Liver fibrosis is an important factor in the progression of disease for millions of people with chronic hepatitis C. There is a fundamental gap in understanding the development of liver fibrosis in people with chronic hepatitis C which currently makes liver biopsy the best way to determine liver fibrosis. The long-term objective of this research is to better understand and predict liver fibrosis in people with hepatitis C, without the need for liver biopsy. The objective of this particular R21 application is to gather preliminary data to support an RO1 application concerning hepatitis C fibrosis. The central hypothesis of this proposal is that proteomic techniques can be used to establish a relationship between serum proteins and hepatic fibrosis that will allow determination of hepatic fibrosis without a liver biopsy in patients with hepatitis C. This research utilizes a remarkable ongoing tissue and data repository located at Oregon Health & Science University that contains more than 26,000 samples of serum, liver biopsies, liver explants and associated clinical data from more than 1,650 subjects with hepatitis C and other liver diseases. Key samples include serum and simultaneous liver biopsies from many individuals. Many of these samples are collected over time from the same patients undergoing various therapies for hepatitis C including liver transplantation.
Two specific aims are identified: 1) Identify and quantify proteins whose serum levels are related to specific fibrosis stages in hepatitis C. Serum samples from this repository will be analyzed with 2-dimensional gel electrophoresis in order to identify specific proteins which correlate with Batts-Ludwig fibrosis scores from liver biopsies obtained simultaneously with the serum samples. These proteins of interest will be identified with tandem mass spectrometry. Antibodies to these proteins will be obtained and used for Western blot analysis, immunoprecipitation and ELISA testing of the same and new serum samples with simultaneous liver biopsies and fibrosis scores. 2) Using the data from specific aim 1, develop and validate an algorithm to predict hepatic fibrosis score. Predicted fibrosis scores based on serum proteins will be compared with actual fibrosis scores by determining sensitivity, specificity and predictive values positive and negative. The final algorithm to predict fibrosis will be validated with samples independent of those from which the algorithm was developed. This research addresses fundamental needs related to the health of millions of individuals with hepatitis C by relating the human serum proteome to hepatitis C fibrosis.
| Yang, Libang; Rudser, Kyle D; Higgins, LeeAnn et al. (2011) Novel biomarker candidates to predict hepatic fibrosis in hepatitis C identified by serum proteomics. Dig Dis Sci 56:3305-15 |
