体质量指数和4种女性特征性癌症的因果关系：一项两样本孟德尔随机化研究

doi:10.3877/cma.j.issn.2095-9605.2023.04.005

目的

采用两样本孟德尔随机化（MR）方法探究BMI增加和4种女性特征性癌症之间的因果关系。

方法

通过GWAS数据库获取BMI和4种女性特征性癌症的相关数据。按照假设筛选单核苷酸多态性（SNPs）作为工具变量（IVs），使用PhenoScanner法去除混杂因素相关的SNP，分别采用包括逆方差加权法（IVW）在内的5种孟德尔随机化分析方法进行两样本孟德尔随机化分析，采用IVW和MR-Egger法进行Cochran Q和Rochra Q异质性检验，用Egger-intercept法进行多效性检验、逐个剔除检验进行敏感性分析，并计算F值以评估是否存在弱IVs偏倚。

结果

遗传预测的BMI的增加与乳腺癌风险降低（OR=0.648，95%CI：0.535-0.783，P=7.74e-06）和子宫内膜癌风险增加（OR=1.534，95%CI：1.195-1.970，P=7.84e-04）有因果关系。

结论

BMI的增加可能会降低女性乳腺癌发生的风险，增加子宫内膜癌发生的风险，但没有充分证据表明BMI的增加对本文研究的其他女性特征性癌症的发生风险存在明显影响，还需要进一步的研究来阐明结果。

关键词: 孟德尔随机化, 体质量指数（BMI）, 乳腺癌, 子宫内膜癌, 卵巢癌, 宫颈癌

Objective

This study employs a two-sample Mendelian randomization (MR) approach to investigate the causal relationship between increased Body Mass Index (BMI) and four characteristic female cancers.

Methods

BMI and data pertaining to the four characteristic female cancers were obtained from the GWAS database. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) based on assumptions. The PhenoScanner method was utilized to eliminate SNPs associated with confounding factors. Five Mendelian randomization analysis methods were employed for two-sample Mendelian randomization analysis, including inverse variance-weighted (IVW). Cochran Q and Rücker Q heterogeneity tests were conducted using IVW and MR-Egger methods. The egger-intercept method was employed for pleiotropy testing, and stepwise exclusion testing was used for sensitivity analysis. F-values were calculated to assess the presence of weak IVs bias.

Results

Genetically predicted increase in BMI was causally associated with reduced risk of breast cancer (OR=0.648, 95% CI: 0.535-0.783, P=7.74e-06) and increased risk of endometrial cancer (OR=1.534, 95% CI: 1.195-1.970, P=7.84e-04).

Conclusions

BMI may potentially decrease the risk of female breast cancer while increasing the risk of endometrial cancer. There is inadequate evidence to indicate a significant impact of increased BMI on the occurrence risk of other characteristic female cancers studied. Further research is warranted to elucidate these findings.

Key words: Mendelian randomisation, Body mass index (BMI), Breast cancer, Endometrial cancer, Ovarian cancer, Cervical cancer

图1 工具变量筛选原理

表1 暴露和结局数据信息

Exposure	Outcome	Cases（n）	Controls（n）	Size（n）
BMI		—	—	330 793
	Breast Cancer	14 910	17 588	32 498
	Endometrial Cancer	2 188	237 839	240 027
	Ovarian Cancer	1 588	244 932	246 520
	Cervix Cancer	3 175	459 835	463 010

表1 暴露和结局数据信息

Exposure	Outcome	Cases（n）	Controls（n）	Size（n）
BMI		—	—	330 793
	Breast Cancer	14 910	17 588	32 498
	Endometrial Cancer	2 188	237 839	240 027
	Ovarian Cancer	1 588	244 932	246 520
	Cervix Cancer	3 175	459 835	463 010

表2 异质性检验结果

	IVW（P-value）	MR-Egger（P-value）
Breast Cancer	0.0008528	0.0008864
Endometrial Cancer	0.0287088	0.0269904
Ovarian Cancer	0.8860324	0.8826452
Cervix Cancer	0.0535872	0.0464912

表2 异质性检验结果

	IVW（P-value）	MR-Egger（P-value）
Breast Cancer	0.0008528	0.0008864
Endometrial Cancer	0.0287088	0.0269904
Ovarian Cancer	0.8860324	0.8826452
Cervix Cancer	0.0535872	0.0464912

表3 水平多效性检验结果

	Egger-intercept（P-value）
Breast Cancer	0.3308104
Endometrial Cancer	0.4706562
Ovarian Cancer	0.4070501
Cervix Cancer	0.9090576

表3 水平多效性检验结果

	Egger-intercept（P-value）
Breast Cancer	0.3308104
Endometrial Cancer	0.4706562
Ovarian Cancer	0.4070501
Cervix Cancer	0.9090576

图4 两样本孟德尔随机化分析结果漏斗图（图A、B、C、D释义同图2）

图5 "Leave-one-out"图（图A、B、C、D释义同图2）

图2 两样本孟德尔随机化分析结果森林图。A：为女性乳腺癌结局因素组；B：为子宫内膜癌结局因素组；C：为卵巢癌结局因素组；D：为宫颈癌结局因素组

图3 两样本孟德尔随机化分析结果散点图（图A、B、C、D释义同图2）

表4 IVW法孟德尔随机化分析结果

	OR（Odds Ratio）	95%CI	P-value
Breast Cancer	0.648	0.535-0.783	7.74e-06*
Endometrial Cancer	1.534	1.195-1.970	7.84e-04*
Ovarian Cancer	0.901	0.695-1.168	0.4296406
Cervix Cancer	1.000	0.999-1.002	0.7945332

表4 IVW法孟德尔随机化分析结果

	OR（Odds Ratio）	95%CI	P-value
Breast Cancer	0.648	0.535-0.783	7.74e-06*
Endometrial Cancer	1.534	1.195-1.970	7.84e-04*
Ovarian Cancer	0.901	0.695-1.168	0.4296406
Cervix Cancer	1.000	0.999-1.002	0.7945332

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Body mass index and causal relationships with four characteristic female cancers: a two-sample mendelian randomization study

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Body mass index and causal relationships with four characteristic female cancers: a two-sample mendelian randomization study