微生物群
子宫内膜异位症
医学
生物
计算生物学
产科
生物信息学
妇科
作者
Farideh Z. Bischoff,Yanqin Yu,Lu Shen,Winghing Wong,Xu Zhu,Xinmei Zhang
标识
DOI:10.1097/aog.0000000000005917.096
摘要
INTRODUCTION: The clinical presentation of endometriosis varies widely, from asymptomatic to severe with often infertility also presented. Screening methods today include imaging, which is subject to operator expertise and poor specificity. Given the potential role of uterine dysbiosis in endometriosis onset or progression, we demonstrate efficacy in screening for endometriosis by using bioinformatics to assess uterine biome composition among women about to undergo surgery for suspected endometriosis. METHODS: Under IRB approval, uterine tissue biopsies were obtained from (n=98) women prior to undergoing laparoscopy surgery with histology for suspected endometriosis. The endometrial microbiome profile was determined based on barcoded sequencing of the bacterial 16S rRNA gene. Bioinformatic/statistical analysis to identify and quantify the composition of the abnormal and normal bacteria was performed. RESULTS: Of the 98 cases, 54 cases were histologically confirmed to be positive for endometriosis. Molecular analysis of the microbiome revealed that 35 of the endometriosis confirmed cases (65%) had an abnormal microbiome composition. When comparing early- to late-stage endometriosis, 7 of 10 (70%) and 25 of 44 (57%) cases, respectively, displayed abnormal microbiomes with a higher prevalence of Gardnerella and Streptococcus . In contrast, of the 44 endometriosis-negative cases, microbiome composition was abnormal in 15 (34%) cases. CONCLUSIONS/IMPLICATIONS: These data suggest that uterine microbiome analysis may serve as a screen test to identify women at risk for endometriosis, potentially enabling earlier detection and intervention. Further studies are underway to evaluate the efficacy of this approach.
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