BackgroundHeart failure (HF) prevalence is increasing in the United States. Mechanical Circulatory Support (MCS) therapy is an option for Advanced HF (AdHF) patients. Perioperatively, multiorgan dysfunction (MOD) is linked to the effects of device implantation, augmented by preexisting HF. Early recognition of MOD allows for better diagnosis, treatment, and risk prediction. Gene expression profiling (GEP) was used to evaluate clinical phenotypes of peripheral blood mononuclear cells (PBMC) transcriptomes obtained from patients' blood samples. Whole blood (WB) samples are clinically more feasible, but their performance in comparison to PBMC samples has not been determined.MethodsWe collected blood samples from 31 HF patients (57±15 years old) undergoing cardiothoracic surgery and 7 healthy age-matched controls, between 2010 and 2011, at a single institution. WB and PBMC samples were collected at a single timepoint postoperatively (median day 8 postoperatively) (25–75% IQR 7–14 days) and subjected to Illumina single color Human BeadChip HT12 v4 whole genome expression array analysis. The Sequential Organ Failure Assessment (SOFA) score was used to characterize the severity of MOD into low (≤ 4 points), intermediate (5–11), and high (≥ 12) risk categories correlating with GEP.ResultsResults indicate that the direction of change in GEP of individuals with MOD as compared to controls is similar when determined from PBMC versus WB. The main enriched terms by Gene Ontology (GO) analysis included those involved in the inflammatory response, apoptosis, and other stress response related pathways. The data revealed 35 significant GO categories and 26 pathways overlapping between PBMC and WB. Additionally, class prediction using machine learning tools demonstrated that the subset of significant genes shared by PBMC and WB are sufficient to train as a predictor separating the SOFA groups.ConclusionGEP analysis of WB has the potential to become a clinical tool for immune-monitoring in patients with MOD.

BackgroundMultiorgan dysfunction syndrome contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant leukocyte activity. We tested the hypothesis that preoperative peripheral blood mononuclear cell (PBMC) gene expression profiles (GEP) can predict early postoperative improvement or non-improvement in patients undergoing MCS implantation. We believe this information may be useful in developing prognostic biomarkers.Methods & designWe conducted a study with 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014. PBMC samples were collected one day before surgery (day -1). Clinical data was collected on day -1 and day 8 postoperatively. Patients were classified by Sequential Organ Failure Assessment score and Model of End-stage Liver Disease Except INR score (measured eight days after surgery): Group I = improving (both scores improved from day -1 to day 8, n = 17) and Group II = not improving (either one or both scores did not improve from day -1 to day 8, n = 12). RNA-sequencing was performed on purified mRNA and analyzed using Next Generation Sequencing Strand. Differentially expressed genes (DEGs) were identified by Mann-Whitney test with Benjamini-Hochberg correction. Preoperative DEGs were used to construct a support vector machine algorithm to predict Group I vs. Group II membership.ResultsOut of 28 MCS-surgery patients alive 8 days postoperatively, one-year survival was 88% in Group I and 27% in Group II. We identified 28 preoperative DEGs between Group I and II, with an average 93% prediction accuracy. Out of 105 DEGs identified preoperatively between year 1 survivors and non-survivors, 12 genes overlapped with the 28 predictive genes.ConclusionsIn AdHF patients following MCS implantation, preoperative PBMC-GEP predicts early changes in organ function scores and correlates with long-term outcomes. Therefore, gene expression lends itself to outcome prediction and warrants further studies in larger longitudinal cohorts.

Immunologic impairment may contribute to poor outcomes after implantation of mechanical circulatory support device (MCSD), with infection often as a terminal event. The study of immune dysfunction is of special relevance given the growing numbers of older patients with heart disease. The aim of the study was to define which immunologic characteristics are associated with development of adverse clinical outcomes after MCSD implantation. We isolated peripheral blood mononuclear cells (PBMC) from patients pre- and up to 20 days post-MCSD implantation and analyzed them by multiparameter flow cytometry for T cell dysfunction, including terminal differentiation, exhaustion, and senescence. We used MELD-XI and SOFA scores measured at each time point as surrogate markers of clinical outcome. Older patients demonstrated increased frequencies of terminally differentiated T cells as well as NKT cells. Increased frequency of terminally differentiated and immune senescent T cells were associated with worse clinical outcome as measured by MELD-XI and SOFA scores, and with progression to infection and death. In conclusion, our data suggest that T cell dysfunction, independently from age, is associated with poor outcomes after MCSD implantation, providing a potential immunologic mechanism behind patient vulnerability to multiorgan dysfunction and death. This noninvasive approach to PBMC evaluation holds promise for candidate evaluation and patient monitoring.

Time-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes.