Objectives: Liver biopsy diagnosis of primary sclerosing cholangitis (PSC) is difficult. We performed a detailed histologic analysis of PSC cases using novel bioinformatics analysis to identify histologic features that may be useful in its diagnosis.
Methods: PSC liver explants were examined and compared with primary biliary cirrhosis and hepatitis C explants to act as controls. Demographic, macroscopic, and histologic variables were analyzed using both conventional statistics and an integrative bioinformatics approach, significance analysis of microarrays (SAM), and hierarchical clustering analysis (HCA).
Results: The PSC group was younger and had distinctive PSC features, including bile duct scars, onion-skin fibrosis, and arterial fibrointimal hyperplasia. SAM allowed the integration of variables by comparing PSC and control groups, whereas HCA was able to correctly categorize each group.
Conclusions: This study demonstrates characteristic PSC histology as well as arterial hyperplasia to be distinctive features that may aid in PSC diagnosis and be confirmed by bioinformatics.
Keywords: Bioinformatics; Cirrhosis; Diagnosis; Explant; Histology; Needle biopsy.
Copyright© by the American Society for Clinical Pathology.