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.
Keywords: Biomarker, cluster, correlation, cystic index, fibrosis, imaging, liver, polycystic kidney disease.
57