Multispectral Imaging Application in Chronic Kidney Disease Drug Discovery

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Chronic kidney disease (CKD) is characterized by gradual loss of kidney functions over time. Several markers such as fibrosis, kidney injury marker-1 (KIM-1) and infiltrating macrophages (F4/80) have been shown to closely associate with CKD stages and treatment efficacy. Immunohistochemistry (IHC) provides detailed antigen expression patterns at sub-mm resolution. Manual IHC evaluation by pathologists is accurate but time consuming and prone to error when the number of sections for review is numerous. The Vectra high-throughput system utilizes multispectral imaging technology and machine learning algorithm to automatically identify and quantify antigen expression. We compared the automated Vectra platform with manual analysis procedures to quantitate kidney antigen expression following unilateral ureteral obstruction (UUO) in rodents. The results showed excellent correlations (fibrosis score r2=0.82, p=0.0008; KIM-1,r2=0.98, p<0.0001; F4/80, r2=0.804, p=0.002). Puromycin aminonucleoside-induced nephrosis (PAN) model induces podocyte damage and proteinuria, a primary prognostic marker of podocyte injury in rats. Using the automated Vectra platform to evaluate several podocyte related markers after puromycin administration we found GLEPP1(as an indicator of podocyte function) correlated significantly to proteinuria (r2=0.53, p<0.0001 with outlier; r2=0.90, p<0.0001 without outliers). In addition results from Vectra are highly reproducible among users. Our tests show that the Vectra imaging platform provides deeper analysis, highly reproducible among users and is a fast and reliable tool for monitoring CKD progression and preclinical drug development.