INTEGRATING THE METPA AND IPA TO VERIFY THE BIOLOGICAL FUNCTION OF THE POTENTIAL BIOMARKERS FROM PLASMA METABONOMICS IN DIABETIC RATS

Introduction: A massive endogenous metabolite in the Type 2 diabetes are generated by the research on metabonomics, however, we don't clearly know the causality relationship in potential biomarkers and the disease. Aim of this study is to provide an efficient strategy to verify the biological function of the potential biomarkers from untargeted metabolomics.Materials and methods:The combination of Metabolomic Pathway Analysis (MetPA) and Ingenuity Pathway Analysis (IPA) software to characterize diabetic rats' 7 potential biomarkers' biological function. MetPA was performed to generate a scatter plot to trace the pathway impact size. IPA was executed to produce the canonical pathways and upstream regulators.Results: 4 metabolites pathways, 12 canonical pathways, 7 upstream regulators (RAS, NFkB, S1PR1-5,et al) were activity predictor for the identification of the 7 potential biomarkers.Conclusion: Our study highlights the use of metabolomic methods and algorithms as an available strategy that may provide new directions for treating candidate metabolomic biomarkers, which enhance to dissect the biological function of the biomarkers from untargeted metabolomics.

引言：代谢组学研究发现2型糖尿病中存在大量内源性代谢物，然而，我们并不清楚潜在生物标志物与疾病之间的因果关系。本研究的目的是提供一种有效的策略来验证非靶向代谢组学中潜在生物标志物的生物学功能。 材料和方法：结合代谢组学通路分析（MetPA）和 Ingenuity通路分析（IPA）软件来表征糖尿病大鼠7种潜在生物标志物的生物学功能。进行MetPA以生成散点图来追踪通路影响大小。执行IPA以产生经典通路和上游调节因子。 结果：4种代谢物通路、12条经典通路、7种上游调节因子（RAS、NFkB、S1PR1 - 5等）是识别7种潜在生物标志物的活性预测因子。 结论：我们的研究强调了代谢组学方法和算法作为一种可行策略的应用，它可能为治疗候选代谢组学生物标志物提供新的方向，有助于剖析非靶向代谢组学中生物标志物的生物学功能。