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Abstract Background Septic acute kidney injury affects 40–50% of all septic patients. Molecular differences between septic patients with and without acute kidney injury (AKI) are only poorly understood. Here, we investigated gene expression changes that differentiated the subjects who developed septic AKI from those who did not and coupled this approach with traditional parameters of renal physiology. Methods In 15 anesthetized, mechanically ventilated and instrumented pigs, progressive sepsis was induced either by peritonitis or by continuous intravenous infusion of Pseudomonas aeruginosa. Animals received standard intensive care including goal-directed hemodynamic management. Analyses were performed on kidneys from sham operated animals, septic pigs without AKI, and pigs with septic AKI. Before, and at 12, 18 and 22 h of progressive sepsis, systemic and renal hemodynamics, cortex microcirculation and plasma IL-6 and TNF-α were measured. At 22 h whole kidney expression of pre-selected genes was analyzed by quantitative Real Time PCR. Results Animals with septic AKI had systemic hemodynamic phenotype (normo- or hyperdynamic) comparable with non-AKI subjects, but demonstrated higher plasma levels of cytokines, an increase in renal vascular resistance and early fall in cortical microcirculatory blood flow. The genes whose expression discriminated septic AKI from non-AKI included Toll like receptor 4 (up-regulated 2.7-fold, P = 0.04); Cyclooxygenase-2 (up-regulated 14.6-fold, P = 0.01), Angiotensin II Receptor (up-regulated 8.1-fold, P = 0.01), Caspase 3 (up-regulated 5.1-fold, P = 0.02), Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Alpha (down-regulated 2-fold, P = 0.02). Conclusions In this preliminary experimental study, kidney gene expression was profoundly different in animals that developed septic AKI as opposed to septic animals that did not. The biological functions of the genes differentially expressed support a role of inflammatory overstimulation coupled with metabolic and apoptotic molecular responses in early septic AKI. Cyclooxygenase-2 and angiotensin type 2 receptor-dependent downstream mechanisms appear fruitful targets for future mechanistic research.

Abstract Background Additional urinary biomarkers for diabetic nephropathy (DN) are needed, providing early and reliable diagnosis and new insights into its mechanisms. Rigorous selection criteria and homogeneous study population may improve reproducibility of the proteomic approach. Methods Long-term type 1 diabetes patients without metabolic comorbidities were included, 11 with sustained microalbuminuria (MA) and 14 without MA (nMA). Morning urine proteins were precipitated and resolved by 2D electrophoresis. Principal component analysis (PCA) and Projection to latent structures discriminatory analysis (PLS-DA) were adopted to assess general data validity, to pick protein fractions for identification with mass spectrometry (MS), and to test predictive value of the resulting model. Results Proteins (n = 113) detected in more than 90% patients were considered representative. Unsupervised PCA showed excellent natural data clustering without outliers. Protein spots reaching Variable Importance in Projection score above 1 in PLS (n = 42) were subjected to MS, yielding 33 positive identifications. The PLS model rebuilt with these proteins achieved accurate classification of all patients (R2X = 0.553, R2Y = 0.953, Q2 = 0.947). Thus, multiple earlier recognized biomarkers of DN were confirmed and several putative new biomarkers suggested. Among them, the highest significance was met in kininogen-1. Its activation products detected in nMA patients exceeded by an order of magnitude the amount found in MA patients. Conclusions Reducing metabolic complexity of the diseased and control groups by meticulous patients’ selection allows to focus the biomarker search in DN. Suggested new biomarkers, particularly kininogen fragments, exhibit the highest degree of correlation with MA and substantiate validation in larger and more varied cohorts.