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Published on: July 16, 2012
Molecular pathways differentiate hepatitis C virus (HCV) recurrence from acute cellular rejection in HCV liver
Ricardo Gehrau1, Daniel Maluf, Kellie Archer
1Department of Surgery, Virginia Commonwealth University, Richmond, Virginia, USA.
Insights
Researchers identified a 15-gene molecular signature to differentiate hepatitis C virus recurrence (HCVrec) from acute cellular rejection (ACR) in liver transplant (LT) recipients. This signature aids in diagnosing these common post-transplant complications.
Area of Science:
- Hepatology
- Immunology
- Genomics
Background:
- Hepatitis C virus (HCV) recurrence and acute cellular rejection (ACR) are frequent post-liver transplantation (LT) complications in HCV patients.
- These conditions share clinical and histological features, complicating differential diagnosis.
Purpose of the Study:
- To identify a molecular signature distinguishing HCV recurrence (HCVrec) from ACR in HCV LT recipients.
- To develop a diagnostic tool for differentiating these post-transplant complications.
Main Methods:
- Microarray analysis of 53 liver allograft samples from HCV LT recipients.
- Differential gene expression analysis using ANOVA and limma package.
- Development and validation of a LASSO model classifier with 15 genes.
Main Results:
- 179 probe sets were differentially expressed; 71 genes were exclusive to HCVrec or HCV-ACR.
- HCVrec-related genes showed a cytotoxic T-cell profile; HCV-ACR genes indicated an inflammatory response.
- The 15-gene LASSO model achieved 100% accuracy in the training set and 78.1% in cross-validation.
Conclusions:
- A validated 15-gene molecular signature can distinguish HCV recurrence from acute cellular rejection in HCV LT recipients.
- This signature provides a potential diagnostic tool for managing post-liver transplant complications.
- Key genes like ARG2, ETHE1, TMEM176A, and TMEM176B were confirmed in the validation set.
Abstract:
Acute cellular rejection (ACR) and hepatitis C virus (HCV) recurrence (HCVrec) are common complications after liver transplantation (LT) in HCV patients, who share common clinical and histological features, making a differential diagnosis difficult. Fifty-three liver allograft samples from unique HCV LT recipients were studied using microarrays, including a training set (n = 32) and a validation set (n = 19). Two no-HCV-ACR samples from LT recipients were also included. Probe set intensity values were obtained using the robust multiarray average method (RMA) method. Analysis of variance identified statistically differentially expressed genes (P ≤ 0.005). The limma package was used to fit the mixed-effects models using a restricted maximum likelihood procedure. The last absolute shrinkage and selection operator (LASSO) model was fit with HCVrec versus ACR as the dependent variable predicted. N-fold cross-validation was performed to provide an unbiased estimate of generalization error. A total of 179 probe sets were differentially expressed among groups, with 71 exclusive genes between HCVrec and HCV-ACR. No differences were found within ACR group (HCV-ACR vs. no-HCV-ACR). Supervised clustering analysis displayed two clearly independent groups, and no-HCV-ACR clustered within HCV-ACR. HCVrec-related genes were associated with a cytotoxic T-cell profile, and HCV-ACR-related genes were associated with the inflammatory response. The best-fitting LASSO model classifier accuracy, including 15 genes, has an accuracy of 100% in the training set. N-fold cross-validation accuracy was 78.1%, and sensitivity, specificity and positive and negative predictive values were 50.0%, 90.9%, 71.4% and 80.0%, respectively. Arginase type II (ARG2), ethylmalonic encephalopathy 1 (ETHE1), transmembrane protein 176A (TMEM176A) and TMEM176B genes were significantly confirmed in the validation set. A molecular signature capable of distinguishing HCVrec and ACR in HCV LT recipients was identified and validated.
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