Associations between serum lactate and renal dysfunction in diabetic kidney disease: An exploratory analysis integrating animal experiments, clinical cohorts, and bioinformatic approaches
- 1Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- 2First Affiliated Hospital of Hebei University of Traditional Chinese Medicine, Shijiazhuang, Hebei, China
Abstract
Objectives: Diabetic kidney disease (DKD) is a major cause of end-stage renal disease, but the metabolic changes associated with its progression are still not well understood. Lactate, traditionally regarded as a byproduct of glycolysis, has been increasingly recognized in recent studies in association with broader metabolic and regulatory processes. This study aimed to evaluate the association between serum lactate and renal dysfunction in DKD and to explore candidate molecular pathways linking lactate-associated metabolic alterations to DKD-related renal injury using animal experiments, clinical cohort analyses, and exploratory bioinformatic approaches. Methods: We established DKD in rats by combining right nephrectomy with streptozotocin-induced diabetes to examine metabolic and kidney changes. Clinical associations were evaluated using data from 593 DKD patients in the MIMIC-IV database and were further examined in an independent eICU validation cohort. Associations between serum lactate and renal function were analyzed using correlation and multivariable regression. Candidate molecular pathways were explored using integrated network-based bioinformatics, including target prediction, protein–protein interaction analysis, enrichment analysis, and molecular docking. Results: DKD rats showed significantly elevated serum lactate and evidence of kidney injury, with lactate strongly correlating with the kidney function marker cystatin C (ρ = 0.748, P = 0.0081). In clinical data, elevated lactate was independently associated with higher serum creatinine (β = 0.13, 95% CI: 0.004–0.256, P = 0.044), and this positive association was further supported in the external eICU cohort. Network analysis identified 43 overlapping targets linking lactate to DKD, highlighting hub proteins such as PTGS2, EGFR, TP53, ESR1, MAPK3, and MMP9, mainly enriched in inflammation, fibrosis, and metabolism-related pathways. Conclusions: Elevated serum lactate was associated with renal dysfunction in DKD across animal and clinical datasets. In ICU-based clinical cohorts, this association suggests that lactate may reflect concurrent metabolic and hemodynamic stress related to renal dysfunction, rather than serving as a DKD-specific biomarker or causal mediator. Exploratory bioinformatic analyses identified candidate inflammatory, fibrotic, vascular, and metabolic pathways that may provide molecular context for this association. These computational findings should be interpreted as hypothesis-generating and require further experimental validation.
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BibTeX
@article{li2026associations,
title = {{Associations between serum lactate and renal dysfunction in diabetic kidney disease: An exploratory analysis integrating animal experiments, clinical cohorts, and bioinformatic approaches}},
author = {Zongtao Li and Wenyu Zhang and Die Fang and Bingwu Zhao and Tianwei Zhang and Xueqin Zhang and Zhiqiang Chen},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0358359},
url = {https://doi.org/10.1371/journal.pone.0358359},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Associations between serum lactate and renal dysfunction in diabetic kidney disease: An exploratory analysis integrating animal experiments, clinical cohorts, and bioinformatic approaches
AU - Zongtao Li
AU - Wenyu Zhang
AU - Die Fang
AU - Bingwu Zhao
AU - Tianwei Zhang
AU - Xueqin Zhang
AU - Zhiqiang Chen
PY - 2026
DA - 2026/09/15
JO - PLOS One
DO - 10.1371/journal.pone.0358359
UR - https://doi.org/10.1371/journal.pone.0358359
AB - Objectives: Diabetic kidney disease (DKD) is a major cause of end-stage renal disease, but the metabolic changes associated with its progression are still not well understood. Lactate, traditionally regarded as a byproduct of glycolysis, has been increasingly recognized in recent studies in association with broader metabolic and regulatory processes. This study aimed to evaluate the association between serum lactate and renal dysfunction in DKD and to explore candidate molecular pathways linking lactate-associated metabolic alterations to DKD-related renal injury using animal experiments, clinical cohort analyses, and exploratory bioinformatic approaches. Methods: We established DKD in rats by combining right nephrectomy with streptozotocin-induced diabetes to examine metabolic and kidney changes. Clinical associations were evaluated using data from 593 DKD patients in the MIMIC-IV database and were further examined in an independent eICU validation cohort. Associations between serum lactate and renal function were analyzed using correlation and multivariable regression. Candidate molecular pathways were explored using integrated network-based bioinformatics, including target prediction, protein–protein interaction analysis, enrichment analysis, and molecular docking. Results: DKD rats showed significantly elevated serum lactate and evidence of kidney injury, with lactate strongly correlating with the kidney function marker cystatin C (ρ = 0.748, P = 0.0081). In clinical data, elevated lactate was independently associated with higher serum creatinine (β = 0.13, 95% CI: 0.004–0.256, P = 0.044), and this positive association was further supported in the external eICU cohort. Network analysis identified 43 overlapping targets linking lactate to DKD, highlighting hub proteins such as PTGS2, EGFR, TP53, ESR1, MAPK3, and MMP9, mainly enriched in inflammation, fibrosis, and metabolism-related pathways. Conclusions: Elevated serum lactate was associated with renal dysfunction in DKD across animal and clinical datasets. In ICU-based clinical cohorts, this association suggests that lactate may reflect concurrent metabolic and hemodynamic stress related to renal dysfunction, rather than serving as a DKD-specific biomarker or causal mediator. Exploratory bioinformatic analyses identified candidate inflammatory, fibrotic, vascular, and metabolic pathways that may provide molecular context for this association. These computational findings should be interpreted as hypothesis-generating and require further experimental validation.
SN - 1932-6203
ER -