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

A perfectly imperfect engine: Utilizing the digital twin paradigm in pulmonary hypertension

Pulmonary hypertension (PH) is a severe medical condition with a number of treatment options, the majority of which are introduced without consideration of the underlying mechanisms driving it within an individual and thus a lack of tailored approach to treatment. The one exception is a patient presenting with apparent pulmonary arterial hypertension and shown to have vaso-responsive disease, whose clinical course and prognosis is significantly improved by high dose calcium channel blockers. PH is however characterized by a relative abundance of available data from patient cohorts, ranging from molecular data characterizing gene and protein expression in different tissues to physiological data at the organ level and clinical information. Integrating available data with mechanistic information at the different scales into computational models suggests an approach to a more personalized treatment of the disease using model-based optimization of interventions for individual patients. That is, constructing digital twins of the disease, customized to a patient, promises to be a key technology for personalized medicine, with the aim of optimizing use of existing treatments and developing novel interventions, such as new drugs. This article presents a perspective on this approach in the context of a review of existing computational models for different aspects of the disease, and it lays out a roadmap for a path to realizing it.

Genetics of Pulmonary Pressure and Right Ventricle Stress Identify Diabetes as a Causal Risk Factor

Background Epidemiologic studies have identified risk factors associated with pulmonary hypertension and right heart failure, but causative drivers of pulmonary hypertension and right heart adaptation are not well known. We sought to leverage unbiased genetic approaches to determine clinical conditions that share genetic architecture with pulmonary pressure and right ventricular dysfunction. Methods and Results We leveraged Vanderbilt University's deidentified electronic health records and DNA biobank to identify 14 861 subjects of European ancestry who underwent at least 1 echocardiogram with available estimates of pulmonary pressure and right ventricular function. Analyses of the study were performed between 2020 and 2022. The final analytical sample included 14 861 participants (mean [SD] age, 63 [15] years and mean [SD] body mass index, 29 [7] kg/m2). An unbiased phenome-wide association study identified diabetes as the most statistically significant clinical International Classifications of Diseases, Ninth Revision (ICD-9) code associated with polygenic risk for increased pulmonary pressure. We validated this finding further by finding significant associations between genetic risk for diabetes and a related condition, obesity, with pulmonary pressure estimate. We then used 2-sample univariable Mendelian randomization and multivariable Mendelian randomization to show that diabetes, but not obesity, was independently associated with genetic risk for increased pulmonary pressure and decreased right ventricle load stress. Conclusions Our findings show that genetic risk for diabetes is the only significant independent causative driver of genetic risk for increased pulmonary pressure and decreased right ventricle load stress. These findings suggest that therapies targeting genetic risk for diabetes may also potentially be beneficial in treating pulmonary hypertension and right heart dysfunction.

Pathophysiology and pathogenic mechanisms of pulmonary hypertension: role of membrane receptors, ion channels, and Ca2+ signaling

The pulmonary circulation is a low-resistance, low-pressure, and high-compliance system that allows the lungs to receive the entire cardiac output. Pulmonary arterial pressure is a function of cardiac output and pulmonary vascular resistance, and pulmonary vascular resistance is inversely proportional to the fourth power of the intraluminal radius of the pulmonary artery. Therefore, a very small decrease of the pulmonary vascular lumen diameter results in a significant increase in pulmonary vascular resistance and pulmonary arterial pressure. Pulmonary arterial hypertension is a fatal and progressive disease with poor prognosis. Regardless of the initial pathogenic triggers, sustained pulmonary vasoconstriction, concentric vascular remodeling, occlusive intimal lesions, in situ thrombosis, and vascular wall stiffening are the major and direct causes for elevated pulmonary vascular resistance in patients with pulmonary arterial hypertension and other forms of precapillary pulmonary hypertension. In this review, we aim to discuss the basic principles and physiological mechanisms involved in the regulation of lung vascular hemodynamics and pulmonary vascular function, the changes in the pulmonary vasculature that contribute to the increased vascular resistance and arterial pressure, and the pathogenic mechanisms involved in the development and progression of pulmonary hypertension. We focus on reviewing the pathogenic roles of membrane receptors, ion channels, and intracellular Ca2+ signaling in pulmonary vascular smooth muscle cells in the development and progression of pulmonary hypertension.

Hemodynamic characteristics in patients with pulmonary hypertension and chronic obstructive pulmonary disease: A retrospective monocentric cohort study

BACKGROUND

Pulmonary hypertension (PH) is a hemodynamic condition characterized by an abnormal elevation in pulmonary arterial pressures. Several pathophysiological pre-capillary and post-capillary mechanisms have been described. PH is a common complication of chronic obstructive pulmonary disease (COPD), however, the prevalence of each mechanism in the development of PH in patients with COPD has been hardly studied.

METHODS

We reported the clinical, functional, hemodynamic characteristics and outcomes of patients diagnosed with COPD and PH among the expert PH center of Nancy between January 1^st, 2015 and March 31^st, 2021.

RESULTS

123 patients with COPD and PH were included. Most patients (n=122, 99%) had a pre-capillary mechanism, 9% (n=11) a post-capillary mechanism, and 1% (n=1) an unclassified mechanism. 111 (90%) patients had pure pre-capillary PH and 11 (9%) patients had combined pre- and post-capillary PH. Combined pre- and post-capillary PH group was characterized by higher prevalence of cardiovascular comorbidities and of sleep apnea-hypopnea syndrome, a higher body mass index, lower lung volumes, higher mean pulmonary arterial pressure, pulmonary arterial wedge pressure and right atrial pressure. At follow-up (median 30 months), 52 patients had died, and 11 had undergone lung transplantation. One-year, three-year and five-year transplant-free survival rates were 71%, 29% and 11% respectively. There was no difference on outcomes between groups.

CONCLUSION

PH in COPD patients is mostly due to pre-capillary mechanism. However, the existence of various and numerous comorbidities in COPD, especially cardiovascular, can lead to the participation of post-capillary mechanisms in the development of PH. Further studies are needed to confirm these findings and to assess the impact on outcomes and management strategies in these different patients.

Proline and glucose metabolic reprogramming supports vascular endothelial and medial biomass in pulmonary arterial hypertension

In pulmonary arterial hypertension (PAH), inflammation promotes a fibroproliferative pulmonary vasculopathy. Reductionist studies emphasizing single biochemical reactions suggest a shift toward glycolytic metabolism in PAH; however, key questions remain regarding the metabolic profile of specific cell types within PAH vascular lesions in vivo. We used RNA-Seq to profile the transcriptome of pulmonary artery endothelial cells (PAECs) freshly isolated from an inflammatory vascular injury model of PAH ex vivo, and these data were integrated with information from human gene ontology pathways. Network medicine was then used to map all aa and glucose pathways to the consolidated human interactome, which includes data on 233,957 physical protein-protein interactions. Glucose and proline pathways were significantly close to the human PAH disease module, suggesting that these pathways are functionally relevant to PAH pathobiology. To test this observation in vivo, we used multi-isotope imaging mass spectrometry to map and quantify utilization of glucose and proline in the PAH pulmonary vasculature at subcellular resolution. Our findings suggest that elevated glucose and proline avidity underlie increased biomass in PAECs and the media of fibrosed PAH pulmonary arterioles. Overall, these data show that anabolic utilization of glucose and proline are fundamental to the vascular pathology of PAH.

IoT-Enabled Classification of Echocardiogram Images for Cardiovascular Disease Risk Prediction with Pre-Trained Recurrent Convolutional Neural Networks

Cardiovascular diseases currently present a key health concern, contributing to an increase in death rates worldwide. In this phase of increasing mortality rates, healthcare represents a major field of research, and the knowledge acquired from this analysis of health information will assist in the early identification of disease. The retrieval of medical information is becoming increasingly important to make an early diagnosis and provide timely treatment. Medical image segmentation and classification is an emerging field of research in medical image processing. In this research, the data collected from an Internet of Things (IoT)-based device, the health records of patients, and echocardiogram images are considered. The images are pre-processed and segmented, and then further processed using deep learning techniques for classification as well as forecasting the risk of heart disease. Segmentation is attained via fuzzy C-means clustering (FCM) and classification using a pretrained recurrent neural network (PRCNN). Based on the findings, the proposed approach achieves 99.5% accuracy, which is higher than the current state-of-the-art techniques.

Mining the Plasma Proteome for Insights into the Molecular Pathology of Pulmonary Arterial Hypertension

Rationale: Pulmonary arterial hypertension (PAH) is characterized by structural remodeling of pulmonary arteries and arterioles. Underlying biological processes are likely reflected in a perturbation of circulating proteins. Objectives: To quantify and analyze the plasma proteome of patients with PAH using inherited genetic variation to inform on underlying molecular drivers. Methods: An aptamer-based assay was used to measure plasma proteins in 357 patients with idiopathic or heritable PAH, 103 healthy volunteers, and 23 relatives of patients with PAH. In discovery and replication subgroups, the plasma proteomes of PAH and healthy individuals were compared, and the relationship to transplantation-free survival in PAH was determined. To examine causal relationships to PAH, protein quantitative trait loci (pQTL) that influenced protein levels in the patient population were used as instruments for Mendelian randomization (MR) analysis. Measurements and Main Results: From 4,152 annotated plasma proteins, levels of 208 differed between patients with PAH and healthy subjects, and 49 predicted long-term survival. MR based on cis-pQTL located in proximity to the encoding gene for proteins that were prognostic and distinguished PAH from health estimated an adverse effect for higher levels of netrin-4 (odds ratio [OR], 1.55; 95% confidence interval [CI], 1.16-2.08) and a protective effect for higher levels of thrombospondin-2 (OR, 0.83; 95% CI, 0.74-0.94) on PAH. Both proteins tracked the development of PAH in previously healthy relatives and changes in thrombospondin-2 associated with pulmonary arterial pressure at disease onset. Conclusions: Integrated analysis of the plasma proteome and genome implicates two secreted matrix-binding proteins, netrin-4 and thrombospondin-2, in the pathobiology of PAH.

A Systematic Review with Meta-analysis of Biomarkers for detection of Pulmonary Arterial Hypertension

Rationale

The blood is a rich source of potential biomarkers for the diagnosis of idiopathic and hereditary pulmonary arterial hypertension (iPAH and hPAH, referred to as “PAH”). While a lot of biomarkers have been identified for PAH, the clinical utility of these biomarkers often remains unclear. Here, we performed an unbiased meta-analysis of published biomarkers to identify biomarkers with the highest performance for detection of PAH.

Methods

A literature search (in PubMed, Embase.com, Clarivate Analytics/Web of Science Core Collection and Wiley/Cochrane Library) was performed up to 28 January 2021. Primary end points were blood biomarker levels in PAH versus asymptomatic controls or patients suspected of pulmonary hypertension (PH) with proven normal haemodynamic profiles.

Results

149 articles were identified by the literature search. Meta-analysis of 26 biomarkers yielded 17 biomarkers that were differentially expressed in PAH and non-PH control subjects. Red cell distribution width, low density lipid-cholesterol, d-dimer, N-terminal prohormone of brain natriuretic protein (NT-proBNP), interleukin-6 (IL-6) and uric acid were biomarkers with the largest observed differences, largest sample sizes and a low risk of publication bias. Receiver operating characteristic curves and sensitivity/specificity analyses demonstrated that NT-proBNP had a high sensitivity, but low specificity for PAH. For the other biomarkers, insufficient data on diagnostic accuracy with receiver operating characteristic curves were available for meta-analysis.

Conclusion

This meta-analysis validates NT-proBNP as a biomarker with high sensitivity for PAH, albeit with low specificity. The majority of biomarkers evaluated in this meta-analysis lacked either external validation or data on diagnostic accuracy. Further validation studies are required as well as studies that test combinations of biomarkers to improve specificity.

Meta-analysis of 26 biomarkers yielded 17 differentially expressed biomarkers in PAH. NT-proBNP had the highest diagnostic accuracy but had a low specificity for PAH. Other markers, including IL-6, RDW, LDL-c, D-dimer and UA, lacked clinical validation.https://bit.ly/3J4YAyC

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.

Prevalence, incidence, and survival of pulmonary arterial hypertension: A systematic review for the global burden of disease 2020 study

Pulmonary arterial hypertension (PAH) is characterized by increased resistance in the pulmonary arterioles as a result of remodeled blood vessels. We sought all available epidemiologic data on population‐based prevalence, incidence, and 1‐year survival of PAH as part of the Global Burden of Disease Study. We performed a systematic review searching Global Index Medicus (GIM) for keywords related to PAH between 1980 and 2021 and identified population‐representative sources of prevalence, incidence, and mortality for clinically diagnosed PAH. Of 6772 articles identified we found 65 with population‐level data: 17 for prevalence, 17 for incidence, and 58 reporting case fatality. Reported prevalence ranged from 0.37 cases/100,000 persons in a referral center of French children to 15 cases/100,000 persons in an Australian study. Reported incidence ranged from 0.008 cases/100,000 person‐years in Finland, to 1.4 cases/100,000 person‐years in a retrospective chart review at a clinic in Utah, United States. Reported 1‐year survival ranged from 67% to 99%. All studies with sex‐specific estimates of prevalence or incidence reported higher levels in females than males. Studies varied in their size, study design, diagnostic criteria, and sampling procedures. Reported PAH prevalence, incidence, and mortality varied by location and study. Prevalence ranged from 0.4 to 1.4 per 100,000 persons. Harmonization of methods for PAH registries would improve efforts at disease surveillance. Results of this search contribute to ongoing efforts to quantify the global burden of PAH.

Computational Simulator Models and Invasive Hemodynamic Monitoring as Tools for Precision Medicine in Pulmonary Arterial Hypertension

Precision medicine, providing the right therapeutic strategy for the right patient, could revolutionize management and prognosis of patients affected by cardiovascular diseases. Big data and artificial intelligence are pivotal for the realization of this ambitious design. In the setting of pulmonary arterial hypertension (PAH), the use of computational models and data derived from ambulatory implantable hemodynamic monitors could provide useful information for tailored treatment, as requested by precision medicine.