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© Research
Publication : GigaScience

Lipidomic profiling reveals distinct differences in plasma lipid composition in healthy, prediabetic, and type 2 diabetic individuals.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in GigaScience - 01 Jul 2017

Zhong H, Fang C, Fan Y, Lu Y, Wen B, Ren H, Hou G, Yang F, Xie H, Jie Z, Peng Y, Ye Z, Wu J, Zi J, Zhao G, Chen J, Bao X, Hu Y, Gao Y, Zhang J, Yang H, Wang J, Madsen L, Kristiansen K, Ni C, Li J, Liu S,

Link to Pubmed [PMID] – 28505362

Link to DOI – 10.1093/gigascience/gix036

Gigascience 2017 07; 6(7): 1-12

The relationship between dyslipidemia and type 2 diabetes mellitus (T2D) has been extensively reported, but the global lipid profiles, especially in the East Asia population, associated with the development of T2D remain to be characterized. Liquid chromatography coupled to tandem mass spectrometry was applied to detect the global lipidome in the fasting plasma of 293 Chinese individuals, including 114 T2D patients, 81 prediabetic subjects, and 98 individuals with normal glucose tolerance (NGT). Both qualitative and quantitative analyses revealed a gradual change in plasma lipid features with T2D patients exhibiting characteristics close to those of prediabetic individuals, whereas they differed significantly from individuals with NGT. We constructed and validated a random forest classifier with 28 lipidomic features that effectively discriminated T2D from NGT or prediabetes. Most of the selected features significantly correlated with diabetic clinical indices. Hydroxybutyrylcarnitine was positively correlated with fasting plasma glucose, 2-hour postprandial glucose, glycated hemoglobin, and insulin resistance index (HOMA-IR). Lysophosphatidylcholines such as lysophosphatidylcholine (18:0), lysophosphatidylcholine (18:1), and lysophosphatidylcholine (18:2) were all negatively correlated with HOMA-IR. The altered plasma lipidome in Chinese T2D and prediabetic subjects suggests that lipid features may play a role in the pathogenesis of T2D and that such features may provide a basis for evaluating risk and monitoring disease development.

https://pubmed.ncbi.nlm.nih.gov/28505362