Potential role of the airway wall in the asthma of obesity

Abstract

The pathogenesis of late-onset TH2-low asthma in obesity is thought to be related to weight-related decreases in lung volume, but why only a subset of individuals with obesity develop this condition is unknown. We tested the hypothesis that natural variations in both airway wall stiffness and airway wall thickness could lead to a subpopulation of hyperresponsive individuals exhibiting the symptoms of asthma in the setting of obesity. Increases in airway resistance (Raw) after airway smooth muscle stimulation were simulated using a computational model of an elastic airway embedded in elastic parenchyma. Using a range of randomly chosen values for both airway wall stiffness and thickness, we determined the resulting probability distributions of Raw responsiveness for a variety of different levels of transpulmonary pressure (Ptp). As Ptp decreased from 5 to 1 cmH2O, the resulting distributions of Raw moved toward progressively higher levels of responsiveness. With appropriate choices for the mean and standard deviation of the parameter that controls either airway wall stiffness or thickness, the model predicts a relationship between airway hyperresponsiveness and body mass index that is similar to that which has been reported in populations with obesity. We conclude that natural variations in airway wall mechanics and geometry between different individuals can potentially explain why an increasing percentage of the population exhibits the symptoms of asthma as the obesity of the population increases.

Keywords: airway hyperresponsiveness; airway resistance; airway-parenchymal interdependence; computational model.

Fig. 1.

A: time courses of airway resistence [R_aw; normalized to its initial relaxed value at transpulmonary pressure (P_tp) = 5 cmH₂O] predicted by the computational model when P_tp was set equal to 5, 4, and 3 cmH₂O while k was assigned a value of 0.7. B: corresponding R_aw (normalized to the initial relaxed value for k = 0.73) time courses when k took values of 0.68, 0.73, and 0.78 while P_tp was fixed at 5 cmH₂O. C: corresponding R_aw (normalized to the initial relaxed value for α = 0.08) time courses when α took values of 0.05, 0.08, and 0.11 while P_tp was fixed at 5 cmH₂O.

Fig. 2.

A: histograms of fractional increase in R_aw obtained with 3 different values of P_tp while k was drawn randomly from a Gaussian distribution with k_mean = 0.73 and k_SD = 0.04. B: corresponding histograms obtained with 3 different values of P_tp while α was drawn randomly from a Gaussian distribution with mean = 0.08 and standard deviation = 0.03. Horizontal axis has been transformed from P_tp to body mass index (BMI) using a published relationship between BMI and reduction in functional residual capacity (FRC), as described in the text.

Fig. 3.

Percentage of the population that is hyperresponsive as a function of BMI predicted by the computational model for k_mean = 0.73 and k_SD = 0.04 (solid line) (A) and for α having a mean value of 0.08 and a standard deviation of 0.03 (dashed line) (B). ⋆ indicate the mid regions of BMI for corresponding incidence of asthma from (26a). Right most ★ is BMI > 60; left-most ⋆ corresponds to the general population.