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Abstract：
BACKGROUND: Evidence indicates that the risk of developing a secondary ovarian cancer (OC) is correlated with estrogen receptor (ER) status. However, the clinical significance of the relationship between ER-associated breast cancer (BC) and clear cell ovarian cancer (CCOC) remains elusive.
METHODS: Independent single nucleotide polymorphisms (SNPs) strongly correlated with exposure were extracted, and those associated with confounders and outcomes were removed using the PhenoScanner database. SNP effects were extracted from the outcome datasets with minor allele frequency > 0.01 as the filtration criterion. Next, valid instrumental variables (IVs) were obtained by harmonizing exposure and outcome effects and further filtered based on F-statistics (> 10). Mendelian randomization (MR) assessment of valid IVs was carried out using inverse variance weighted (IVW), MR Egger (ME), weighted median (WM), and multiplicative random effects-inverse variance weighted (MRE-IVW) methods. For sensitivity analysis and visualization of MR findings, a heterogeneity test, a pleiotropy test, a leave-one-out test, scatter plots, forest plots, and funnel plots were employed.
RESULTS: MR analyses with all four methods revealed that CCOC was not causally associated with ER-negative BC (IVW results: odds ratio (OR) = 0.89, 95% confidence interval (CI) = 0.66-1.20, P = 0.431) or ER-positive BC (IVW results: OR = 0.99, 95% CI = 0.88-1.12, P = 0.901). F-statistics were computed for each valid IV, all of which exceeded 10. The stability and reliability of the results were confirmed by sensitivity analysis.
CONCLUSIONS: Our findings indicated that CCOC dids not have a causal association with ER-associated BC. The absence of a definitive causal link between ER-associated BC and CCOC suggested a minimal true causal influence of ER-associated BC exposure factors on CCOC. These results indicated that individuals afflicted by ER-associated BC could alleviate concerns regarding the developing of CCOC, thereby aiding in preserving their mental well-being stability and optimizing the efficacy of primary disease treatment.
METHODS: Independent single nucleotide polymorphisms (SNPs) strongly correlated with exposure were extracted, and those associated with confounders and outcomes were removed using the PhenoScanner database. SNP effects were extracted from the outcome datasets with minor allele frequency > 0.01 as the filtration criterion. Next, valid instrumental variables (IVs) were obtained by harmonizing exposure and outcome effects and further filtered based on F-statistics (> 10). Mendelian randomization (MR) assessment of valid IVs was carried out using inverse variance weighted (IVW), MR Egger (ME), weighted median (WM), and multiplicative random effects-inverse variance weighted (MRE-IVW) methods. For sensitivity analysis and visualization of MR findings, a heterogeneity test, a pleiotropy test, a leave-one-out test, scatter plots, forest plots, and funnel plots were employed.
RESULTS: MR analyses with all four methods revealed that CCOC was not causally associated with ER-negative BC (IVW results: odds ratio (OR) = 0.89, 95% confidence interval (CI) = 0.66-1.20, P = 0.431) or ER-positive BC (IVW results: OR = 0.99, 95% CI = 0.88-1.12, P = 0.901). F-statistics were computed for each valid IV, all of which exceeded 10. The stability and reliability of the results were confirmed by sensitivity analysis.
CONCLUSIONS: Our findings indicated that CCOC dids not have a causal association with ER-associated BC. The absence of a definitive causal link between ER-associated BC and CCOC suggested a minimal true causal influence of ER-associated BC exposure factors on CCOC. These results indicated that individuals afflicted by ER-associated BC could alleviate concerns regarding the developing of CCOC, thereby aiding in preserving their mental well-being stability and optimizing the efficacy of primary disease treatment.
摘要：
背景：证据表明发生继发性卵巢癌（OC）的风险与雌激素受体（ER）状态相关。然而,ER相关乳腺癌（BC）和透明细胞卵巢癌（CCOC）之间的关系的临床意义仍然难以捉摸。
方法：提取与暴露密切相关的独立单核苷酸多态性（SNPs），使用PhenoScanner数据库删除了与混杂因素和结果相关的因素。从次要等位基因频率>0.01的结果数据集中提取SNP效应作为过滤标准。接下来,有效的工具变量(IVs)是通过协调暴露和结果效应获得的,并根据F统计量(>10)进一步过滤.使用逆方差加权（IVW）进行有效静脉的孟德尔随机化（MR）评估，艾格先生（ME），加权中位数(WM)，和乘法随机效应-逆方差加权(MRE-IVW)方法。对于MR发现的敏感性分析和可视化，异质性测试，多效性测试，一次离开测试，散点图,森林地块,和漏斗图被采用。
结果：所有四种方法的MR分析显示，CCOC与ER阴性BC无因果关系（IVW结果：比值比（OR）=0.89，95％置信区间（CI）=0.66-1.20，P=0.431）或ER阳性BC（IVW结果：OR=0.99，95％CI=0.88-1.12，P=0.901）。计算每个有效IV的F统计量，所有这些都超过了10。敏感性分析证实了结果的稳定性和可靠性。
结论：我们的研究结果表明，CCOC与ER相关的BC没有因果关系。ER相关BC和CCOC之间没有明确的因果关系，这表明ER相关BC暴露因素对CCOC的真正因果关系最小。这些结果表明，患有ER相关BC的个体可以减轻对CCOC发展的担忧，从而有助于保持他们的精神健康稳定性和优化原发疾病治疗的功效。
方法：提取与暴露密切相关的独立单核苷酸多态性（SNPs），使用PhenoScanner数据库删除了与混杂因素和结果相关的因素。从次要等位基因频率>0.01的结果数据集中提取SNP效应作为过滤标准。接下来,有效的工具变量(IVs)是通过协调暴露和结果效应获得的,并根据F统计量(>10)进一步过滤.使用逆方差加权（IVW）进行有效静脉的孟德尔随机化（MR）评估，艾格先生（ME），加权中位数(WM)，和乘法随机效应-逆方差加权(MRE-IVW)方法。对于MR发现的敏感性分析和可视化，异质性测试，多效性测试，一次离开测试，散点图,森林地块,和漏斗图被采用。
结果：所有四种方法的MR分析显示，CCOC与ER阴性BC无因果关系（IVW结果：比值比（OR）=0.89，95％置信区间（CI）=0.66-1.20，P=0.431）或ER阳性BC（IVW结果：OR=0.99，95％CI=0.88-1.12，P=0.901）。计算每个有效IV的F统计量，所有这些都超过了10。敏感性分析证实了结果的稳定性和可靠性。
结论：我们的研究结果表明，CCOC与ER相关的BC没有因果关系。ER相关BC和CCOC之间没有明确的因果关系，这表明ER相关BC暴露因素对CCOC的真正因果关系最小。这些结果表明，患有ER相关BC的个体可以减轻对CCOC发展的担忧，从而有助于保持他们的精神健康稳定性和优化原发疾病治疗的功效。
