Towards clinical application of GlycA and GlycB for early detection of inflammation associated with (pre)diabetes and cardiovascular disease: recent evidence and updates

Journal of Inflammation

Review

Ka Man Yu¹  Kwan Hung Ng¹  Erik Fung²  Huijun Li³  Eunice Y. S. Chan³  Yulan Wang⁴ 

[1] Department of Medicine & Therapeutics, Laboratory for Heart Failure + Circulation Research, Li Ka Shing Institute of Health Sciences, and Centre for Cardiovascular Genomics & Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China;Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong Children’s Hospital, Kowloon Bay, Kowloon, Hong Kong SAR, China;Department of Medicine & Therapeutics, Laboratory for Heart Failure + Circulation Research, Li Ka Shing Institute of Health Sciences, and Centre for Cardiovascular Genomics & Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China;Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong Children’s Hospital, Kowloon Bay, Kowloon, Hong Kong SAR, China;Neural, Vascular, and Metabolic Biology Programme, and Ministry of Education Laboratory for Regenerative Medicine, School of Biomedical Sciences, Faculty of Medicine, Lo Kwee-Seong Integrated Biomedical Sciences Building, Area 39, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China;Department of Epidemiology & Biostatistics, School of Public Health, St Mary’s Campus, Imperial College London, London, UK;School of Medicine, The Chinese University of Hong Kong, Shenzhen, China;Prince of Wales Hospital, Room 124010, 10/F, LCWCSB, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong SAR, China;School of Medicine, The Chinese University of Hong Kong, Shenzhen, China;Singapore Phenome Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore;

关键词: Glycoproteins;    Nuclear magnetic resonance spectroscopy;    Inflammation;    Diabetes mellitus;    Atherosclerosis;    Cardiovascular disease;   

DOI  :  10.1186/s12950-023-00358-7

 received in 2023-07-03, accepted in 2023-09-18,  发布年份 2023

来源: Springer

【 摘 要 】

SummaryCardiometabolic diseases are associated with low-grade inflammation early in life and persists into old age. The long latency period presents opportunities for early detection, lifestyle modification and intervention. However, the performance of conventional biomarker assays to detect low-grade inflammation has been variable, particularly for early-stage cardiometabolic disorder including prediabetes and subclinical atherosclerotic vascular inflammation. During the last decade, the application of nuclear magnetic resonance (NMR) spectroscopy for metabolic profiling of biofluids in translational and epidemiological research has advanced to a stage approaching clinical application. Proton (1H)-NMR profiling induces no destructible physical changes to specimens, and generates quantitative signals from deconvoluted spectra that are highly repeatable and reproducible. Apart from quantitative analysis of amino acids, lipids/lipoproteins, metabolic intermediates and small proteins, 1H-NMR technology is unique in being able to detect composite signals of acute-phase and low-grade inflammation indicated by glycosylated acetyls (GlycA) and N-acetylneuraminic acid (sialic acid) moieties (GlycB). Different from conventional immunoassays that target epitopes and are susceptible to conformational variation in protein structure and binding, GlycA and GlycB signals are stable over time, and maybe complementary as well as superior to high-sensitivity C-reactive protein and other inflammatory cytokines. Here we review the physicochemical principles behind 1H-NMR profiling of GlycA and GlycB, and the available evidence supporting their potential clinical application for the prediction of incident (pre)diabetes, cardiovascular disease, and adverse outcomes.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

Fig. 6