Use of novel structural features to identify urinary biomarkers during acute
kidney injury that predict progression to chronic kidney disease.
Authors Charlton JR, Li T, Wu T, deRonde K, Xu Y, Baldelomar EJ, Bennett KM
Submitted By Submitted Externally on 8/28/2023
Status Published
Journal BMC nephrology
Year 2023
Date Published 6/1/2023
Volume : Pages 24 : 178
PubMed Reference 37331957
Abstract A significant barrier to biomarker development in the field of acute kidney
injury (AKI) is the use of kidney function to identify candidates. Progress in
imaging technology makes it possible to detect early structural changes prior to
a decline in kidney function. Early identification of those who will advance to
chronic kidney disease (CKD) would allow for the initiation of interventions to
halt progression. The goal of this study was to use a structural phenotype
defined by magnetic resonance imaging and histology to advance biomarker
discovery during the transition from AKI to CKD., Urine was collected and
analyzed from adult C57Bl/6 male mice at four days and 12 weeks after folic
acid-induced AKI. Mice were euthanized 12 weeks after AKI and structural metrics
were obtained from cationic ferritin-enhanced-MRI (CFE-MRI) and histologic
assessment. The fraction of proximal tubules, number of atubular glomeruli
(ATG), and area of scarring were measured histologically. The correlation
between the urinary biomarkers at the AKI or CKD and CFE-MRI derived features
was determined, alone or in combination with the histologic features, using
principal components., Using principal components derived from structural
features, twelve urinary proteins were identified at the time of AKI that
predicted structural changes 12 weeks after injury. The raw and normalized
urinary concentrations of IGFBP-3 and TNFRII strongly correlated to the
structural findings from histology and CFE-MRI. Urinary fractalkine
concentration at the time of CKD correlated with structural findings of CKD., We
have used structural features to identify several candidate urinary proteins
that predict whole kidney pathologic features during the transition from AKI to
CKD, including IGFBP-3, TNFRII, and fractalkine. In future work, these
biomarkers must be corroborated in patient cohorts to determine their
suitability to predict CKD after AKI.