Contribution of allergy in the acquisition of uncontrolled severe asthma

Abstract

Asthma is a multifactorial, heterogeneous disease that has a challenging management. It can be divided in non-allergic and allergic (usually associated with house dust mites (HDM) sensitization). There are several treatments options for asthma (corticosteroids, bronchodilators, antileukotrienes, anticholinergics,…); however, there is a subset of patients that do not respond to any of the treatments, who can display either a T2 or a non-T2 phenotype. A deeper understanding of the differential mechanisms underlying each phenotype will help to decipher the contribution of allergy to the acquisition of this uncontrolled severe phenotype. Here, we aim to elucidate the biological pathways associated to allergy in the uncontrolled severe asthmatic phenotype. To do so, twenty-three severe uncontrolled asthmatic patients both with and without HDM-allergy were recruited from Hospital Universitario de Gran Canaria Dr. Negrin. A metabolomic fingerprint was obtained through liquid chromatography coupled to mass spectrometry, and identified metabolites were associated with their pathways. 9/23 patients had uncontrolled HDM-allergic asthma (UCA), whereas 14 had uncontrolled, non-allergic asthma (UCNA). 7/14 (50%) of the UCNA patients had Aspirin Exacerbated Respiratory Disease. There were no significant differences regarding gender or body mass index; but there were significant differences in age and onset age, which were higher in UCNA patients; and in total IgE, which was higher in UCA. The metabolic fingerprint revealed that 103 features were significantly different between UCNA and UCA (p < 0.05), with 97 being increased in UCA and 6 being decreased. We identified lysophosphocholines (LPC) 18:2, 18:3 and 20:4 (increased in UCA patients); and deoxycholic acid and palmitoleoylcarnitine (decreased in UCA). These metabolites were related with a higher activation of phospholipase A2 (PLA2) and other phospholipid metabolism pathways. Our results show that allergy induces the activation of specific inflammatory pathways, such as the PLA2 pathway, which supports its role in the development of an uncontrolled asthma phenotype. There are also clinical differences, such as higher levels of IgE and earlier onset ages for the allergic asthmatic group, as expected. These results provide evidences to better understand the contribution of allergy to the establishment of a severe uncontrolled phenotype.

Keywords: HDM-allergy; allergy; asthma; bile acids (BAs); lysophospholipids; metabolomics.

Figure 1

PCA models showed that QC samples (black dots) clustered together in both ESI+ (A) and ESI− (B), ensuring quality of the data. Sample of patients (gray dots) are also shown.

Figure 2

Multivariant analysis of metabolomic data from serum samples. An unsupervised PCA model (let) of UCA and UCNA patients was built using 593 features for ESI – (above) and 734 for ESI + (below). Then, supervised PLS-DA (center) and OPLS-DA (right) models were built; but only models for the ESI– mode were found. All data were UV scaled. UCA, red dots; UCNA, purple dots. R² is the capability of the model to classify the samples; Q² is the capability of the model to predict the class of a new sample.

Figure 3

Hierarchical clustering analysis heatmap of the UCA (red) and UCNA (purple) patients (in columns) built using the 103 significantly different signals between the groups (in columns). Samples and metabolites were clustered according to their similarity. Red and blue cells represent an increase or decrease in the abundance of a given metabolite.

Figure 4

Trajectories of relevant identified metabolites in box and whiskers plots between UCA (red) and UCNA (purple). Mean is represented by “+” inside the boxes, and individual data points are shown in dots. Mann–Witney U test was used to calculate significant differences. *p < 0.05.

Figure 5

Enrichment analysis of the most changed biological categories for the altered compounds. P-value is shown by a yellow-red color scale; and the relevance of the change is shown by an enrichment ratio.