Molecular pathways underlying lung-brain axis signaling in asthma: Relevance for psychopathology and neuroinflammation

Abstract

Background: Accumulating evidence indicates that asthma has systemic effects and affects brain function. Although airway inflammation is proposed to initiate afferent communications with the brain, the signaling pathways have not been established.

Objective: We sought to identify the cellular and molecular pathways involved in afferent lung-brain communication during airway inflammation in asthma.

Methods: In 23 adults with mild asthma, segmental bronchial provocation with allergen (SBP-Ag) was used to provoke airway inflammation and retrieve bronchoalveolar lavage fluid for targeted protein analysis and RNA sequencing to determine gene expression profiles. Neural responses to emotional cues in nodes of the salience network were assessed with functional magnetic resonance imaging at baseline and 48 hours after SBP-Ag.

Results: Cell deconvolution and gene coexpression network analysis identified 11 cell-associated gene modules that changed in response to SBP-Ag. SBP-Ag increased bronchoalveolar lavage eosinophils and expression of an eosinophil-associated module enriched for genes related to T_H17-type inflammation (eg, IL17A), as well as cell proliferation in lung and brain (eg, NOTCH1, VEGFA, and LIF). Increased expression of genes in this module, as well as several T_H17-type inflammation-related proteins, was associated with an increase from baseline in salience network reactivity.

Conclusions: Our results identify a specific inflammatory pathway linking asthma-related airway inflammation and emotion-related neural function. Systemically, T_H17-type inflammation has been implicated in both depression and neuroinflammation, with impacts on long-term brain health. Thus, our data emphasize that inflammation in the lung in asthma may have profound effects outside of the lung that may be targetable with novel therapeutic approaches.

Keywords: Asthma; IL-17; T(H)17; depression; eosinophils; fMRI; gene expression network analysis; salience network.