IgG N-Glycosylation Cardiovascular Age Tracks Cardiovascular Risk Beyond Calendar Age

被引:5
|
作者
Wu, Zhiyuan
Guo, Zheng [1 ]
Zheng, Yulu [1 ]
Wang, Yutao [3 ]
Zhang, Haiping [2 ]
Pan, Huiying [2 ]
Li, Zhiwei [2 ]
Balmer, Lois [1 ]
Li, Xia [4 ]
Tao, Lixin [2 ]
Guo, Xiuhua [2 ]
Wang, Wei [1 ,2 ]
机构
[1] Edith Cowan Univ, Ctr Precis Hlth, Joondalup, WA 6027, Australia
[2] Capital Med Univ, Sch Publ Hlth, Beijing Municipal Key Lab Clin Epidemiol, Beijing 100069, Peoples R China
[3] Shanghai Fufan Informat Technol Co Ltd, Shanghai 200433, Peoples R China
[4] La Trobe Univ, Dept Math & Stat, Melbourne, Vic 3086, Australia
基金
中国国家自然科学基金; 澳大利亚国家健康与医学研究理事会;
关键词
IgG N-glycosylation cardiovascular age; Cardiovascular aging; Immunoglobulin G; Glycosylation; Inflammation; Feature selection; Machine learning; ANTIBODY GLYCOSYLATION; IMMUNOGLOBULIN-G; DISEASE; BIOMARKER; AUTOIMMUNITY; INFLAMMATION; ASSOCIATION; INHIBITION;
D O I
10.1016/j.eng.2022.12.004
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The use of an altered immunoglobulin G (IgG) N-glycan pattern as an inflammation metric has been reported in subclinical atherosclerosis and metabolic disorders, both of which are important risk factors in cardiovascular health. However, the usable capacity of IgG N-glycosylation profiles for the risk stratification of cardiovascular diseases (CVDs) remains unknown. This study aimed to develop a cardiovascular aging index for tracking cardiovascular risk using IgG N-glycans. This cross-sectional investigation enrolled 1465 individuals aged 40-70 years from the Busselton Healthy and Ageing Study. We stepwise selected the intersection of altered N-glycans using feature-selection methods in machine learning (recursive feature elimination and penalized regression algorithms) and developed an IgG N-glycosylation cardiovascular age (GlyCage) index to reflect the deviation from calendar age attributable to cardiovascular risk. The strongest contributors to GlyCage index were fucosylated N-glycans with bisecting N-acetylglucosamine (GlcNAc) (glycan peak 6 (GP6), FA2B,) and digalactosylated N-glycans with bisecting GlcNAc (GP13, A2BG2). A one-unit increase of GlyCage was significantly associated with a higher Framingham ten-year cardiovascular risk (odds ratio (OR), 1.09; 95% confidence interval (95% CI): 1.05-1.13) and probability of CVDs (OR, 1.07; 95% CI: 1.01-1.13) independent of calendar age. Individuals with excessive GlyCage (exceeding a calendar age > 3 years) had an increased cardiovascular risk and probability of CVDs, with adjusted ORs of 2.22 (95% CI: 1.41-3.53) and 2.71 (95% CI: 1.25-6.41), respectively. The area under curve (AUC) values of discriminating high cardiovascular risk and events were 0.73 and 0.65 for GlyCage index, and 0.65 and 0.63 for calendar age. The GlyCage index developed in this study can thus be used to track cardiovascular health using IgG N-glycosylation profiles. The distance between GlyCage and calendar age independently indicates the cardiovascular risk, suggesting that IgG N-glycosylation plays a role in the pathogenesis of CVDs. The generalization of the observed associations and the predictive capability of GlyCage index require external and longitudinal validation in other populations.(c) 2022 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:99 / 107
页数:9
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