Summary of Study ST001490
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001007. The data can be accessed directly via it's Project DOI: 10.21228/M8J106 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Study ID | ST001490 |
| Study Title | Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled cross over feeding study |
| Study Summary | 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 a clinical lipid panel 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. A clinical lipid 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 were used to test for a diet effect. Results: Lipids from the clinical panel were not significantly different between diets. Lipidomics analysis showed that 67 lipid species, predominantly in the triacylglycerol class, differed between diets (FDR<0.05). A majority of these were higher after the LGL diet compared to the HGL. Conclusion: While the clinical lipid measures did not differ between diets, some lipid species were higher after the LGL diet in the lipidomics analysis. The two diets were eucaloric and had similar percentage of energy from carbohydrate, protein and fat. Thus, the difference in macronutrient, particularly carbohydrate, quality of the LGL diet is likely affecting the composition of lipid species. |
| Institute | Fred Hutchinson Cancer Research Center |
| Last Name | Dibay Moghadam |
| First Name | Sepideh |
| Address | 1100 Fairview Ave N, Seattle, WA 98109 |
| sdibaymo@fredhutch.org | |
| Phone | 206-667-4068 |
| Submit Date | 2020-09-10 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | wiff |
| Analysis Type Detail | FIA-MS |
| Release Date | 2020-09-24 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO001559 |
| Collection Summary: | We collected blood at baseline and the end of each 28-d dietary period after a minimum of a 12-h overnight fast. We used a standard protocol to process and store samples at -80°C until analysis. Homeostasis model assessment for insulin resistance (HOMA-IR), which was used as a measure of insulin resistance for our post-hoc analysis, was calculated by dividing the product of fasting insulin and fasting glucose by a normalizing factor. Lipidomics Sample Preparation and Mass Spectrometry Frozen plasma samples were thawed at room temperature (25 °C) for 30 min, vortexed, and 25 µL plasma was transferred to a borosilicate glass culture tube (16 x 100 mm). Next, 0.475 mL water, 1.45 mL 1:0.45 methanol:dichloromethane, and 25 µL isotope-labeled internal standards mixture were added to the tube. The Lipidyzer isotope labeled internal standards mixture consisted of 54 isotopes from 13 lipid classes (Sciex, Framingham, MA). The mixture was vortexed for 5 sec and incubated at room temperature for 30 min. Next, another 0.5 mL water and 0.45 mL dichloromethane were added to the tube, followed by gentle vortexing for 5 sec, and centrifugation at 2500 g at 15 °C for 10 min. The bottom organic layer was transferred to a new tube and 0.9 mL of dichloromethane was added to the original tube for a second extraction. The combined extracts were concentrated under nitrogen and reconstituted in 0.25 mL of the mobile phase (10 mM ammonium acetate in 50:50 methanol:dichloromethane). Quantitative lipidomics was performed with the Sciex Lipidyzer platform consisting of Shimadzu Nexera X2 LC-30AD pumps, a Shimadzu Nexera X2 SIL-30AC autosampler, and a Sciex QTRAP® 5500 mass spectrometer equipped with SelexION® for differential mobility spectrometry (DMS). 1-propanol was used as the chemical modifier for the DMS. Samples were introduced to the mass spectrometer by flow injection at 8 µL/min. Each sample was injected twice, once with the DMS on [phosphatidylcholines (PC); phosphatidylethanolamines (PE); lysophosphatidylcholines (LPC); lysophosphatidylethanolamines (LPE); sphingomyelins (SM)], and once with the DMS off ([cholesterol esters (CE); ceramides (CER); diacylglycerols (DAG); dihydroceramides (DCER)/ free fatty acids(FFA); hexosylceramides (HCER); lactosylceramides (LCER); triacylglycerols (TAG)]. The lipid molecular species were measured using multiple reaction monitoring and positive/negative polarity switching. Positive ion mode detected lipid classes SM, DAG, CE, CER, DCER, HCER, DCER, and TAG, and negative ion mode detected lipid classes LPE, LPC, PC, PE, and FFA. A total of 1070 lipids and fatty acids were targeted in the analysis. Data was acquired and processed using Analyst 1.6.3 and Lipidomics Workflow Manager 1.0.5.0. |
| Sample Type: | Blood (plasma) |
