We have updated our metabolite set library to better support enrichment analysis from lipidomics data (see below)
How were these metabolite sets created?
The metabolite sets for lipidomics functional analysis were designed to capture biologically meaningful modules of lipid metabolism. To build them, we integrated information from major biochemical pathway databases (KEGG, Reactome, WikiPathways, PathBank) with chemical classification systems such as LIPID MAPS and ClassyFire.
What counts as a “lipid” in these sets?
For consistency, we used widely accepted chemical ontology definitions. Lipids are hydrophobic or amphipathic small molecules that include fatty acids, glycerolipids, glycerophospholipids, sphingolipids, sterols, prenol lipids, and related structural classes. Only compounds that were classified as lipids or lipid-like molecules in both LIPID MAPS and ClassyFire were included as lipid members in the metabolite sets.
What do these metabolite sets include?
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Canonical lipid metabolism pathways or modules (e.g., fatty acid biosynthesis, beta-oxidation, glycerophospholipid metabolism, ceramide biosynthesis).
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Broader metabolic pathways that involve metabolites classified as lipids or lipid-like molecules by both ClassyFire and LIPID MAPS, even if the pathways are not exclusively lipid-focused.
Why do some sets include non-lipid molecules?
Metabolic pathways naturally involve cofactors and small molecules such as ATP, NADPH, CoA, choline, or CMP. These were retained in pathway annotations to preserve full biochemical context and reaction completeness. Additionally, certain molecules not considered biological lipids (e.g., acetyl-CoA, succinyl-CoA, other acyl-CoA intermediates) meet structural criteria for lipid or fatty-acyl derivative classes within LIPID MAPS and ClassyFire. As a result, these derivatives may appear in lipid-related sets, and many of them participate in metabolic processes that connect to lipid metabolism.