Dyslipidemia is a hallmark of T2DM, and as such, analyses of lipid metabolic profiles in affected patients have the potential to permit the development of an integrated lipid metabolite-based biomarker model that can facilitate early patient diagnosis and treatment.
Untargeted and targeted lipidomics approaches were used to analyze serum samples from newly diagnosed 93 Chinese participants in discovery cohort and 440 in validation cohort
Through these analyses, we developed a novel integrated biomarker signature composed of LPC 22:6, PC(16:0/20:4), PE(22:6/16:0), Cer(d18:1/24:0)/SM(d18:1/19:0), Cer(d18:1/24:0)/SM(d18:0/16:0), TG(18:1/18:2/18:2), TG(16:0/16:0/20:3), and TG(18:0/16:0/18:2). The area under the curve (AUC) values for this integrated biomarker signature for prediabetes and T2DM patients were 0.841 (cutoff: 0.565) and 0.894 (cutoff: 0.633), respectively. Furthermore, theresults of western blot analysis of frozen adipose tissue from 3 week (prediabetes) and 12 week (T2DM) Goto–Kakizaki (GK) rats also confirmed that acid sphingomyelinase is responsible for significant disruptions in ceramide and sphingomyelin homeostasis. Network analyses of the biomarkers associated with this biosignature suggested that the most profoundly affected lipid metabolism pathways in the context of diabetes include