Metabolomic Profiling Delineates Stage‐Associated Metabolic Remodelling in Cardiovascular‐Kidney‐Metabolic Syndrome
Xuemei Gong, Chunyang Li, Jing Chen, Yujiao Wang, Wenge Tang, Xuehui Zhang, Jianzhong Yin, Xing Zhao, Haopeng Yu, Ping Fu, Xiaoxi ZengABSTRACT
Aims
Cardiovascular–kidney–metabolic (CKM) syndrome represents an integrated continuum of metabolic, kidney, and cardiovascular abnormalities. However, the stage‐specific metabolic heterogeneity underlying this clinical framework remains incompletely characterised.
Materials and Methods
We performed plasma metabolomic profiling in 1374 participants from the China Multi‐Ethnic Cohort across CKM stages 0–4. Participants from Chengdu and Chongqing provinces comprised the discovery cohort ( n = 969), whereas those from Yunnan province comprised the validation cohort ( n = 405). Stage‐associated metabolites were identified using prespecified pairwise comparisons with OPLS‐DA and covariate‐adjusted limma analyses. Weighted correlation network analysis identified coordinated metabolic modules. Machine‐learning models were developed to evaluate discrimination of advanced CKM (stages 3–4) using metabolite signatures independent of conventional CKM‐defining variables.
Results
Among 858 endogenous metabolites, 261 unique metabolites were associated with CKM stages, revealing distinct metabolic patterns from early to advanced CKM. Stage 1 was characterised by altered lipid‐ and bile acid‐related metabolites, stage 2 by broader lipid and amino‐acid remodelling, and stage 3 by additional carbohydrate, aromatic amino‐acid, secondary bile acid, host–microbial, and renal‐handling signals. Metabolic separation between stages 3 and 4 was comparatively weak. WGCNA identified a CKM‐associated turquoise module, with γ‐glutamylvaline as a hub metabolite. A model incorporating age, sex, and eight metabolites derived from the discovery cohort showed favourable performance for distinguishing advanced CKM from earlier stages and achieved an AUROC of 0.874 (95% CI, 0.802–0.931) in the validation cohort.
Conclusions
CKM stages exhibit distinct and non‐linear metabolic signatures. A compact metabolomic panel independent of conventional CKM‐defining variables may provide complementary molecular information for advanced CKM phenotyping and future risk stratification.