A peripheral blood transcriptome biomarker test to diagnose functional recovery potential in advanced heart failure

Towards identification of postharvest fruit quality transcriptomic markers in Malus domestica

Gene expression is highly impacted by the environment and can be reflective of past events that affected developmental processes. It is therefore expected that gene expression can serve as a signal of a current or future phenotypic traits. In this paper we identify sets of genes, which we call Prognostic Transcriptomic Biomarkers (PTBs), that can predict firmness in Malus domestica (apple) fruits. In apples, all individuals of a cultivar are clones, and differences in fruit quality are due to the environment. The apples transcriptome responds to these differences in environment, which makes PTBs an attractive predictor of future fruit quality. PTBs have the potential to enhance supply chain efficiency, reduce crop loss, and provide higher and more consistent quality for consumers. However, several questions must be addressed. In this paper we answer the question of which of two common modeling approaches, Random Forest or ElasticNet, outperforms the other. We answer if PTBs with few genes are efficient at predicting traits. This is important because we need few genes to perform qPCR, and we answer the question if qPCR is a cost-effective assay as input for PTBs modeled using high-throughput RNA-seq. To do this, we conducted a pilot study using fruit texture in the 'Gala' variety of apples across several postharvest storage regiments. Fruit texture in 'Gala' apples is highly controllable by post-harvest treatments and is therefore a good candidate to explore the use of PTBs. We find that the RandomForest model is more consistent than an ElasticNet model and is predictive of firmness (r2 = 0.78) with as few as 15 genes. We also show that qPCR is reasonably consistent with RNA-seq in a follow up experiment. Results are promising for PTBs, yet more work is needed to ensure that PTBs are robust across various environmental conditions and storage treatments.

The Role of Gut Microbiota in Heart Failure: When Friends Become Enemies

Heart failure is a complex health issue, with important consequences on the overall wellbeing of patients. It can occur both in acute and chronic forms and, in the latter, the immune system appears to play an important role in the pathogenesis of the disease. In particular, in the forms with preserved ejection fraction or with only mildly reduced ejection fraction, some specific associations with chronic inflammatory diseases have been observed. Another interesting aspect that is worth considering is the role of microbiota modulation, in this context: given the importance of microbiota in the modulation of immune responses, it is possible that changes in its composition may somewhat influence the progression and even the pathogenesis of heart failure. In this narrative review, we aim to examine the relationship between immunity and heart failure, with a special focus on the role of microbiota in this pathological condition.

The evolution of patient-specific precision biomarkers to guide personalized heart-transplant care

Introduction

In parallel to the clinical maturation of heart transplantation over the last 50 years, rejection testing has been revolutionized within the systems biology paradigm triggered by the Human Genome Project.

Areas Covered

We have co-developed the first FDA-cleared diagnostic and prognostic leukocyte gene expression profiling biomarker test in transplantation medicine that gained international evidence-based medicine guideline acceptance to rule out moderate/severe acute cellular cardiac allograft rejection without invasive endomyocardial biopsies. This work prompted molecular re-classification of intragraft biology, culminating in the identification of a pattern of intragraft myocyte injury, in addition to acute cellular rejection and antibody-mediated rejection. This insight stimulated research into non-invasive detection of myocardial allograft injury. The addition of a donor-organ specific myocardial injury marker based on donor-derived cell-free DNA further strengthens the non-invasive monitoring concept, combining the clinical use of two complementary non-invasive blood-based measures, host immune activity-related risk of acute rejection as well as cardiac allograft injury.

Expert Opinion

This novel complementary non-invasive heart transplant monitoring strategy based on leukocyte gene expression profiling and donor-derived cell-free DNA that incorporates longitudinal variability measures provides an exciting novel algorithm of heart transplant allograft monitoring. This algorithm's clinical utility will need to be tested in an appropriately designed randomized clinical trial which is in preparation.

Comparing NGS and NanoString platforms in peripheral blood mononuclear cell transcriptome profiling for advanced heart failure biomarker development

In preparation to create a clinical assay that predicts 1-year survival status of advanced heart failure (AdHF) patients before surgical/interventional therapies and to select the appropriate clinical assay platform for the future assay, we compared the properties of next generation sequencing (NGS) used in the gene discovery phase to the NanoString platform used in the clinical assay development phase. In 25 AdHF patients in a tertiary academic medical center from 2015 to 2016, PBMC samples were collected and aliquoted for NGS RNA whole transcriptome sequencing and compared to 770 genes represented on NanoString's PanCancer IO 360 Gene Expression research panel. Prior to statistical analysis, NanoString and NGS expression values were log transformed. We computed Pearson correlation coefficients for each sample, comparing gene expression values between NanoString and NGS across the set of matched genes and for each of the matched genes across the set of samples. Genes were grouped by average NGS expression, and the NanoString-NGS correlation for each group was computed. Out of 770 genes from the NanoString panel, 734 overlapped between both platforms and showed high intrasample correlation. Within an individual sample, there was an expression-level dependent correlation between both platforms. The low- vs. intermediate/high-expression groups showed NGS average correlation 0.21 vs. 0.58-0.68, respectively, and NanoString average correlation 0.07-0.34 vs. 0.59-0.70, respectively. NanoString demonstrated high reproducibility (R 2 > 0.99 for 100 ng input), sensitivity (probe counts between 100 and 500 detected and quantified), and robustness (similar gene signature scores across different RNA input concentrations, cartridges, and outcomes). Data from NGS and NanoString were highly correlated. These platforms play a meaningful, complementary role in the biomarker development process.

Short-Term Therapies for Treatment of Acute and Advanced Heart Failure-Why so Few Drugs Available in Clinical Use, Why Even Fewer in the Pipeline?

Both acute and advanced heart failure are an increasing threat in term of survival, quality of life and socio-economical burdens. Paradoxically, the use of successful treatments for chronic heart failure can prolong life but-per definition-causes the rise in age of patients experiencing acute decompensations, since nothing at the moment helps avoiding an acute or final stage in the elderly population. To complicate the picture, acute heart failure syndromes are a collection of symptoms, signs and markers, with different aetiologies and different courses, also due to overlapping morbidities and to the plethora of chronic medications. The palette of cardio- and vasoactive drugs used in the hospitalization phase to stabilize the patient's hemodynamic is scarce and even scarcer is the evidence for the agents commonly used in the practice (e.g. catecholamines). The pipeline in this field is poor and the clinical development chronically unsuccessful. Recent set backs in expected clinical trials for new agents in acute heart failure (AHF) (omecamtiv, serelaxine, ularitide) left a field desolately empty, where only few drugs have been approved for clinical use, for example, levosimendan and nesiritide. In this consensus opinion paper, experts from 26 European countries (Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, The Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, Turkey, U.K. and Ukraine) analyse the situation in details also by help of artificial intelligence applied to bibliographic searches, try to distil some lesson-learned to avoid that future projects would make the same mistakes as in the past and recommend how to lead a successful development project in this field in dire need of new agents.

Established and Emerging Roles of Biomarkers in Heart Failure

Heart failure (HF) is a complex syndrome with an enormous societal burden in terms of cost, morbidity, and mortality. Natriuretic peptide testing is now widely used to support diagnosis, prognostication, and management of patients with HF and are incorporated into HF clinical practice guidelines. Beyond the natriuretic peptides, novel biomarkers may supplement traditional clinical and laboratory testing to improve understanding of the complex disease process of HF and possibly to personalize care for those affected through better individual phenotyping. In this review, we will discuss natriuretic peptides and the more novel biomarkers by dividing them into categories based on the major pathophysiologic pathways they represent. Given the complex physiology in HF, it is reasonable to expect that the future of biomarker testing lies in the application of multimarker testing panels, precision medicine to improve HF care delivery, and the use of biomarkers in proteomics and metabolomics to further improve HF care.