Covariation Analysis of Serumal and Urinary Metabolites Suggests Aberrant Glycine and Fatty Acid Metabolism in Chronic Hepatitis B.

BACKGROUND:Chronic hepatitis b (CHB) is one of the most serious viral diseases threatening human health by putting patients at lifelong risk of cirrhosis and hepatocellular carcinoma (HCC). Although some proofs of altered metabolites in CHB were accumulated, its metabolic mechanism remains poorly un...

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Bibliographic Details
Main Authors: Linlin Yang, Xue Yang, Xiangliang Kong, Zhiwei Cao, Yongyu Zhang, Yiyang Hu, Kailin Tang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4881891?pdf=render
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Summary:BACKGROUND:Chronic hepatitis b (CHB) is one of the most serious viral diseases threatening human health by putting patients at lifelong risk of cirrhosis and hepatocellular carcinoma (HCC). Although some proofs of altered metabolites in CHB were accumulated, its metabolic mechanism remains poorly understood. Analyzing covariations between metabolites may provide new hints toward underlying metabolic pathogenesis in CHB patients. METHODS:The present study collected paired urine and serum samples from the same subjects including 145 CHB and 23 healthy controls. A large-scale analysis of metabolites' covariation within and across biofluids was systematically done to explore the underlying biological evidences for reprogrammed metabolism in CHB. Randomization and relative ranking difference were introduced to reduce bias caused by different sample size. More importantly, functional indication was interpreted by mapping differentially changed covariations to known metabolic pathways. RESULTS:Our results suggested reprogrammed pathways related to glycine metabolism, fatty acids metabolism and TCA cycle in CHB patients. With further improvement, the covariation analysis combined with network association study would pave new alternative way to interpret functional clues in clinical multi-omics data.
ISSN:1932-6203