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

Efficient uncertainty quantification in a spatially multiscale model of pulmonary arterial and venous hemodynamics

Pulmonary hypertension (PH) is a debilitating disease that alters the structure and function of both the proximal and distal pulmonary vasculature. This alters pressure-flow relationships in the pulmonary arterial and venous trees, though there is a critical knowledge gap in the relationships between proximal and distal hemodynamics in disease. Multiscale computational models enable simulations in both the proximal and distal vasculature. However, model inputs and measured data are inherently uncertain, requiring a full analysis of the sensitivity and uncertainty of the model. Thus, this study quantifies model sensitivity and output uncertainty in a spatially multiscale, pulse-wave propagation model of pulmonary hemodynamics. The model includes fifteen proximal arteries and twelve proximal veins, connected by a two-sided, structured tree model of the distal vasculature. We use polynomial chaos expansions to expedite sensitivity and uncertainty quantification analyses and provide results for both the proximal and distal vasculature. We quantify uncertainty in blood pressure, blood flow rate, wave intensity, wall shear stress, and cyclic stretch. The latter two are important stimuli for endothelial cell mechanotransduction. We conclude that, while nearly all the parameters in our system have some influence on model predictions, the parameters describing the density of the microvascular beds have the largest effects on all simulated quantities in both the proximal and distal arterial and venous circulations.

Alveolar hypoxia induces organ-specific inflammasome-related inflammation in male mouse lungs

Inflammation through activation of caspase-1, seems to play a role in pulmonary hypertension induced by alveolar hypoxia. Whether alveolar hypoxia induces caspase-1-mediated inflammation and influx of leukocytes in other organs than the lungs, is not known. Our aim was to explore sites of caspase-1-related inflammation in alveolar hypoxia. Wild type (WT) mice were exposed to environmental hypoxia or room-air, and organs were analyzed. Right heart catheterization was performed after 14 days of alveolar hypoxia in WT mice and mice transplanted with WT or caspase-1-/- bone marrow. Hypoxia induced leukocyte accumulation and increased caspase-1 protein in the lungs, not in other organs. WT mice transplanted with WT or caspase-1-/- bone marrow showed no difference in pulmonary leukocyte accumulation or development of pulmonary hypertension after alveolar hypoxia. Caspase-1 and IL-18 were detected in bronchial epithelium in WT mice, and hypoxia induced IL-18 secretion from bronchial epithelial cells. IL-18 stimulation generated IL-6 mRNA in monocytes. Phosphorylated STAT3 was increased in hypoxic lungs, not in other organs. Alveolar hypoxia induces caspase-1 activation and leukocyte accumulation specific to the lungs, not in other organs. Caspase-1 activation and IL-18 secretion from bronchial epithelial cells might initiate hypoxia-induced inflammation, leading to pulmonary hypertension.

Pulmonary hypertension in chronic obstructive pulmonary disease: current understanding, knowledge gaps and future directions

PURPOSE OF REVIEW

Despite the advent of effective and mechanistically diverse treatments for pulmonary arterial hypertension (PAH) and their positive impacts on the functional capacities and outcomes for PAH patients, the much larger population of patients with pulmonary hypertension (PH) in chronic lung diseases like chronic obstructive pulmonary disease (PH-COPD) remain without effective therapies.

RECENT FINDINGS

In this review, we will highlight advances in the understanding of PH-COPD pathobiology, the clinical impact comorbid PH has on COPD outcomes, and detail the spectrum of disease and clinical phenotypes that encompass the heterogenous disease manifestations of PH-COPD. Finally, we will examine recent studies exploring the effects of potential treatments for PH-COPD and highlight sub-populations and treatment options that warrant further study.

SUMMARY

As the PAH population-base ages and comorbid diseases become more frequently diagnosed in PAH patients, the need to clearly delineate subpopulations for clinical applications of PH therapies and research becomes even more urgent. Through an improved understanding of the clinical phenotypes of PH-COPD and the overlap with certain subpopulations of PAH, a framework for future research and potential for therapeutic impact is highlighted.

Efficient Uncertainty Quantification in a Multiscale Model of Pulmonary Arterial and Venous Hemodynamics

Computational hemodynamics models are becoming increasingly useful in the management and prognosis of complex, multiscale pathologies, including those attributed to the development of pulmonary vascular disease. However, diseases like pulmonary hypertension are heterogeneous, and affect both the proximal arteries and veins as well as the microcirculation. Simulation tools and the data used for model calibration are also inherently uncertain, requiring a full analysis of the sensitivity and uncertainty attributed to model inputs and outputs. Thus, this study quantifies model sensitivity and output uncertainty in a multiscale, pulse-wave propagation model of pulmonary hemodynamics. Our pulmonary circuit model consists of fifteen proximal arteries and twelve proximal veins, connected by a two-sided, structured tree model of the distal vasculature. We use polynomial chaos expansions to expedite the sensitivity and uncertainty quantification analyses and provide results for both the proximal and distal vasculature. Our analyses provide uncertainty in blood pressure, flow, and wave propagation phenomenon, as well as wall shear stress and cyclic stretch, both of which are important stimuli for endothelial cell mechanotransduction. We conclude that, while nearly all the parameters in our system have some influence on model predictions, the parameters describing the density of the microvascular beds have the largest effects on all simulated quantities in both the proximal and distal circulation.