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Gas chromatography-mass spectrometric method-based urine metabolomic profile of rats with pelvic inflammatory disease

Pelvic inflammatory disease (PID) can lead to a poor outcome of severe sequelae, and the current methods of clinical diagnosis are not satisfactory. Metabolomics is an effective method for the identification of disease-related metabolite biomarkers to facilitate disease diagnosis. However, to the be...

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Detalles Bibliográficos
Autores principales: ZOU, WEI, WEN, XIAOKE, SHENG, XIAOQI, ZHENG, YI, XIAO, ZUOQI, LUO, JIEYING, CHEN, SHUQIONG, WANG, YICHAO, CHENG, ZENENG, XIANG, DAXIONG, NIE, YICHU
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4840532/
https://www.ncbi.nlm.nih.gov/pubmed/27168785
http://dx.doi.org/10.3892/etm.2016.3142
Descripción
Sumario:Pelvic inflammatory disease (PID) can lead to a poor outcome of severe sequelae, and the current methods of clinical diagnosis are not satisfactory. Metabolomics is an effective method for the identification of disease-related metabolite biomarkers to facilitate disease diagnosis. However, to the best of our knowledge, no PID-associated metabolomic study has yet been carried out. The metabolomic changes of rats with PID were investigated in the present study. A PID model was constructed by the multi-pathogenic infection of the upper genital tract in rats. Infiltration of inflammatory cells and elevated expression levels of the cytokines interleukin (IL)-1β and IL-6 in the uterus and fallopian tubes validated the disease model. Gas chromatography-mass spectrometry coupled with derivatization was used to determine the urine metabolomic profile. Principal component analysis and partial least squares-discriminant analysis of the data sets showed a clear separation of metabolic profiles between rats with PID and control rats. Eighteen differentiating metabolites were found, including four amino acids, three fatty acids, nine organic acids, and two sugars, which indicated alterations in sugar metabolism, the citric acid cycle, amino acid metabolism and fatty acid metabolism. These metabolites could be potential biomarkers of PID, and this research may offer a new approach to evaluate the effect of anti-PID drugs in pre-clinical or clinical trials.