*Purpose: Liver steatosis is a known risk factor for exacerbated ischemia-reperfusion injury (IRI) and poor outcomes after liver transplantation (LT). RNA profiling was performed to gain hepatic expression profiles of mRNAs and miRNAs in fatty (F) and non-fatty (NF) liver donors in paired pre-implantation (PI) and post-Reperfusion (PR) biopsies to identify those pathways associated with worse injury during IRI.

*Methods: A total of 88 samples from 44 LT patients were evaluated. Liver steatosis was defined by histology with macro steatosis >20%. Gene and miRNA expression was done using microarrays and thresholds of a two-fold change and a false discovery rate (FDR) less than 0.05 were used. Ingenuity Pathway Analyses and Cytoscape were used for data analyses, integration and network identification.

*Results: 237 mRNAs and 17 miRNAs (most of them targeting genes associated with increased inflammatory disease and response) were identified as differentially expressed when comparing PI biopsies between F vs. NF liver donors (FC >2, FDR <0.05). When comparing PI vs. PR samples, 53 and 24 miRNAs and 2,730 and 1,338 probe sets were significant between F vs non-F livers, respectively. Using IPA filters, 18 miRNAs (including miR-486-5p, miR-297, miR-6780b-5p with FC>6) targeting 331 mRNAs with appropriated directionality in expression were identified from integrative analyses for F livers. Cell-to cell signaling interaction, cell cycle, cell death and lipid metabolism were the top biological functions associated with the differentially expressed molecular features. Adipogenesis pathway was identified as the top canonical function. Then, 10 miRNA -mRNA regulatory pathways were obtained, and networks were constructed for the F livers. The top regulatory network included as disease and molecular functions accumulation of lipids, apoptosis cell lines, quantity of antigen presenting cells, and quantity of macrophages with high positive consistency score: 89.3 (a high consistency score associates with increased consistent paths— those that connect an upstream regulator to a target and then to a disease or function). This regulatory network included 73 nodes and 42 regulators (i.e., Ca2, CAMP, CD40, EBK1/2, miR-155-5p, palmate acid, among others) targeting 23 differentially expressed molecular features in our data set (i.e., ABCA1, ATF3, CCL20, CCL3, CDKNJA1, CXL1, KRAS, NF2, SERPINE 1). Representative miRNAs and mRNAs were validated by real-time qPCR.

*Conclusions: The analyses of regulators effects using integrative approaches allow to identify how the fatty liver is affected during IRI by activated or inhibited upstream regulators. Consequently, integrated analysis of mRNA and miRNA profiles in liver tissue represents a powerful tool to identify novel targets for assessing with accuracy organ injury associated with graft steatosis.

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