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Abstract：
BACKGROUND: Recent studies demonstrated that chronic prostatitis (CP) is closely related to the gut microbiota (GM). Nevertheless, the causal relationship between GM and CP has not been fully elucidated. Therefore, the two-sample Mendelian randomization (MR) analysis was employed to investigate this association.
METHODS: The summary data of gut microbiota derived from a genome-wide association study (GWAS) involving 18,340 individuals in the MiBioGen study served as the exposure, and the corresponding summary statistics for CP risk, representing the outcome, were obtained from the FinnGen databases (R9). The causal effects between GM and CP were estimated using the inverse-variance weighted (IVW) method supplemented with MR-Egger, weighted median, weighted mode, and simple mode methods. Additionally, the false discovery rate (FDR) correction was performed to adjust results. The detection and quantification of heterogeneity and pleiotropy were accomplished through the MR pleiotropy residual sum and outlier method, Cochran\'s Q statistics, and MR-Egger regression.
RESULTS: The IVW estimates indicated that a total of 11 GM taxa were related to the risk of CP. Seven of them was correlated with an increased risk of CP, while the remained linked with a decreased risk of CP. However, only Methanobacteria (OR 0.86; 95% CI 0.74-0.99), Methanobacteriales (OR 0.86; 95% CI 0.74-0.99), NB1n (OR 1.16; 95% CI 1.16-1.34), Methanobacteriaceae (OR 0.86; 95% CI 0.74-0.99), Odoribactergenus Odoribacter (OR 1.43; 95% CI 1.05-1.94), and Sutterellagenus Sutterella (OR 1.33; 95% CI 1.01-1.76) still maintain significant association with CP after FDR correction. Consistent directional effects for all analyses were observed in the supplementary methods. Subsequently, sensitivity analyses indicated the absence of heterogeneity, directional pleiotropy, or outliers concerning the causal effect of specific gut microbiota on CP (p > 0.05).
CONCLUSIONS: Our study demonstrated a gut microbiota-prostate axis, offering crucial data supporting the promising use of the GM as a candidate target for CP prevention, diagnosis, and treatment. There is a necessity for randomized controlled trials to validate the protective effect of the linked GM against the risk of CP, and to further investigate the underlying mechanisms involved.
METHODS: The summary data of gut microbiota derived from a genome-wide association study (GWAS) involving 18,340 individuals in the MiBioGen study served as the exposure, and the corresponding summary statistics for CP risk, representing the outcome, were obtained from the FinnGen databases (R9). The causal effects between GM and CP were estimated using the inverse-variance weighted (IVW) method supplemented with MR-Egger, weighted median, weighted mode, and simple mode methods. Additionally, the false discovery rate (FDR) correction was performed to adjust results. The detection and quantification of heterogeneity and pleiotropy were accomplished through the MR pleiotropy residual sum and outlier method, Cochran\'s Q statistics, and MR-Egger regression.
RESULTS: The IVW estimates indicated that a total of 11 GM taxa were related to the risk of CP. Seven of them was correlated with an increased risk of CP, while the remained linked with a decreased risk of CP. However, only Methanobacteria (OR 0.86; 95% CI 0.74-0.99), Methanobacteriales (OR 0.86; 95% CI 0.74-0.99), NB1n (OR 1.16; 95% CI 1.16-1.34), Methanobacteriaceae (OR 0.86; 95% CI 0.74-0.99), Odoribactergenus Odoribacter (OR 1.43; 95% CI 1.05-1.94), and Sutterellagenus Sutterella (OR 1.33; 95% CI 1.01-1.76) still maintain significant association with CP after FDR correction. Consistent directional effects for all analyses were observed in the supplementary methods. Subsequently, sensitivity analyses indicated the absence of heterogeneity, directional pleiotropy, or outliers concerning the causal effect of specific gut microbiota on CP (p > 0.05).
CONCLUSIONS: Our study demonstrated a gut microbiota-prostate axis, offering crucial data supporting the promising use of the GM as a candidate target for CP prevention, diagnosis, and treatment. There is a necessity for randomized controlled trials to validate the protective effect of the linked GM against the risk of CP, and to further investigate the underlying mechanisms involved.
摘要：
背景：最近的研究表明，慢性前列腺炎（CP）与肠道菌群（GM）密切相关。然而，GM和CP之间的因果关系尚未完全阐明.因此,我们采用孟德尔随机双样本(MR)分析来研究这种关联.
方法：来自MiBioGen研究中涉及18,340名个体的全基因组关联研究（GWAS）的肠道微生物群汇总数据作为暴露量，以及CP风险的相应汇总统计数据，代表结果，从FinnGen数据库(R9)获得。GM和CP之间的因果效应是使用补充MR-Egger的逆方差加权(IVW)方法估计的。加权中位数，加权模式，和简单的模式方法。此外,进行错误发现率(FDR)校正以调整结果.通过MR多效性残差和离群值法实现了异质性和多效性的检测和量化,Cochran的Q统计数据，和MR-Egger回归。
结果：IVW估计表明，共有11个GM分类单元与CP的风险有关。其中七个与CP的风险增加有关，而这仍然与CP风险降低有关。然而,仅甲烷细菌（OR0.86；95%CI0.74-0.99），甲烷杆菌（OR0.86；95%CI0.74-0.99），NB1n（OR1.16；95%CI1.16-1.34），甲烷杆菌科（OR0.86；95%CI0.74-0.99），OdoribacusOdoribacter（OR1.43；95%CI1.05-1.94），和SutterylagenusSutterilla（OR1.33;95％CI1.01-1.76）在FDR校正后仍与CP保持显着相关性。在补充方法中观察到所有分析的一致定向效应。随后，敏感性分析表明不存在异质性，方向性多效性，或关于特定肠道菌群对CP的因果效应的异常值(p>0.05)。
结论：我们的研究表明，肠道菌群-前列腺轴，提供关键数据，支持将GM用作CP预防的候选目标，诊断,和治疗。有必要进行随机对照试验来验证相关GM对CP风险的保护作用。并进一步调查其中的潜在机制。
方法：来自MiBioGen研究中涉及18,340名个体的全基因组关联研究（GWAS）的肠道微生物群汇总数据作为暴露量，以及CP风险的相应汇总统计数据，代表结果，从FinnGen数据库(R9)获得。GM和CP之间的因果效应是使用补充MR-Egger的逆方差加权(IVW)方法估计的。加权中位数，加权模式，和简单的模式方法。此外,进行错误发现率(FDR)校正以调整结果.通过MR多效性残差和离群值法实现了异质性和多效性的检测和量化,Cochran的Q统计数据，和MR-Egger回归。
结果：IVW估计表明，共有11个GM分类单元与CP的风险有关。其中七个与CP的风险增加有关，而这仍然与CP风险降低有关。然而,仅甲烷细菌（OR0.86；95%CI0.74-0.99），甲烷杆菌（OR0.86；95%CI0.74-0.99），NB1n（OR1.16；95%CI1.16-1.34），甲烷杆菌科（OR0.86；95%CI0.74-0.99），OdoribacusOdoribacter（OR1.43；95%CI1.05-1.94），和SutterylagenusSutterilla（OR1.33;95％CI1.01-1.76）在FDR校正后仍与CP保持显着相关性。在补充方法中观察到所有分析的一致定向效应。随后，敏感性分析表明不存在异质性，方向性多效性，或关于特定肠道菌群对CP的因果效应的异常值(p>0.05)。
结论：我们的研究表明，肠道菌群-前列腺轴，提供关键数据，支持将GM用作CP预防的候选目标，诊断,和治疗。有必要进行随机对照试验来验证相关GM对CP风险的保护作用。并进一步调查其中的潜在机制。
