Ren Dongmei, Li Yong, Zhang Guangnian, Li Tiantian, Liu Zhenglong
Department of Hepatobiliary Surgery II, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
School of Basic Medical Sciences and Forensic Medicine, North Sichuan Medical College, Nanchong, China.
Front Physiol. 2024 Oct 24;15:1457349. doi: 10.3389/fphys.2024.1457349. eCollection 2024.
Hyperlipidemic acute pancreatitis (HLAP) is a form of pancreatitis induced by hyperlipidemia, posing significant diagnostic challenges due to its complex lipid metabolism disturbances.
This study compared the serum lipid profiles of HLAP patients with those of a healthy cohort using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify distinct lipid metabolites. Logistic regression and LASSO regression were used to develop a diagnostic model based on the lipid molecules identified.
A total of 393 distinct lipid metabolites were detected, impacting critical pathways such as fatty acid, sphingolipid, and glycerophospholipid metabolism. Five specific lipid molecules were selected to construct a diagnostic model, which achieved an area under the curve (AUC) of 1 in the receiver operating characteristic (ROC) analysis, indicating outstanding diagnostic accuracy.
These findings highlight the importance of lipid metabolism disturbances in HLAP. The identified lipid molecules could serve as valuable biomarkers for HLAP diagnosis, offering potential for more accurate and early detection.
高脂血症性急性胰腺炎（HLAP）是一种由高脂血症诱发的胰腺炎形式，因其复杂的脂质代谢紊乱而带来重大的诊断挑战。
本研究使用超高效液相色谱-串联质谱法（UPLC-MS/MS）比较了HLAP患者与健康队列的血清脂质谱。应用正交偏最小二乘判别分析（OPLS-DA）来识别不同的脂质代谢物。使用逻辑回归和LASSO回归基于所识别的脂质分子建立诊断模型。
共检测到393种不同的脂质代谢物，影响脂肪酸、鞘脂和甘油磷脂代谢等关键途径。选择了五种特定的脂质分子构建诊断模型，该模型在受试者工作特征（ROC）分析中的曲线下面积（AUC）为1，表明诊断准确性出色。
这些发现突出了脂质代谢紊乱在HLAP中的重要性。所识别的脂质分子可作为HLAP诊断的有价值生物标志物，为更准确和早期的检测提供了潜力。
