Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.
Hospital Office, The Second Xiangya Hospital, Central South University, Changsha, China.
Neuroendocrinology. 2024;114(11):981-992. doi: 10.1159/000541298. Epub 2024 Sep 9.
Neuroendocrine tumors (NETs) are a heterogeneous group of epithelial tumors originating from different anatomical sites, and identifying the gut microbiota and metabolic mechanisms involved in the onset of NETs may help to develop appropriate disease prevention and monitoring strategies.
We employed a mediated two-sample Mendelian randomization (MR) approach, analyzing gut microbiota from German studies and NET datasets from the 10th round of the FinnGen project. Mediation analyses were conducted using the metabolites dataset from the Canadian Longitudinal Study of Aging (CLSA) and the TwinsUK study. Instrumental variables were chosen according to established MR criteria and analyzed using the Wald ratio, inverse-variance weighted (IVW), MR-Egger, and weighted median methods. To ensure robustness, sensitivity analyses were performed using Cochrane's Q, Egger's intercept, MR-PRESSO, and leave-one-out methods.
Causal relationships were identified between the genetic determinants of 6, 5, 2, 1, 2, 3 gut microbiotas and the risk of colorectal, lung, pancreatic, rectum, small intestine, and stomach NETs. Similarly, the genetic determinants of 4, 6, 1, 5, 10, and 7 metabolites were found to be causally related to the risk of colorectal, lung, pancreatic, rectum, small intestine, and stomach NETs, respectively. Through Wald ratio and IVW methods, we preliminarily identified 957 microbiota-metabolite pairs with significant causal associations and formed 13 mediated relationships between the impact of gut microbiotas on NETs.
Our study suggests that gut microbiotas and its derived metabolites may contribute to the onset of NET, offering a novel insight into the disease's pathogenesis.
神经内分泌肿瘤（NETs）是一组起源于不同解剖部位的上皮肿瘤，确定与 NET 发病相关的肠道微生物群和代谢机制，可能有助于制定适当的疾病预防和监测策略。
我们采用中介两样本孟德尔随机化（MR）方法，分析了德国研究中的肠道微生物群和 FinnGen 项目第 10 轮的 NET 数据集。使用加拿大老龄化纵向研究（CLSA）和英国双胞胎研究（TwinsUK）的代谢物数据集进行中介分析。根据既定的 MR 标准选择工具变量，并使用 Wald 比、逆方差加权（IVW）、MR-Egger 和加权中位数方法进行分析。为了确保稳健性，使用 Cochrane's Q、Egger 的截距、MR-PRESSO 和逐一剔除方法进行敏感性分析。
鉴定出 6、5、2、1、2、3 种肠道微生物组的遗传决定因素与结直肠、肺、胰腺、直肠、小肠和胃 NET 发病风险之间存在因果关系。同样，鉴定出 4、6、1、5、10 和 7 种代谢物的遗传决定因素与结直肠、肺、胰腺、直肠、小肠和胃 NET 发病风险之间存在因果关系。通过 Wald 比和 IVW 方法，我们初步鉴定出 957 对具有显著因果关联的微生物组-代谢物对，并形成了肠道微生物组对 NET 影响的 13 个中介关系。
本研究表明，肠道微生物群及其衍生代谢物可能参与 NET 的发病，为该疾病的发病机制提供了新的见解。
