ArticleFrontiers in endocrinology2026
Metabolic phenotype dimensions and longitudinal renal function in type 2 diabetes: a principal component analysis-based approach with UACR integration.
Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Type 2 diabetes (T2D) exhibits substantial phenotypic heterogeneity, yet the relationship between multidimensional metabolic phenotypes and longitudinal renal function decline remains poorly characterized, particularly regarding albuminuria status. Objective: To identify metabolic phenotype dimensions using principal component analysis (PCA) in a Chinese T2D cohort and evaluate their associations with estimated glomerular filtration rate (eGFR) trajectories, rapid eGFR decline, cardiometabolic comorbidities, and KDIGO 2024 risk categories incorporating urinary albumin-to-creatinine ratio (UACR). Methods: In this retrospective cohort study of 1,427 patients from Dazhou Tongchuan District People's Hospital (January 2024-July 2026), baseline metabolic variables were subjected to PCA with Varimax rotation (N = 621 with ≥6 variables). Multiple imputation by chained equations (MICE, 20 imputations) addressed missing data. UACR was calculated from simultaneously measured urine creatinine and microalbumin (374 observations). Longitudinal eGFR trajectories were analyzed using linear mixed models (LMM; N = 162, 415 observations), with UACR-adjusted sensitivity analysis (N = 103). Rapid eGFR decline (annual slope Results: Three principal components explained 53.1% of total variance: PC1 (Blood Pressure Axis, 20.2%), PC2 (Metabolic Syndrome Axis, HDL-/TG+, 17.3%), and PC3 (Renal Function Axis, eGFR+/UA-, 15.6%). Parallel analysis suggested 4 components; the 4-component model improved predictive discrimination (AUC: 0.633 vs. 0.699; LRT Conclusions: In this single-center, short-term retrospective study, PCA-derived metabolic phenotype dimensions, particularly the blood pressure axis (PC1), were associated with differential eGFR trajectories and albuminuria status. The attenuation of the PC1-eGFR association after UACR adjustment generates the hypothesis that blood pressure-associated renal function decline may involve albuminuric pathways. Temporal validation confirmed PCA loading structure stability, though predictive model generalization was limited. These findings are hypothesis-generating given the observational design, limited UACR availability, short followup, and absence of independent external validation. Prospective, multi-center studies with comprehensive phenotyping are required before clinical translation can be considered.
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