Association between breast cancer and thyroid cancer risk: a two-sample Mendelian randomization study

Causal relationship between breast cancer and acute myeloid leukemia based on two-sample bidirectional Mendelian randomization and transcriptome overlap analysis

BACKGROUND

Breast cancer is the most prevalent malignancy and the leading cause of cancer-related deaths among women worldwide. Several case reports have shown that some breast cancer patients subsequently develop acute myeloid leukemia (AML) within a short period. However, the causal relationship and pathogenic mechanisms between breast cancer and AML remain incompletely understood.

METHODS

Mendelian randomization (MR) analyses were conducted to explore the bidirectional causal relationships between breast cancer and AML. Additionally, we applied the Bayesian Weighted Mendelian Randomization (BWMR) approach to validate the results of the MR analysis. Subsequently, we utilized RNA-seq data from various sources to explore the potential molecular signaling pathways between breast cancer and AML.

RESULTS

Both IVW method and BWMR approach demonstrated that data from three distinct sources consistently indicated breast cancer as a risk factor for AML, with all sources showing statistically significant results (all P < 0.05, Odds Ratios [ORs] > 1). Bioinformatic analyses suggested that extracellular vesicle functions and p53 signaling pathway may mediate molecular links between breast cancer and AML. Using machine learning, we identified 8 genes with high diagnostic efficacy for predicting the occurrence of AML in breast cancer patients.

CONCLUSIONS

MR analyses indicated a causal relationship between breast cancer and AML. Additionally, transcriptome analysis offered a theoretical basis for understanding the potential mechanisms and therapeutic targets of AML in breast cancer patients.

Causal effect of breast cancer on endometrial cancer risk: A two-sample Mendelian randomization study

BACKGROUND

Observational studies have indicated a higher incidence of endometrial cancer in individuals with breast cancer. However, to date, there is a dearth of Mendelian randomization (MR) studies that explore the causal relationship between breast cancer and the risk of endometrial cancer.

MATERIAL AND METHODS

We conducted MR to investigate the causal relationship between breast cancer and endometrial cancer risk in European populations.

RESULTS

A total of 112 valid instrumental variables (IVs) were included in the analysis. Our research has revealed a compelling causal association between genetic predisposition for breast cancer and an augmented likelihood of developing endometrial cancer (Inverse variance weighted (IVW) method, odds ratio (OR) = 1.105, 95 % confidence interval (CI): 1.025 to 1.181, p = 0.003; Weighted median method, OR = 1.109, 95 % CI: 1.020 to 1.205, p = 0.015; Weighted mode method, OR = 1.101, 95 % CI: 1.013 to 1.195, p = 0.025).

CONCLUSION

To our knowledge, this study is the first to report a causal association between breast cancer and endometrial cancer risk. Robust results were obtained through rigorous testing for heterogeneity and pleiotropy. Our findings indicate a causal effect of breast cancer on the risk of endometrial cancer.

Investigation of the causal relationship between breast cancer and thyroid cancer: a set of two-sample bidirectional Mendelian randomization study

PURPOSE

A potential association between breast (BC) and thyroid cancer (TC) has been observed. We investigated if the relationship between BC and TC is causal using bidirectional Mendelian randomization (MR) in Asian and European populations.

METHODS

BC-linked single nucleotide polymorphisms (SNPs) were acquired from a genome-wide association study (GWAS) conducted by the Breast Cancer Association Consortium and Biobank Japan. The most recent TC GWAS data were obtained from the FinnGen Project and National Biobank of Korea. We assessed the potential causal relationship between BC and TC using various MR methods, including inverse-variance-weighting (IVW). Sensitivity, heterogeneity, and pleiotropic tests were performed to assess reliability.

RESULTS

We found a bidirectional causal association between BC and TC within Europeans (IVW, TC on BC: odds ratio [OR] 1.090, 95% confidence interval [CI]: 1.012-1.173, P = 0.023; BC on TC: OR 1.265, 95% CI: 1.158-1.381, P < 0.001). A one-way causal relationship between BC susceptibility and TC risk was found in Asians (IVW BC on TC: OR 2.274, 95% CI: 2.089-2.475, P < 0.001). Subsequently, we identified a noteworthy bidirectional causal relationship between estrogen receptor (ER)-positive BC and TC (IVW, TC on ER-positive BC: OR 1.104, 95% CI: 1.001-1.212, P = 0.038; ER-positive BC on TC: OR 1.223, 95%CI: 1.072-1.395, P = 0.003), but not ER-negative BC and TC in Europeans.

CONCLUSION

We revealed a reciprocal causal association between ER-positive BC and TC. These findings establish a theoretical framework for the simultaneous surveillance and treatment of BC and TC.

Application of Mendelian randomization in thyroid diseases: a review

Thyroid diseases are increasingly prevalent, posing significant challenges to patients' quality of life and placing substantial financial burdens on families and society. Despite these impacts, the underlying pathophysiology of many thyroid conditions remains poorly understood, complicating efforts in treatment, management, and prevention. Observational studies can identify associations between exposure variables and disease; however, they often struggle to account for confounding factors and reverse causation. Understanding disease occurrence, epidemiological trends, and clinical diagnosis, prevention, and treatment relies heavily on robust etiological research. Mendelian randomization, a method grounded in genetics and epidemiology, has been widely employed in studying the etiology of thyroid diseases, offering a solution to some of these challenges. This paper categorizes thyroid diseases into thyroid dysfunction and thyroid cancer, reviewing related Mendelian randomization studies. It further provides novel perspectives and approaches for investigating the mechanisms underlying thyroid diseases and designing intervention strategies.

Causal Pathways Between Breast Cancer and Cardiovascular Disease Through Mediator Factors: A Two-Step Mendelian Randomization Analysis

Background

The causal relationship of breast cancer (BC) with cardiovascular disease (CVD) and the underlying mediating pathways remains elusive. Our study endeavors to investigate the causal association between BC and CVD, with a focus on identifying potential metabolic mediators and elucidating their mediation effects in this causality.

Methods

In this study, we conducted two-sample Mendelian randomization (MR) to estimate the causal effect of BC (overall BC, ER+ BC, ER- BC) from the Breast Cancer Association Consortium (BCAC) on CVD including coronary heart disease (CHD), hypertensive heart disease (HHD), ischaemic heart disease (IHD), and heart failure (HF) from the FinnGen consortium. Then, we used two-step MR to evaluate 18 metabolic mediators of the association and calculate the mediated proportions.

Results

Genetically predicted ER+ BC was causally associated with an increased risk of CVD including CHD (OR = 1.034, 95% CI: 1.004-1.065, p = 0.026), HHD (OR = 1.061, 95% CI: 1.002-1.124, p = 0.041), IHD (OR = 1.034, 95% CI: 1.007-1.062, p=0.013), and HF (OR = 1.055, 95% CI: 1.013-1.099, p = 0.010), while no causality was observed for overall BC and ER- BC. Furthermore, high-density lipoprotein cholesterol (HDL-C) was identified as a mediator of the association between ER+BC and CVD, including CHD (with 15.2% proportion)) and IHD (with 15.5% proportion), respectively.

Conclusion

This study elucidates the potential causal impact of ER+ BC on subsequent risk of CVD, including CHD, HHD, IHD, and HF. We also outline the metabolic mediator HDL-C as a priority target for preventive measures to reduce excessive risk of CVD among patients diagnosed with ER+BC.

Medullary Thyroid Carcinoma in the Background of Non-neoplastic Toxic Nodular Goiter

Background/Objective

Medullary thyroid carcinoma (MTC) is an uncommon thyroid cancer (TC), rarely found in hyperfunctioning goiter.

Case Report

We present a case of a woman treated for breast carcinoma (BCA) found to have a benign hyperfunctioning nodular goiter, its likely transformation to MTC, and its treatment. Family history revealed papillary thyroid cancer in her nephew.

Discussion

Most TCs in hyperfunctioning nodules are differentiated carcinomas. Familial MTC or MTC in association with multiple endocrine neoplasia 2 is the expected genetic association in this case.

Conclusion

The association of BCA and MTC may have been coincidental, given the high prevalence of BCA in females. It could have been the result of a common genetic precursor of both tumors and/or treatment modality such as external beam radiation therapy used to treat BCA. This case highlights the importance of considering MTC as a potential diagnosis even in cases of hyperfunctioning nodular goiter. We call for consideration of calcitonin level measurement in the workup of thyroid nodules in select cases. Close follow-up of thyroid nodules, particularly in patients with another primary malignancy, is important because of possible common genotype triggers.

Elucidating the relationship between breast cancer and brain cortical structure: a Mendelian randomization study

Cancer-associated cognitive impairment is a significant challenge for individuals who have survived breast cancer, affecting their quality of life. In this study, we conducted an inaugural comprehensive Mendelian randomization analysis discerning the causal relationship between breast cancer, including its two subtypes, and the cerebral cortical structure. Our analysis indicated that estrogen receptor-negative breast cancer significantly decreased surface area (β = -593.01 mm2, 95% CI: -1134.9 to -51.1 mm2, P = 0.032). At the regional level, estrogen receptor-negative breast cancer showed a significant association with surface area and thickness in 17 cortical regions. These regions included the insula, posterior cingulate, superior frontal, precuneus, fusiform, lateral occipital, and rostral middle frontal. Specifically, estrogen receptor-negative breast cancer had a significant impact on decreasing the surface area of the insula without considering global weight (β = -14.09 mm2, 95% CI: -22.91 to -5.27 mm2, P = 0.0017). The results from meta-analysis and LD Score Regression provide support for our findings. This investigation unveils the correlations between breast cancer, its various subcategories, and the cerebral cortical structure. Notably, breast cancer of the estrogen receptor-negative variety may elicit more widespread cerebral atrophy.

The Role of Blood Microbiome in the Development of Thyroid Cancer in Breast Cancer Survivors

Patients diagnosed with breast cancer are likely to be diagnosed with thyroid cancer as a second primary cancer. Similarly, patients with thyroid cancer are likely to develop breast cancer. In this study, we found an association between these two types of cancers in the microbiomes of patients with breast cancer. Blood samples were collected from 96 patients with breast cancer, their bacterial extracellular vesicles were isolated, and their microbiomes were analyzed. After microbiome analysis, researchers performed thyroid function tests, estrogen levels, and thyroid ultrasound results of these patients, and the relationships among these parameters were analyzed. Based on the thyroid ultrasonography results, differences in the microbiome were confirmed in the normal, cyst, nodule, and thyroid lobectomy groups. We investigated the microbiome differences between normal thyroid and thyroid cancer. In particular, the abundance of the genus Bacillus is related to estrogen levels, which could affect thyroid abnormalities and increase thyroid-stimulating hormone levels. This study explains the causes of thyroid cancer in patients with breast cancer using microbiomes and serological tests for thyroid hormones and estrogen. These can be used as basic data for preventing thyroid cancer in patients with breast cancer.