Urine-based metabolomic analysis of patients with Clostridium difficile infection: a pilot study

被引:1
|
作者
Kao, Dina [1 ,2 ,4 ]
Ismond, Kathleen P. [1 ,2 ,3 ]
Tso, Victor [1 ,2 ,3 ]
Millan, Braden [1 ,2 ]
Hotte, Naomi [1 ,2 ]
Fedorak, Richard N. [1 ,2 ,3 ]
机构
[1] Univ Alberta, Div Gastroenterol, Dept Med, Edmonton, AB, Canada
[2] Univ Alberta, CEGIIR, Edmonton, AB, Canada
[3] Metabol Technol Inc, Edmonton, AB, Canada
[4] Univ Alberta, Zeidler Ledcor Ctr, Edmonton, AB T6G 2X8, Canada
关键词
Predictor; Metabolomics; Clostridium difficile infection; Recurrent Clostridium difficile infection; METABOLITES; MICROBIOTA; CHOLINE; RISK;
D O I
10.1007/s11306-016-1080-z
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Introduction Recurrent Clostridium difficile infection (CDI) is associated with intestinal dysbiosis. Currently, there is no diagnostic test to predict at-risk patients for CDI recurrences. Urine metabolomics may have prognostic value, but have not been characterized in this patient population. Objective The aim of this pilot study was to profile the urine metabolomics of patients with various frequencies of CDI. Methods Spot urine samples were prospectively collected from 31 adults who at various stages of recurrent CDI (1 to >5 episodes). Patients were age-and sex-matched in a 1:1 ratio with healthy controls. Urine metabolomics was performed and spectra were assessed using Chenomx NMRSuite v7 and analyzed using multivariate statistics with MetaboAnalyst 3.0. Stool metagenomic analyses were performed in six patients with >3 episodes of CDI and compared to 7 healthy controls, which were correlated with urine metabolomics. Results Using 53 metabolites, a two-component, partial least squares-discriminant analysis (PLS-DA) was built that clearly discriminated between healthy controls and CDI patients. The anticipated gender-based difference was not found within the CDI patient group. However, separations between (1) healthy control and CDI patients, as well as (2) patients with different episodes of CDI were possible and the permutations found were significant. Furthermore, choline was found to be the single most important urine metabolite separating healthy controls from CDI patients, and the microbiota from recurrent CDI patients was found to have decreased abundance of choline metabolizing bacteria. Conclusions Using small groups in a preliminary study, we have demonstrated that urine metabolomics has the potential to distinguish between healthy controls and patients with CDI. Furthermore, it could discriminate between patients experiencing different frequencies of recurrent CDI. If validated in larger cohorts, urine metabolomics has potential at identifying patients who are at risk for recurrent CDI. The significance of choline-deficient microbiota in CDI patients should be further examined.
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