Professional paper
Prediction of liver fibrosis and cirrhosis in chronic hepatitis B infection by serum proteomic fingerprinting
Maro Bujak
; Division of molecular medicine, Laboratory for systemic biomedicine, Rudjer Boskovic Institute, Zagreb, Croatia
Abstract
Aim: Most noninvasive predicti ve models of liver fi brosis are complicated and
have subopti mal sensiti vity. The study described in this paper was designed to identi fy serum
proteomic signatures associated with liver fi brosis and to develop a proteome-based
fi ngerprinti ng model for predicti on of liver fi brosis. Methods: Serum proteins from 46 pati
ents with chronic liver hepati ti s B were profi led quanti tati vely on surface-enhanced laser
desorpti on/ionizati on proteinChip arrays. This liver fi brosis-associated proteomic fi ngerprint
was used to construct an arti fi cial neural network (ANN) model that produced a fi brosis index
with a range of 0-6. Results: Values for 30 serum proteomic features were signifi cantly
associated with the degree of fi brosis. Conclusions: A unique serum proteomic fi ngerprint is
present in the sera of pati ents with fi brosis. An ANN fi brosis index derived from this fi ngerprint
could diff erenti ate between diff erent stages of fi brosis and predict fi brosis and cirrhosis
in chronic hepati ti s B.
Keywords
hepatitis B; liver cirrhosis; protein profile; proteinchip arrays; SELDI
Hrčak ID:
43671
URI
Publication date:
1.9.2009.
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