Chen Zi-Jin, Wang Rui, Yao Meng-Ying, Zhao Jing-Hong, Liang Bo
Department of Nephrology, Chongqing Key Laboratory of Prevention and Treatment of Kidney Disease, Chongqing Clinical Research Center of Kidney and Urology Diseases, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Department of Massage, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Kidney Dis (Basel). 2025 Feb 27;11(1):170-185. doi: 10.1159/000544915. eCollection 2025 Jan-Dec.
Although recent research suggests that alterations in gut microbiota play a critical role in the pathophysiology of kidney diseases, the causal relationship between specific intestinal flora and the risk of kidney diseases remains unclear. Here, we investigated the causal relationship between gut microbiota and different kidney diseases through mendelian randomization analysis.
Gut microbiota and three types of kidney diseases, including diabetic nephropathy, IgA nephropathy, and membranous nephropathy, were identified from large-scale genome-wide association studies summary data. Inverse variance weighted method was employed to estimate causal relationships. Cochran's test was utilized to uncover any heterogeneity. The mendelian randomization-Egger intercept test was employed to detect horizontal pleiotropy, and the leave-one-out method was used for testing the stability. In addition, the reverse, multivariable, and two-step mendelian randomization analysis was conducted to assess the causation possibilities. Furthermore, the associations between three types of kidney diseases and immune infiltration were determined.
We identified 1,531 single-nucleotide polymorphisms. There were 6 positive and 9 negative causal effects between gut microbiota and three types of kidney diseases. Specifically, was a protective factor for diabetic nephropathy while was a risk factor. was a protective factor for IgA nephropathy, while , 1, , , , , and were risk factors for IgA nephropathy. , , , and were associated with an increased risk of membranous nephropathy, while was associated with a decreased risk of membranous nephropathy. Sensitivity analysis indicated the results were robust. No significant pleiotropy or heterogeneity was identified. Notably, the reverse mendelian randomization analysis did not reveal any causal relationship. After adjusting for environmental confounders, including CO, PM 2.5, PM 10, and exposure to tobacco smoke at home, these causal relationships still exist. Additionally, immune infiltration analysis indicated unique immune cell distribution in each type of kidney disease, which are largely consistent with later two-step approach, emphasizing the significance of immunological processes in the diseases.
This study uncovered the causal relationship between gut microbiota and three types of kidney diseases. This discovery provides fresh perspectives on how microbes contribute to kidney diseases, paving the way for more in-depth clinical studies.
尽管最近的研究表明肠道微生物群的改变在肾脏疾病的病理生理学中起关键作用,但特定肠道菌群与肾脏疾病风险之间的因果关系仍不清楚。在此,我们通过孟德尔随机化分析研究了肠道微生物群与不同肾脏疾病之间的因果关系。
从大规模全基因组关联研究汇总数据中确定肠道微生物群和三种类型的肾脏疾病,包括糖尿病肾病、IgA肾病和膜性肾病。采用逆方差加权法估计因果关系。利用 Cochr an检验发现任何异质性。采用孟德尔随机化 - Egger截距检验检测水平多效性,并采用留一法检验稳定性。此外,进行了反向、多变量和两步孟德尔随机化分析以评估因果可能性。此外,还确定了三种类型肾脏疾病与免疫浸润之间的关联。
我们鉴定出1531个单核苷酸多态性。肠道微生物群与三种类型的肾脏疾病之间存在6个正向和9个负向因果效应。具体而言, 是糖尿病肾病的保护因素,而 是风险因素。 是IgA肾病的保护因素,而 、 、 、 、 、 和 是IgA肾病的风险因素。 、 、 和 与膜性肾病风险增加相关,而 与膜性肾病风险降低相关。敏感性分析表明结果具有稳健性。未发现显著的多效性或异质性。值得注意的是,反向孟德尔随机化分析未揭示任何因果关系。在调整环境混杂因素,包括一氧化碳、细颗粒物2.5、可吸入颗粒物10和家庭烟草烟雾暴露后,这些因果关系仍然存在。此外,免疫浸润分析表明每种类型的肾脏疾病中存在独特的免疫细胞分布,这在很大程度上与后期的两步法一致,强调了免疫过程在这些疾病中的重要性。
本研究揭示了肠道微生物群与三种类型肾脏疾病之间的因果关系。这一发现为微生物如何导致肾脏疾病提供了新的视角,为更深入的临床研究铺平了道路。