Frontiers in Physiology (Jun 2023)

Chronic pulmonary fibrosis alters the functioning of the respiratory neural network

  • Céline-Hivda Yegen,
  • Dominique Marchant,
  • Jean-François Bernaudin,
  • Jean-François Bernaudin,
  • Carole Planes,
  • Carole Planes,
  • Emilie Boncoeur,
  • Nicolas Voituron,
  • Nicolas Voituron

DOI
https://doi.org/10.3389/fphys.2023.1205924
Journal volume & issue
Vol. 14

Abstract

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Some patients with idiopathic pulmonary fibrosis present impaired ventilatory variables characterised by low forced vital capacity values associated with an increase in respiratory rate and a decrease in tidal volume which could be related to the increased pulmonary stiffness. The lung stiffness observed in pulmonary fibrosis may also have an effect on the functioning of the brainstem respiratory neural network, which could ultimately reinforce or accentuate ventilatory alterations. To this end, we sought to uncover the consequences of pulmonary fibrosis on ventilatory variables and how the modification of pulmonary rigidity could influence the functioning of the respiratory neuronal network. In a mouse model of pulmonary fibrosis obtained by 6 repeated intratracheal instillations of bleomycin (BLM), we first observed an increase in minute ventilation characterised by an increase in respiratory rate and tidal volume, a desaturation and a decrease in lung compliance. The changes in these ventilatory variables were correlated with the severity of the lung injury. The impact of lung fibrosis was also evaluated on the functioning of the medullary areas involved in the elaboration of the central respiratory drive. Thus, BLM-induced pulmonary fibrosis led to a change in the long-term activity of the medullary neuronal respiratory network, especially at the level of the nucleus of the solitary tract, the first central relay of the peripheral afferents, and the Pre-Bötzinger complex, the inspiratory rhythm generator. Our results showed that pulmonary fibrosis induced modifications not only of pulmonary architecture but also of central control of the respiratory neural network.

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