Nasal Bacteriomes of Patients with Asthma and Allergic Rhinitis Show Unique Composition, Structure, Function and Interactions

Methodology for biomarker discovery with reproducibility in microbiome data using machine learning

BACKGROUND

In recent years, human microbiome studies have received increasing attention as this field is considered a potential source for clinical applications. With the advancements in omics technologies and AI, research focused on the discovery for potential biomarkers in the human microbiome using machine learning tools has produced positive outcomes. Despite the promising results, several issues can still be found in these studies such as datasets with small number of samples, inconsistent results, lack of uniform processing and methodologies, and other additional factors lead to lack of reproducibility in biomedical research. In this work, we propose a methodology that combines the DADA2 pipeline for 16s rRNA sequences processing and the Recursive Ensemble Feature Selection (REFS) in multiple datasets to increase reproducibility and obtain robust and reliable results in biomedical research.

RESULTS

Three experiments were performed analyzing microbiome data from patients/cases in Inflammatory Bowel Disease (IBD), Autism Spectrum Disorder (ASD), and Type 2 Diabetes (T2D). In each experiment, we found a biomarker signature in one dataset and applied to 2 other as further validation. The effectiveness of the proposed methodology was compared with other feature selection methods such as K-Best with F-score and random selection as a base line. The Area Under the Curve (AUC) was employed as a measure of diagnostic accuracy and used as a metric for comparing the results of the proposed methodology with other feature selection methods. Additionally, we use the Matthews Correlation Coefficient (MCC) as a metric to evaluate the performance of the methodology as well as for comparison with other feature selection methods.

CONCLUSIONS

We developed a methodology for reproducible biomarker discovery for 16s rRNA microbiome sequence analysis, addressing the issues related with data dimensionality, inconsistent results and validation across independent datasets. The findings from the three experiments, across 9 different datasets, show that the proposed methodology achieved higher accuracy compared to other feature selection methods. This methodology is a first approach to increase reproducibility, to provide robust and reliable results.

Role of the ocular surface microbiome in allergic eye diseases

PURPOSE OF REVIEW

The purpose of this review is to provide an update on emerging literature on the role of the ocular surface microbiome (OSM) in allergic eye diseases.

RECENT FINDINGS

Findings in the literature suggest that the ocular surface microbiome plays a role in the pathophysiology and course of allergic disease of the ocular surface.

SUMMARY

Knowledge regarding the role of the ocular surface microbiome in allergic disease is important to guide development of targets for future therapeutic interventions.

Characterization of the upper respiratory tract microbiota in Chilean asthmatic children reveals compositional, functional, and structural differences

Around 155 million people worldwide suffer from asthma. In Chile, the prevalence of this disease in children is around 15% and has a high impact in the health system. Studies suggest that asthma is caused by multiple factors, including host genetics, antibiotic use, and the development of the airway microbiota. Here, we used 16S rRNA high-throughput sequencing to characterize the nasal and oral mucosae of 63 asthmatic and 89 healthy children (152 samples) from Santiago, Chile. We found that the nasal mucosa was dominated by a high abundance of Moraxella, Dolosigranulum, Haemophilus, Corynebacterium, Streptococcus, and Staphylococcus. In turn, the oral mucosa was characterized by a high abundance of Streptococcus, Haemophilus, Gemella, Veillonella, Neisseria, and Porphyromonas. Our results showed significantly (P < 0.001) lower alpha diversity and an over-abundance of Streptococcus (P < 0.01) in nasal samples from asthmatics compared to samples from healthy subjects. Community structure, as revealed by co-occurrence networks, showed different microbial interactions in asthmatic and healthy subjects, particularly in the nasal microbiota. The networks revealed keystone genera in each body site, including Prevotella, Leptotrichia, and Porphyromonas in the nasal microbiota, and Streptococcus, Granulicatella, and Veillonella in the oral microbiota. We also detected 51 functional pathways differentially abundant on the nasal mucosa of asthmatic subjects, although only 13 pathways were overrepresented in the asthmatic subjects (P < 0.05). We did not find any significant differences in microbial taxonomic (composition and structure) and functional diversity between the oral mucosa of asthmatic and healthy subjects. This study explores for the first time the relationships between the upper respiratory airways bacteriome and asthma in Chile. It demonstrates that the nasal cavity of children from Santiago harbors unique bacterial communities and identifies potential taxonomic and functional biomarkers of pediatric asthma.

The oral bacteriomes of patients with allergic rhinitis and asthma differ from that of healthy controls

Allergic rhinitis and asthma are two of the most common chronic respiratory diseases in developed countries and have become a major public health concern. Substantial evidence has suggested a strong link between respiratory allergy and upper airway dysbacteriosis, but the role of the oral bacteriota is still poorly understood. Here we used 16S rRNA massive parallel sequencing to characterize the oral bacteriome of 344 individuals with allergic rhinitis (AR), allergic rhinitis with asthma (ARAS), asthma (AS) and healthy controls (CT). Four of the most abundant (>2%) phyla (Actinobacteriota, Firmicutes, Fusobacteriota, and Proteobacteria) and 10 of the dominant genera (Actinomyces, Fusobacterium, Gemella, Haemophilus, Leptotrichia, Neisseria, Porphyromonas, Prevotella, Streptococcus, and Veillonella) in the oral cavity differed significantly (p ≤ 0.03) between AR, ARAS or AS and CT groups. The oral bacteriome of ARAS patients showed the highest intra-group diversity, while CT showed the lowest. All alpha-diversity indices of microbial richness and evenness varied significantly (p ≤ 0.022) in ARAS vs. CT and ARAS vs. AR, but they were not significantly different in AR vs. CT. All beta-diversity indices of microbial structure (Unifrac, Bray-Curtis, and Jaccard distances) differed significantly (p ≤ 0.049) between each respiratory disease group and controls. Bacteriomes of AR and ARAS patients showed 15 and 28 upregulated metabolic pathways (PICRUSt2) mainly related to degradation and biosynthesis (p < 0.05). A network analysis (SPIEC-EASI) of AR and ARAS bacteriomes depicted simpler webs of interactions among their members than those observed in the bacteriome of CT, suggesting chronic respiratory allergic diseases may disrupt bacterial connectivity in the oral cavity. This study, therefore, expands our understanding of the relationships between the oral bacteriome and allergy-related conditions. It demonstrates for the first time that the mouth harbors distinct bacteriotas during health and allergic rhinitis (with and without comorbid asthma) and identifies potential taxonomic and functional microbial biomarkers of chronic airway disease.

New insights into the pathophysiology and therapeutic targets of asthma and comorbid chronic rhinosinusitis with or without nasal polyposis

Asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) or without (CRSsNP) are chronic respiratory diseases. These two disorders often co-exist based on common anatomical, immunological, histopathological, and pathophysiological basis. Usually, asthma with comorbid CRSwNP is driven by type 2 (T2) inflammation which predisposes to more severe, often intractable, disease. In the past two decades, innovative technologies and detection techniques in combination with newly introduced targeted therapies helped shape our understanding of the immunological pathways underlying inflammatory airway diseases and to further identify several distinct clinical and inflammatory subsets to enhance the development of more effective personalized treatments. Presently, a number of targeted biologics has shown clinical efficacy in patients with refractory T2 airway inflammation, including anti-IgE (omalizumab), anti-IL-5 (mepolizumab, reslizumab)/anti-IL5R (benralizumab), anti-IL-4R-α (anti-IL-4/IL-13, dupilumab), and anti-TSLP (tezepelumab). In non-type-2 endotypes, no targeted biologics have consistently shown clinical efficacy so far. Presently, multiple therapeutical targets are being explored including cytokines, membrane molecules and intracellular signalling pathways to further expand current treatment options for severe asthma with and without comorbid CRSwNP. In this review, we discuss existing biologics, those under development and share some views on new horizons.