实用医学杂志 ›› 2024, Vol. 40 ›› Issue (21): 3023-3030.doi: 10.3969/j.issn.1006-5725.2024.21.010

• 临床研究 • 上一篇    下一篇

深部浸润型子宫内膜异位症病灶微生物组学研究

黄平1,兰康云1,梁炎春2,3,陈勍4,金瑛5,陈光元1,牛刚2,3()   

  1. 1.深圳市宝安区松岗人民医院,妇科,(广东 深圳 518000 )
    2.深圳市宝安区松岗人民医院,病理科,(广东 深圳 518000 )
    2.中山大学附属第一医院妇科 (广东 广州 510080 )
    3.广东省妇产疾病临床医学研究中心 (广东 广州 510080 )
    4.中山大学孙逸仙纪念医院妇产科 (广东 广州 510120 )
  • 收稿日期:2024-07-11 出版日期:2024-11-10 发布日期:2024-11-19
  • 通讯作者: 牛刚 E-mail:niugang@mail.sysu.edu.cn
  • 基金资助:
    国家自然科学基金项目(82071618);广东省科技创新战略专项资金项目(2023A1515010018);深圳市宝安区基础研究医疗卫生类项目(2021JD235)

Microbiome study of deep invasive endometriosis lesions

Ping HUANG1,Kangyun LAN1,Yanchun LIANG2,3,Qing CHEN4,Ying JIN5,Guangyuan CHEN1,Gang. NIU2,3()   

  1. *.Department of Obstetrics and Gynecology,Shenzhen Baoan distric SongGang People′s Hospital,Shenzhen 518000,Guangdong,China
  • Received:2024-07-11 Online:2024-11-10 Published:2024-11-19
  • Contact: Gang. NIU E-mail:niugang@mail.sysu.edu.cn

摘要:

目的 探讨深部浸润型子宫内膜异位症病灶微生物组学,为其发病机制、诊断及治疗提供新思路。 方法 将手术病理证实为深部浸润子宫内膜异位症患者及子宫内膜正常健康育龄期女性纳入研究,收集正常子宫内膜(正常组,n = 10)、深部浸润型子宫内膜异位症患者在位内膜(DIE在位内膜组,n = 14)及病灶(DIE病灶组,n = 10),进行16s rRNA测序。使用细菌群落多样性算法(alpha多样性、beta多样性)、主坐标分析(PCoA)距离矩阵算法(Bray-Curtis和Unifrac矩阵)、生物学标识算法(LeFSe)找出组间微生物组学差异,相关的差异细菌及KEGG功能富集。 结果 3组菌群多样性无显著性差异,β多样性差异有统计学意义(P = 0.005 5)。病灶组在门水平上厚壁菌门(Firmicutes)丰度相对较低,梭杆菌门(Fusobacteria)丰度相对增加。在属水平上肠球菌属(Enterococcus),普雷沃特拉菌属(Prevotella)丰度相对增加。LEFse分析提示病灶组中微生物菌群中以变形菌门(Proteobacteria)、伽马变形菌纲(Gammaproteobacteria)占主要优势。3组微生物菌群之间的关键差异物种有伽马变形菌门,其差异有统计学意义(P = 0.021 2)。 结论 相较于正常组及DIE在位内膜组,DIE病灶组梭杆菌门、变形菌门、伽马变形菌纲、肠球菌属和普雷沃特拉菌属的丰度显著增加,为深部浸润型子宫内膜异位症预防和干预提供新的治疗靶点。

关键词: 深部浸润型子宫内膜异位症, 微生物组学, 肠道菌群

Abstract:

Objective To investigate the microbiome composition of deep invasive endometriosis lesions, offering novel insights into its pathogenesis, diagnosis, and treatment strategies. Methods From May 2021 to May 2022, we collected samples of normal endometrium (normal group, n = 10), endometrium from patients with deep infiltrating endometriosis (DIE endometrium group, n = 14), and lesions from these patients (DIE lesion group, n = 10) for 16s rRNA sequencing analysis. We employed the bacterial community diversity algorithm (alpha diversity and beta diversity), principal coordinate analysis (PCoA) distance matrix algorithms (Bray?Curtis and Unifrac matrices), as well as the biological identification algorithm (LeFSe) to investigate microbiome differences between groups and identify differentially abundant bacteria and enriched KEGG functions. Results The diversity of the three groups did not show any significant difference, while the β diversity exhibited a statistically significant distinction (P = 0.005 5). The focus group had a relatively low abundance of Firmicutes at the phylum level and a relatively increased abundance of Fusobacteria. At the genus level, there was an increased relative abundance of Enterococcus and Prevotella. LEFse analysis suggested that Proteobacteria and Gammaproteobacteria were the main dominant in the lesion group. Notably, Gamma proteobacteria emerged as a key differential species among the three groups' microbial flora with statistical significance (P = 0.021 2). Conclusion Compared to the normal group and DIE group, there was a significant increase in the abundance of Fusobacteria, Proteobacteria, Gammaproteobacteria, Enterococcus, and Prevotella. These findings offer novel therapeutic targets for the prevention and intervention of deep infiltrating endometriosis.

Key words: deep invasive endometriosis, microbiome, gut microbiome

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