AI Article Synopsis

  • A genetic risk score (GRS) developed in the FAS Study was tested for its ability to predict how plasma triglycerides (TG) respond to omega-3 fatty acid supplementation.
  • Recent findings from the UK Biobank identified new SNPs linked to plasma lipid levels, which were added to the original GRS in the hopes of improving prediction accuracy.
  • However, after testing these modified GRSs (GRS32, GRS38, GRS46), the original GRS31 still demonstrated the best predictive capability for TG responses, indicating that adding new SNPs didn't enhance its effectiveness.

Article Abstract

A genetic risk score (GRS) predictive of the plasma triglyceride (TG) response to an omega-3 fatty acid (-3 FA) supplementation has been previously developed in the Fatty Acid Sensor (FAS) Study. Recently, novel single nucleotide polymorphisms (SNPs) interacting with a fish oil supplementation and associated with plasma lipid levels have been identified in the UK Biobank. The aim of this study was to verify whether the addition of SNPs identified in the UK Biobank to the GRS built in the FAS Study improves its capacity to predict the plasma TG response to an -3 FA supplementation. SNPs interacting with fish oil supplementation in the modulation of plasma lipid levels in the UK Biobank and associated with plasma TG levels have been genotyped in participants of the FAS Study ( = 141). Participants have been supplemented with 5 g fish oil/day for six weeks. Plasma TG concentrations were measured before and after the supplementation. Based on the initial GRS of 31 SNPs (GRS31), we computed three new GRSs by adding new SNPs identified in the UK Biobank: GRS32 (rs55707100), GRS38 (seven new SNPs specifically associated with plasma TG levels), and GRS46 (all 15 new SNPs associated with plasma lipid levels). The initial GRS31 explained 50.1% of the variance in plasma TG levels during the intervention, whereas GRS32, GRS38, and GRS46 explained 49.1%, 45.9%, and 45%, respectively. A significant impact on the probability of being classified as a responder or a nonresponder was found for each of the GRSs analyzed, but none of them outperformed the predictive capacity of GRS31 in any of the metrics analyzed, i.e., accuracy, area under the response operating curve (AUC-ROC), sensitivity, specificity and McFadden's pseudo R. The addition of SNPs identified in the UK Biobank to the initial GRS31 did not significantly improve its capacity to predict the plasma TG response to an -3 FA supplementation. Thus, GRS31 still remains the most precise tool so far by which to discriminate the individual responsiveness to -3 FAs. Further studies are needed in the field to increase our knowledge of factors underlying the heterogeneity observed in the metabolic response to an -3 FA supplementation.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005670PMC
http://dx.doi.org/10.3390/nu15051156DOI Listing

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