Title:A Biomarker Cluster for Polycystic Kidney Disease: Correlation with Cystic Index
Volume: 5
Issue: 1
Author(s): Brian Huang, Prani Paka, Siobhan McCormack, Ping Zhou, Latha Paka, Michael Yamin, Itzhak D. Goldberg and Prakash Narayan
Affiliation:
Keywords:
Biomarker, cluster, correlation, cystic index, fibrosis, imaging, liver, polycystic kidney disease.
Abstract: Polycystic kidney disease (PKD) is characterized by the formation and expansion of fluidfilled
cysts within the kidneys, painful renal enlargement and declining kidney function. Often, PKD
manifests in other organs, including the liver and pancreas. In addition to cyst formation, interstitial
collagen deposition is sometimes observed in both the kidney and the liver. While a diagnosis of PKD
may be made using ultrasonography coupled with family history, monitoring disease progression is
challenging as imaging techniques remain inadequate to track an increasing cystic index over time.
Using the PCK rat model of PKD, we have identified a minimally invasive biomarker cluster with high correlative value
for renal cystic index. This finding is important in that disease prognosis, patient compliance, interventional decisions and
outcomes stand to be improved by regular disease monitoring. Identification of biomarkers of PKD also can better stratify
transplant waitlists for kidneys or livers. Furthermore, rather than reliance upon a single biomarker, clinical outcomes may
be better predicted from a cluster of disease-relevant biomarkers that correlates strongly with outcome. Clinical trials
would also benefit from such biomarkers given the reluctance to invest in trials wherein clinical endpoints could be years
away. Moreover, relevant patents are also discussed related to the use of renal biomarkers as diagnostics.
