Genomic Prediction of One Year Survival Status Related to Functional Recovery Potential in Advanced Heart Failure Patients Undergoing Mechanical Circulatory Support

2019 
Purpose Multiorgan Dysfunction Syndrome (MOD) contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant Peripheral Blood Mononuclear Cells (PBMC) activity. We hypothesize that a subset of previously reported 12 preoperative differentially expressed genes (DEGs) correlating with both, Functional Recovery Potential (FRP) (28 genes) and One Year Survival (1YS) (105 genes) [Bondar 2017], could directly predict FRP-related 1YS after MCS surgery. Methods In 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014, PBMC samples were collected on day-1. Clinical data were collected on day-1, day 8 and 1 year after surgery. FRP was classified as Improving if SOFA+MELD-XI scores improved from day -1 to day 8 (n=17) and Non-improving if either one or both scores did not improve from day -1 to day 8 (n=12). The 1YS showed 18 Surviving and 11 Non-surviving patients. Next-generation RNA sequencing transcriptome analysis was performed on purified mRNA and analyzed using Strand NGS. DEGs were identified by Mann-Whitney test with Benjamini-Hochberg correction. We used a support vector machine algorithm to predict FRP- and 1YS-status. Results 1YS was 88% in Improving and 27% in Non-improving groups (log rank p=0.00182). The 12 preoperative DEGs predicted 1YS (accuracy 86%). Hierarchical Clustering analysis (Figures 1A and 1B) demonstrated the consistent expression pattern between FRP and 1YS, suggesting a biological link, supported by gene ontology and pathway analyses. Conclusion In AdHF patients undergoing MCS, the previously reported 12 genes could directly predict the FRP-related 1-year survival. We currently explore the utility of this PBMC biomarker to improve outcome prediction for AdHF patients undergoing various high-risk interventions [Deng 2018].
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