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. 2017 Jun 15;195(12):1640-1650.
doi: 10.1164/rccm.201607-1408OC.

Host-Microbial Interactions in Idiopathic Pulmonary Fibrosis

Philip L Molyneaux  1   2 , Saffron A G Willis-Owen  1 , Michael J Cox  1 , Phillip James  1 , Steven Cowman  1   2 , Michael Loebinger  1   2 , Andrew Blanchard  3 , Lindsay M Edwards  3 , Carmel Stock  1   2 , Cécile Daccord  1   2 , Elisabetta A Renzoni  1   2 , Athol U Wells  2 , Miriam F Moffatt  1 , William O C Cookson  1   2 , Toby M Maher  1   2
Affiliations

Host-Microbial Interactions in Idiopathic Pulmonary Fibrosis

Philip L Molyneaux et al. Am J Respir Crit Care Med. .

Abstract

Rationale: Changes in the respiratory microbiome are associated with disease progression in idiopathic pulmonary fibrosis (IPF). The role of the host response to the respiratory microbiome remains unknown.

Objectives: To explore the host-microbial interactions in IPF.

Methods: Sixty patients diagnosed with IPF were prospectively enrolled together with 20 matched control subjects. Subjects underwent bronchoalveolar lavage (BAL), and peripheral whole blood was collected into PAXgene tubes for all subjects at baseline. For subjects with IPF, additional samples were taken at 1, 3, and 6 months and (if alive) 1 year. Gene expression profiles were generated using Affymetrix Human Gene 1.1 ST arrays.

Measurements and main results: By network analysis of gene expression data, we identified two gene modules that strongly associated with a diagnosis of IPF, BAL bacterial burden (determined by 16S quantitative polymerase chain reaction), and specific microbial operational taxonomic units, as well as with lavage and peripheral blood neutrophilia. Genes within these modules that are involved in the host defense response include NLRC4, PGLYRP1, MMP9, and DEFA4. The modules also contain two genes encoding specific antimicrobial peptides (SLPI and CAMP). Many of these particular transcripts were associated with survival and showed longitudinal overexpression in subjects experiencing disease progression, further strengthening the relationship of the transcripts with disease.

Conclusions: Integrated analysis of the host transcriptome and microbial signatures demonstrated an apparent host response to the presence of an altered or more abundant microbiome. These responses remained elevated in longitudinal follow-up, suggesting that the bacterial communities of the lower airways may act as persistent stimuli for repetitive alveolar injury in IPF.

Keywords: acute lung injury; expression; idiopathic pulmonary fibrosis; microbiome; usual interstitial pneumonia.

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Figures

Figure 1.
Figure 1.
Associations between WGCNA (Weighted Gene Co-expression Network Analysis) modules and phenotypic traits. Positive correlations are shown in red, and negative correlations are shown in blue. *P < 0.05; **P < 0.01; ***P < 0.001. BAL = bronchoalveolar lavage; Corr Coef = correlation coefficient; IPF = idiopathic pulmonary fibrosis; MUC5B = mucin 5B; TOLLIP1 = Toll-interacting protein 1; TOLLIP2 = Toll-interacting protein 2.
Figure 2.
Figure 2.
Visualization of the most highly connected nodes in the blue module. For improved clarity, only those nodes with the highest module memberships are considered (up to a maximum of 40), and only those connections with a topological overlap greater than 0.025 are shown. Cytoscape 3.2.158 was used to visualize the network with a prefuse force-directed layout. Genes are represented by nodes of different colors, with colors corresponding to degree (green to red indicating low to high). Edge thickness is proportional to the strength of the association.
Figure 3.
Figure 3.
Expression values over time in genes of interest. The expression of MMP9, CAMP, DEFA4, NLRC4, and TXN increased over time. LCK expression decreased. There was no significant change in the expression levels of SLPI, COMMD6, and POLYGPR over the 12-month period.
Figure 4.
Figure 4.
Expression values over time in genes of interest in stable and progressive idiopathic pulmonary fibrosis. The trend of change is the same in progressive and stable disease, but the absolute expression levels vary depending on disease state.
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