Association Between Serum Advanced Glycation End Products and Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A 3-Year Longitudinal Cohort Study (2019-2022)

Abstract

Background: Cardiovascular-kidney-metabolic (CKM) syndrome begins with obesity and glucose abnormalities, advancing to cardiovascular and kidney complications. This study investigates the relationship of advanced glycation end products (AGEs) with CKM syndrome staging and transition patterns.

Methods: This 3-year longitudinal study (2019-2022) of 1264 adults identified five CKM trajectory groups: Group 1 (stable low-risk, 6.7%, stage 0/1), Group 2 (fluctuating, 15.8%, stages 0/1-2), Group 3 (stable intermediate, 52.8%, stage 2), Group 4 (progressors, 8.9%, to stage 3/4), and Group 5 (stable high-risk, 15.8%, stage 3/4), from baseline distributions of stage 0 (1.6%), 1 (12.3%), 2 (71.0%), 3 (5.8%), and 4 (9.2%). Serum AGEs were quantified by UPLC-MS/MS.

Results: Higher AGEs levels showed significant associations with CKM severity, with each 1-SD increase corresponding to a 30% greater likelihood of advanced staging (95% CI:10%-54%). Quartile analysis revealed a dose-response relationship (Q2:1.66[1.15-2.41]; Q3:1.67[1.12-2.48]; Q4:1.92[1.31-2.81]). Longitudinally, the total AGEs score was significantly associated with CKM transition patterns from 2019 to 2022. The odds ratios (ORs) for Group 2, Group 3, Group 4, and Group 5 compared to Group 1 were 1.61 (1.06-2.45), 1.64 (1.11-2.41), 1.71 (1.07-2.73), and 2.03 (1.32-3.13), respectively.

Conclusions: These findings suggest that serum AGEs are linked to CKM severity and progression, potentially serving as biomarkers for CKM staging and targets for intervention.

Keywords: cardiovascular‐kidney‐metabolic syndrome; cohort study; serum advanced glycation end products.

FIGURE 1

The relationship between serum AGEs and CKM syndrome. (A) Differences in AGEs among CKM syndrome stage subjects. (B) Linear/nonlinear relationship between AGEs score and CKM syndrome. (C) Association of AGEs score and concentration of specific serum AGEs with CKM syndrome in baseline. Serum AGEs concentration were adjusted for age, educational level, alcohol consumption, physical activity and DII in (B). Data are ORs (95% CIs) in (C). OR odds ratio, CI confidence interval. In (C) Model 1 Only AGEs score or concentration of specific serum AGEs. Model 2: adjusted for age, educational level, alcohol consumption, physical activity and dietary inflammation index. Q1 Quantile 1, Q2 Quantile 2, Q3 Quantile 3, Q4 Quantile 4.

FIGURE 2

The relationship between serum AGEs and CKM syndrome stage transitions. (A) The transition of CKM syndrome stage from 2019 to 2022. (B) Relationship between AGEs scores and CKM syndrome stage transitions at different time periods. Data are ORs (95% CIs). OR, odds ratio for the association per 1‐SD increment of standard; CI confidence interval. 2019–2020 period: adjusted for age, education level, physical activity, smoking status, and dietary inflammation index. 2019–2021 period: adjusted for age, education level, smoking status, physical activity; 2019–2022 period: adjusted for age, education level, and physical activity; Group1: Stage0/1 → Stage0/1; Group2: Stage0/1 → Stage2 or Stage2 → Stage0/1; Group3: Stage2 → Stage2; Group4: Stage0/1/2 → Stage3/4; Group5: Stage3/4 → Stage3/4.