificial neural network, limit gradient enhancement and support vector machine, were used to predict the development of breast cancer and find out the best algorithm.

RESULTS

Body mass index (BMI), race and smoking were statistically different between breast cancer and non-breast cancer groups. Participants with depression were associated with breast cancer (OR = 1.99, 95%CI: 1.55-3.51). Compared with 7-9h of sleep, the ORs for <7 and >9 h of sleep were 1.25 (95% CI: 0.85-1.37) and 1.05 (95% CI: 0.95-1.15), respectively. The AdaBoost model outperformed other machine learning algorithms and predicted well for breast cancer, with an area under curve (AUC) of 0.84 (95%CI: 0.81-0.87).

CONCLUSIONS

No significant association was observed between sleep duration and breast cancer, and participants with depression were associated with an increased risk for breast cancer. This finding provides new clues into the relationship between breast cancer and depression and sleep duration, and provides potential evidence for subsequent studies of pathological mechanisms.

Causality between six psychiatric disorders and digestive tract cancers risk: a two-sample Mendelian randomization study

Associations between psychiatric disorders and digestive tract cancers have been proposed. However, the causal link between these factors remains unclear. This study pioneers Mendelian randomization (MR) analysis to explore the genetic link between psychiatric disorders and digestive tract cancers risk. We analysed data on six psychiatric disorders [schizophrenia, bipolar disorder, major depressive disorder (MDD), attention deficit hyperactivity disorder, autism spectrum disorder, and panic disorder (PD)] and digestive tract cancers [esophagus cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)] from genome-wide association studies databases. Using instrumental variables identified from significant single nucleotide polymorphism associations, we employed the inverse variance weighted (IVW) method alongside the weighted median (WM) method and MR-Egger regression. The results revealed no causal link between psychiatric disorders and the risk of EC or GC. Psychiatric disorders were not identified as risk factors for CRC. Notably, PD demonstrated a lower CRC risk (OR = 0.79, 95% CI 0.66-0.93, P = 0.01). This MR analysis underscores the lack of a causal association between psychiatric disorders and digestive tract cancers risk while suggesting a potential protective effect of PD against CRC.

Trajectories of depressive symptoms and risk of cardiovascular disease, cancer and mortality: a prospective cohort study

Background

Depressive symptoms are established risk factors for various health outcomes. However, previous studies assessed depressive symptoms at a single time point, neglecting individual variations over time.

Aims

To identify depressive symptoms trajectories through repeated measures and examine their associations with cardiovascular disease (CVD), cancer and mortality.

Methods

This study included 20 634 UK Biobank participants free of CVD and cancer at baseline with two or more assessments of depressive symptoms during 2006-2016. Group-based trajectory modelling identified depressive symptoms trajectories. Incident CVD, cancer and mortality were followed up until 2021 through linked registries.

Results

Six depressive symptoms trajectories were identified: no symptoms (n=6407), mild-stable (n=11 539), moderate-stable (n=2183), severe-decreasing (n=206), moderate-increasing (n=177) and severe-stable (n=122). During a median follow-up of 5.5 years, 1471 CVD cases, 1275 cancer cases and 503 deaths were documented. Compared with the no symptoms trajectory, the mild-stable, moderate-stable and severe-stable trajectories exhibited higher CVD risk, with hazard ratios (HRs) (95% CIs) of 1.19 (1.06 to 1.34), 1.32 (1.08 to 1.34) and 2.99 (1.85 to 4.84), respectively. Moderate-increasing and severe-stable trajectories were associated with higher mortality risks, with HRs (95% CIs) of 2.27 (1.04 to 4.93) and 3.26 (1.55 to 6.88), respectively. However, the severe-decreasing trajectory was not associated with higher risks of adverse outcomes. We did not find significant associations between any trajectory and cancer.

Conclusions

Trajectories related to stable and increasing depressive symptoms, but not the trajectory associated with severe depressive symptoms at the initial assessment but decreasing at the follow-up, were associated with higher risks of CVD and mortality. Alleviating severe depressive symptoms at the initial onset may mitigate CVD and mortality risks.

Identification of shared gene signatures in major depressive disorder and triple-negative breast cancer

BACKGROUND

Patients with major depressive disorder (MDD) have an increased risk of breast cancer (BC), implying that these two diseases share similar pathological mechanisms. This study aimed to identify the key pathogenic genes that lead to the occurrence of both triple-negative breast cancer (TNBC) and MDD.

METHODS

Public datasets GSE65194 and GSE98793 were analyzed to identify differentially expressed genes (DEGs) shared by both datasets. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape to identify key PPI genes using cytoHubba. Hub DEGs were obtained from the intersection of hub genes from a PPI network with genes in the disease associated modules of the Weighed Gene Co-expression Network Analysis (WGCNA). Independent datasets (TCGA and GSE76826) and RT-qPCR validated hub gene expression.

RESULTS

A total of 113 overlapping DEGs were identified between TNBC and MDD. The PPI network was constructed, and 35 hub DEGs were identified. Through WGCNA, the blue, brown, and turquoise modules were recognized as highly correlated with TNBC, while the brown, turquoise, and yellow modules were similarly correlated with MDD. Notably, G3BP1, MAF, NCEH1, and TMEM45A emerged as hub DEGs as they appeared both in modules and PPI hub DEGs. Within the GSE65194 and GSE98793 datasets, G3BP1 and MAF exhibited a significant downregulation in TNBC and MDD groups compared to the control, whereas NCEH1 and TMEM45A demonstrated a significant upregulation. These findings were further substantiated by TCGA and GSE76826, as well as through RT-qPCR validation.

CONCLUSIONS

This study identified G3BP1, MAF, NCEH1 and TMEM45A as key pathological genes in both TNBC and MDD.

An exploration of causal relationships between nine neurological diseases and the risk of breast cancer: a Mendelian randomization study

BACKGROUND

Some preceding researches have observed that certain neurological disorders, such as Alzheimer's disease and multiple sclerosis, may affect breast cancer risk. However, whether there are causal relationships between these neurological conditions and breast cancer is inconclusive. This study was designed to explore whether neurological disorders affected the risks of breast cancer overall and of the two subtypes (ER+ and ER-).

METHODS

In the course of this study, genome-wide association study (GWAS) data for nine neurological diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, generalized epilepsy, intracerebral haemorrhage, cerebral atherosclerosis, brain glioblastoma, and benign meningeal tumour) were collected from the Complex Trait Genetics lab and the MRC Integrative Epidemiology Unit, and single-nucleotide polymorphisms (SNPs) extensively associated with these neurological ailments had been recognized as instrumental variables (IVs). GWAS data on breast cancer were collected from the Breast Cancer Association Consortium (BCAC). Two-sample Mendelian randomization (MR) analyses as well as multivariable MR analyses were performed to determine whether these SNPs contributed to breast cancer risk. Additionally, the accuracy of the results was evaluated using the false discovery rate (FDR) multiple correction method. Both heterogeneity and pleiotropy were evaluated by analyzing sensitivities.

RESULTS

According to the results of two-sample MR analyses, Alzheimer's disease significantly reduced the risks of overall (OR 0.925, 95% CI [0.871-0.982], P = 0.011) and ER+ (OR 0.912, 95% CI [0.853-0.975], P = 0.007) breast cancer, but there was a negative result in ER- breast cancer. However, after multiple FDR corrections, the effect of Alzheimer's disease on overall breast cancer was not statistically significant. In contrast, multiple sclerosis significantly increased ER+ breast cancer risk (OR 1.007, 95% CI [1.003-1.011], P = 0.001). In addition, the multivariable MR analyses showed that Alzheimer's disease significantly reduced the risk of ER+ breast cancer (IVW: OR 0.929, 95% CI [0.864-0.999], P=0.047; MR-Egger: OR 0.916, 95% CI [0.846-0.992], P=0.031); however, multiple sclerosis significantly increased the risk of ER+ breast cancer (IVW: OR 1.008, 95% CI [1.003-1.012], P=4.35×10-4; MR-Egger: OR 1.008, 95% CI [1.003-1.012], P=5.96×10-4). There were no significant associations between the remainder of the neurological diseases and breast cancer.

CONCLUSIONS

This study found the trends towards a decreased risk of ER+ breast cancer in patients with Alzheimer's disease and an increased risk in patients with multiple sclerosis. However, due to the limitations of Mendelian randomization, we cannot determine whether there are definite causal relationships between neurological diseases and breast cancer risk. For conclusive evidences, more prospective randomized controlled trials will be needed in the future.

Exposure to psychotropic drugs and breast cancer risk in patients with bipolar disorder and major depressive disorder: a nested case-control study

Breast cancer is one of the most prevalent and serious types of cancer globally. Previous literature has shown that women with mental illness may have an increased risk of breast cancer, however whether this risk is associated with the use of psychotropic drugs has yet to be elucidated. This study aimed to assess such risk among women with major depressive disorder (MDD) and bipolar disorder (BD). A nested case-control study design was used with data obtained from the Taiwan National Health Insurance Research Database. Logistic regression analysis with adjustments for demographic characteristics, medical and mental comorbidities, and all-cause clinical visits was performed to estimate the risk of breast cancer according to the cumulative defined daily dose (cDDD) of psychotropic drugs. The study included 1564 women with MDD or BD who had breast cancer, and 15,540 women with MDD or BD who did not have breast cancer. After adjusting for important confounders, the long-term use of valproic acid (odds ratio, 95% confidence interval: 0.58, 0.39-0.56, cDDD ≥ 365), citalopram (0.58, 0.37-0.91, cDDD 180-365), and sertraline (0.77, 0.61-0.91, cDDD ≥ 365) was associated with a lower risk of breast cancer compared to a cDDD < 30. The short-term use of fluvoxamine (0.82, 0.69-0.96, cDDD 30-180), olanzapine (0.54, 0.33-0.89, cDDD 30-179), risperidone (0.7, 0.51-0.98, cDDD 30-179), and chlorpromazine (0.48, 0.25-0.90, cDDD 30-179) was associated with a lower risk of breast cancer. We found no evidence of an increased risk of breast cancer in patients with MDD or BD receiving psychotropic drugs.

Subjective and Personal Characteristics of Women with Breast Cancer: A Factorial Model of Disease Risks and the Course of Disease

OBJECTIVE

The purpose of this study was to evaluate psychological factors influencing the incidence of breast cancer in women.

METHODS

Basic beliefs, coping strategies, hardiness, subjective control, personal helplessness and independence were studied in 184 women, of which 80 women diagnosed with breast cancer, 104 women without a cancer diagnosis. All study participants completed psychodiagnostic methods and sociodemographic questionnaires. First, we analyzed differences in the psychological characteristics of women depending on the presence of an oncological diagnosis (F - Fisher's test). Second, we conducted factor analysis (principal component analysis with Varimax with Kaiser Normalization) to obtain psychological risk factors for breast cancer in women.

RESULTS

Distinctive psychological characteristics of women with breast cancer have been discovered. Women with breast cancer underestimate their worth and importance (p=0.021), as well as their luck (p=0.006) and the ability to control events in their lives (p=0.019). Women with breast cancer are very independent (arrogance) (p=0.000), rarely use confrontation-type coping (p=0.05), positive reappraisal (p=0.05), and planful problem-solving (p=0.035). Women diagnosed with breast cancer have an external locus of control (p=0.002), and are low hardiness (p=0.029). The listed features that distinguish women with breast cancer from cancer-free women were considered as probabilistic psychological risk factors for breast cancer. As a result of factor analysis, a model was obtained that included psychological factors associated with breast cancer in women: Independence (arrogance) (28.88% of variance), Belief system (24.83% of variance), Maladaptive coping (20.17% of variance).

CONCLUSIONS

Extreme independence, beliefs about one's failure, insignificance and inability to control life, as well as maladaptive coping are probabilistic psychological risk factors for breast cancer among Russian women.

Association of non-HDL-C and depression: a cross-sectional analysis of the NHANES data

Objectives

Non-high-density lipoprotein cholesterol (non-HDL-C) has attracted attention because it is associated with a variety of diseases and is easy to measure. However, the relationship between non-HDL-C and depression is still unclear. Our aim was to assess the relationship between non-HDL-C and depression using the cross-sectional NHANES survey from 2005 to 2018.

Methods

We examined the association between non-HDL-C and depression using weighted multivariable logistic regression models and subgroup analysis. Sensitivity analysis demonstrated the robustness of the results.

Results

There were 42,143 participants in this study and 8.6% had depression (weighted 7.53%). Non-HDL-C was higher in participants with depression compared to those without depression (weighted mean 3.64 vs. 3.73, p < 0.01). There was a positive association between non-HDL-C and depression with a 95% OR of 1.22 adjusted for multifactorial (95% CI,1.03-1.45). In subgroup analyses, non-HDL-C was positively associated with depression in men (OR, 1.31; 95% CI, 1.01-1.70), normal BMI (OR: 0.93; 95% CI: 0.66-1.32) and in participants without hypertension (OR, 1.29; 95% CI, 1.01-1.66).

Conclusion

Non-HDL-C positively correlated with depression, and further research may be better for clinical service.

Severe mental illness and the risk of breast cancer: A two-sample, two-step multivariable Mendelian randomization study

BACKGROUND

Based on epidemiological reports, severe mental illness (SMI) and breast cancer (BC) risk are linked positively. However, it is susceptible to clinical confounding factors, such as smoking, alcohol consumption, etc. Here, we performed a two-sample, two-step multivariable Mendelian randomization (MR) research to explore how the SMI etiologically influences BC risk and to quantify mediating effects of known modifiable risk factors.

METHODS

Data concerning the single nucleotide polymorphism (SNP)-associated with schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), and BC were obtained from two large consortia: the Breast Cancer Association Consortium (BCAC) and the Psychiatric Genomics Consortium (PGC). Then, the correlations of the previous SMI with the BC prevalence and the potential impact of mediators were explored through the two-sample and two-step MR analyses.

RESULTS

In two-sample MR, schizophrenia increased BC incidence (odds ratio (OR) 1.06, 95% confidence interval (CI) 1.02-1.10, P = 0.001). In subgroup analysis, schizophrenia increased ER+ BC (OR 1.06, 95% CI 1.03-1.10, P = 0.0009) and ER-BC (OR 1.06, 95% CI 1.01-1.11, P = 0.0123) incidences. Neither MDD nor BD elevated the BC risk. In two-step MR, smoking explained 11.29% of the schizophrenia-all BC risk association.

CONCLUSIONS

Our study indicates that schizophrenia increases susceptibility to breast cancer, with smoking playing a certain mediating role. Therefore, BC screening and smoking should be incorporated into the health management of individuals with schizophrenia.

An exploration of the correlations between seven psychiatric disorders and the risks of breast cancer, breast benign tumors and breast inflammatory diseases: Mendelian randomization analyses

Background

Previous observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases.

Methods

During our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs' effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses.

Results

When the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10^-6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10^-6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10^-5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer.

Conclusions

The correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases.

Investigating the relationship between depression and breast cancer: observational and genetic analyses

BACKGROUND

Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression and BC.

METHODS

We first evaluated phenotypic association using longitudinal follow-up data from the UK Biobank (N = 250,294). We then investigated genetic relationships leveraging summary statistics from the hitherto largest genome-wide association study of European individuals conducted for depression (N = 500,199), BC (N = 247,173), and its subtypes based on the status of estrogen receptor (ER + : N = 175,475; ER - : N = 127,442).

RESULTS

Observational analysis suggested an increased hazard of BC in depression patients (HR = 1.10, 95%CIs = 0.95-1.26). A positive genetic correlation between depression and overall BC was observed ([Formula: see text] = 0.08, P = 3.00 × 10-4), consistent across ER + ([Formula: see text] = 0.06, P = 6.30 × 10-3) and ER - subtypes ([Formula: see text] = 0.08, P = 7.20 × 10-3). Several specific genomic regions showed evidence of local genetic correlation, including one locus at 9q31.2, and four loci at, or close, to 6p22.1. Cross-trait meta-analysis identified 17 pleiotropic loci shared between depression and BC. TWAS analysis revealed five shared genes. Bi-directional Mendelian randomization suggested risk of depression was causally associated with risk of overall BC (OR = 1.12, 95%Cis = 1.04-1.19), but risk of BC was not causally associated with risk of depression.

CONCLUSIONS

Our work demonstrates a shared genetic basis, pleiotropic loci, and a putative causal relationship between depression and BC, highlighting a biological link underlying the observed phenotypic relationship; these findings may provide important implications for future studies aimed reducing BC risk.

Cancer mortality in Common Mental Disorders: A 10-year retrospective cohort study

PURPOSE

Individuals with Common Mental Disorders (CMDs) may have a higher cancer mortality. The purpose of this study was to examine cancer-related mortality among patients with CMDs and verify which cancer types are predominantly involved.

METHODS

We used the Regional Mental Health Registry of the Emilia-Romagna region, in Northern Italy to identify patients aged ≥ 18 years who received an ICD 9-CM diagnosis of CMDs (i.e., depressive and neurotic disorders) over a 10 year period (2008-2017). Information on cause of death was retrieved from the Regional Cause of Death Registry. Comparisons were made with data from the regional population without CMDs.

RESULTS

Among 101,487 patients suffering from CMDs (55.7% depression; 44.3% neurotic disorders), 3,087 (37.8%) died from neoplasms. The total standardized mortality ratio (SMR) was 1.82 (95% CI 1.78-1.86) while the SMR for all neoplasms was 2.08 (95% CI 2.01-2.16). Individuals of both genders, with both depressive and neurotic disorders had a higher risk of death from almost all cancers compared with the regional population.

CONCLUSION

Patients with CMDs have considerably higher cancer mortality risk than the general population. Higher mortality was observed for a broad range of cancers associated with different aetiologies. It is imperative to promote cancer awareness, prevention and treatment for people with CMDs.