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作 者:王豪[1] 许韩峰[1] 阳源[1] 宋喆 WANG Hao;XU Hanfeng;YANG Yuan;SONG Zhe(Department of Urology,The First Affiliated Hospital of University of South China,Hengyang 421005;Department of Urology,The Second Affiliated Hospital of University of South China,Hengyang 421005,China)
机构地区:[1]南华大学附属第一医院泌尿外科,湖南衡阳421005 [2]南华大学附属第二医院泌尿外科,湖南衡阳421005
出 处:《现代泌尿外科杂志》2024年第8期723-727,共5页Journal of Modern Urology
基 金:湖南省卫生健康委科研计划项目(No.202104050005)。
摘 要:目的通过孟德尔随机化(MR)分析基因预测的身体质量指数(BMI)与前列腺癌(PCa)发病风险之间的因果关系,以期探索PCa的潜在风险因素,制定预防策略。方法汇总统计339224个样本的BMI全基因组关联研究(GWAS)数据和463010个样本的PCa GWAS数据进行两样本MR。使用BMI的69个单核苷酸多态性(SNP)作为工具变量对PCa进行MR分析。采用逆方差加权法(IVW)、MR-Egger法、加权中位数法(WME)、简单众数法(SM)和加权众数法(WM)进行MR分析。采用异质性检验、多效性检验和留一法敏感性检验验证数据的稳定性和可靠性。结果IVW分析发现BMI与PCa发病风险存在关联(OR:0.997,95%CI:0.995~0.999,P=0.001);在WME(OR:0.996,95%CI:0.994~0.999,P=0.009)和WM(OR:0.995,95%CI:0.991~1.000,P=0.045)中得到相同的结果。而在MR-Egger法(OR:0.996,95%CI:0.991~1.002,P=0.205)和SM法中(OR:0.995,95%CI:0.990~1.000,P=0.079),差异无统计学意义。结论两样本MR分析基因预测的BMI较高与较低的PCa患病风险之间存在因果关系,这一发现可为探究PCa的潜在风险因素及制定预防策略提供参考。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 339224 samples and PCa GWAS data of 463010 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.
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