Dataset Information

Distinct patterns of the lipid alterations between genotype 1 and 2 chronic hepatitis C patients after viral clearance.

ABSTRACT:

Background

The hepatitis C virus (HCV) genotype-specific impacts on the host metabolic alterations remained inconclusive.

Methods

A prospective study including 229 (118 genotype 1 (G1) and 111 G2) consecutive chronic HCV patients who had completed a course of anti-HCV treatment and underwent pre- and 24 weeks post-treatment surveys of metabolic profiles was conducted. Patients were stratified according to the therapeutic response, viral genotype and baseline insulin resistance (IR: homeostasis model assessments of IR (HOMA-IR) ? 2.5). Paired t-tests were used to compare the pre- and post-treatment variables.

Results

Significant post-therapeutic increases in cholesterol, triglyceride, HDL, LDL, apolipoprotein A1 and apolipoprotein B were observed in patients with sustained virological response (SVR) but not in those without. Among those with SVR, post-therapeutic increases in HDL (p<0.001) and apolipoprotein A1 (p = 0.012) were only found in G2, whereas increased triglyceride/HDL (p = 0.01) ratios were only found in G1 patients. When stratified by baseline IR among those with SVR, a significant increase in post-treatment HDL (p = 0.019) and apolipoprotein A1 (p = 0.012) but a decrease in HOMA-IR (p = 0.04), C-peptide (p = 0.019) and hemoglobin A1c (p = 0.047) were found in patients with baseline IR; a significant increase in HOMA-IR (p = 0.002) was found in patients without baseline IR. The latter change was observed only in G1 (p = 0.01) but not G2 patients. Although the pre-treatment metabolic profiles of G1 and G2 patients were indifferent, G1 had higher post-treatment triglyceride/HDL ratios (p = 0.041) and triglyceride (p = 0.044) levels than G2 patients.

Conclusions

G2 benefit more than G1 patients from viral clearance in metabolic alterations, particularly in those without baseline IR.

SUBMITTER: Chang ML

PROVIDER: S-EPMC4133245 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Distinct patterns of the lipid alterations between genotype 1 and 2 chronic hepatitis C patients after viral clearance.

Chang Ming-Ling ML Tsou Yung-Kuan YK Hu Tsung-Hui TH Lin Cheng-Hui CH Lin Wey-Ran WR Sung Chang-Mu CM Chen Tsung-Hsing TH Cheng Mei-Ling ML Chang Kuo-Chin KC Chiu Cheng-Tang CT Yeh Chau-Ting CT Pang Jong-Hwei Su JH Shiao Ming-Shi MS

PloS one 20140814 8

<h4>Background</h4>The hepatitis C virus (HCV) genotype-specific impacts on the host metabolic alterations remained inconclusive.<h4>Methods</h4>A prospective study including 229 (118 genotype 1 (G1) and 111 G2) consecutive chronic HCV patients who had completed a course of anti-HCV treatment and underwent pre- and 24 weeks post-treatment surveys of metabolic profiles was conducted. Patients were stratified according to the therapeutic response, viral genotype and baseline insulin resistance (IR ...[more]

PMID: 25122116

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Project description:Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC. KEY POINTS: • Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker. • Gut microbiota composition is significantly altered in different etiological factors of HCC. • Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.

Dataset Information

Distinct patterns of the lipid alterations between genotype 1 and 2 chronic hepatitis C patients after viral clearance.

Background

Methods

Results

Conclusions

Publications

Distinct patterns of the lipid alterations between genotype 1 and 2 chronic hepatitis C patients after viral clearance.

Similar Datasets

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