Mapping the lung-brain axis: Causal relationships between brain network connectivity and respiratory disorders

The mechanistic relationship between respiratory disorders and brain function remains poorly understood, despite growing evidence of cognitive and neurological manifestations in respiratory diseases. We aim to identify whether specific brain network connectivity patterns causally influence respiratory disease susceptibility, while respiratory conditions might reciprocally affect brain network architecture.

We performed bidirectional Mendelian randomization (MR) analyses using genome-wide association studies (GWAS) of brain network connectivity from UK Biobank resting-state functional MRI (rs-fMRI) data (N = 31,453) and GWAS data from ten major respiratory conditions: chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), sleep apnea syndrome (SAS), lung squamous carcinoma (LUSC), lung adenocarcinoma (LUAD), small cell lung carcinoma (SCLC), hospitalized COVID-19, very severe COVID-19, and bronchiectasis. Five MR methods, inverse variance weighted (IVW) with multiplicative random-effect model, weighted median, weighted mode, MR Egger, and MR-robust adjusted profile score (MR-RAPS) were employed to ensure causal inference.

In forward analysis, five respiratory disorders - asthma, IPF, SAS, LUSC, and very severe COVID-19 - showed significant causal associations (p < 1.31 ×10^-4) with 11 rs-fMRI phenotypes, spanning multiple brain networks including the central executive, subcortical-cerebellum, motor, limbic, attention, salience, visual, and default mode networks. In reverse analysis, twelve brain functional networks demonstrated genetic associations with eight respiratory conditions (COPD, asthma, IPF, SAS, LUSC, SCLC, hospitalized COVID-19, and very severe COVID-19), predominantly involving attention, salience, default mode, visual, and central executive networks.

Our study provides preliminary genetic evidence suggesting potential causal relationships between brain network connectivity and respiratory disorders, contributing to our understanding of the lung-brain axis. While the identification of disease-specific network alterations offers promising insights, further clinical validation is needed before these findings can be translated into therapeutic interventions.