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A network-based approach to identify expression modules underlying rejection in pediatric liver transplantation

ABSTRACT: Selecting the right immunosuppressant to ensure rejection-free outcomes poses unique challenges in pediatric liver transplant (LT) recipients. A molecular predictor can comprehensively address these challenges. Although early acute cellular rejection (ACR) is mediated by cytotoxic T-cells, late rejection also includes antibody-mediated damage in addition to cell-mediated injury. Currently, there are no well-validated blood-based biomarkers for pediatric LT recipients either pre- or post- transplant. Here, we discover and validate separate pre- and post- transplant molecular signatures of LT outcome from whole blood transcriptomes. Using an integrative machine learning approach, we combine transcriptomic data with the high-quality reference human protein interactome network to identify differentially regulated functional sub-components of the network, or “network module signatures”, which drive ACR. Unlike gene signatures, our approach is inherently multivariate, more robust to replication and captures the structure of the underlying molecular network, encapsulating additive effects. We also identify, in a patient-specific manner, network module signatures that can be targeted by current anti-rejection drugs and other mechanisms that can be repurposed. Overall, our approach can enable personalized adjustment of drug regimens for the dominant targetable pathways in pre- and post- LT in children.

ORGANISM(S): Homo sapiens

PROVIDER: GSE200340 | GEO | 2022/04/11

REPOSITORIES: GEO

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Project description:Recurrent hepatitis C virus (rHCV) is universal post-liver transplantation (LT), with accelerated fibrosis rates compared to non-transplanted patients. rHCV is associated with increased mortality and morbidity post-transplant and is a leading indication for re-transplantation. We hypothesized that miRNA expression profiles from liver grafts can distinguish severity of HCV recurrence and differentiate this from acute cellular rejection (ACR). Methods Using microarrays, we characterized global microRNA (miRNA) expression from patients with slow HCV fibrosis progression (F<2 Ishak), fast HCV fibrosis progression (FM-bM-^IM-%2 Ishak), ACR and non-HCV transplanted patients. Selected miRNA were analysed by quantitative PCR (qPCR) using both liver tissue and serum samples. Results We demonstrated changes in miRNA expression in patients with slow HCV fibrosis progression that were anti-fibrogenic, anti-angiogenic and anti-inflammatory in comparison to patients with fast HCV fibrosis progression. miRNA-146a, miRNA-19a, miRNA- 20a and miRNA-let-7e expression were increased in the slow HCV fibrosis progression group. In addition, comparison of patients with fast HCV progression against patients with ACR identified pro-fibrogenic pathways. qPCR analysis on liver tissue and serum confirmed the up-regulation of miRNAs in the slow HCV fibrosis progression group. Conclusion We demonstrate specific miRNA expression signatures that distinguish rate of progression of HCV recurrence and ACR post M-bM-^@M-^Sliver transplantation. Pathway analysis indicates that specific miRNA may play a regulatory role in these processes. The miRNAs identified may act as potential biomarkers for HCV recurrence post-LT and help distinguish between ACR and recurrent HCV. We compared 29 patients in total; 11 patients with slow HCV fibrosis progression, 9 patients with fast HCV fibrosis progression, 5 patients with acute cellular rejection and 4 HCV negative patients with normal liver histology that acted as controls. RNA was extracted from archived histology samples of the RG and NRG and miRNA expression was analysed using the affymetrix Genechip miRNA 2.0 assays.

Project description:Operational tolerance after solid organ transplantation is defined as stable graft acceptance without immunosuppression while maintaining normal immunocompetence against immunological insults. However, it is not clear yet which cellular and molecular pathways are driving tolerance in these patients and how this state can be induced in order to improve graft survival. Several transcriptomic analysis have shown that transcription signatures in blood can reflect the immunological state associated with operational tolerance in kidney transplant. Nonetheless, epigenetic dynamics orchestrating these transcription signatures have not yet been studied. Here, we performed genome-wide analysis of DNA methylation of kidney transplant recipients with chronic rejection and operational tolerance. Our data showed that chronic rejection and operational tolerance recipients have differential DNA methylation in 2737 genes, indicating that each patient group has a specific epigenetic signature associated with transplant outcome. In addition, we observed that operational tolerance is associated with DNA demethylation in genes involved in immune function, including B cell activation (e.g. ST6GAL1, MS4A1 and MEF2C) and the Th17 differentiation program (e.g. LY9 and BATF), while in CR patients is mostly associated intracellular signaling and ubiquitination pathways. Finally, we used weighted gene co-expression network analysis (WGCNA) to select the more defining epigenetic changes associated with operational tolerance. By this method, we select 12 genomic regions specifically hypomethylated (HIVEP2, HOMER1, UTRN, PTPRO, SP100 and JAZF1) or hypermethylated (EMZ8, EZR-AS, WDR20, NADSYN1, TBCD and MED17) in tolerant patients. Analysis of these genes in stable transplant recipients with immunosuppression showed that these patients have a similar methylation signature to operational tolerance recipients. Overall, these results demonstrate that DNA methylation in blood can mirror the immune status associated with kidney transplant outcome and provides a starting point for understanding the epigenetic mechanisms associated with operational tolerance.

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A network-based approach to identify expression modules underlying rejection in pediatric liver transplantation

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