Zhong Xunlong, Xiao Chang, Wang Ruolun, Deng Yunfeng, Du Tao, Li Wangen, Zhong Yanmei, Tan Yongzhen
Department of Pharmacy, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Department of Endocrinology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Heliyon. 2024 Feb 13;10(4):e26326. doi: 10.1016/j.heliyon.2024.e26326. eCollection 2024 Feb 29.
Dyslipidemia often accompanies type 2 diabetes mellitus (T2DM). Elevated blood glucose in patients commonly leads to high levels of lipids. Lipid molecules can play a crucial role in early detection, treatment, and prognosis of T2DM with dyslipidemia. Previous lipid studies on T2DM mainly focused on Western diabetic populations with elevated blood glucose. In this research, we investigate both high blood sugar and high lipid levels to better understand changes in plasma lipid metabolism in newly diagnosed Chinese T2DM patients with dyslipidemia (NDDD). We used a plasma lipid analysis method based on ultra-high performance liquid chromatography coupled with mass spectrometry technology (UHPLC-MS) and statistical analysis to characterize lipid profiles and identify potential biomarkers in NDDD patients compared to healthy control (HC) subjects. Additionally, we examined the differences in lipid profiles between hyperlipidemia (HL) patients and HC subjects. We found significant changes in 15 and 23 lipid molecules, including lysophosphatidylcholine (LysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), and ceramide (Cer), in the NDDD and HL groups compared to the HC group. These altered lipid molecules are associated with five metabolic pathways, with sphingolipid metabolism and glycerophospholipid metabolism being the most relevant to glucose and lipid metabolism changes. These lipid biomarkers are strongly correlated with traditional markers of glucose and lipid metabolism. Notably, Cer(d18:1/24:0), SM(d18:1/24:0), SM(d18:1/16:1), SM(d18:1/24:1), and SM(d18:2/24:1) were identified as essential potential biomarkers closely linked to clinical parameters through synthetic analysis of receiver operating characteristic curves, random forest analysis, and Pearson matrix correlation. These lipid biomarkers can enhance the risk prediction for the development of T2DM in individuals with dyslipidemia but no clinical signs of high blood sugar. Furthermore, they offer insights into the pathological mechanisms of T2DM with dyslipidemia.
血脂异常常伴随2型糖尿病（T2DM）出现。患者血糖升高通常会导致血脂水平升高。脂质分子在伴有血脂异常的T2DM的早期检测、治疗及预后中可能起关键作用。既往关于T2DM的脂质研究主要集中于血糖升高的西方糖尿病患者群体。在本研究中，我们同时研究高血糖和高血脂水平，以更好地了解新诊断的伴有血脂异常的中国T2DM患者（NDDD）血浆脂质代谢的变化。我们采用基于超高效液相色谱-质谱联用技术（UHPLC-MS）的血浆脂质分析方法及统计分析，以表征脂质谱并识别NDDD患者与健康对照（HC）受试者相比的潜在生物标志物。此外，我们还研究了高脂血症（HL）患者与HC受试者之间脂质谱的差异。我们发现，与HC组相比，NDDD组和HL组中有15种和23种脂质分子发生了显著变化，包括溶血磷脂酰胆碱（LysoPC）、磷脂酰胆碱（PC）、磷脂酰乙醇胺（PE）、鞘磷脂（SM）和神经酰胺（Cer）。这些改变的脂质分子与五条代谢途径相关，其中鞘脂代谢和甘油磷脂代谢与葡萄糖和脂质代谢变化最为相关。这些脂质生物标志物与传统的葡萄糖和脂质代谢标志物密切相关。值得注意的是，通过对受试者工作特征曲线、随机森林分析和Pearson矩阵相关性的综合分析，Cer（d18:1/24:0）、SM（d18:1/24:0）、SM（d18:1/16:1）、SM（d18:1/24:1）和SM（d18:2/24:1）被确定为与临床参数密切相关的重要潜在生物标志物。这些脂质生物标志物可增强对无高血糖临床症状但伴有血脂异常个体发生T2DM风险的预测。此外，它们还为伴有血脂异常的T2DM的病理机制提供了见解。
