Network Analysis to Risk Stratify Patients With Exercise Intolerance

Cluster analysis identifies novel real-world lung disease-pulmonary hypertension subphenotypes: implications for treatment response

Background

Clinical trials repurposing pulmonary arterial hypertension (PAH) therapies to patients with lung disease- or hypoxia-pulmonary hypertension (PH) (classified as World Health Organization Group 3 PH) have failed to show a consistent benefit. However, Group 3 PH clinical heterogeneity suggests robust phenotyping may inform detection of treatment-responsive subgroups. We hypothesised that cluster analysis would identify subphenotypes with differential responses to oral PAH therapy.

Methods

Two k-means analyses were performed on a national cohort of US veterans with Group 3 PH; an inclusive model (I) of all treated patients (n=196) and a haemodynamic model (H) limited to patients with right heart catheterisations (n=112). The primary outcome was organ failure or all-cause mortality by cluster. An exploratory analysis evaluated within-cluster treatment effects.

Results

Three distinct clusters of Group 3 PH patients were identified. In the inclusive model (C1I n=43, 21.9%; C2I n=102, 52.0%; C3I n=51, 26.0%), lung disease and spirometry drove cluster assignment. By contrast, in the haemodynamic model (C1H n=44, 39.3%; C2H n=43, 38.4%; C3H n=25, 22.3%), right heart catheterisation data surpassed the importance of lung disease and spirometry. In the haemodynamic model, compared to C3H, C1H experienced the greatest hazard for respiratory failure or death (HR 6.1, 95% CI 3.2-11.8). In an exploratory analysis, cluster determined treatment response (p=0.006). Conclusions regarding within-cluster treatment responses were limited by significant differences between select variables in the treated and untreated groups.

Conclusions

Cluster analysis identifies novel real-world subphenotypes of Group 3 PH patients with distinct clinical trajectories. Future studies may consider this methodological approach to identify subgroups of heterogeneous patients that may be responsive to existing pulmonary vasodilatory therapies.

Advanced hemodynamic and cluster analysis for identifying novel RV function subphenotypes in patients with pulmonary hypertension

BACKGROUND

Quantifying right ventricular (RV) function is important to describe the pathophysiology of in pulmonary hypertension (PH). Current phenotyping strategies in PH rely on few invasive hemodynamic parameters to quantify RV dysfunction severity. The aim of this study was to identify novel RV phenotypes using unsupervised clustering methods on advanced hemodynamic features of RV function.

METHODS

Participants were identified from the University of Arizona Pulmonary Hypertension Registry (n = 190). RV-pulmonary artery coupling (Ees/Ea), RV systolic (Ees), and diastolic function (Eed) were quantified from stored RV pressure waveforms. Consensus clustering analysis with bootstrapping was used to identify the optimal clustering method. Pearson correlation analysis was used to reduce collinearity between variables. RV cluster subphenotypes were characterized using clinical data and compared to pulmonary vascular resistance (PVR) quintiles.

RESULTS

Five distinct RV clusters (C1-C5) with distinct RV subphenotypes were identified using k-medoids with a Pearson distance matrix. Clusters 1 and 2 both have low diastolic stiffness (Eed) and afterload (Ea) but RV-PA coupling (Ees/Ea) is decreased in C2. Intermediate cluster (C3) has a similar Ees/Ea as C2 but with higher PA pressure and afterload. Clusters C4 and C5 have increased Eed and Ea but C5 has a significant decrease in Ees/Ea. Cardiac output was high in C3 distinct from the other clusters. In the PVR quintiles, contractility increased and stroke volume decreased as a function of increased afterload. World Symposium PH classifications were distributed across clusters and PVR quintiles.

CONCLUSIONS

RV-centric phenotyping offers an opportunity for a more precise-medicine-based management approach.

Elevated Pulmonary Arterial Compliance Is Associated with Survival in Pulmonary Hypertension: Results from a Novel Network Medicine Analysis

Rationale: Predictors of adverse outcome in pulmonary hypertension (PH) are well established; however, data that inform survival are lacking. Objectives: We aim to identify clinical markers and therapeutic targets that inform the survival in PH. Methods: We included data from patients with elevated mean pulmonary artery pressure (mPAP) diagnosed by right heart catheterization in the U.S. Veterans Affairs system (October 1, 2006-September 30, 2018). Network medicine framework was used to subgroup patients when considering an N of 79 variables per patient. The results informed outcome analyses in the discovery cohort and a sex-balanced validation right heart catheterization cohort from Vanderbilt University (September 24, 1998-December 20, 2013). Measurements and Main Results: From an N of 4,737 complete case patients with mPAP of 19-24 mm Hg, there were 21 distinct subgroups (network modules) (all-cause mortality range = 15.9-61.2% per module). Pulmonary arterial compliance (PAC) drove patient assignment to modules characterized by increased survival. When modeled continuously in patients with mPAP ⩾19 mm Hg (N = 37,744; age, 67.2 yr [range = 61.7-73.8 yr]; 96.7% male; median follow-up time, 1,236 d [range = 570-1,971 d]), the adjusted all-cause mortality hazard ratio was <1.0 beginning at PAC ⩾3.0 ml/mm Hg and decreased progressively to ∼7 ml/mm Hg. A protective association between PAC ⩾3.0 ml/mm Hg and mortality was also observed in the validation cohort (N = 1,514; age, 60.2 yr [range = 49.2-69.1 yr]; 48.0% male; median follow-up time, 2,485 d [range = 671-3,580 d]). The association was strongest in patients with precapillary PH at the time of catheterization, in whom 41% (95% confidence interval, 0.55-0.62; P < 0.001) and 49% (95% confidence interval, 0.38-0.69; P < 0.001) improvements in survival were observed for PAC ⩾3.0 versus <3.0 ml/mm Hg in the discovery and validation cohorts, respectively. Conclusions: These data identify elevated PAC as an important parameter associated with survival in PH. Prospective studies are warranted that consider PAC ⩾3.0 ml/mm Hg as a therapeutic target to achieve through proven interventions.

Integrative Interpretation of Cardiopulmonary Exercise Tests for Cardiovascular Outcome Prediction: A Machine Learning Approach

Integrative interpretation of cardiopulmonary exercise tests (CPETs) may improve assessment of cardiovascular (CV) risk. Here, we identified patient phenogroups based on CPET summary metrics and evaluated their predictive value for CV events. We included 2280 patients with diverse CV risk who underwent maximal CPET by cycle ergometry. Key CPET indices and information on incident CV events (median follow-up time: 5.3 years) were derived. Next, we applied unsupervised clustering by Gaussian Mixture modeling to subdivide the cohort into four male and four female phenogroups solely based on differences in CPET metrics. Ten of 18 CPET metrics were used for clustering as eight were removed due to high collinearity. In males and females, the phenogroups differed significantly in age, BMI, blood pressure, disease prevalence, medication intake and spirometry. In males, phenogroups 3 and 4 presented a significantly higher risk for incident CV events than phenogroup 1 (multivariable-adjusted hazard ratio: 1.51 and 2.19; p ≤ 0.048). In females, differences in the risk for future CV events between the phenogroups were not significant after adjustment for clinical covariables. Integrative CPET-based phenogrouping, thus, adequately stratified male patients according to CV risk. CPET phenomapping may facilitate comprehensive evaluation of CPET results and steer CV risk stratification and management.

Medical Management of Pulmonary Arterial Hypertension: Current Approaches and Investigational Drugs

Pulmonary arterial hypertension (PAH) is a malignant pulmonary vascular syndrome characterized by a progressive increase in pulmonary vascular resistance and pulmonary arterial pressure, which eventually leads to right heart failure and even death. Although the exact mechanism of PAH is not fully understood, pulmonary vasoconstriction, vascular remodeling, immune and inflammatory responses, and thrombosis are thought to be involved in the development and progression of PAH. In the era of non-targeted agents, PAH had a very dismal prognosis with a median survival time of only 2.8 years. With the deep understanding of the pathophysiological mechanism of PAH as well as advances in drug research, PAH-specific therapeutic drugs have developed rapidly in the past 30 years, but they primarily focus on the three classical signaling pathways, namely the endothelin pathway, nitric oxide pathway, and prostacyclin pathway. These drugs dramatically improved pulmonary hemodynamics, cardiac function, exercise tolerance, quality of life, and prognosis in PAH patients, but could only reduce pulmonary arterial pressure and right ventricular afterload to a limited extent. Current targeted agents delay the progression of PAH but cannot fundamentally reverse pulmonary vascular remodeling. Through unremitting efforts, new therapeutic drugs such as sotatercept have emerged, injecting new vitality into this field. This review comprehensively summarizes the general treatments for PAH, including inotropes and vasopressors, diuretics, anticoagulants, general vasodilators, and anemia management. Additionally, this review elaborates the pharmacological properties and recent research progress of twelve specific drugs targeting three classical signaling pathways, as well as dual-, sequential triple-, and initial triple-therapy strategies based on the aforementioned targeted agents. More crucially, the search for novel therapeutic targets for PAH has never stopped, with great progress in recent years, and this review outlines the potential PAH therapeutic agents currently in the exploratory stage to provide new directions for the treatment of PAH and improve the long-term prognosis of PAH patients.

Tensions in Taxonomies: Current Understanding and Future Directions in the Pathobiologic Basis and Treatment of Group 1 and Group 3 Pulmonary Hypertension

In the over 100 years since the recognition of pulmonary hypertension (PH), immense progress and significant achievements have been made with regard to understanding the pathophysiology of the disease and its treatment. These advances have been mostly in idiopathic pulmonary arterial hypertension (IPAH), which was classified as Group 1 Pulmonary Hypertension (PH) at the Second World Symposia on PH in 1998. However, the pathobiology of PH due to chronic lung disease, classified as Group 3 PH, remains poorly understood and its treatments thus remain limited. We review the history of the classification of the five groups of PH and aim to provide a state-of-the-art review of the understanding of the pathogenesis of Group 1 PH and Group 3 PH including insights gained from novel high-throughput omics technologies that have revealed heterogeneities within these categories as well as similarities between them. Leveraging the substantial gains made in understanding the genomics, epigenomics, proteomics, and metabolomics of PAH to understand the full spectrum of the complex, heterogeneous disease of PH is needed. Multimodal omics data as well as supervised and unbiased machine learning approaches after careful consideration of the powerful advantages as well as of the limitations and pitfalls of these technologies could lead to earlier diagnosis, more precise risk stratification, better predictions of disease response, new sub-phenotype groupings within types of PH, and identification of shared pathways between PAH and other types of PH that could lead to new treatment targets. © 2023 American Physiological Society. Compr Physiol 13:4295-4319, 2023.

A Sedentary and Unhealthy Lifestyle Fuels Chronic Disease Progression by Changing Interstitial Cell Behaviour: A Network Analysis

Managing chronic diseases, such as heart disease, stroke, diabetes, chronic lung disease and Alzheimer’s disease, account for a large proportion of health care spending, yet they remain in the top causes of premature mortality and are preventable. It is currently accepted that an unhealthy lifestyle fosters a state of chronic low-grade inflammation that is linked to chronic disease progression. Although this is known to be related to inflammatory cytokines, how an unhealthy lifestyle causes cytokine release and how that in turn leads to chronic disease progression are not well known. This article presents a theory that an unhealthy lifestyle fosters chronic disease by changing interstitial cell behavior and is supported by a six-level hierarchical network analysis. The top three networks include the macroenvironment, social and cultural factors, and lifestyle itself. The fourth network includes the immune, autonomic and neuroendocrine systems and how they interact with lifestyle factors and with each other. The fifth network identifies the effects these systems have on the microenvironment and two types of interstitial cells: macrophages and fibroblasts. Depending on their behaviour, these cells can either help maintain and restore normal function or foster chronic disease progression. When macrophages and fibroblasts dysregulate, it leads to chronic low-grade inflammation, fibrosis, and eventually damage to parenchymal (organ-specific) cells. The sixth network considers how macrophages change phenotype. Thus, a pathway is identified through this hierarchical network to reveal how external factors and lifestyle affect interstitial cell behaviour. This theory can be tested and it needs to be tested because, if correct, it has profound implications. Not only does this theory explain how chronic low-grade inflammation causes chronic disease progression, it also provides insight into salutogenesis, or the process by which health is maintained and restored. Understanding low-grade inflammation as a stalled healing process offers a new strategy for chronic disease management. Rather than treating each chronic disease separately by a focus on parenchymal pathology, a salutogenic strategy of optimizing interstitial health could prevent and mitigate multiple chronic diseases simultaneously.

The Right Heart Network and Risk Stratification in Pulmonary Arterial Hypertension

BACKGROUND

Prognosis in pulmonary arterial hypertension (PAH) is closely related to indexes of right ventricular function. A better understanding of their relationship may provide important implications for risk stratification in PAH.

RESEARCH QUESTION

Can clinical network graphs inform risk stratification in PAH?

STUDY DESIGN AND METHODS

The study cohort consisted of 231 patients with PAH followed up for a median of 7.1 years. An undirected, correlation network was used to visualize the relationship between clinical features in PAH. This network was enriched for right heart parameters and included N-terminal pro-hormone B-type natriuretic peptide (NT-proBNP), comprehensive echocardiographic parameters, and hemodynamics, as well as 6-min walk distance (6MWD), vital signs, laboratory data, and diffusing capacity for carbon monoxide (Dlco). Connectivity was assessed by using eigenvector and betweenness centrality to reflect global and regional connectivity, respectively. Cox proportional hazards regression was used to model event-free survival for the combined end point of death or lung transplantation.

RESULTS

A network of closely intertwined features centered around NT-proBNP with 6MWD emerging as a secondary hub were identified. Less connected nodes included Dlco, systolic BP, albumin, and sodium. Over the follow-up period, death or transplantation occurred in 92 patients (39.8%). A strong prognostic model was achieved with a Harrell's C-index of 0.81 (0.77-0.85) when combining central right heart features (NT-proBNP and right ventricular end-systolic remodeling index) with 6MWD and less connected nodes (Dlco, systolic BP, albumin, sodium, sex, connective tissue disease etiology, and prostanoid therapy). When added to the baseline risk model, serial change in NT-proBNP significantly improved outcome prediction at 5 years (increase in C-statistic of 0.071 ± 0.024; P = .003).

INTERPRETATION

NT-proBNP emerged as a central hub in the intertwined PAH network. Connectivity analysis provides explainability for feature selection and combination in outcome models.

Harnessing Big Data to Advance Treatment and Understanding of Pulmonary Hypertension

Pulmonary hypertension is a complex disease with multiple causes, corresponding to phenotypic heterogeneity and variable therapeutic responses. Advancing understanding of pulmonary hypertension pathogenesis is likely to hinge on integrated methods that leverage data from health records, imaging, novel molecular -omics profiling, and other modalities. In this review, we summarize key data sets generated thus far in the field and describe analytical methods that hold promise for deciphering the molecular mechanisms that underpin pulmonary vascular remodeling, including machine learning, network medicine, and functional genetics. We also detail how genetic and subphenotyping approaches enable earlier diagnosis, refined prognostication, and optimized treatment prediction. We propose strategies that identify functionally important molecular pathways, bolstered by findings across multi-omics platforms, which are well-positioned to individualize drug therapy selection and advance precision medicine in this highly morbid disease.

Learning in Medicine: The Importance of Statistical Thinking

In many fields, including medicine and biology, there has been in the last years an increasing diffusion and availability of complex data from different sources. Examples include biological experiments or data from health care providers. These data encompass information that can potentially enhance therapeutic advancement and constitute the core of modern system medicine. When analyzing these complex data, it is important to appropriately quantify uncertainty, avoiding using only algorithmic and automated approaches, which are not always appropriate. Improper application of algorithmic approaches, which ignore domain knowledge, could result in filling the literature with imprecise and/or misleading conclusions. In this chapter, we highlight the importance of statistical thinking when leveraging complex data and models to enhance science progress. In particular, we discuss the reproducibility and replicability issues, the importance of uncertainty quantification, and some common pitfalls in the analysis of big data.

Dyspnea in Chronic Low Ventricular Preload States

Dyspnea in low-preload states is an underrecognized but growing diagnosis in patients with unexplained dyspnea. Patients can often experience debilitating symptoms at rest and with exertion, as low measured preload often leads to decreased cardiac output and ultimately dyspnea. In the present article, we performed a review of the literature and a multidisciplinary evaluation to understand the pathophysiology, diagnosis, and treatment of dyspnea in low-preload states. We explored selected etiologies and suggested an algorithm to approach unexplained dyspnea. The mainstay of diagnosis remains as invasive cardiopulmonary exercise testing. We concluded with a variety of nonpharmacological and pharmacological therapies, highlighting that a multifactorial approach may lead to the best results.

Cardiac risk stratification in cancer patients: A longitudinal patient-patient network analysis

BACKGROUND

Cardiovascular disease is a leading cause of death in general population and the second leading cause of mortality and morbidity in cancer survivors after recurrent malignancy in the United States. The growing awareness of cancer therapy-related cardiac dysfunction (CTRCD) has led to an emerging field of cardio-oncology; yet, there is limited knowledge on how to predict which patients will experience adverse cardiac outcomes. We aimed to perform unbiased cardiac risk stratification for cancer patients using our large-scale, institutional electronic medical records.

METHODS AND FINDINGS

We built a large longitudinal (up to 22 years' follow-up from March 1997 to January 2019) cardio-oncology cohort having 4,632 cancer patients in Cleveland Clinic with 5 diagnosed cardiac outcomes: atrial fibrillation, coronary artery disease, heart failure, myocardial infarction, and stroke. The entire population includes 84% white Americans and 11% black Americans, and 59% females versus 41% males, with median age of 63 (interquartile range [IQR]: 54 to 71) years old. We utilized a topology-based K-means clustering approach for unbiased patient-patient network analyses of data from general demographics, echocardiogram (over 25,000), lab testing, and cardiac factors (cardiac). We performed hazard ratio (HR) and Kaplan-Meier analyses to identify clinically actionable variables. All confounding factors were adjusted by Cox regression models. We performed random-split and time-split training-test validation for our model. We identified 4 clinically relevant subgroups that are significantly correlated with incidence of cardiac outcomes and mortality. Among the 4 subgroups, subgroup I (n = 625) has the highest risk of de novo CTRCD (28%) with an HR of 3.05 (95% confidence interval (CI) 2.51 to 3.72). Patients in subgroup IV (n = 1,250) had the worst survival probability (HR 4.32, 95% CI 3.82 to 4.88). From longitudinal patient-patient network analyses, the patients in subgroup I had a higher percentage of de novo CTRCD and a worse mortality within 5 years after the initiation of cancer therapies compared to long-time exposure (6 to 20 years). Using clinical variable network analyses, we identified that serum levels of NT-proB-type Natriuretic Peptide (NT-proBNP) and Troponin T are significantly correlated with patient's mortality (NT-proBNP > 900 pg/mL versus NT-proBNP = 0 to 125 pg/mL, HR = 2.95, 95% CI 2.28 to 3.82, p < 0.001; Troponin T > 0.05 μg/L versus Troponin T ≤ 0.01 μg/L, HR = 2.08, 95% CI 1.83 to 2.34, p < 0.001). Study limitations include lack of independent cardio-oncology cohorts from different healthcare systems to evaluate the generalizability of the models. Meanwhile, the confounding factors, such as multiple medication usages, may influence the findings.

CONCLUSIONS

In this study, we demonstrated that the patient-patient network clustering methodology is clinically intuitive, and it allows more rapid identification of cancer survivors that are at greater risk of cardiac dysfunction. We believed that this study holds great promise for identifying novel cardiac risk subgroups and clinically actionable variables for the development of precision cardio-oncology.

A precision medicine approach to sex-based differences in ideal cardiovascular health

Cardiovascular disease risk factor profiles and health behaviors are known to differ between women and men. Sex-based differences in ideal cardiovascular health were examined in the My Research Legacy study, which collected cardiovascular health and lifestyle data via Life’s Simple 7 survey and digital health devices. As the study overenrolled women (n = 1251) compared to men (n = 310), we hypothesized that heterogeneity among women would affect comparisons of ideal cardiovascular health. We identified 2 phenogroups of women in our study cohort by cluster analysis. The phenogroups differed significantly across all 7 cardiovascular health and behavior domains (all p < 0.01) with women in phenogroup 1 having a lower Life’s Simple 7 Health Score than those in phenogroup 2 (5.9 ± 1.3 vs. 7.6 ± 1.3, p < 0.01). Compared to men, women in phenogroup 1 had a higher burden of cardiovascular disease risk factors, exercised less, and had lower ideal cardiovascular health scores (p < 0.01). In contrast, women in phenogroup 2 had fewer cardiovascular risk factors but similar exercise habits and higher ideal cardiovascular health scores than men (p < 0.01). These findings suggest that heterogeneity among study participants should be examined when evaluating sex-based differences in ideal cardiovascular health.

Personalized Medicine for Pulmonary Hypertension:: The Future Management of Pulmonary Hypertension Requires a New Taxonomy

Pulmonary hypertension is a convergent phenotype that presents late in the natural history of the condition. The current clinical classification of patients lacks granularity, and this impacts on the development and deployment of treatment. Deep molecular phenotyping using platform 'omic' technologies is beginning to reveal the genetic and molecular architecture that underlies the phenotype, promising better targeting of patients with new treatments. The future treatment of pulmonary hypertension depends on the integration of clinical and molecular information to create a new taxonomy that defines patient groups coupled to druggable targets.

Exercise intolerance in pulmonary arterial hypertension: insight into central and peripheral pathophysiological mechanisms

Exercise intolerance is a cardinal symptom of pulmonary arterial hypertension (PAH) and strongly impacts patients' quality of life (QoL). Although central cardiopulmonary impairments limit peak oxygen consumption (V' O2peak ) in patients with PAH, several peripheral abnormalities have been described over the recent decade as key determinants in exercise intolerance, including impaired skeletal muscle (SKM) morphology, convective O2 transport, capillarity and metabolism indicating that peripheral abnormalities play a greater role in limiting exercise capacity than previously thought. More recently, cerebrovascular alterations potentially contributing to exercise intolerance in patients with PAH were also documented. Currently, only cardiopulmonary rehabilitation has been shown to efficiently improve the peripheral components of exercise intolerance in patients with PAH. However, more extensive studies are needed to identify targeted interventions that would ultimately improve patients' exercise tolerance and QoL. The present review offers a broad and comprehensive analysis of the present literature about the complex mechanisms and their interactions limiting exercise in patients and suggests several gaps in knowledge that need to be addressed in the future for a better understanding of exercise intolerance in patients with PAH.

Cardiopulmonary Exercise Testing with Echocardiography to Identify Mechanisms of Unexplained Dyspnea

Little data is available about the pathophysiological mechanisms of unexplained dyspnea and their clinical meaning. Consecutive patients with unexplained dyspnea underwent prospective standardized cardiopulmonary exercise testing with echocardiography (CPETecho). Patients were grouped as having normal exercise capacity (peak VO₂ > 80% with respiratory exchange [RER] > 1.05), reduced exercise capacity (peak VO₂ ≤ 80% with RER > 1.05), or a submaximal exercise test (RER ≤ 1.05). From 307 patients, 144 (47%) had normal and 116 (38%) reduced exercise capacity, and 47 (15%) had a submaximal exercise test. Patients with reduced versus normal exercise capacity had significantly more mechanisms for unexplained dyspnea (2.3±1.0 vs 1.5±1.0, respectively; p<0.001). Exercise PH (42%), low heart rate reserve (51%), low stroke volume reserve (38%), low diastolic reserve (18%), and peripheral muscle limitation (17%) were most common. Patients with more mechanisms for dyspnea displayed poorer peak VO₂ and had an increased risk for cardiovascular hospitalization (p=0.002). Patients with unexplained dyspnea display multiple coexisting mechanisms for exercise intolerance, which relate to the severity of exercise limitation and risk of subsequent cardiovascular hospitalizations.

Diagnosis and Treatment of Right Heart Failure in Pulmonary Vascular Diseases: A National Heart, Lung, and Blood Institute Workshop

Right ventricular dysfunction is a hallmark of advanced pulmonary vascular, lung parenchymal, and left heart disease, yet the underlying mechanisms that govern (mal)adaptation remain incompletely characterized. Owing to the knowledge gaps in our understanding of the right ventricle (RV) in health and disease, the National Heart, Lung, and Blood Institute (NHLBI) commissioned a working group to identify current challenges in the field. These included a need to define and standardize normal RV structure and function in populations; access to RV tissue for research purposes and the development of complex experimental platforms that recapitulate the in vivo environment; and the advancement of imaging and invasive methodologies to study the RV within basic, translational, and clinical research programs. Specific recommendations were provided, including a call to incorporate precision medicine and innovations in prognosis, diagnosis, and novel RV therapeutics for patients with pulmonary vascular disease.

NHLBI-CMREF Workshop Report on Pulmonary Vascular Disease Classification: JACC State-of-the-Art Review

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease.

Network medicine in Cardiovascular Research

The ability to generate multi-omics data coupled with deeply characterizing the clinical phenotype of individual patients promises to improve understanding of complex cardiovascular pathobiology. There remains an important disconnection between the magnitude and granularity of these data and our ability to improve phenotype-genotype correlations for complex cardiovascular diseases. This shortcoming may be due to limitations associated with traditional reductionist analytical methods, which tend to emphasize a single molecular event in the pathogenesis of diseases more aptly characterized by crosstalk between overlapping molecular pathways. Network medicine is a rapidly growing discipline that considers diseases as the consequences of perturbed interactions between multiple interconnected biological components. This powerful integrative approach has enabled a number of important discoveries in complex disease mechanisms. In this review, we introduce the basic concepts of network medicine and highlight specific examples by which this approach has accelerated cardiovascular research. We also review how network medicine is well-positioned to promote rational drug design for patients with cardiovascular diseases, with particular emphasis on advancing precision medicine.

A global network for network medicine

Network Medicine is now an established scientific discipline, having generated key insights on integrated mechanisms underlying complex human diseases. The next discovery phase will emphasize innovating analytics that optimize networks for advancing precision medicine. Accomplishing this goal will require organizing a scientifically diverse team studying big datasets shared globally.

The application of big data to cardiovascular disease: paths to precision medicine

Advanced phenotyping of cardiovascular diseases has evolved with the application of high-resolution omics screening to populations enrolled in large-scale observational and clinical trials. This strategy has revealed that considerable heterogeneity exists at the genotype, endophenotype, and clinical phenotype levels in cardiovascular diseases, a feature of the most common diseases that has not been elucidated by conventional reductionism. In this discussion, we address genomic context and (endo)phenotypic heterogeneity, and examine commonly encountered cardiovascular diseases to illustrate the genotypic underpinnings of (endo)phenotypic diversity. We highlight the existing challenges in cardiovascular disease genotyping and phenotyping that can be addressed by the integration of big data and interpreted using novel analytical methodologies (network analysis). Precision cardiovascular medicine will only be broadly applied to cardiovascular patients once this comprehensive data set is subjected to unique, integrative analytical strategies that accommodate molecular and clinical heterogeneity rather than ignore or reduce it.

Implications of the complex biology and micro-environment of cardiac sarcomeres in the use of high affinity troponin antibodies as serum biomarkers for cardiac disorders

Cardiac troponin I (cTnI), the inhibitory-unit, and cardiac troponin T (cTnT), the tropomyosin-binding unit together with the Ca-binding unit (cTnC) of the hetero-trimeric troponin complex signal activation of the sarcomeres of the adult cardiac myocyte. The unique structure and heart myocyte restricted expression of cTnI and cTnT led to their worldwide use as biomarkers for acute myocardial infarction (AMI) beginning more than 30 years ago. Over these years, high sensitivity antibodies (hs-cTnI and hs-cTnT) have been developed. Together with careful determination of history, physical examination, and EKG, determination of serum levels using hs-cTnI and hs-cTnT permits risk stratification of patients presenting in the Emergency Department (ED) with chest pain. With the ability to determine serum levels of these troponins with high sensitivity came the question of whether such measurements may be of diagnostic and prognostic value in conditions beyond AMI. Moreover, the finding of elevated serum troponins in physiological states such as exercise and pathological states where cardiac myocytes may be affected requires understanding of how troponins may be released into the blood and whether such release may be benign. We consider these questions by relating membrane stability to the complex biology of troponin with emphasis on its sensitivity to the chemo-mechanical and micro-environment of the cardiac myocyte. We also consider the role determinations of serum troponins play in the precise phenotyping in personalized and precision medicine approaches to promote cardiac health.

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Serum levels of cardiac TnI and cardiac TnT permit stratification of patients with chest pain.

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Release of troponins into blood involves not only frank necrosis but also programmed necroptosis.

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Genome wide analysis of serum troponin levels in the general population may be prognostic about cardiovascular health.

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Significant levels of serum troponins with exhaustive exercise may not be benign.

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Troponin in serum can lead to important data related to personalized and precision medicine.

Pulmonary arterial hypertension: Rationale for using multiple vs. single drug therapy

Pulmonary arterial hypertension (PAH) is defined by a heterogenous pathobiology that corresponds to variable clinical presentation, treatment response, and prognosis across affected patients. The approach to pharmacotherapeutics in PAH has evolved since the introduction of the first prostacyclin replacement drug, which was trialed in patients with end-stage disease as a strategy by which to delay or prevent mortality. Subsequently, the aim of care in PAH has shifted toward minimizing symptoms, improving functional capacity, delaying disease progression, and prolonging life. Thus, treatments are now implemented earlier and according to the evidence base, which spans more than twenty years and includes patients at various stages of disease. Overall, the evidence supports multidrug therapy rather than monotherapy in the majority of PAH patients. Among incident patients, up-front combination therapy with ambrisentan and tadalafil or other comparable agents within these drug classes is recommended based on strong clinical trial data. In the near future, up-front triple therapy may be emerge as bona fide treatment approach in selected patients. Future goals that are already under consideration in PAH include stronger integration of pathobiological characteristics when considering the use of specific drugs, or the development of novel therapies, toward precision medicine-based clinical pharmacology.

Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine

The First International Conference in Systems and Network Medicine gathered together 200 global thought leaders, scientists, clinicians, academicians, industry and government experts, medical and graduate students, postdoctoral scholars and policymakers. Held at Georgetown University Conference Center in Washington D.C. on September 11-13, 2019, the event featured a day of pre-conference lectures and hands-on bioinformatic computational workshops followed by two days of deep and diverse scientific talks, panel discussions with eminent thought leaders, and scientific poster presentations. Topics ranged from: Systems and Network Medicine in Clinical Practice; the role of -omics technologies in Health Care; the role of Education and Ethics in Clinical Practice, Systems Thinking, and Rare Diseases; and the role of Artificial Intelligence in Medicine. The conference served as a unique nexus for interdisciplinary discovery and dialogue and fostered formation of new insights and possibilities for health care systems advances.

Correlation network analysis shows divergent effects of a long-term, high-fat diet and exercise on early stage osteoarthritis phenotypes in mice

BACKGROUND

Obesity increases knee osteoarthritis (OA) risk through metabolic, inflammatory, and biomechanical factors, but how these systemic and local mediators interact to drive OA pathology is not well understood. We tested the effect of voluntary running exercise after chronic diet-induced obesity on knee OA-related cartilage and bone pathology in mice. We then used a correlation-based network analysis to identify systemic and local factors associated with early-stage knee OA phenotypes among the different diet and exercise groups.

METHODS

Male C57BL/6J mice were fed a defined control (10% kcal fat) or high fat (HF) (60% kcal fat) diet from 6 to 37 weeks of age. At 25 weeks, one-half of the mice from each diet group were housed in cages with running wheels for the remainder of the study. Histology, micro computed tomography, and magnetic resonance imaging were used to evaluate changes in joint tissue structure and OA pathology. These local variables were then compared to systemic metabolic (body mass, body fat, and glucose tolerance), inflammatory (serum adipokines and inflammatory mediators), and functional (mechanical tactile sensitivity and grip strength) outcomes using a correlation-based network analysis. Diet and exercise effects were evaluated by two-way analysis of variance.

RESULTS

An HF diet increased the infrapatellar fat pad size and posterior joint osteophytes, and wheel running primarily altered the subchondral cortical and trabecular bone. Neither HF diet nor exercise altered average knee cartilage OA scores compared to control groups. However, the coefficient of variation was ≥25% for many outcomes, and some mice in both diet groups developed moderate OA (≥33% maximum score). This supported using correlation-based network analyses to identify systemic and local factors associated with early-stage knee OA phenotypes. In wheel-running cohorts, an HF diet reduced the network size compared to the control diet group despite similar running distances, suggesting that diet-induced obesity dampens the effects of exercise on systemic and local OA-related factors. Each of the 4 diet and activity groups showed mostly unique networks of local and systemic factors correlated with early-stage knee OA.

CONCLUSION

Despite minimal group-level effects of chronic diet-induced obesity and voluntary wheel running on knee OA pathology under the current test durations, diet and exercise substantially altered the relationships among systemic and local variables associated with early-stage knee OA. These results suggest that distinct pre-OA phenotypes may exist prior to the development of disease.

Clinical implications of idiopathic pulmonary arterial hypertension phenotypes defined by cluster analysis

BACKGROUND

>Despite advances in drug development, life expectancy in idiopathic pulmonary arterial hypertension (IPAH) remains unacceptable. Contemporary IPAH characterization is based on criteria that may not adequately capture disease heterogeneity and may be proposed as a possible explanation for why patient outcome is still unfavorable. The aim of this study was to apply cluster analysis to improve phenotyping of patients with IPAH and analyze long-term clinical outcome of derived clusters.

METHODS

Patients with IPAH from 2 referral centers (n = 252) were evaluated with clinical, hemodynamic, and echocardiographic assessment and cardiopulmonary exercise test. Patients were classified according to cluster analysis and followed for clinical worsening occurrence.

RESULTS

The cluster analysis identified 4 IPAH phenotypes. Cluster 1 was characterized by young patients, mild pulmonary hypertension (PH), mild right ventricular (RV) dilation and high oxygen (O₂) pulse; Cluster 2 by severe PH and RV dilation and high O₂ pulse; and Cluster 3 by male patients, severe PH and RV dilation, and low O₂ pulse. Cluster 4 patients were older and overweight, with mild PH and RV dilation and low O₂ pulse. After a mean follow-up of 995 ± 623 days, 123 (48.8%) patients had clinical worsening. Cluster 1 patients presented the best prognosis, whereas Cluster 3 had the highest rates of clinical worsening. Compared with Cluster 1, risk of clinical worsening ranged from 4.12 (confidence interval [CI] 1.43-11.92; p = 0.009) for Cluster 4 to 7.38 (CI 2.80-19.40) for Cluster 2 and 13.8 (CI 5.60-34.0; p = 0.0001) for Cluster 3.

CONCLUSIONS

Cluster analysis of clinical variables identified 4 distinct phenotypes of IPAH. Our findings underscore the high degree of disease heterogeneity that exists within patients with IPAH and the need for advanced clinical testing to define phenotypes to improve treatment strategy decision-making. CONDENSED ABSTRACT Idiopathic pulmonary arterial hypertension (IPAH) characterization is based on criteria that may not adequately capture disease heterogeneity. The aim of this study was to apply cluster analysis to improve phenotyping of IPAH. Patients with IPAH (n = 252) were evaluated with clinical, hemodynamic, and echocardiographic assessment and cardiopulmonary exercise test. Within the umbrella category of IPAH, it was the combination of mean pulmonary arterial pressure, right ventricular size, and oxygen pulse that further stratified patients into novel IPAH phenotypes that significantly associate with clinical worsening. These findings underscore the need for novel multidimensional IPAH phenotyping for improved patient care and trial quality.

Immunoglobulin-driven Complement Activation Regulates Proinflammatory Remodeling in Pulmonary Hypertension

Rationale: Pulmonary hypertension (PH) is a life-threatening cardiopulmonary disorder in which inflammation and immunity have emerged as critical early pathogenic elements. Although proinflammatory processes in PH and pulmonary arterial hypertension (PAH) are the focus of extensive investigation, the initiating mechanisms remain elusive.Objectives: We tested whether activation of the complement cascade is critical in regulating proinflammatory and pro-proliferative processes in the initiation of experimental hypoxic PH and can serve as a prognostic biomarker of outcome in human PAH.Methods: We used immunostaining of lung tissues from experimental PH models and patients with PAH, analyses of genetic murine models lacking specific complement components or circulating immunoglobulins, cultured human pulmonary adventitial fibroblasts, and network medicine analysis of a biomarker risk panel from plasma of patients with PAH.Measurements and Main Results: Pulmonary perivascular-specific activation of the complement cascade was identified as a consistent critical determinant of PH and PAH in experimental animal models and humans. In experimental hypoxic PH, proinflammatory and pro-proliferative responses were dependent on complement (alternative pathway and component 5), and immunoglobulins, particularly IgG, were critical for activation of the complement cascade. We identified Csf2/GM-CSF as a primary complement-dependent inflammatory mediator. Furthermore, using network medicine analysis of a biomarker risk panel from plasma of patients with PAH, we demonstrated that complement signaling can serve as a prognostic factor for clinical outcome in PAH.Conclusions: This study establishes immunoglobulin-driven dysregulated complement activation as a critical pathobiological mechanism regulating proinflammatory and pro-proliferative processes in the initiation of experimental hypoxic PH and demonstrates complement signaling as a critical determinant of clinical outcome in PAH.

Circulating NEDD9 is increased in pulmonary arterial hypertension: A multicenter, retrospective analysis

BACKGROUND

Pulmonary arterial hypertension (PAH) is a highly morbid disease characterized by elevated pulmonary vascular resistance (PVR) and pathogenic right ventricular remodeling. Endothelial expression of the prometastatic protein NEDD9 is increased in fibrotic PAH arterioles, and NEDD9 inhibition decreases PVR in experimental PAH. We hypothesized that circulating NEDD9 is increased in PAH and informs the clinical profile of patients.

METHODS

Clinical data and plasma samples were analyzed retrospectively for 242 patients from 5 referral centers (2010-2017): PAH (n = 139; female 82%, 58 [48-67] years), non-PAH pulmonary hypertension (PH) (n = 54; female 56%, 63.4 ± 12.2 years), and dyspnea non-PH controls (n = 36; female 75%, 54.2 ± 14.0 years).

RESULTS

Compared with controls, NEDD9 was increased in PAH by 1.82-fold (p < 0.0001). Elevated NEDD9 correlated with PVR in idiopathic PAH (ρ = 0.42, p < 0.0001, n = 54), connective tissue disease (CTD)-PAH (ρ = 0.53, p < 0.0001, n = 53), and congenital heart disease-PAH (ρ = 0.68, p < 0.0001, n = 10). In CTD-PAH, NEDD9 correlated with 6-minute walk distance (ρ = -0.35, p = 0.028, n = 39). In contrast to the PAH biomarker N-terminal pro-brain natriuretic peptide (n = 38), NEDD9 correlated inversely with exercise pulmonary artery wedge pressure and more strongly with right ventricular ejection fraction (ρ = -0.41, p = 0.006, n = 45) in a mixed population. The adjusted hazard ratio for lung transplant-free survival was 1.12 (95% confidence interval [CI], 1.02-1.22, p = 0.01) and 1.75 (95% CI, 1.12-2.73, p = 0.01) per 1 ng/ml and 5 ng/ml increase in plasma NEDD9, respectively, by Cox proportional hazard model.

CONCLUSIONS

In PAH, plasma NEDD9 is increased and associates with key prognostic variables. Prospective studies that include hard end points are warranted to validate NEDD9 as a novel PAH biomarker.

Moving Beyond the Sarcomere to Explain Heterogeneity in Hypertrophic Cardiomyopathy: JACC Review Topic of the Week

Hypertrophic cardiomyopathy (HCM) has been considered a heterogeneous cardiac disease ascribed solely to single sarcomere gene mutations. However, limitations of this hypothesis suggest that sarcomere mutations alone do not adequately explain all HCM clinical and pathobiological features. Disease-causing sarcomere mutations are absent in ∼70% of patients with established disease, and sarcomere gene carriers can live to advanced ages without developing HCM. Some features of HCM are also inconsistent with the single sarcomere gene hypothesis, such as regional left ventricular hypertrophy and myocardial fibrosis, as well as structurally abnormal elongated mitral valve leaflets and remodeled intramural coronary arterioles, which involve tissue types that do not express cardiomyocyte sarcomere proteins. It is timely to expand the HCM research focus beyond a single molecular event toward more inclusive models to explain this disease in its entirety. The authors chart paths forward addressing this knowledge gap using novel analytical approaches, particularly network medicine, to unravel the pathobiological complexity of HCM.

Network Medicine in Pathobiology

The past decade has witnessed exponential growth in the generation of high-throughput human data across almost all known dimensions of biological systems. The discipline of network medicine has rapidly evolved in parallel, providing an unbiased, comprehensive biological framework through which to interrogate and integrate systematically these large-scale, multi-omic data to enhance our understanding of disease mechanisms and to design drugs that reflect a deep knowledge of molecular pathobiology. In this review, we discuss the key principles of network medicine and the human disease network and explore the latest applications of network medicine in this multi-omic era. We also highlight the current conceptual and technological challenges, which serve as exciting opportunities by which to improve and expand the network-based applications beyond the artificial boundaries of the current state of human pathobiology.

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

The cardiovascular disease (CVD) pandemic has placed considerable strain on healthcare systems, quality of life, and physical function, while remaining the leading cause of death globally. Decades of scientific investigations have fortified the protective effects of cardiorespiratory fitness (CRF), exercise training, and physical activity (PA) against the development of CVD. This review will summarize recent efforts that have made significant strides in; 1) the application of novel analytic techniques to increase the predictive utility of CRF; 2) understanding the protective effects of long-term compliance to PA recommendations through large cohort studies with multiple points of assessment; 3) and understanding the potential harms associated with extreme volumes of PA.