Early-stage chronic kidney disease (early-stage CKD, stages G1–G3B) is frequently asymptomatic, and coexisting type 2 diabetes mellitus (T2DM) accelerates metabolic changes that precede conventional clinical markers. The study aimed to define disease-specific serum metabolic alterations that distinguish early-stage diabetic CKD from non-diabetic CKD, with the goal of identifying potential biomarkers to improve early diagnosis and patient stratification.
The investigation applied quantitative proton 1H NMR serum metabolomics to a cohort of 100 patients with early-stage CKD (G1–G3B). The approach focused on untargeted profiling of polar metabolites in serum. The goal of this analytic design was to capture broad metabolic reprogramming associated with rising glycemic burden in early renal disease.
Data interrogation used both univariate and multivariate frameworks. Principal component analysis (PCA), partial least squares–discriminant analysis (PLS-DA), and Random Forest classification were applied to assess whether metabolic profiles could clearly separate diabetic CKD from non-diabetic CKD. The study also implemented pathway enrichment and linear regression trend analyses to examine relationships across non-diabetic CKD, prediabetic CKD, and diabetic CKD categories.
Multilevel analyses consistently showed that patients with diabetic CKD had lower serum levels of specific metabolites compared with non-diabetic early-stage CKD. Notably, concentrations of methionine, serine, and citrate were reduced in the diabetic CKD group. The authors interpret these reductions as evidence of early disturbances in cellular energy metabolism and one-carbon metabolism.
Pathway-level analysis identified several biochemical pathways as dysregulated in diabetic early-stage CKD relative to non-diabetic CKD. Affected pathways included the tricarboxylic acid (TCA) cycle, pyruvate metabolism, glycine–serine–threonine metabolism, cysteine–methionine metabolism, and the one-carbon pool mediated by folate. Collectively, these pathway perturbations align with the observed decreases in citrate and one-carbon–related metabolites and point to coordinated alterations in energy production and methylation-related biochemistry.
Receiver operating characteristic (ROC) analysis of the metabolic signature produced a moderate level of diagnostic accuracy, with an area under the curve (AUC) reported as 0.77. This indicates potential usefulness of the serum metabolite profile as a discriminative tool between diabetic and non-diabetic early-stage CKD, while also highlighting that the performance is not definitive and would require further validation.
Linear regression trend analyses conducted across three ordered groups—early-stage non-diabetic CKD, prediabetic CKD, and diabetic CKD—revealed a progressive metabolic decline that correlated with increasing glycemic burden. These graded changes suggest that metabolic reprogramming begins before overt diabetes and worsens with higher levels of dysglycemia.
The study identifies early metabolic signatures that differentiate diabetic early-stage CKD from non-diabetic early-stage CKD and links these signatures to specific biochemical pathways, including the TCA cycle and one-carbon metabolism. The findings support the concept that T2DM drives distinct metabolic reprogramming in CKD well before changes are apparent with routine clinical markers. The reported AUC of 0.77 suggests moderate discriminative potential for the metabolite panel, but further validation and prospective evaluation would be necessary before clinical application. The authors propose that these metabolomic insights could aid improved patient stratification and the development of targeted therapeutic strategies.
The abstract reports cohort size (n = 100), analytical methods, main metabolite and pathway findings, ROC AUC, and trend-analysis outcomes. Detailed information beyond the abstract—such as full metabolite lists with effect sizes, sample selection criteria, demographic and clinical covariates, preprocessing steps, exact statistical thresholds, and external validation—were not reported in the abstract and therefore are not available in this source summary.
The authors declared no known competing financial interests or personal relationships that could have influenced the reported work.