High-Performance Liquid Chromatography-Mass Spectrometry-Based Lipid Metabolite Profiling of Acromegaly

• Published in: The journal of clinical endocrinology and metabolism 2020-04, Vol.105 (4), p.e1075-e1084
• Main Authors: Wang, Meng, Guo, Shizhe, He, Min, Shao, Xiaoqing, Feng, Lei, Yu, Yifei, Gong, Wei, Liu, Qingfeng, Melnikov, Vladimir, Wang, Xiaoxue, He, Zhian, Jiang, Lin, Chen, Maohua, Sun, Jun, Cai, Jianyong, Zhao, Yao, Li, Yiming, Tritos, Nicholas A, Hu, Zhiyu, Zhang, Zhaoyun
• Format: Article
• Language: English
• Subjects: Acromegaly; Cardiovascular diseases; Chromatography; Diabetes mellitus; Discriminant analysis; Echocardiography; Glucose; Glucose tolerance; Heart; High-performance liquid chromatography; Linoleic acid; Lipid metabolism; Lipids; Lysophosphatidylcholine; Macromolecules; Mass spectrometry; Mass spectroscopy; Metabolic disorders; Metabolism; Metabolites; Metabolomics; Phosphatidylethanolamine; Principal components analysis; Scientific imaging; Structure-function relationships; Ventricle
• ISSN: 0021-972X; 1945-7197
• DOI: 10.1210/clinem/dgaa014

Abstract Context Metabolic disorders, especially dysregulated lipid metabolism, increase the risk of cardiovascular mortality in acromegaly. Previous studies measuring plasma macromolecular lipids have yielded conflicting results. Purpose To explore the plasma lipid metabolite profiles by metabolomics analysis and identify potential metabolites associated with cardiac function in acromegaly. Methods Plasma was obtained from 80 newly diagnosed, untreated patients with acromegaly and 80 healthy controls. Echocardiography was performed. Based on the results of an oral glucose tolerance test (OGTT), patients were categorized into 2 groups: normal glucose tolerance (NGT, n = 28) and impaired glucose tolerance or diabetes mellitus (IGT/DM, n = 52). High-performance liquid chromatography–mass spectrometry (HPLC–MS)-based metabolomics analysis was conducted. Data were processed by principal components analysis (PCA), orthogonal partial least square-discriminant analysis (OPLS-DA), and MetaboAnalyst 4.0. Associations between metabolic substances and cardiovascular parameters were also explored. Results Metabolomics uncovered a distinct metabolic pattern between acromegaly and healthy controls, and perturbed pathways mainly include glycerophospholipid metabolism, sphingolipid metabolism, as well as linoleic acid metabolism. Collective analysis showed that phosphatidylethanolamine (PE) (22:6/16:0) was positively correlated with LV mass, while lysophosphatidylcholine (LysoPC) (16:0) was positively correlated with fractional shortening (FS) and left ventricle ejection fraction (LVEF). Conclusion Patients with acromegaly have distinct lipid metabolite profiling, while PE (22:6/16:0) and LysoPC (16:0) are correlated with cardiac structure and function, which may contribute to the risk of cardiovascular complications.