Summary
This methodological paper presents LipidOne's NMLP module, a computational framework designed to translate high-dimensional plasma lipidomic data into actionable nutritional-metabolic profiles. Applied to three public datasets spanning glycemic-load feeding, high-fat diet intervention, and insulin sensitivity studies, the module successfully identified metabolic lipid shifts and phenotypic heterogeneity not captured by standard clinical panels, suggesting utility for precision nutrition and metabolic phenotyping research.
Regional applicability
The study is methodology-focused with no specific geographic restriction; the NMLP framework is applicable globally wherever plasma lipidomics is performed. Adoption in United Kingdom clinical nutrition and metabolic research would depend on integration with existing lipidomics workflows and validation in UK-specific populations.
Key measures
Lipid indices reflecting cardiometabolic lipid status, fatty acid remodelling, lipid quality, oxidative protection, and omega-3/essential fatty acid status; neutral lipid storage indices; category-level clustering of nutritional-metabolic states
Outcomes reported
The study presents the Nutritional-Metabolic Lipid Profile (NMLP) module within LipidOne, which converts complex plasma lipidomic data into interpretable nutritional-metabolic indices, functional categories, and visual outputs. The module was validated across three human plasma lipidomics datasets to assess its utility in capturing metabolic lipid shifts, temporal lipid remodelling, and phenotypic heterogeneity in insulin resistance.
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