N-glycan profiles of acute myocardial infarction patients reveal potential biomarkers for diagnosis, severity assessment and treatment monitoring. (22nd December 2021)

• Record Type: Journal Article
• Authors: Lim, Si Ying; Hendra, Christopher; Yeo, Xin Hao; Tan, Xin Yi; Ng, Bao Hui; Laserna, Anna Karen Carrasco; Tan, Sock Hwee; Chan, Mark Y; Khan, Shaheer H; Chen, Shiaw-Min; Li, Sam Fong Yau
• Is Part Of: Glycobiology. Volume 32:Number 6(2022)
• Page Start: 469
• Page End: 482
• Publication Date: 2021-12-22
• Subjects: acute myocardial infarction -- biomarker -- coronary heart disease -- glycan -- glycomics; Glycoproteins -- Periodicals; Glycolipids -- Periodicals; Glycoconjugates -- Periodicals; 572.567
• DOI: 10.1093/glycob/cwab129
• Languages: English
• ISSNs: 0959-6658

Abstract

Abstract: Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Diagnostic challenges remain in this highly time-sensitive condition. Using capillary electrophoresis-laser-induced fluorescence, we analyzed the blood plasma N-glycan profile in a cohort study comprising 103 patients with AMI and 69 controls. Subsequently, the data generated was subjected to classification modeling to identify potential AMI biomarkers. An area under the Receiving Operating Characteristic curve (AUCROC ) of 0.81 was obtained when discriminating AMI vs. non-MI patients. We postulate that the glycan profile involves a switch from a pro- to an anti-inflammatory state in the AMI pathophysiology. This was supported by significantly decreased levels in galactosylation, alongside increased levels in sialylation, afucosylation and GlcNAc bisection levels in the blood plasma of AMI patients. By substantiating the glycomics analysis with immunoglobulin G (IgG) protein measurements, robustness of the glycan-based classifiers was demonstrated. Changes in AMI-related IgG activities were also confirmed to be associated with alterations at the glycosylation level. Additionally, a glycan-biomarker panel derived from glycan features and current clinical biomarkers performed remarkably (AUCROC = 0.90, sensitivity = 0.579 at 5% false positive rate) when discriminating between patients with ST-segment elevation MI ( n = 84) and non-ST-segment elevation MI ( n = 19). Moreover, by applying the model trained using glycomics information, AMI and controls can still be discriminated at 1 and 6 months after baseline. Thus, glycomics biomarkers could potentially serve as a valuable complementary test to current diagnostic biomarkers. Additional research on their utility and associated biomechanisms via a large-scale study is recommended. Graphical Abstract: