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Genomics- and Proteomics-based Approach to Develop Novel Serum Markers in HIV/HCV-co-infected Individuals
Daniel Suzman*1, M McLaughlin1, D Kliener2, A Suffredini3, S Kern3, K Reitano1, D Gonzales3, R Lempicki4, M Polis1, and S Kottilil1
1Lab of Immunoregulation, NIAID, NIH, Bethesda, MD, US; 2NCI, NIH, Bethesda, MD, US; 3NIH, Bethesda, MD, US; and 4SAIC-Frederick/NCI-Frederick, MD, US
Background: The degree of liver fibrosis is a determinant
for initiation of therapy for hepatitis C virus (HCV). Liver biopsy is
invasive, risky, and costly, but is required to assess fibrosis. The purpose of
this study was to develop a model incorporating both previously validated serum
markers, as well as genomic and proteomic fingerprinting to accurately assess
fibrosis in HIV/HCV-co-infected patients.
Methods: Fibrosis was assessed in 59 liver biopsies
obtained from 31 HIV/HCV co-infected patients. Age, sex, CD4+ T cell
count, ART and nevirapine (NVP) use, gene expression profiles and 11 serum
markers identified using Affymetrix U133A also determined. Markers of highest
importance in distinguishing biopsies with Ishak fibrosis scores <3 and ³3 were identified using Radom Forest
analysis and then used in a logistic regression analysis to generate a
predictive model. In addition, serum protein profiling on these patients pre-
and post-HCV therapy was also performed and protein peaks that were
differentially expressed between the those with mild
and advanced fibrosis were identified.
Results: We identified 2 serum markers (α2-macroglobulin
and haptoglobin) and 2 genes (alanyl amino peptidase and mitogen activated
protein) with the highest significance using Random Forest analysis and
included them in the model. Using these 4 markers, the area under the ROC curve
was 0.92. Univariate analysis also revealed 20 protein peaks that were
differentially expressed in mild vs advanced fibrotic biopsies (p <0.01).
Conclusions: Our model using 4 markers accurately predicted
fibrosis in HIV/HCV-co-infected patients. We scored 78% of biopsies as either
above or below our cut-off points, which could thus be classified as having
either mild or advanced fibrosis. In these biopsies, classification was 91%
accurate. Thus, biopsies could have been avoided in the majority of these
patients. In addition, genomic and protein profiling offer additional accuracy
and provide novel markers for correctly predicting fibrosis. Future research
will focus on identifying the functional role of these novel genetic markers in
patients with liver fibrosis. Validating this model on larger cohorts of
HIV/HCV-co-infected patients is necessary to develop non-invasive markers for
liver fibrosis and avoid liver biopsies.
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