Background: Height-adjusted total kidney volume (htTKV) is considered as the best predictor of kidney function in patients with autosomal dominant polycystic kidney disease (ADPKD), but its limited predictive capacity stresses the need to find new biomarkers of ADPKD progression. The aim of this study was to investigate urinary biomarkers of ADPKD progression.
Methods: This observational study included ADPKD patients, and two comparator groups of ischaemic and non-ischaemic kidney injury: benign nephroangiosclerosis patients and non-ischaemic chronic kidney disease (CKD) patients. Proteinuria, htTKV and urinary levels of molecules are associated with ischaemia and/or tubular injury. The slope of estimated glomerular filtration rate (eGFR) was used as a dependent variable in univariate and multivariate models of kidney function decline.
Results: The study included 130 patients with ADPKD, 55 with nephroangiosclerosis and 40 with non-ischaemic CKD. All patients had increased urinary concentrations of biomarkers associated with tubular lesions (liver fatty acid-binding protein, kidney injury molecule-1, β2-microglobulin) and molecules overexpressed under ischaemic conditions [hypoxia-inducible factor-1α, vascular endothelial growth factor (VEGF) and monocyte chemoattractant protein-1 (MCP-1)]. These biomarkers correlated positively with htTKV and negatively with the eGFR slope. htTKV was the single best predictor of the eGFR slope variability in univariate analyses. However, a multivariate model including urinary levels of β2-microglobulin, MCP-1 and VEGF improved the capacity to predict the decline of eGFR in ADPKD patients compared with htTKV alone.
Conclusions: The urinary levels of molecules associated with either renal ischaemia (VEGF and MCP-1) or tubular damage (β2-microglobulin) are associated with renal function deterioration in ADPKD patients, and are, therefore, candidates as biomarkers of ADPKD progression.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467584 | PMC |
http://dx.doi.org/10.1093/ckj/sfz105 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!