Chen Rong, He Liujie, Huang Zhiyao, Sun Jie, Wang Qiang
Department of Graduate, Hebei North University, Zhangjiakou, Hebei Province, China.
Naval Medical University, Shanghai, China.
Medicine (Baltimore). 2025 Jun 6;104(23):e42577. doi: 10.1097/MD.0000000000042577.
The plasma lipidome has been found to be closely related to inflammation, obesity, aging, and other diseases, including various cancers. However, the causal relationship between specific plasma lipid species and the risk of urological cancers remains unclear. This study aimed to investigate the causal relationship between 179 lipid species and 3 common types of urological cancers using a two-sample Mendelian randomization (MR) approach. Large-scale genome-wide association study datasets of 179 lipid species were analyzed to evaluate the association between the plasma lipidome and urological cancers, including bladder cancer, kidney cancer, and prostate cancer. The inverse variance weighted method was employed as the primary analysis approach, supplemented by MR-Egger regression, weighted median, weighted mode, and simple mode methods to ensure the reliability of the findings. Sensitivity analyses, including Cochran Q test, MR-Egger intercept test, MR Pleiotropy Residual Sum And Outlier, and leave-one-out analysis, were performed to assess the stability and robustness of the causal relationship. The inverse variance weighted analysis showed that higher levels of sterol ester (SE) (27:1/16:0) and other plasma lipidome were causally associated with increased bladder cancer risk. Similarly, elevated levels of phosphatidylcholine (16:0_22:6) and others were linked to increased kidney cancer risk. For prostate cancer, higher levels of SE (27:1/17:0) and others were associated with increased risk, while higher levels of SE (27:1/18:2) and others were associated with decreased risk. The study provides strong evidence for the causal relationships between plasma lipidome and bladder, kidney, and prostate cancers. These findings illuminate complex lipid metabolism pathways in urinary system cancer etiology and highlight specific lipid structures' differential impact on cancer risk. This research lays a foundation for further exploring biological mechanisms and developing early screening tools and targeted therapies for urological cancers.
血浆脂质组已被发现与炎症、肥胖、衰老及其他疾病（包括各种癌症）密切相关。然而，特定血浆脂质种类与泌尿系统癌症风险之间的因果关系仍不清楚。本研究旨在使用两样本孟德尔随机化（MR）方法，调查179种脂质种类与3种常见泌尿系统癌症之间的因果关系。分析了179种脂质种类的大规模全基因组关联研究数据集，以评估血浆脂质组与泌尿系统癌症（包括膀胱癌、肾癌和前列腺癌）之间的关联。采用逆方差加权法作为主要分析方法，并辅以MR-Egger回归、加权中位数、加权模式和简单模式方法，以确保研究结果的可靠性。进行了敏感性分析，包括 Cochr an Q检验、MR-Egger截距检验、MR多效性残差总和及离群值检验和留一法分析，以评估因果关系的稳定性和稳健性。逆方差加权分析表明，较高水平的甾醇酯（SE）（27:1/16:0）和其他血浆脂质组与膀胱癌风险增加存在因果关系。同样，磷脂酰胆碱（16:0_22:6）等水平升高与肾癌风险增加有关。对于前列腺癌，较高水平的SE（27:1/17:0）等与风险增加有关，而较高水平的SE（27:1/18:2）等与风险降低有关。该研究为血浆脂质组与膀胱癌、肾癌和前列腺癌之间的因果关系提供了有力证据。这些发现阐明了泌尿系统癌症病因中复杂的脂质代谢途径，并突出了特定脂质结构对癌症风险的不同影响。本研究为进一步探索生物学机制以及开发泌尿系统癌症的早期筛查工具和靶向治疗奠定了基础。
