Two-sample Mendelian randomization analysis of the causal relationship between body mass index and prostate cancer
10.3969/j.issn.1009-8291.2024.08.013
- VernacularTitle:两样本孟德尔随机化分析身体质量指数与前列腺癌发病风险的因果关系
- Author:
Hao WANG
1
;
Hanfeng XU
1
;
Yuan YANG
1
;
Zhe SONG
2
Author Information
1. Department of Urology, The First Affiliated Hospital of University of South China, Hengyang 421005
2. Department of Urology, The Second Affiliated Hospital of University of South China, Hengyang 421005, China
- Publication Type:Journal Article
- Keywords:
Mendelian randomization;
body mass index;
prostate cancer;
single nucleotide polymorphism
- From:
Journal of Modern Urology
2024;29(8):723-727
- CountryChina
- Language:Chinese
-
Abstract:
【Objective】 To analyze the causal relationship between genetically predicted body mass index (BMI) and prostate cancer (PCa) risk with Mendelian randomization (MR), in order to explore the potential risk factors for PCa and the development of prevention strategies. 【Methods】 Two-sample MR was performed using BMI genome-wide association study (GWAS) data of 339 224 samples and PCa GWAS data of 463 010 samples.After that, 69 single nucleotide polymorphisms (SNP) of BMI were used as instrumental variables to perform MR analysis on PCa.MR analysis adopted the inverse variance weighting method (IVW), MR-Egger method, weighted median method (WME), simple mode method (SM) and weighted mode method (WM).Heterogeneity test, pleiotropy test and leave-one-out sensitivity test were used to verify the stability and reliability of the data. 【Results】 In the IVW analysis, it was found that BMI was associated with the risk of PCa (OR:0.997, 95%CI:0.995-0.999, P=0.001).In the WME (OR:0.996, 95%CI:0.994-0.999, P=0.009), and WM (OR:0.995, 95%CI:0.991-1.000, P=0.045), the same results were obtained.There was no statistical significant difference between the MR-Egger method (OR:0.996, 95%CI:0.991-1.002, P=0.205) and SM (OR:0.995, 95%CI:0.990-1.000, P=0.079). 【Conclusion】 There is a causal relationship between a genetically predicted higher BMI and a lower risk of PCa by two sample MR analysis. This finding can prove a reference for identifying potential risk factors for PCa and the development of prevention strategies.
