Identification of noninvasive biomarkers for alcohol-induced liver disease using urinary metabolomics and the ppara -null mouse

Soumen K. Manna, Andrew D. Patterson, Qian Yang, Kristopher W. Krausz, Henghong Li, Jeffrey R. Idle, Albert J. Fornace, Frank J. Gonzalez

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


Alcohol-induced liver disease (ALD) is a leading cause of nonaccident-related deaths in the United States. Although liver damage caused by ALD is reversible when discovered at the earlier stages, current risk assessment tools are relatively nonspecific. Identification of an early specific signature of ALD would aid in therapeutic intervention and recovery. In this study, the metabolic changes associated with ALD were examined using alcohol-fed male Ppara-null mouse as a model of ALD. Principal components analysis of the mass spectrometry-based urinary metabolic profile showed that alcohol-treated wild-type and Ppara-null mice could be distinguished from control animals without information on history of alcohol consumption. The urinary excretion of ethyl-sulfate, ethyl-β-d-glucuronide, 4-hydroxyphenylacetic acid, and 4-hydroxyphenylacetic acid sulfate was elevated and that of the 2-hydroxyphenylacetic acid, adipic acid, and pimelic acid was depleted during alcohol treatment in both wild-type and the Ppara-null mice albeit to different extents. However, indole-3-lactic acid was exclusively elevated by alcohol exposure in Ppara-null mice. The elevation of indole-3-lactic acid is mechanistically related to the molecular events associated with development of ALD in alcohol-treated Ppara-null mice. This study demonstrated the ability of a metabolomics approach to identify early, noninvasive biomarkers of ALD pathogenesis in Ppara-null mouse model.

Original languageEnglish (US)
Pages (from-to)4176-4188
Number of pages13
JournalJournal of Proteome Research
Issue number8
StatePublished - Aug 6 2010

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Chemistry(all)


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