Heart Failure in the Era of Precision Medicine: A Scientific Statement From the American Heart Association

Research landscape of genetics in dilated cardiomyopathy: insight from a bibliometric analysis

Background

Dilated cardiomyopathy (DCM) is a heterogeneous myocardial disorder with diverse genetic or acquired origins. Notable advances have been achieved in discovering and understanding the genetics of DCM. This study aimed to depict the distribution of the main research forces, hotspots, and frontiers in the genetics of DCM, thus shaping future research directions.

Methods

Based on the documents published in the Web of Science Core Collection database from 2013 to 2022, co-authorship of authors, institutions, and countries/regions, co-citation of references, and co-occurrence of keywords were conducted respectively to present the distribution of the leading research forces, research hotspots, and emerging trends in the genetics of DCM.

Results

4,141 documents were included, and the annual publications have steadily increased. Seidman, Christine E, Meder, Benjamin, Sinagra, Gianfranco were the most productive authors, German Centre for Cardiovascular Research was the most productive institution, and the USA, China, and Germany were the most prolific countries. The co-occurrence of keywords has generated 8 clusters, including DCM, lamin a/c, heart failure, sudden cardiac death, hypertrophic cardiomyopathy, cardiac hypertrophy, arrhythmogenic cardiomyopathy, and next-generation sequencing. Frequent keywords with average publication time after 2019 mainly included arrhythmogenic cardiomyopathy, whole-exome sequencing, RBM 20, phenotype, risk stratification, precision medicine, genotype, and machine learning.

Conclusion

The research landscape of genetics in DCM is continuously evolving. Deciphering the genetic profiles by next-generation sequencing and illustrating pathogenic mechanisms of gene variants, establishing innovative treatments for heart failure and improved risk stratification for SCD, uncovering the genetic overlaps between DCM and other inherited cardiomyopathies, as well as identifying genotype-phenotype correlations are the main research hotspots and frontiers in this field.

Machine learning-based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure

Aims

Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical characteristics and established biomarkers, carry optimal prognostic capacity for adverse events, in patients with HFrEF.

Methods and results

In 382 patients, we performed repeated blood sampling (median follow-up: 2.1 years) and applied an aptamer-based multiplex proteomic approach. We used machine learning to select the optimal set of predictors for the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization). The association between repeated measures of selected proteins and PEP was investigated by multivariable joint models. Internal validation (cross-validated c-index) and external validation (Henry Ford HF PharmacoGenomic Registry cohort) were performed. Nine proteins were selected in addition to the MAGGIC risk score, N-terminal pro-hormone B-type natriuretic peptide, and troponin T: suppression of tumourigenicity 2, tryptophanyl-tRNA synthetase cytoplasmic, histone H2A Type 3, angiotensinogen, deltex-1, thrombospondin-4, ADAMTS-like protein 2, anthrax toxin receptor 1, and cathepsin D. N-terminal pro-hormone B-type natriuretic peptide and angiotensinogen showed the strongest associations [hazard ratio (95% confidence interval): 1.96 (1.17-3.40) and 0.66 (0.49-0.88), respectively]. The multivariable model yielded a c-index of 0.85 upon internal validation and c-indices up to 0.80 upon external validation. The c-index was higher than that of a model containing established risk factors (P = 0.021).

Conclusion

Nine serially measured proteins captured the most essential prognostic information for the occurrence of adverse events in patients with HFrEF, and provided incremental value for HF prognostication beyond established risk factors. These proteins could be used for dynamic, individual risk assessment in a prospective setting. These findings also illustrate the potential value of relatively 'novel' biomarkers for prognostication.

Clinical Trial Registration

https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 24.

Multi-omic analyses and network biology in cardiovascular disease

Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.

Transcriptome studies of inherited dilated cardiomyopathies

Dilated cardiomyopathy (DCM) is a group of heart muscle diseases that often lead to heart failure, with more than 50 causative genes have being linked to DCM. The heterogenous nature of the inherited DCMs suggest the need of precision medicine. Consistent with this emerging concept, transcriptome studies in human patients with DCM indicated distinct molecular signature for DCMs of different genetic etiology. To facilitate this line of research, we reviewed the status of transcriptome studies of inherited DCMs by focusing on three predominant DCM causative genes, TTN, LMNA, and BAG3. Besides studies in human patients, we summarized transcriptomic analysis of these inherited DCMs in a variety of model systems ranging from iPSCs to rodents and zebrafish. We concluded that the RNA-seq technology is a powerful genomic tool that has already led to the discovery of new modifying genes, signaling pathways, and related therapeutic avenues. We also pointed out that both temporal (different pathological stages) and spatial (different cell types) information need to be considered for future transcriptome studies. While an important bottle neck is the low throughput in experimentally testing differentially expressed genes, new technologies in efficient animal models such as zebrafish starts to be developed. It is anticipated that the RNA-seq technology will continue to uncover both unique and common pathological events, aiding the development of precision medicine for inherited DCMs.

The role of dietary salt in metabolism and energy balance: Insights beyond cardiovascular disease

Dietary salt (NaCl) is essential to an organism's survival. However, today's diets are dominated by excessive salt intake, which significantly impacts individual and population health. High salt intake is closely linked to cardiovascular disease (CVD), especially hypertension, through a number of well-studied mechanisms. Emerging evidence indicates that salt overconsumption may also be associated with metabolic disorders. In this review, we first summarize recent updates on the mechanisms of salt-induced CVD, the effects of salt reduction and the use of salt substitution as a therapy. Next, we focus on how high salt intake can impact metabolism and energy balance, describing the mechanisms through which this occurs, including leptin resistance, the overproduction of fructose and ghrelin, insulin resistance and altered hormonal factors. A further influence on metabolism worth noting is the reported role of salt in inducing thermogenesis and increasing body temperature, leading to an increase in energy expenditure. While this result could be viewed as a positive metabolic effect because it promotes a negative energy balance to combat obesity, caution must be taken with this frame of thinking given the deleterious consequences of chronic high salt intake on cardiovascular health. Nevertheless, this review highlights the importance of salt as a noncaloric nutrient in regulating whole-body energy homeostasis. Through this review, we hope to provide a scientific framework for future studies to systematically address the metabolic impacts of dietary salt and salt replacement treatments. In addition, we hope to form a foundation for future clinical trials to explore how these salt-induced metabolic changes impact obesity development and progression, and to elucidate the regulatory mechanisms that drive these changes, with the aim of developing novel therapeutics for obesity and CVD.

Prevalence of Fabry Disease in patients with left ventricular hypertrophy in Turkey: Multicenter study (LVH-TR subgroup analysis)

PURPOSE

In this prospective study we aimed to determine the rate of Fabry Disease (FD) in patients with left ventricular hypertrophy (LVH), and to evaluate the clinical presentations of patients with FD in a comprehensive manner. In addition, we aimed to raise awareness about this issue by allowing early diagnosis and treatment of FD.

METHODS

Our study was planned as national, multicenter, observational. Totally 22 different centers participated in this study. A total of 886 patients diagnosed with LVH by echocardiography (ECHO) were included in the study. Demographic data, biochemical parameters, electrocardiography (ECG) findings, ECHO findings, treatments and clinical findings of the patients were recorded. Dry blood samples were sent from male patients with suspected FD. The α-Gal A enzyme level was checked and genetic testing was performed in patients with low enzyme levels. Female patients suspected of FD were genetically tested with the GLA Gene Mutation Analysis.

RESULTS

FD was suspected in a total of 143 (16.13%) patients included in the study. The α-Gal-A enzyme level was found to be low in 43 (4.85%) patients whom enzyme testing was requested. GLA gene mutation analysis was positive in 14 (1.58%) patients. Male gender, E/e' mean ,and severe hypertrophy are important risk factor for FD.

CONCLUSION

In daily cardiology practice, FD should be kept in mind not only in adult patients with unexplained LVH but also in the entire LVH population. Dry blood test (DBS) should be considered in high-risk patients, and mutation analysis should be considered in required patients.

The heart and gut relationship: a systematic review of the evaluation of the microbiome and trimethylamine-N-oxide (TMAO) in heart failure

There is an expanding body of research on the bidirectional relationship of the human gut microbiome and cardiovascular disease, including heart failure (HF). Researchers are examining the microbiome and gut metabolites, primarily trimethylamine-N-oxide (TMAO), to understand clinically observed outcomes. This systematic review explored the current state of the science on the evaluation and testing of the gut biome in persons with HF. Using electronic search methods of Medline, Embase, CINAHL, and Web of Science, until December 2021, we identified 511 HF biome investigations between 2014 and 2021. Of the 30 studies included in the review, six were 16S rRNA and nineteen TMAO, and three both TMAO and 16S rRNA, and two bacterial cultures. A limited range of study designs were represented, the majority involving single cohorts (n = 10) and comparing individuals with HF to controls (n = 15). Patients with HF had less biodiversity in fecal samples compared to controls. TMAO is associated with age, BNP, eGFR, HF severity, and poor outcomes including hospitalizations and mortality. Inconsistent across studies was the ability of TMAO to predict HF development, the independent prognostic value of TMAO when controlling for renal indices, and the relationship of TMAO to LVEF and CRP. Gut microbiome dysbiosis is associated with HF diagnosis, disease severity, and prognostication related to hospitalizations and mortality. Gut microbiome research in patients with HF is developing. Further longitudinal and multi-centered studies are required to inform interventions to promote clinical decision-making and improved patient outcomes.

New strategies and therapies for the prevention of heart failure in high-risk patients

Despite declines in total cardiovascular mortality rates in the United States, heart failure (HF) mortality rates as well as hospitalizations and readmissions have increased in the past decade. Increases have been relatively higher among young and middle-aged adults (<65 years). Therefore, identification of individuals HF at-risk (Stage A) or with pre-HF (Stage B) before the onset of overt clinical signs and symptoms (Stage C) is urgently needed. Multivariate risk models (e.g., Pooled Cohort Equations to Prevent Heart Failure [PCP-HF]) have been externally validated in diverse populations and endorsed by the 2022 HF Guidelines to apply a risk-based framework for the prevention of HF. However, traditional risk factors included in the PCP-HF model only account for half of an individual's lifetime risk of HF; novel risk factors (e.g., adverse pregnancy outcomes, impaired lung health, COVID-19) are emerging as important risk-enhancing factors that need to be accounted for in personalized approaches to prevention. In addition to determining the role of novel risk-enhancing factors, integration of social determinants of health (SDoH) in identifying and addressing HF risk is needed to transform the current clinical paradigm for the prevention of HF. Comprehensive strategies to prevent the progression of HF must incorporate pharmacotherapies (e.g., sodium glucose co-transporter-2 inhibitors that have also been termed the "statins" of HF prevention), intensive blood pressure lowering, and heart-healthy behaviors. Future directions include investigation of novel prediction models leveraging machine learning, integration of risk-enhancing factors and SDoH, and equitable approaches to interventions for risk-based prevention of HF.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021. Structure: Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021.

STRUCTURE

Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure

Patients with heart failure (HF) are heterogeneous with various intrapersonal and interpersonal characteristics contributing to clinical outcomes. Bias, structural racism, and social determinants of health have been implicated in unequal treatment of patients with HF. Through several methodologies, artificial intelligence (AI) can provide models in HF prediction, prognostication, and provision of care, which may help prevent unequal outcomes. This review highlights AI as a strategy to address racial inequalities in HF; discusses key AI definitions within a health equity context; describes the current uses of AI in HF, strengths and harms in using AI; and offers recommendations for future directions.

Reviewing the suitability of mitochondrial transplantation as therapeutic approach for pulmonary hypertension in the era of personalised medicine

Pulmonary hypertension (PH) is a fatal disease, defined as a mean pulmonary artery pressure ≥ 25 mm Hg. It is caused, in part, by mitochondrial dysfunction. Among the various biological therapies proposed to rescue mitochondrial dysfunction, evidence going back as far as 2009, suggests that mitochondrial transplantation is an alternative. Although scant, recent PH findings and other literature supports a role for mitochondrial transplantation as a therapeutic approach in the context of PH. In experimental models of PH, it confers beneficial effects that include reduced pulmonary vasoconstriction, reduced pulmonary vascular remodelling, and improved right ventricular function. It also reduces the proliferation of pulmonary artery smooth muscle cells. However, first, we must understand that more research is needed before mitochondrial transplantation can be considered an effective therapy in the clinical setting, as many of the mechanisms or potential long-term risks are still unknown. Second, the current challenges of mitochondrial transplantation are surmountable and should not deter researchers from further investigating its effectiveness and trying to overcome these challenges in creative ways.

Underrecognition of sleep-disordered breathing and other common health conditions in the West Virginia Medicaid population: a driver of poor health outcomes

STUDY OBJECTIVES

To assess the prevalence rates of sleep-disordered breathing (SDB) in a high-risk and rural-dwelling Medicaid population with significant comorbidities.

METHODS

Our study analyzed anonymized administrative claims data from West Virginia (WV) Medicaid. Claims data from 2019 were aggregated at the individual level to assess the overall prevalence of SDB and related conditions among adult Medicaid beneficiaries. The prevalence rate of SDB, specifically among individuals who had comorbid congestive heart failure, chronic obstructive pulmonary disease, or obesity, was determined. Finally, we compared our prevalence estimates from this Medicaid database with prevalence rates from national datasets including the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.

RESULTS

Of the total 413,757 Medicaid enrollees ≥ 18 years old analyzed, 36,433 had a diagnosis code of SDB for an overall prevalence of 8.8%. Based on national datasets and our study cohort characteristics, we conservatively estimated the prevalence of SDB in this WV Medicaid population to be 25%. For our secondary analyses, we determined the prevalence of SDB in specific disease cohorts of congestive heart failure (SDB prevalence 45%), chronic obstructive pulmonary disease (SDB prevalence 27%), and obesity (SDB prevalence 14%).

CONCLUSIONS

Our analysis of WV Medicaid claims data indicates that SDB and other important medical conditions are underrecognized in this vulnerable, high-risk, primarily rural population. Interestingly, SDB was identified at high rates in the disease cohorts of interest. Our team believes SDB represents an ideal target/model for addressing the growing health disparities in the United States, which is a major concern for all stakeholders in health care.

CITATION

Stansbury R, Strollo P, Pauly N, et al. Underrecognition of sleep-disordered breathing and other common health conditions in the West Virginia Medicaid population: a driver of poor health outcomes. J Clin Sleep Med. 2022;18(3):817-824.

Dynamic personalized risk prediction in chronic heart failure patients: a longitudinal, clinical investigation of 92 biomarkers (Bio-SHiFT study)

The aim of our observational study was to derive a small set out of 92 repeatedly measured biomarkers with optimal predictive capacity for adverse clinical events in heart failure, which could be used for dynamic, individual risk assessment in clinical practice. In 250 chronic HFrEF (CHF) patients, we collected trimonthly blood samples during a median of 2.2 years. We selected 537 samples for repeated measurement of 92 biomarkers with the Cardiovascular Panel III (Olink Proteomics AB). We applied Least Absolute Shrinkage and Selection Operator (LASSO) penalization to select the optimal set of predictors of the primary endpoint (PE). The association between repeatedly measured levels of selected biomarkers and the PE was evaluated by multivariable joint models (mvJM) with stratified fivefold cross validation of the area under the curve (cvAUC). The PE occurred in 66(27%) patients. The optimal set of biomarkers selected by LASSO included 9 proteins: NT-proBNP, ST2, vWF, FABP4, IGFBP-1, PAI-1, PON-3, transferrin receptor protein-1, and chitotriosidase-1, that yielded a cvAUC of 0.88, outperforming the discriminative ability of models consisting of standard biomarkers (NT-proBNP, hs-TnT, eGFR clinically adjusted) − 0.82 and performing equally well as an extended literature-based set of acknowledged biomarkers (NT-proBNP, hs-TnT, hs-CRP, GDF-15, ST2, PAI-1, Galectin 3) − 0.88. Nine out of 92 serially measured circulating proteins provided a multivariable model for adverse clinical events in CHF patients with high discriminative ability. These proteins reflect wall stress, remodelling, endothelial dysfunction, iron deficiency, haemostasis/fibrinolysis and innate immunity activation. A panel containing these proteins could contribute to dynamic, personalized risk assessment.

Clinical Trial Registration: 10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1.

Advance Care Planning Documentation and Intensity of Care at the End of Life for Adults With Congestive Heart Failure, Chronic Kidney Disease, and Both Illnesses

CONTEXT

Heart failure (HF) and chronic kidney disease (CKD) are associated with high morbidity and mortality, especially in combination, yet little is known about the impact of these conditions together on end-of-life care.

OBJECTIVES

Compare end-of-life care and advance care planning (ACP) documentation among patients with both HF and CKD to those with either condition.

METHODS

We conducted a retrospective analysis of deceased patients (2010-2017) with HF and CKD (n = 1673), HF without CKD (n = 2671), and CKD without HF (n = 1706), excluding patients with cancer or dementia. We compared hospitalizations and intensive care unit (ICU) admissions in the last 30 days of life, hospital deaths, and ACP documentation >30 days before death.

RESULTS

39% of patients with HF and CKD were hospitalized and 33% were admitted to the ICU in the last 30 days vs. 30% and 28%, respectively, for HF, and 26% and 23% for CKD. Compared to patients with both conditions, those with only 1 were less likely to be admitted to the hospital [HF: adjusted odds ratio (aOR) 0.72, 95%CI 0.63-0.83; CKD: aOR 0.63, 95%CI 0.53-0.75] and ICU (HF: aOR 0.83, 95%CI 0.71-0.94; CKD: aOR 0.68, 95%CI 0.56-0.80) and less likely to have ACP documentation (aOR 0.53, 95%CI 0.47-0.61 and aOR 0.70, 95%CI 0.60-0.81).

CONCLUSIONS

Decedents with both HF and CKD had more ACP documentation and received more intensive end-of-life care than those with only 1 condition. These findings suggest that patients with co-existing HF and CKD may benefit from interventions to ensure care received aligns with their goals.

Clinical Implication of Genetic Testing in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is one of the important causes of heart failure (HF). With the rapidly evolving technologies for gene analysis and tremendous advances in knowledge of HF genetics, the importance of genetic testing in DCM is currently highlighted. Several genetic variants causing DCM have been identified and this information is used for diagnosis, risk stratification and family screening of DCM patients. However, there are still several challenges in applying genetic testing to real clinical practice. In this review, we will summarize recent understandings in DCM genetics and provide an evidence-based practical guide to the use of genetic testing for DCM patients.

Dietary Management of Heart Failure: DASH Diet and Precision Nutrition Perspectives

Heart failure (HF) is a major health care burden increasing in prevalence over time. Effective, evidence-based interventions for HF prevention and management are needed to improve patient longevity, symptom control, and quality of life. Dietary Approaches to Stop Hypertension (DASH) diet interventions can have a positive impact for HF patients. However, the absence of a consensus for comprehensive dietary guidelines and for pragmatic evidence limits the ability of health care providers to implement clinical recommendations. The refinement of medical nutrition therapy through precision nutrition approaches has the potential to reduce the burden of HF, improve clinical care, and meet the needs of diverse patients. The aim of this review is to summarize current evidence related to HF dietary recommendations including DASH diet nutritional interventions and to develop initial recommendations for DASH diet implementation in outpatient HF management. Articles involving human studies were obtained using the following search terms: Dietary Approaches to Stop Hypertension (DASH diet), diet pattern, diet, metabolism, and heart failure. Only full-text articles written in English were included in this review. As DASH nutritional interventions have been proposed, limitations of these studies are the small sample size and non-randomization of interventions, leading to less reliable evidence. Randomized controlled interventions are needed to offer definitive evidence related to the use of the DASH diet in HF management.

The clinical utility of pediatric cardiomyopathy genetic testing: From diagnosis to a precision medicine-based approach to care

Background

Pediatric-onset cardiomyopathies are rare yet cause significant morbidity and mortality in affected children. Genetic testing has a major role in the clinical evaluation of pediatric-onset cardiomyopathies, and identification of a variant in an associated gene can be used to confirm the clinical diagnosis and exclude syndromic causes that may warrant different treatment strategies. Further, risk-predictive testing of first-degree relatives can assess who is at-risk of disease and requires continued clinical follow-up.

Aim of Review

In this review, we seek to describe the current role of genetic testing in the clinical diagnosis and management of patients and families with the five major cardiomyopathies. Further, we highlight the ongoing development of precision-based approaches to diagnosis, prognosis, and treatment.

Key Scientific Concepts of Review

Emerging application of genotype-phenotype correlations opens the door for genetics to guide a precision medicine-based approach to prognosis and potentially for therapies. Despite advances in our understanding of the genetic etiology of cardiomyopathy and increased accessibility of clinical genetic testing, not all pediatric cardiomyopathy patients have a clear genetic explanation for their disease. Expanded genomic studies are needed to understand the cause of disease in these patients, improve variant classification and genotype-driven prognostic predictions, and ultimately develop truly disease preventing treatment.

HFIP: an integrated multi-omics data and knowledge platform for the precision medicine of heart failure

As the terminal clinical phenotype of almost all types of cardiovascular diseases, heart failure (HF) is a complex and heterogeneous syndrome leading to considerable morbidity and mortality. Existing HF-related omics studies mainly focus on case/control comparisons, small cohorts of special subtypes, etc., and a large amount of multi-omics data and knowledge have been generated. However, it is difficult for researchers to obtain biological and clinical insights from these scattered data and knowledge. In this paper, we built the Heart Failure Integrated Platform (HFIP) for data exploration, fusion analysis and visualization by collecting and curating existing multi-omics data and knowledge from various public sources and also provided an auto-updating mechanism for future integration. The developed HFIP contained 253 datasets (7842 samples), multiple analysis flow, and 14 independent tools. In addition, based on the integration of existing databases and literature, a knowledge base for HF was constructed with a scoring system for evaluating the relationship between molecular signals and HF. The knowledge base includes 1956 genes and annotation information. The literature mining module was developed to assist the researcher to overview the hotspots and contexts in basic and clinical research. HFIP can be used as a data-driven and knowledge-guided platform for the basic and clinical research of HF.

Database URL: http://heartfailure.medical-bigdata.com

Towards precision medicine in heart failure

The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.

Comparison of household income in in-hospital outcomes after implantation of left ventricular assist device

INTRODUCTION

Due to the inability to keep up with the demand for heart transplantation, there is an increased utilization of left ventricular assist devices (LVAD). However, paucity of data exists regarding the association of household income with in-hospital outcomes after LVAD implantation.

METHODS

Retrospective cohort study using the NIS to identify all patients ⩾18 years who underwent LVAD implantation from 2011 to 2017. Statistical analysis was performed comparing low household income (⩽50th percentile) and high income (>50th percentile).

RESULTS

A total of 25,503 patients underwent LVAD implantation. The low-income group represented 53% and the high-income group corresponded to 47% of the entire cohort. The low-income group was found to be younger (mean age 55 ± 14 vs 58 ± 14 years), higher proportion of females (24% vs 22%), and higher proportion of blacks (32% vs 16%, p < 0.001 for all). The low-income group was found to have higher prevalence of hypertension, chronic pulmonary disease, smoking, dyslipidemia, obesity, and pulmonary hypertension (p < 0.001 for all). However, the high-income cohort had higher rate of atrial tachyarrhythmias and end-stage renal disease (p < 0.001). During hospitalization, patients in the high-income group had increased rates of ischemic stroke, acute kidney injury, acute coronary syndrome, bleeding, and need of extracorporeal membrane oxygenation (p < 0.001 for all). We found that the unadjusted mortality had an OR 1.30 (CI 1.21-1.41, p < 0.001) and adjusted mortality of OR 1.14 (CI 1.05-1.23, p = 0.002).

CONCLUSION

In patients undergoing LVAD implantation nationwide, low-income was associated with increased comorbidity burden, younger age, and fewer in-hospital complications and all-cause mortality.

Endotyping in Heart Failure - Identifying Mechanistically Meaningful Subtypes of Disease

Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle "big data", a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.

What can heart failure trialists learn from oncology trialists?

Globally, there has been little change in mortality rates from cardiovascular (CV) diseases or cancers over the past two decades (1997-2018). This is especially true for heart failure (HF) where 5-year mortality rates remain as high as 45-55%. In the same timeframe, the proportion of drug revenue, and regulatory drug approvals for cancer drugs, far out paces those for CV drugs. In 2018, while cancer drugs made 27% of Food and Drug Administration drug approvals, only 1% of drug approvals was for a CV drug, and over this entire 20 year span, only four drugs were approved for HF in the USA. Cardiovascular trialists need to reassess the design, execution, and purpose of CV clinical trials. In the area of oncology research, trials are much smaller, follow-up is shorter, and targeted therapies are common. Cardiovascular diseases and cancer are the two most common causes of death globally, and although they differ substantially, this review evaluates whether some elements of oncology research may be applicable in the CV arena. As one of the most underserved CV diseases, the review focuses on aspects of cancer research that may be applicable to HF research with the aim of streamlining the clinical trial process and decreasing the time and cost required to bring safe, effective, treatments to patients who need them. The paper is based on discussions among clinical trialists, industry representatives, regulatory authorities, and patients, which took place at the Cardiovascular Clinical Trialists Workshop in Washington, DC, on 8 December 2019 (https://www.globalcvctforum.com/2019 (14 September 2020)).

Senescence mechanisms and targets in the heart

Cellular senescence is a state of irreversible cell cycle arrest associated with ageing. Senescence of different cardiac cell types can direct the pathophysiology of cardiovascular diseases such as atherosclerosis, myocardial infarction, and cardiac fibrosis. While age-related telomere shortening represents a major cause of replicative senescence, the senescent state can also be induced by oxidative stress, metabolic dysfunction, and epigenetic regulation, among other stressors. It is critical that we understand the molecular pathways that lead to cellular senescence and the consequences of cellular senescence in order to develop new therapeutic approaches to treat cardiovascular disease. In this review, we discuss molecular mechanisms of cellular senescence, explore how cellular senescence of different cardiac cell types (including cardiomyocytes, cardiac endothelial cells, cardiac fibroblasts, vascular smooth muscle cells, valve interstitial cells) can lead to cardiovascular disease, and highlight potential therapeutic approaches that target molecular mechanisms of cellular senescence to prevent or treat cardiovascular disease.

Refocusing on the Primary Prevention of Heart Failure

Purpose of review

The burden of heart failure (HF) is a significant national and global public health problem, with prevalence rates on the rise. Given the significant morbidity, mortality, and healthcare costs attributable to HF, it is of utmost importance to utilize preventive strategies to prevent the development of HF. Therefore, we sought to address how a multi-modal risk assessment approach can be used to stratify patients for HF risk and guide implementation of therapeutic strategies to prevent HF.

Recent findings

New externally validated, multivariate prediction models for incident HF can be applied in the general population and may be used to aide clinicians in assessing individualized HF risk and screening for HF. Recent clinical trial data suggest a natriuretic peptide biomarker-based screening approach coupled with team-based cardiovascular care to focus on optimization of guideline-directed medical therapy may help prevent new-onset HF. However, widespread implementation of clinical risk scores and/or biomarkers is needed.

Summary

In addition to promoting a heart healthy lifestyle, prevention and management of modifiable risk factors, including intensive blood pressure lowering and use of sodium-glucose cotransporter-2 inhibitors, can prevent incident HF.

Toward the Effective Bioengineering of a Pathological Tissue for Cardiovascular Disease Modeling: Old Strategies and New Frontiers for Prevention, Diagnosis, and Therapy

Cardiovascular diseases (CVDs) still represent the primary cause of mortality worldwide. Preclinical modeling by recapitulating human pathophysiology is fundamental to advance the comprehension of these diseases and propose effective strategies for their prevention, diagnosis, and treatment. In silico, in vivo, and in vitro models have been applied to dissect many cardiovascular pathologies. Computational and bioinformatic simulations allow developing algorithmic disease models considering all known variables and severity degrees of disease. In vivo studies based on small or large animals have a long tradition and largely contribute to the current treatment and management of CVDs. In vitro investigation with two-dimensional cell culture demonstrates its suitability to analyze the behavior of single, diseased cellular types. The introduction of induced pluripotent stem cell technology and the application of bioengineering principles raised the bar toward in vitro three-dimensional modeling by enabling the development of pathological tissue equivalents. This review article intends to describe the advantages and disadvantages of past and present modeling approaches applied to provide insights on some of the most relevant congenital and acquired CVDs, such as rhythm disturbances, bicuspid aortic valve, cardiac infections and autoimmunity, cardiovascular fibrosis, atherosclerosis, and calcific aortic valve stenosis.

Updates in pharmacotherapy of heart failure with reduced ejection fraction

Heart failure is a common entity encountered in healthcare with a vast socioeconomic impact. Recent advances in pharmacotherapy have led to the development of novel therapies with mortality benefits, improvement in heart failure symptoms and hospitalizations. This article is intended to explore those newer pharmacotherapies and summarize the evidence behind guideline directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF). It has been several years since any significant advances in pharmacotherapy of heart failure have resulted in survival benefit. Angiotensin-neprilysin inhibitors through the PARADIGM-HF and PIONEER-HF trials have shown mortality benefits and a reduction in heart failure hospitalizations and are considered landmark trials in heart failure. Vericiguat is an oral guanylate cyclase stimulator that through the recent VICTORIA trial showed a 10% relative difference in death from cardiovascular cause or hospitalization for heart failure. The sodium-glucose transport protein 2 (SGLT2) inhibitors are another class of medications that have shown promise in the treatment of patients with HFrEF and diabetes mellitus. The CANVAS and EMPA-REG OUTCOME trials showed the potential benefit of SGLT2 inhibitors on cardiovascular mortality, DECLARE-TIMI 58 trial showed that treatment with dapagliflozin reduced the risk of cardiovascular death or hospitalization for heart failure to a greater extent in patients with reduced ejection fraction (EF). Although novel pharmacotherapy is the current focus of intense research, there have been numerous studies on potential benefit of iron supplementation in ferropenic patients with heart failure. Another rapidly expanding area of research in the realm of heart failure is precision medicine and its impact on the development, progression, and treatment of heart failure. The field of heart failure is dynamic and with the influx of data from recent and ongoing trials, newer therapies with morbidity and mortality benefits in HFrEF are now available, nonetheless, much work is still needed.

Precision medicine in acute respiratory distress syndrome: workshop report and recommendations for future research

Acute respiratory distress syndrome (ARDS) is a devastating critical illness that can be triggered by a wide range of insults and remains associated with a high mortality of around 40%. The search for targeted treatment for ARDS has been disappointing, possibly due to the enormous heterogeneity within the syndrome. In this perspective from the European Respiratory Society research seminar on "Precision medicine in ARDS", we will summarise the current evidence for heterogeneity, explore the evidence in favour of precision medicine and provide a roadmap for further research in ARDS. There is evident variation in the presentation of ARDS on three distinct levels: 1) aetiological; 2) physiological and 3) biological, which leads us to the conclusion that there is no typical ARDS. The lack of a common presentation implies that intervention studies in patients with ARDS need to be phenotype aware and apply a precision medicine approach in order to avoid the lack of success in therapeutic trials that we faced in recent decades. Deeper phenotyping and integrative analysis of the sources of variation might result in identification of additional treatable traits that represent specific pathobiological mechanisms, or so-called endotypes.

Cell-Based Therapies for Heart Failure

Heart failure has reached epidemic proportions with the advances in cardiovascular therapies for ischemic heart diseases and the progressive aging of the world population. Efficient pharmacological therapies are available for treating heart failure, but unfortunately, even with optimized therapy, prognosis is often poor. Their last therapeutic option is, therefore, a heart transplantation with limited organ supply and complications related to immunosuppression. In this setting, cell therapies have emerged as an alternative. Many clinical trials have now been performed using different cell types and injection routes. In this perspective, we will analyze the results of such trials and discuss future perspectives for cell therapies as an efficacious treatment of heart failure.

Screening for Fabry Disease in patients with unexplained left ventricular hypertrophy

Fabry Disease (FD) is a systemic disorder that can result in cardiovascular, renal, and neurovascular disease leading to reduced life expectancy. FD should be considered in the differential of all patients with unexplained left ventricular hypertrophy (LVH). We therefore performed a prospective screening study in Edmonton and Hong Kong using Dried Blood Spot (DBS) testing on patients with undiagnosed LVH. Participants found to have unexplained LVH on echocardiography were invited to participate and subsequently subjected to DBS testing. DBS testing was used to measure α-galactosidase (α-GAL) enzyme activity and for mutation analysis of the α-galactosidase (GLA) gene, both of which are required to make a diagnosis of FD. DBS testing was performed as a screening tool on patients (n = 266) in Edmonton and Hong Kong, allowing for detection of five patients with FD (2% prevalence of FD) and one patient with hydroxychloroquine-induced phenocopy. Left ventricular mass index (LVMI) by GLA genotype showed a higher LVMI in patients with IVS4 + 919G > A mutations compared to those without the mutation. Two patients were initiated on ERT and hydroxychloroquine was discontinued in the patient with a phenocopy of FD. Overall, we detected FD in 2% of our screening cohort using DBS testing as an effective and easy to administer screening tool in patients with unexplained LVH. Utilizing DBS testing to screen for FD in patients with otherwise undiagnosed LVH is clinically important due to the availability of effective therapies and the value of cascade screening in extended families.

Advances in the Genetics and Genomics of Heart Failure

PURPOSE OF REVIEW

The purpose of this review is to provide an update on the recent advances in the genetics and genomics of dilated cardiomyopathy and heart failure.

RECENT FINDINGS

Over the last decade, the approach to the discovery of the genetic contribution to heart failure has evolved from investigation of rare variants implicated in Mendelian cardiomyopathies through linkage studies and candidate gene studies to the exploration of the contribution of common variants through large-scale genome-wide association and genome-first studies. The combination and integration of multiple of case-control heart failure cohorts, refinement of the heart failure phenotype, and utilization of large biobanks linked to electronic health records have advanced the understanding of the heritability of heart failure.

Two-Dimensional and Three-Dimensional Transthoracic Echocardiography as Predictive and Prognostic Indicators of All-Cause Mortality in Heart Failure with Reduced Ejection Fraction in Patients with Ischemic Heart Disease

Background

This study aimed to compare the predictive role of two-dimensional transthoracic echocardiography (2D-TTE) and three-dimensional transthoracic echocardiography (3D-TTE) on in-hospital all-cause mortality in patients with heart failure and reduced ejection fraction (HFrEF) due to ischemic heart disease (IHD).

Material/Methods

Patients (N-224) with HFrEF due to IHD who had a left ventricular ejection fraction (LVEF) <40% on admission when measured by 2D-TTE and 3D-TTE were studied and divided into survival and mortality groups. Baseline demographic and clinical characteristics were compared.

Results

Compared with the survival group (n=142), patients who died during hospitalization (n=82) were more commonly older (67.3 vs. 62.6 years), female (48.8% vs. 38.7%), with diabetes mellitus (51.2% vs. 32.4%), chronic kidney disease (48.8% vs. 32.4%), intravenous inotropes (85.4% vs. 76.1%), and intravenous vasodilators (70.7% vs. 61.3%). Regression model analysis for all-cause mortality identified significant associations with age, diabetes mellitus, myocardial infarction (MI), intravenous inotropes, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and LVEF following 2D-TTE. Age, diabetes mellitus, prior MI, the use of intravenous inotropes, NT-proBNP, LVEF, and left ventricular end-diastolic volume (LVEDV) index following 3D-TTE were significantly associated with all-cause mortality. Modeling of 2D-TTE parameters showed that the concordance statistic (C-index) increased significantly after including the LVEF, from 0.72 to 0.77 and from 0.72 to 0.80, respectively. Modeling of 3D-TTE parameters showed that the C-index increased significantly after including the LVEDV index (from 0.80 to 0.76).

Conclusions

In patients with HFrEF due to IHD, 3D-TTE was a better predictor than 2D-TTE of in-hospital all-cause mortality.