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

Ren, Fei; Shang, Qingyao; Zhao, Shuangtao; Yang, Chenxuan; Feng, Kexin; Liu, Jiaxiang; Kang, Xiangpeng; Zhang, Ruixuan; Wang, Xiang; Wang, Xin

doi:10.3389/fpsyt.2023.1179562

Cited by 8 publications

(3 citation statements)

References 73 publications

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“…We used F-statistics to evaluate the statistical strength. The Fstatistics are equal to ((N-k-1)/k) × (R2/(1-R2)), where N and k represent the sample size and number of SNP, respectively (34). An F-statistic < 10 indicates that the genetic variation used is a weak tool variable that may contribute to a bias.…”

Section: P Value and F-statistics Calculationmentioning

confidence: 99%

Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study

Zhou,

Liu,

Liu

et al. 2024

Front. Oncol.

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BackgroundPatients with schizophrenia are at a higher risk of developing cancer. However, the causal relationship between schizophrenia and different tumor types remains unclear.MethodsUsing a two-sample, two-way Mendelian randomization method, we used publicly available genome-wide association analysis (GWAS) aggregate data to study the causal relationship between schizophrenia and different cancer risk factors. These tumors included lung adenocarcinoma, lung squamous cell carcinoma, small-cell lung cancer, gastric cancer, alcohol-related hepatocellular cancer, tumors involving the lungs, breast, thyroid gland, pancreas, prostate, ovaries and cervix, endometrium, colon and colorectum, and bladder. We used the inverse variance weighting (IVW) method to determine the causal relationship between schizophrenia and different tumor risk factors. In addition, we conducted a sensitivity test to evaluate the effectiveness of the causality.ResultsAfter adjusting for heterogeneity, evidence of a causal relationship between schizophrenia and lung cancer risk was observed (odds ratio [OR]=1.001, 95% confidence interval [CI], 1.000–1.001; P=0.0155). In the sensitivity analysis, the causal effect of schizophrenia on the risk of lung cancer was consistent in both direction and degree. However, no evidence of causality or reverse causality between schizophrenia and other tumors was found.ConclusionThis study elucidated a causal relationship between the genetic predictors of schizophrenia and the risk of lung cancer, thereby providing a basis for the prevention, pathogenesis, and treatment of schizophrenia in patients with lung cancer.

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Section: P Value and F-statistics Calculationmentioning

confidence: 99%

Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study

Zhou,

Liu,

Liu

et al. 2024

Front. Oncol.

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“…We additionally calculated the Fstatistic to examine the statistical strength of every instrumental variable by the following formula: F=[R 2 ×(N-k-1)]/[(1-R 2 )×k], and k was the number of instrumental variables [32][33][34]. F>10 indicated that the instrumental variables were robust and could be used for MR analyses [19,35,36]. Next, we extracted SNPs for neurological diseases from the breast cancer data and eliminated the ones associated with outcomes.…”

Section: Instrumental Variable Selectionmentioning

confidence: 99%

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

Ren,

Yang,

Feng

et al. 2024

Aging

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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 singlenucleotide 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.

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“…Therefore, for AN and AXD we relaxed the threshold of the p-value of exposure-associated IVs in the screening condition to < 5 × 10 -5 and the linkage disequilibrium [LD] r 2 to 0.01. The settings above were previously also used in many MR studies of psychiatric disorders (30,31). The causal effect of psychiatric disorders on AS is currently analyzed using the MR analysis methods described above except for phenotype "AN", which applies only to the WR method because only one SNP is available.…”

Section: Reverse Mendelian Randomization Analysismentioning

confidence: 99%

Ankylosing spondylitis and psychiatric disorders in European population: a Mendelian randomization study

Zuo,

2023

Front. Immunol.

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BackgroundEpidemiologic evidence has demonstrated a correlation between ankylosing spondylitis and psychiatric disorders. However, little is known about the common genetics and causality of this association. This study aimed to investigate the common genetics and causality between ankylosing spondylitis (AS) and psychiatric disorders.MethodsA two-sample Mendelian Randomization (MR) analysis was carried out to confirm causal relationships between ankylosing spondylitis and five mental health conditions including major depressive disorder (MDD), anxiety disorder (AXD), schizophrenia (SCZ), bipolar disorder (BIP), and anorexia nervosa (AN). Genetic instrumental variables associated with exposures and outcomes were derived from the largest available summary statistics of genome-wide association studies (GWAS). Bidirectional causal estimation of MR was primarily obtained using the inverse variance weighting (IVW) method. Other MR methods include MR-Egger regression, Weighted Median Estimator (WME), Weighted Mode, Simple Mode, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO). Sensitivity analyses are conducted to estimate the robustness of MR results.ResultsThe findings suggest that AS may be causally responsible for the risk of developing SCZ (OR = 1.18, 95% confidence interval = (1.06, 1.31), P = 2.58 × 10-3) and AN (OR = 1.32, 95% confidence interval = (1.07, 1.64), P = 9.43 × 10-3). In addition, MDD, AXD, SCZ, AN, and BIP were not inversely causally related to AS (all p > 0.05).ConclusionOur study provides fresh insights into the relationship between AS and psychiatric disorders (SCZ and AN). Furthermore, it may provide new clues for risk management and preventive interventions for mental disorders in patients with AS.

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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

Cited by 8 publications

References 73 publications

Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study

Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study

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

Ankylosing spondylitis and psychiatric disorders in European population: a Mendelian randomization study

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