Acylcarnitine Profiles for Disease Biomarker Discovery

Reverse metabolomics analysis of 76 chemically synthesized acylcarnitines searched against public LC-MS/MS data. The work, authored by Allison J. Keys and updated in June 2026, found about 90% of these structures present in human and mouse blood and fecal samples. Machine learning models using AC presence/absence data accurately predicted healthy versus unhealthy individuals.

Use Cases

• Train disease classification models based on acylcarnitine presence/absence patterns.
• Validate potential health biomarkers based on associations between specific AC structures and disease.
• Compare metabolic profiles across species based on AC detection frequency in human and mouse samples.
• Explore metabolic pathway activity using the library of 76 synthesized acylcarnitine structures.

Strengths

• Includes data for 76 chemically synthesized acylcarnitine structures.
• Analysis covers a substantial repository of public untargeted LC-MS/MS data.
• Machine learning models demonstrated good precision and recall for health status prediction.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The machine learning models are noted to lack disease specificity.

Provenance

Source

figshare

Collection Method

Reverse metabolomics search of synthesized metabolite library against public data repositories.

Freshness

Last updated 2026-06-04 21:03:36