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Open access

Jia Li, Yan Zhao, Caoxin Huang, Zheng Chen, Xiulin Shi, Long Li, Zhong Chen and Xuejun Li

Objective

Exercise benefits people with nonalcoholic fatty liver disease (NAFLD). The aim of this study was to identify a panel of biomarkers and to provide the possible mechanism for the effect of exercise on NAFLD patients via an untargeted mass spectrometry-based serum metabolomics study.

Methods

NAFLD patients were classified randomly into a control group (n = 74) and a 6-month vigorous exercise (n = 68) group. Differences in serum metabolic profiles were analyzed using untargeted ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to validate the differences between these two groups, and altered metabolites were obtained by ANOVA (fold change >2, P < 0.05) and identified with the online database Metlin and an in-house database.

Results

Metabolic profiling and multiple statistical analyses of the serum samples indicated significant differences between the NAFLD patients in the control and the 6-month vigorous exercise groups. Finally, 36 metabolites were identified between the control vs exercise groups. These metabolites were mainly associated with glycerophospholipid- and sphingolipid-related pathways.

Conclusion

Our study demonstrates that glycerophospholipid and sphingolipid alterations may contribute to the mechanism underlying the effect of exercise on NAFLD patients. A LC-MS-based metabolomics approach has a potential value for screening exercise-induced biomarkers.

Open access

Hui Long, Yanhong Nie, Li Wang, Yong Lu, Yan Wang, Yijun Cai, Zhen Liu, Miaomiao Jia, Qifeng Lyu, Yanping Kuang and Qiang Sun

AMH as a promising predictor of ovarian response has been studied extensively in women undergoing assisted reproductive technology treatment, but little is known about its prediction value in monkeys undergoing ovarian stimulation. In the current study, a total of 380 cynomolgus monkeys ranging from 5 to 12 years received 699 ovarian stimulation cycles. Serum samples were collected for AMH measure with enzyme-linked immunosorbent assay. It was found that serum AMH levels were positive correlated with the number of retrieved oocytes (P < 0.01) in the first, second and third stimulation cycles. In the first cycles, area under the curve (ROCAUC) of AMH is 0.688 for low response and 0.612 for high response respectively, indicating the significant prediction values (P = 0.000 and P = 0.005). The optimal AMH cutoff value was 9.68 ng/mL for low ovarian response and 15.88 ng/mL for high ovarian response prediction. In the second stimulation cycles, the significance of ROCAUC of AMH for high response rather than the low response was observed (P = 0.001 and P = 0.468). The optimal AMH cutoff value for high ovarian response was 15.61 ng/mL. In the third stimulation cycles, AMH lost the prediction value with no significant ROCAUC. Our data demonstrated that AMH, not age, is a cycle-dependent predictor for ovarian response in form of oocyte yields, which would promote the application of AMH in assisted reproductive treatment (ART) of female cynomolgus monkeys. AMH evaluation would optimize candidate selection for ART and individualize the ovarian stimulation strategies, and consequentially improve the efficiency in monkeys.