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Size-Resolved Lipoprotein Fatty Acid Content as a Novel Nuclear Magnetic Resonance-Derived Trait Specifically
Aziz Belkadi1, Gaurav Thareja1, Nisha Stephan1
1Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha24144, Qatar.
Abstract:
Population-level nuclear magnetic resonance (NMR)-based lipoprotein profiling is a key tool for investigating dysregulated lipoprotein metabolism and its role in cardiovascular disorders. However, associations with size-resolved lipoprotein composition readouts are difficult to dissect, as these traits are often highly correlated. Derived variables can therefore be more relevant to biological interpretation. Here, we show that the total fatty acid (FA) content of the lipoproteins derived from their lipid headgroup concentrations using the formula FA = 3TG + 2PL + CE strongly correlates (Spearman rho = 0.98) with the independently measured total fatty acid content. This observation is not self-evident since these variables are determined using different portions of the NMR spectrum. Using NMR data acquired on the Nightingale platform for 274,303 UK Biobank (UKB) participants and genetic associations as a readout, we then show that this relationship also holds at the size-resolved lipoprotein level. We identified eight gene loci where the proposed FA variables display a significantly stronger genetic association signal than that of the corresponding lipid headgroup variables. Five of these loci (LIPC, LIPG, PLB1, LPL, and APOC3) have a direct function in FA metabolism. Including computed size-resolved FA variables may therefore improve the biological interpretation of future studies based on Nightingale's data.
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