Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled crossover feedin
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ORIGINAL ARTICLE
Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled crossover feeding study Sepideh Dibay Moghadam1,2 · Sandi L. Navarro1 · Ali Shojaie3 · Timothy W. Randolph1 · Lisa F. Bettcher4 · Cynthia B. Le4 · Meredith A. Hullar1 · Mario Kratz1 · Marian L. Neuhouser1 · Paul D. Lampe1 · Daniel Raftery1,4 · Johanna W. Lampe1 Received: 28 April 2020 / Accepted: 9 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Background Dietary patterns low in glycemic load are associated with reduced risk of cardiometabolic diseases. Improvements in serum lipid concentrations may play a role in these observed associations. Objective We investigated how dietary patterns differing in glycemic load affect clinical lipid panel measures and plasma lipidomics profiles. Methods In a crossover, controlled feeding study, 80 healthy participants (n = 40 men, n = 40 women), 18–45 y were randomized to receive low-glycemic load (LGL) or high glycemic load (HGL) diets for 28 days each with at least a 28-day washout period between controlled diets. Fasting plasma samples were collected at baseline and end of each diet period. Lipids on a clinical panel including total-, VLDL-, LDL-, and HDL-cholesterol and triglycerides were measured using an auto-analyzer. Lipidomics analysis using mass-spectrometry provided the concentrations of 863 species. Linear mixed models and lipid ontology enrichment analysis were implemented. Results Lipids from the clinical panel were not significantly different between diets. Univariate analysis showed that 67 species on the lipidomics panel, predominantly in the triacylglycerol class, were higher after the LGL diet compared to the HGL (FDR 25% based on blinded QC samples and also 221 species which were missing in more than 20% of the samples. As samples were not collected in a way that would prevent ex vivo lipolysis, 14 FFA species were not included in the analysis. Thus, a total of 607 lipid species were available for final analysis. We imputed all zero values with a value equivalent to half of the lowest concentration in the dataset (0.015 µM). The Lipidyzer output was in absolute concentration, calculated through the use of multiple isotope labeled internal standards as described above. The median reproducibility of the method was 5% overall. Clinical lipid and lipidomics measures were not distributed normally, and thus natural log-transformed data were used. We used linear mixed models to test for a diet effect on a) clinical lipid measures and b) each of the 607 lipid species individually. These measures constituted our primary outcomes. Both analyses were adjusted for diet sequence, age, gender, batch, baseline lipid values, fat mass (%) and participant as a random variable. Benjamini–Hochberg FDR 0.1, Table 3). However, evaluating the effects of diet on the plasma lipidome in the univariate models Table 2 Baseline characteristics of 80 participants on the low glycemic load and high glycemic load die
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