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Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein studies, integrative views of the coordinated behavior of multiple proteins in cardiac remodeling are scarce. Here, we developed a workflow that integrates deuterium oxide (2H2O) labeling, high-resolution mass spectrometry (MS), and custom computational methods to systematically interrogate in vivo protein turnover. Using this workflow, we characterized the in vivo turnover kinetics of 2,964 proteins in a mouse model of β-adrenergic-induced cardiac remodeling. The data provided a quantitative and longitudinal view of cardiac remodeling at the molecular level, revealing widespread kinetic regulations in calcium signaling, metabolism, proteostasis, and mitochondrial dynamics. We translated the workflow to human studies, creating a reference dataset of 496 plasma protein turnover rates from 4 healthy adults. The approach is applicable to short, minimal label enrichment and can be performed on as little as a single biopsy, thereby overcoming critical obstacles to clinical investigations. The protein turnover quantitation experiments and computational workflow described here should be widely applicable to large-scale biomolecular investigations of human disease mechanisms with a temporal perspective.

Over the last decade, expanding use of molecular diagnostics in heart transplantation has allowed implementation of non-invasive surveillance strategies for monitoring allograft health. The commercially available HeartCare platform combines the AlloMap gene expression profiling assay and the AlloSure donor-derived cell-free DNA test (dd-cfDNA). Beyond their established use for assessment of rejection, evidence is building for predictive utility, with the longitudinal AlloMap Variability score previously shown to correlate with the risk of future rejection, graft dysfunction, re-transplantation, or death. In this single-center, retrospective pilot study, we evaluated the performance of a novel AlloSure Variability metric in predicting mortality in a cohort of heart transplant recipients. Seventy-two adult heart transplant recipients with at least 3 concurrent AlloMap/AlloSure results were included. Demographic, clinical, imaging, and laboratory parameters were captured. Variability was defined as the standard deviation of longitudinal AlloMap/AlloSure results. A Cox multivariable adjusted proportional hazards model was used to evaluate the variability metrics as predictors of mortality. Associations between AlloMap/AlloSure variability and donor specific antibody (DSA) status were also assessed. A total of 5 patients (6.9%) died during a median follow-up of 480 days. In a univariate Cox proportional hazards model, higher AlloSure variability (HR 1.66, 95%CI 1.14 - 2.41), but not AlloMap variability or the cross-sectional AlloSure/AlloMap results was associated with increased mortality risk. Longitudinal AlloSure variability was also higher among patients with both preformed DSA and those developing DSA. Our results suggest that increased variability of dd-cfDNA in heart transplant patients is associated with both mortality risk and the presence of donor specific antibodies. These findings highlight the added value of longitudinal data in the interpretation of AlloMap/AlloSure scores in this population and open the door to larger studies investigating the utility of these metrics in shaping post-transplant clinical care paradigms.

Multiorgan 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. We 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. Out 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. In 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.

Statin-associated muscle symptoms (SAMS) are a significant clinical issue, and their exact cause is not well understood. Immunological mechanisms have been suggested but have not been confirmed. This study is a rare, longitudinal case-based analysis that uses transcriptomics to explore immune-related gene expression changes in peripheral blood mononuclear cells (PBMCs) in response to exercise before, during, and after the onset and resolution of SAMS. A healthy volunteer (HV1) enrolled in an exercise immuno-fitness study underwent cardiopulmonary exercise testing (CPX) with blood collected at three timepoints: pre-exercise (TP1), peak exercise (TP2), and 1 hour post-exercise (TP3). After baseline testing (Visit 1), the participant began statin therapy on their own, developed SAMS, and had repeat CPX testing during the symptomatic phase (Visit 2) and partial recovery phase (Visit 3). RNA was extracted from PBMCs and analyzed using next-generation RNA sequencing. The data were evaluated using differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Pathway and gene ontology enrichment were used to identify immunologic signatures associated with SAMS. The PBMC gene expression profiles showed distinct changes during SAMS compared to the baseline and recovery phases. WGCNA identified 39 co-expression modules. Several modules had high expression at peak exercise in the healthy state (V1), which was attenuated in SAMS (V2) and partially restored in recovery (V3). Gene ontology and Reactome analyses of key modules identified 16 genes that were differentially expressed at peak exercise and may be involved in specific immune pathways in SAMS pathogenesis. This case study suggests that profiling the exercise-induced immune transcriptome can reveal dynamic immunological changes related to statin-induced myopathy. These findings support the hypothesis of an immune-mediated component in SAMS and provide a basis for future studies to validate transcriptomic biomarkers for the early detection and management of SAMS.

Identification of risk is essential to prevent cardiac allograft vasculopathy (CAV) and graft failure due to CAV (GFDCAV) in heart transplant patients, which account for 30% of all deaths. Early CAV detection involves invasive, risky, and expensive monitoring approaches. We determined whether prediction of CAV and GFDCAV improves by adding inflammatory markers to a previously validated atherothrombotic (AT) model. AT and inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP) were measured in heart biopsies and sera of 172 patients followed prospectively for 8.9±5.0 years. Models were estimated for 5- and 10-year risk using (1) the first post-transplant biopsy only, or (2) all biopsies obtained within 3 months. Multivariate models were adjusted for other covariates and cross-validated by bootstrapping. After adding IL-6 and CRP to the AT models, we evaluated the significance of odds ratios (ORs) associated with the additional inflammatory variables and the degree of improvement in the area under the receiver operating characteristic curve (AUROC). When inflammatory markers were tested alone in prediction models, CRP (not IL-6) was a significant predictor of CAV and GFDCAV at 5 (CAV: p<0.0001; GFDCAV: p = 0.005) and 10 years (CAV: p<0.0001; GFDCAV: p = 0.003). Adding CRP (not IL-6) to the best AT models improved discriminatory power to identify patients destined to develop CAV (using 1st biopsy: p<0.001 and p = 0.001; using all 3-month biopsies: p<0.04 and p = 0.008 at 5- and 10-years, respectively) and GFDCAV (using 1st biopsy: 0.92 vs. 0.95 and 0.86 vs. 0.89; using all 3-month biopsies: 0.94 vs. 0.96 and 0.88 vs. 0.89 at 5- and 10-years, respectively), as indicated by an increase in AUROC. Early inflammatory status, measured by a patient's CRP level (a non-invasive, safe and inexpensive test), independently predicts CAV and GFDCAV. Adding CRP to a previously established AT model improves its predictive power.

Staphylococcus epidermidis remains the predominant pathogen in prosthetic-device infections. Ventricular assist devices, a recently developed form of therapy for end-stage congestive heart failure, have had considerable success. However, infections, most often caused by Staphylococcus epidermidis, have limited their long-term use. The transcutaneous driveline entry site acts as a potential portal of entry for bacteria, allowing development of either localized or systemic infections. A novel in vitro binding assay using explanted drivelines obtained from patients undergoing transplantation and a heterologous lactococcal system of surface protein expression were used to identify S. epidermidis surface components involved in the pathogenesis of driveline infections. Of the four components tested, SdrF, SdrG, PIA, and GehD, SdrF was identified as the primary ligand. SdrF adherence was mediated via its B domain attaching to host collagen deposited on the surface of the driveline. Antibodies directed against SdrF reduced adherence of S. epidermidis to the drivelines. SdrF was also found to adhere with high affinity to Dacron, the hydrophobic polymeric outer surface of drivelines. Solid phase binding assays showed that SdrF was also able to adhere to other hydrophobic artificial materials such as polystyrene. A murine model of infection was developed and used to test the role of SdrF during in vivo driveline infection. SdrF alone was able to mediate bacterial adherence to implanted drivelines. Anti-SdrF antibodies reduced S. epidermidis colonization of implanted drivelines. SdrF appears to play a key role in the initiation of ventricular assist device driveline infections caused by S. epidermidis. This pluripotential adherence capacity provides a potential pathway to infection with SdrF-positive commensal staphylococci first adhering to the external Dacron-coated driveline at the transcutaneous entry site, then spreading along the collagen-coated internal portion of the driveline to establish a localized infection. This capacity may also have relevance for other prosthetic device-related infections.

Immune checkpoint inhibitor (ICI)‐associated myocarditis is a rare, potentially life‐threatening complication of immunotherapy. We report a case of a 60‐year‐old female with a history of colorectal cancer treated with nivolumab immunotherapy who presented with new cardiomyopathy complicated by cardiogenic shock and ventricular arrhythmias. Treatment of ICI‐associated myocarditis requires aggressive immunosuppression and supportive therapy. In this case, the patient required advanced mechanical circulatory support as a bridge to recovery. This case highlights the complexity of diagnosis, haemodynamic management, and treatment of fulminant ICI myocarditis.

Staphylococcus aureus is a leading cause of ventricular assist device-related infections. This study evaluated the protective effect against S. aureus infection of active and passive immunization that targeted 3 proteins involved in bacterial attachment to a murine intra-aortic polyurethane patch. Active immunization of mice with a combination of the A domains of clumping factor A (ClfA), fibronectin-binding protein A (FnBPA) and fibronectin-binding protein B or passive immunization with monoclonal antibodies against ClfA and FnBPA resulted in a higher level of protection than that obtained by vaccination with either protein or antibody alone. The combination of antibodies or protein antigens appears to provide enhanced protection against prosthetic-device infection.

Anthracyclines are highly effective against a variety of malignancies. However, their dose-dependent cardiotoxic effects can potentially limit their use. In the past decade, serum biomarkers have been used to diagnose, monitor, predict, and prognosticate disease. Biomarkers such as cardiac troponin and natriuretic peptides have some predictive value, but still lack reliability in this patient population. Novel biomarkers such as galectin-3, soluble ST-2 proteins, myeloperoxidase, and fibrocytes are being explored as potential biomarkers to reliably predict the onset of cardiotoxicity. Leveraging multiomics technology to map highly sensitive biomarkers in an integrated approach through pattern deconvolution may better define those at highest risk of developing cardiotoxicity and further the goal of precision medicine. In this work, we aim to provide a brief overview of traditional serum biomarkers, summarize current investigations on novel circulating biomarkers, and discuss a systems-based approach to anthracycline-induced cardiotoxicity through “omics” technology.

This engaging book provides a state-of-the-art introduction to the rapidly evolving field of mechanical circulatory support therapy in the care of patients with advanced heart failure. It is aimed at healthcare teams around the world who are involved in patient care, research, and teaching of advanced heart failure; healthcare professionals in training; and interested lay persons.