Real-time quantitative reverse transcription-polymerase chain reaction to detect propionibacterial ribosomal RNA in the lymph nodes of Chinese patients with sarcoidosis

实时定量逆转录-聚合酶链式反应检测中国结节病患者淋巴结中丙酸杆菌核糖体RNA

阅读:1

Abstract

The aim of this study was to investigate the diagnostic value of using the copy number of propionibacterial rRNA as a biomarker for sarcoidosis. Ribosomal RNA of Propionibacterium acnes and P. granulosum was measured by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR) using formalin-fixed and paraffin-embedded tissue of lymph node biopsy from 65 Chinese patients with sarcoidosis, 45 with tuberculosis and 50 controls with other diseases (23 with non-specific lymphadenitis and 27 with mediastinal lymph node metastasis from lung cancer). The receiver operating characteristic (ROC) curve was analysed to determine an optimal cut-off value for diagnosis, and the diagnostic accuracy of the cut-off value was evaluated in additional tissue samples [24 patients with sarcoidosis and 22 with tuberculosis (TB)]. P. acnes or P. granulosum rRNA was detected in 48 of the 65 sarcoidosis samples but only in four of the 45 TB samples and three of the 50 control samples. Analysis of the ROC curve revealed that an optimal cut-off value of the copy number of propionibacterial rRNA for diagnosis of sarcoidosis was 50·5 copies/ml with a sensitivity and specificity of 73·8 and 92·6%, respectively. Based on the cut-off value, 19 of the 24 additional sarcoidosis samples exhibited positive P. acnes or P. granulosum, whereas only one of the 22 additional TB samples was positive, resulting in a sensitivity and specificity of 79·2 and 95·5%, respectively. These findings suggest that propionibacteria might be associated with sarcoidosis granulomatous inflammation. Detection of propionibacterial rRNA by RT-PCR might possibly distinguish sarcoidosis from TB.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。