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Lipidomics has attracted attention in the discovery of unknown biomolecules and for capturing the changes in metabolism caused by genetic and environmental factors in an unbiased manner. However, obtaining reliable lipidomics data, including structural diversity and quantification data, is still challenging. Supercritical fluid chromatography (SFC) is a suitable technique for separating lipid molecules with high throughput and separation efficiency.

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Polyunsaturated fatty acids (PUFAs) including omega-3 and omega-6 are obtained from diet and can be measured objectively in plasma or red blood cells (RBCs) membrane biomarkers, representing different dietary exposure windows. In vivo conversion of omega-3 and omega-6 PUFAs from short- to long-chain counterparts occurs via a shared metabolic pathway involving fatty acid desaturases and elongase. This analysis leveraged genome-wide association study (GWAS) summary statistics for RBC and plasma PUFAs, along with expression quantitative trait loci (eQTL) to estimate tissue-specific genetically predicted gene expression effects for delta-5 desaturase (FADS1), delta-6 desaturase (FADS2), and elongase (ELOVL2) on changes in RBC and plasma biomarkers.

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