Airway Microbiome and Serum Metabolomics Analysis Identify Differential Candidate Biomarkers in Allergic Rhinitis

Abstract

Allergic rhinitis (AR) is a common heterogeneous chronic disease with a high prevalence and a complex pathogenesis influenced by numerous factors, involving a combination of genetic and environmental factors. To gain insight into the pathogenesis of AR and to identity diagnostic biomarkers, we combined systems biology approach to analyze microbiome and serum composition. We collected inferior turbinate swabs and serum samples to study the microbiome and serum metabolome of 28 patients with allergic rhinitis and 15 healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from the upper respiratory samples. Metabolomics was used to examine serum samples. Finally, we combined differential microbiota and differential metabolites to find potential biomarkers. We found no significant differences in diversity between the disease and control groups, but changes in the structure of the microbiota. Compared to the HC group, the AR group showed a significantly higher abundance of 1 phylum (Actinobacteria) and 7 genera (Klebsiella, Prevotella and Staphylococcus, etc.) and a significantly lower abundance of 1 genus (Pelomonas). Serum metabolomics revealed 26 different metabolites (Prostaglandin D2, 20-Hydroxy-leukotriene B4 and Linoleic acid, etc.) and 16 disrupted metabolic pathways (Linoleic acid metabolism, Arachidonic acid metabolism and Tryptophan metabolism, etc.). The combined respiratory microbiome and serum metabolomics datasets showed a degree of correlation reflecting the influence of the microbiome on metabolic activity. Our results show that microbiome and metabolomics analyses provide important candidate biomarkers, and in particular, differential genera in the microbiome have also been validated by random forest prediction models. Differential microbes and differential metabolites have the potential to be used as biomarkers for the diagnosis of allergic rhinitis.

Characterization of dysbiosis of the conjunctival microbiome and nasal microbiome associated with allergic rhinoconjunctivitis and allergic rhinitis

“…Using high-throughput sequencing of 16S rRNA, they reported no significant difference in the abundance, diversity, or homogeneity of bacterial populations between the AR group and HCs, but the microbiota structure had changed. They observed that the microbiota in the inferior turbinate of patients with AR in the acute-exacerbation stage consisted mainly of the phyla Proteobacteria , Firmicutes , and Bacteroidetes , which was similar to the situation in HCs, but differed in that the abundance of the phylum Actinobacteria was increased markedly in patients ( 45 ).…”

The Present and Future of Allergen Immunotherapy in Personalized Medicine

“…Studies on the role of metabolomics showed that, in serum samples collected from 29 healthy controls and 72 patients allergic to dust mites, including 30 mild and 42 moderate-to-severe allergic rhinitis (AR) patients, metabolomics allowed the researchers to distinguish the different categories, suggesting that its profiling may offer novel understandings of the pathophysiological mechanisms of dust mite allergy [ 22 ]. In another study by Yuan et al, the combination of microbiome and metabolomics analyses identified important candidate biomarkers in patients with AR as differential genera of microbes and differential metabolites that could be potentially used as biomarkers for the diagnosis of AR [ 23 ]. A review of 23 studies assessing asthma or wheezing and 6 studies assessing allergy endpoints, altered metabolic pathways revealed some of the underlying biochemical mechanisms triggering these common childhood disorders, which have potential value in clinical practice, reinforcing the evidence from metabolomics studies of childhood atopic diseases [ 24 ].…”

Metabolomics in Otorhinolaryngology

“…An intriguing study was performed by Yuan et al (2022) who aimed at gaining insight into the role of microflora and the metabolic characteristics of AR patients in order to identify new diagnostic biomarkers. In this study, the microorganisms of the nasal airways and the serum collected from 28 patients and 15 healthy individuals were explored using both 16S rRNA sequencing and UPLC-Q/TOF-MS/MS untargeted metabolomics.…”

“…Concerning allergic rhinitis, in different studies ( Zheng et al, 2021 ; Yuan et al, 2022 ), the authors using the same approach (UPLC-QTOF-MS), found different metabolites, mostly belonging to the same pathway. However, most metabolites were related to the arachidonic acid metabolism which is considered helpful at mirroring a reduction of inflammation after therapy.…”

“…Regrettably, even considering the same disorder, metabolic alterations were highly heterogeneous. For example, the most significant metabolites identified differed between Tiziani et al (2009) , Sugimoto et al (2010) , Zheng et al (2021) , and Yuan et al (2022) . Therefore, the application of metabolomics to develop a tailored medicine, also called precision medicine, although considered crucial for identifying the mechanistic origin of altered metabolism, seems not yet ready for comparing and performing epidemiological studies.…”