Lipidomics as a tool of predicting progression from non-alcoholic fatty pancreas disease to type 2 diabetes mellitus

Abstract

The lipid metabolism relationship between non-alcoholic fatty pancreas disease (NAFPD) and type 2 diabetes mellitus (T2DM) is poorly defined. We aim to identify novel T2DM-related lipid biomarkers in addition to previous studies and provide the evidence for elucidating the relationship between NAFPD and T2DM in a lipid perspective. In this study, multi-dimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) was used to investigate the potential discriminating lipid profile of the fasting plasma of 105 Chinese individuals (39 NAFPD patients, 38 T2DM patients and 30 healthy controls). Then multivariate statistical analysis combined with pathway analysis was performed to identify the lipid biomarker and explore the potential relationship of these two important diseases. The results described a marked reduction of plasmalogen and a significant 4-hydroxynonenal increase in the two diagnostic group, which indicated increased oxidative stress and peroxisomal dysfunction in patients. 60 discriminating metabolites were identified by multivariate statistical analysis of the lipidomics data. In addition, ingenuity pathway analysis (IPA) and a metabolic network constructed by prediction of IPA indicated that lipid metabolism, molecular transport, carbohydrate metabolism and small molecule biochemistry were correlated with disease progression. Our results revealed that the profile of plasma lipid alteration characteristic of NAFPD was similar to that of T2DM, especially during the period prior to the onset of T2DM.