Khanna Sahil, Montassier Emmanuel, Schmidt Bradley, Patel Robin, Knights Daniel, Pardi Darrell S, Kashyap Purna
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN.
EA 3826 Thérapeutiques Cliniques et Expérimentales des Infections, Faculté de Médecine, Université de Nantes, Nantes, France.
Aliment Pharmacol Ther. 2016 Oct;44(7):715-727. doi: 10.1111/apt.13750. Epub 2016 Aug 2.
BACKGROUND: Clostridium difficile infection (CDI) may not respond to initial therapy and frequently recurs, but predictors of response and recurrence are inconsistent. The impact of specific alterations in the gut microbiota determining treatment response and recurrence in patients with CDI is unknown. AIM: To assess microbial signatures as predictors of treatment response and recurrence in CDI. METHODS: Pre-treatment stool samples and clinical metadata including outcomes were collected prospectively from patients with their first CDI episode. Next generation 16s rRNA sequencing using MiSeq Illumina platform was performed and changes in microbial community structure were correlated with CDI outcomes. RESULTS: Eighty-eight patients (median age 52.7 years, 60.2% female) were included. Treatment failure occurred in 12.5% and recurrence after response in 28.5%. Patients who responded to treatment had an increase in Ruminococcaceae, Rikenellaceae, Clostridiaceae, Bacteroides, Faecalibacterium and Rothia compared to nonresponders. A risk-index built from this panel of microbes differentiated responders (mean 0.07 ± 0.24) from nonresponders (0.52 ± 0.42; P = 0.0002). Receiver operating characteristic (ROC) curve demonstrated that risk-index was a strong predictor of treatment response with an area under the curve (AUC) of 0.85. Among clinical parameters tested, only proton pump inhibitor use predicted recurrent CDI (OR 3.75, 95% CI 1.27-11.1, P = 0.01). Patients with recurrent CDI had statistically significant increases in Veillonella, Enterobacteriaceae, Streptococci, Parabacteroides and Lachnospiraceae compared to patients without recurrence and a risk index was able to predict recurrence (AUC = 0.78). CONCLUSION: Gut microbiota signatures predict treatment response and recurrence potentially, allowing identification of patients with Clostridium difficile infection that may benefit from early institution of alternate therapies.
背景:艰难梭菌感染(CDI)可能对初始治疗无反应且频繁复发,但反应和复发的预测因素并不一致。肠道微生物群的特定改变对CDI患者治疗反应和复发的影响尚不清楚。 目的:评估微生物特征作为CDI治疗反应和复发的预测指标。 方法:前瞻性收集首次发生CDI发作患者的治疗前粪便样本和包括结局在内的临床元数据。使用Illumina MiSeq平台进行下一代16s rRNA测序,并将微生物群落结构的变化与CDI结局相关联。 结果:纳入88例患者(中位年龄52.7岁,60.2%为女性)。治疗失败率为12.5%,治疗有效后复发率为28.5%。与无反应者相比,治疗有反应的患者瘤胃球菌科、理研菌科、梭菌科、拟杆菌属、粪杆菌属和罗氏菌属增加。由这一组微生物构建的风险指数区分了有反应者(平均0.07±0.24)和无反应者(0.52±0.42;P = 0.0002)。受试者工作特征(ROC)曲线表明,风险指数是治疗反应的有力预测指标,曲线下面积(AUC)为0.85。在所测试的临床参数中,只有使用质子泵抑制剂可预测复发性CDI(OR 3.75,95%CI 1.27 - 11.1,P = 0.01)。与未复发患者相比,复发性CDI患者的韦荣球菌属、肠杆菌科、链球菌属、副拟杆菌属和毛螺菌科有统计学意义的增加,且风险指数能够预测复发(AUC = 0.78)。 结论:肠道微生物群特征可能预测治疗反应和复发,有助于识别可能从早期采用替代疗法中获益的艰难梭菌感染患者。
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