Year: 2021
Type: conference-abstract
Abstract: RATIONALE: Current guidelines do not sufficiently capture the heterogenous nature of asthma leading to suboptimal management strategies.A more comprehensive classification of asthma into biologically meaningful subgroups is needed.Given its position on the central biological dogma as the 'ome closest to phenotype, reflecting genetics, environment and their interactions, metabolomics represents a novel and compelling approach to accurately identifying asthma endotypes; i.e. subtypes defined by functional or pathobiological mechanisms, with the potential for clinical translation.METHODS: We performed plasma metabolomic profiling of 1155 asthmatic children from the Genetics of Asthma in Costa Rica Study (GACRS) across four profiling platforms covering a broad range of the metabolome.We generated patient similarity networks for each platform that connected asthmatics via edges representing patient-to-patient similarity in their metabolomic profiles (controlling for age, sex and body mass index).We then fused the four platform-specific networks using Similarity Network Fusion and performed spectral clustering on the resulting fused similarity network to identify metaboendotypes.We explored phenotypic and clinical differences across metabo-endotypes using ANOVA and chi-square tests.For validation we recapitulated the endotypes in an independent population of asthmatic children (CAMP, n=911) to determine whether the same between-endotype differences were observed.Finally, we identified metabolomic and genomic drivers of validated metabo-endotype membership, meta-analyzing findings from GACRS and CAMP.RESULTS: We identified five metabo-endotypes in GACRS and observed significant differences across metabo-endotypes in asthma-relevant phenotypes: pre-bronchodilator (p-ANOVA=8.3x10 - ) and post-bronchodilator (p-ANOVA=1.8x10 - ) FEV 1 /FVC ratio; use of inhaled (p-ANOVA=5.0x10 -1 ) and oral (p-ANOVA=0.007)steroids, and airway hyperresponsiveness to methacholine (AHR PC 20 <16.8, p-ANOVA=8.4x10 - ).Furthermore, there was a significant difference in eosinophil count (p-ANOVA=0.009).The recapitulated metabo-endotypes in CAMP displayed significant differences (p<0.05) in many of the same phenotypes.(Table 1).The "most-severe" asthma endotype was defined by the lowest FEV 1 /FVC ratio, and the highest prevalence of AHR and oral steroid usage.It was characterized by higher levels of glycerolipids and lysophospholipids, and lower levels of nucleotides relative to the other endotypes.These findings suggest dysregulation of pulmonary surfactant homeostasis in the "most-severe" endotype and were supported by the genetic analysis, which found that members of this endotype were more likely to carry variants in key pulmonary surfactant regulation genes such as BACH3 (meta-analyzed p=5.2x10 -4 ) and BMP3 (meta-analyzed p=8.5x10 -4 ).CONCLUSIONS: These findings demonstrate that clinically meaningful endotypes can be derived and validated using metabolomic data, and that interrogating the drivers of these metabo-endotypes can help understand their pathophysiology and identify therapeutic targets.
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4234222135