A Multi-Omics Approach Reveals New Signatures in Obese Allergic Asthmatic Children

Abstract

Background: Asthma is a multifactorial condition where patients with identical clinical diagnoses do not have the same clinical history or respond to treatment. This clinical heterogeneity is reflected in the definition of two main endotypes. We aimed to explore the metabolic and microbiota signatures that characterize the clinical allergic asthma phenotype in obese children. Methods: We used a multi-omics approach combining clinical data, plasma and fecal inflammatory biomarkers, metagenomics, and metabolomics data in a cohort of allergic asthmatic children. Results: We observed that the obese allergic asthmatic phenotype was markedly associated with higher levels of leptin and lower relative proportions of plasma acetate and a member from the Clostridiales order. Moreover, allergic children with a worse asthma outcome showed higher levels of large unstained cells, fecal D lactate and D/L lactate ratio, and with a higher relative proportion of plasma creatinine and an unclassified family member from the RF39 order belonging to the Mollicutes class. Otherwise, children with persistent asthma presented lower levels of plasma citrate and dimethylsulfone. Conclusion: Our integrative approach shows the molecular heterogeneity of the allergic asthma phenotype while highlighting the use of omics technologies to examine the clinical phenotype at a more holistic level.

Variable-Selection ANOVA Simultaneous Component Analysis (VASCA)

“…The BIOASMA data set (Gomez-Llorente et al, 2020) comprises clinical, biochemical, anthropometrical parameters, inflammatory biomarkers, metagenomic and metabolomic data for 46 children (12 girls and 34 boys, aged 4-13 years) with an allergic asthma diagnosed based on the Spanish Guidelines for Asthma Management (GEMA criteria 4.4)- (Moral et al, 2016). The children were also classified into normal-weight (n=13), overweight (n=8) and obese (n=25) according to the age and sexspecific thresholds proposed by Cole et al (2000).…”

“…Metagenomic data were obtained by 16sRNA barcoding sequencing and the Amplicon sequence variants (ASVs) were normalized by the rarefaction method. Deriving potential biomarkers from this data set represents a real challenge (Gomez-Llorente et al, 2020), given the low sample size and the complexity of the experimental design: two potential conflicting factors (asthma severity and weight classification/status) with three levels each are taken into account and the individuals distribution is significantly unbalanced.…”

“…The statistical results obtained from the original analysis of the data set (Gomez-Llorente et al, 2020) are based on Partial Least Squares Discriminant Analysis (PLS-DA) (Barker and Rayens, 2003) and its sparse variant sPLS-DA (Lê Cao et al, 2008). sPLS-DA considers variable selection during model calibration with the idea of discarding non-informative variables.…”

Research Progress of Metabolomics in Asthma

“…The metabolic characteristics of obese asthma are different from those of lean asthma, and the metabolic spectrum of serum showed that the contents of valine, uric acid, and N-methyl-DL-alanine β-glycerophosphate in serum of obese patients with asthma were higher than those of patients with lean asthma, while the contents of asparagine 1 and D-glyceric acid were decreased [ 41 ]. Furthermore, a recent study suggested that the relative proportion of acetic acid in obese children with asthma was significantly lower than in children with normal weight asthma [ 42 ]. The difference in the pathway of bioenergy metabolism between thin and obese asthmatic patients is partly due to the different sensory effects of NO signals [ 43 ].…”

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

“…In addition, a noteworthy approach involving metagenomics, metabolomics and proteomics data from the BIOASMA cohort (n = 46) has provided important insights regarding obesity-related characteristics in asthmatic children with persistent or episodic asthma [174]. Patients were stratified based on the frequency and severity of the disease as groups of occasional, frequent or persistent asthmatics.…”