Targeted UPLC-MS/MS high-throughput metabolomics approach to assess the purine and pyrimidine metabolism.

Purines and pyrimidines, the important components of DNA and RNA, are closely related to metabolic syndrome and disorder, such as renal disease, gout and diabetic nephropathy etc. Given the importance of the biological significance of purines and pyrimidines, it is necessary to further develop a rapid and sensitive method for practical detection of a large-scale analyses. In this study, based on 96-well solid phase extraction plates-ultra performance liquid chromatography-triple quadrupole mass spectrometry (SPE-UPLC-QqQ-MS/MS), a novel approach for simultaneous determination of 23 purines and pyrimidines in biological samples was developed. First, plasma samples were pretreated by SPE using 96-well plates, which lead to an automated, simplified and rapid sample preparation process. In the methodology development, a large-scale test was performed to evaluate the stability and reliability of the approach. Finally, the levels of purines and pyrimidines in the biological samples were analyzed by this strategy. Experimental results showed that lowest limit of quantification (LLOQ) range from 6.678 × 10-2 µg/mL to 4.275 × 10-6 µg/mL; intra- and inter-day precision are <15% for all analytes. The stability and maximal capability of a single analytical batch could be extended to at least 431 injections (about 70 h). Analysis time of a single run was controlled in 10 min. Under the optimized conditions, wide linear ranges and good correlation coefficients (R2 > 0.99) were acquired. The successful development of this method provides a feasible protocol for a large-scale metabolomics study and it also lays the foundation of quantitative analysis in endogenous analytes.

Plasma metabolic profiling analysis of Strychnos nux-vomica Linn. and Tripterygium wilfordii Hook F-induced renal toxicity using metabolomics coupled with UPLC/Q-TOF-MS.

Both Strychnos nux-vomica Linn. (SNV) and Tripterygium wilfordii Hook F (TwHF) have received extensive attention due to their excellent clinical efficacies. However, clinical applications of SNV and TwHF have been limited by their narrow therapeutic windows and severe kidney toxicities. In this paper, based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS), endogenous metabolites after administration of SNV and TwHF extracts were detected, and biomarkers were screened successfully. Additionally, the levels of Cr and BUN in serum and pathological findings of kidneys were detected and observed. Finally, both biochemical and pathological tests of the SNV group and TwHF group indicated that kidney damage had occurred. After comparison with the normal saline group, 15 nephrotoxic biomarkers were selected from the SNV group, and 17 nephrotoxic biomarkers were selected from the TwHF group. The experimental results showed that there are some differences in the mechanisms of nephrotoxicity induced by SNV and TwHF, which are significant for revealing the mechanisms of renal injury of different medicines.

Metabolomics study on primary dysmenorrhea patients during the luteal regression stage based on ultra performance liquid chromatography coupled with quadrupole­time­of­flight mass spectrometry.

Primary dysmenorrhea (PD) is a common gynecological disorder which, while not life­threatening, severely affects the quality of life of women. Most patients with PD suffer ovarian hormone imbalances caused by uterine contraction, which results in dysmenorrhea. PD patients may also suffer from increases in estrogen levels caused by increased levels of prostaglandin synthesis and release during luteal regression and early menstruation. Although PD pathogenesis has been previously reported on, these studies only examined the menstrual period and neglected the importance of the luteal regression stage. Therefore, the present study used urine metabolomics to examine changes in endogenous substances and detect urine biomarkers for PD during luteal regression. Ultra performance liquid chromatography coupled with quadrupole­time­of­flight mass spectrometry was used to create metabolomic profiles for 36 patients with PD and 27 healthy controls. Principal component analysis and partial least squares discriminate analysis were used to investigate the metabolic alterations associated with PD. Ten biomarkers for PD were identified, including ornithine, dihydrocortisol, histidine, citrulline, sphinganine, phytosphingosine, progesterone, 17­hydroxyprogesterone, androstenedione, and 15­keto­prostaglandin F2α. The specificity and sensitivity of these biomarkers was assessed based on the area under the curve of receiver operator characteristic curves, which can be used to distinguish patients with PD from healthy controls. These results provide novel targets for the treatment of PD.

Screening and verifying endometrial carcinoma diagnostic biomarkers based on a urine metabolomic profiling study using UPLC-Q-TOF/MS.

BACKGROUND: Endometrial carcinoma (EOC) is a gynecological disease with one of the highest worldwide incidences. Due to the lack of typical clinical symptoms and limited sensitive screening methods used to diagnose endometrial carcinoma, the disease is easily neglected before patients are aware of its presence. Therefore, EOC results in serious impacts on women's lives and health. We screened diagnostic biomarkers of EOC with a noninvasive method that compared healthy individuals and endometrial hyperplasia (EOH) patients. METHODS: The morning urine of 25 healthy individuals, 25 patients with EOC and 10 patients with EOH were analyzed using an ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) platform. Metabolomics data were used to screen the different metabolites according to principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) analyses. Furthermore, the screened biomarkers of the newly diagnosed EOC and EOH candidates and healthy individuals were verified using the predictive model of the support vector machine (SVM) to obtain EOC diagnostic biomarkers. RESULTS: An EOC diagnostic biomarker group was found according to the metabolomics method. Five diagnostic biomarkers, including porphobilinogen, acetylcysteine, N-acetylserine, urocanic acid and isobutyrylglycine, were significantly changed in the EOC patients. Among them, porphobilinogen and acetylcysteine were significantly down-regulated, while N-acetylserine, urocanic acid and isobutyrylglycine were significantly up-regulated. CONCLUSIONS: Disturbances in these biomarkers have negative impacts on the body's metabolic functioning. The EOC diagnostic biomarker group can provide a clinical reference for diagnosing EOC and insight into the diagnosis of other diseases in the clinic.