Hepatic gene expression profiles differentiate presymptomatic patients with mild versus severe nonalcoholic fatty liver disease.

Journal Article

UNLABELLED: Clinicians rely upon the severity of liver fibrosis to segregate patients with well-compensated nonalcoholic fatty liver disease (NAFLD) into subpopulations at high- versus low-risk for eventual liver-related morbidity and mortality. We compared hepatic gene expression profiles in high- and low-risk NAFLD patients to identify processes that distinguish the two groups and hence might be novel biomarkers or treatment targets. Microarray analysis was used to characterize gene expression in percutaneous liver biopsies from low-risk, "mild" NAFLD patients (fibrosis stage 0-1; n = 40) and high-risk, "severe" NAFLD patients (fibrosis stage 3-4; n = 32). Findings were validated in a second, independent cohort and confirmed by real-time polymerase chain reaction and immunohistochemistry (IHC). As a group, patients at risk for bad NAFLD outcomes had significantly worse liver injury and more advanced fibrosis (severe NAFLD) than clinically indistinguishable NAFLD patients with a good prognosis (mild NAFLD). A 64-gene profile reproducibly differentiated severe NAFLD from mild NAFLD, and a 20-gene subset within this profile correlated with NAFLD severity, independent of other factors known to influence NAFLD progression. Multiple genes involved with tissue repair/regeneration and certain metabolism-related genes were induced in severe NAFLD. Ingenuity Pathway Analysis and IHC confirmed deregulation of metabolic and regenerative pathways in severe NAFLD and revealed overlap among the gene expression patterns of severe NAFLD, cardiovascular disease, and cancer. CONCLUSION: By demonstrating specific metabolic and repair pathways that are differentially activated in livers with severe NAFLD, gene profiling identified novel targets that can be exploited to improve diagnosis and treatment of patients who are at greatest risk for NAFLD-related morbidity and mortality.

Full Text

Duke Authors

Cited Authors

  • Moylan, CA; Pang, H; Dellinger, A; Suzuki, A; Garrett, ME; Guy, CD; Murphy, SK; Ashley-Koch, AE; Choi, SS; Michelotti, GA; Hampton, DD; Chen, Y; Tillmann, HL; Hauser, MA; Abdelmalek, MF; Diehl, AM

Published Date

  • February 2014

Published In

Volume / Issue

  • 59 / 2

Start / End Page

  • 471 - 482

PubMed ID

  • 23913408

Electronic International Standard Serial Number (EISSN)

  • 1527-3350

Digital Object Identifier (DOI)

  • 10.1002/hep.26661

Language

  • eng

Conference Location

  • United States