Multi-Omics Data for Childhood Asthma Biomarker Study

124 transcriptomic and 30 metabolomic samples from children with and without asthma were integrated to identify potential diagnostic biomarkers. The study identified 15 differentially expressed genes and 516 differential metabolites, with three metabolites showing area under the curve values between 0.818 and 0.844 for diagnostic performance. Author Junlin Zhao published this preliminary research on figshare in 2026.

Use Cases

• Training diagnostic models based on the three identified plasma metabolite biomarkers (L-tryptophan, 5-aminolevulinic acid, L-aspartate semialdehyde).
• Analyzing pathway-level convergence in multi-omics data, specifically within the glycine-serine-threonine metabolism pathway.
• Investigating correlations between specific metabolites (e.g., 5-aminolevulinic acid) and clinical parameters like serum IgE and eosinophil counts.
• Studying the association between bisphosphoglycerate mutase (BPGM) downregulation and metabolic alterations in childhood asthma.

Strengths

• Includes data from two distinct cohorts: a transcriptomic cohort of 124 samples and a metabolomic cohort of 30 samples.
• Identifies specific diagnostic candidates with reported performance metrics, such as 5-aminolevulinic acid achieving 80% sensitivity and 80% specificity.
• Released under a permissive CC-BY-4.0 license, facilitating reuse and sharing.

Limitations

• The dataset is very small at 75.6 KB, indicating limited raw data or a summary document rather than a full primary dataset.
• Column-level documentation is absent; field semantics must be inferred after download.
• The cross-population design (US and China) precludes direct gene-metabolite correlation at the individual level, limiting mechanistic inference.

Provenance

Source

figshare, author Junlin Zhao.

Collection Method

Integration of public transcriptomic data (GSE35571) with in-house untargeted metabolomics from treatment-naive children.

Freshness

Last updated 2026-05-07 04:45:22; freshness should be verified.

Geography

Transcriptomic cohort from Detroit, Michigan, USA; metabolomic cohort from Xinjiang, China.