Phenotype-Aware Biomarker Discovery in Childhood Asthma: Microbiome-Metabolome Signatures and Translational Readiness

Childhood asthma is a common but biologically heterogeneous disease, and this heterogeneity limits the performance of one-size-fits-all biomarkers for diagnosis, risk stratification, and disease monitoring. Microbiome and metabolome profiling are attractive in pediatric asthma because they reflect host-environment interactions at mucosal surfaces and may capture clinically relevant variation not fully explained by conventional markers. However, their translational value in children remains uncertain. This review critically examines the current evidence on microbiome- and metabolome-based biomarkers in childhood asthma from a clinically oriented perspective, with emphasis on four settings of practical relevance: early-life risk and disease development, allergic and non-allergic asthma, severe, uncontrolled, or exacerbation-prone disease, and lung-function or inflammatory phenotypes. Current data suggest that composite and phenotype-linked signatures are more informative than isolated taxa or single metabolites. The most convincing signals arise in early-life microbial maturation trajectories and in unstable disease, where upper-airway microbial patterns and integrated metabolic profiles show the greatest potential for clinical stratification. Allergic burden appears to be reflected more consistently by metabolomic than microbiome findings, whereas lung-function and inflammatory phenotypes currently show stronger metabolite-trait associations than reproducible airway microbial correlates. Across phenotypes, pathway-level convergence is more robust than single-marker reproducibility, with recurring signals involving microbial fermentation and short-chain fatty acid biology, bile acid metabolism, tryptophan and histamine pathways, and lipid remodeling. Nevertheless, most pediatric studies remain cross-sectional, modest in size, and heterogeneous in phenotype definitions, sampling matrices, and analytical platforms. No microbiome- or metabolome-based signature is currently ready for routine pediatric clinical use. The most realistic near-term translational direction is the development of age-contextualized, phenotype-oriented reduced panels that are prospectively validated in multicenter cohorts and shown to provide clinical value beyond existing tools for childhood asthma diagnosis, risk stratification, and monitoring.