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
Email	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

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR001007
Project DOI:	doi: 10.21228/M8J106
Project Title:	Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled cross over feeding study
Project 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
Email:	sdibaymo@fredhutch.org
Phone:	206-667-4068

Subject:

Subject ID:	SU001564
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Age Or Age Range:	18-45
Gender:	Male and female
Human Nutrition:	Low glycemic load and high glycemic load diet
Human Inclusion Criteria:	We recruited non-smoking, healthy individuals between the ages of 18-45 years from the Greater Seattle area.
Human Exclusion Criteria:	Exclusion criteria consisted of impaired fasting glucose (fasting blood glucose ≥5.6 mmol/L), any physician-diagnosed condition requiring a restricted diet, food allergies, regular use of hormones or anti-inflammatory medication, current pregnancy or lactation or plans to become pregnant, or heavy use of alcohol (>2 drinks/d)

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id	local_sample_id	Treatment
SA125448	13200563	Baseline
SA125449	13200662	Baseline
SA125450	13200944	Baseline
SA125451	13200399	Baseline
SA125452	13200696	Baseline
SA125453	13200597	Baseline
SA125454	13200712	Baseline
SA125455	13200688	Baseline
SA125456	13200449	Baseline
SA125457	13200647	Baseline
SA125458	13200787	Baseline
SA125459	13200720	Baseline
SA125460	13200613	Baseline
SA125461	13200803	Baseline
SA125462	13200746	Baseline
SA125463	13200035	Baseline
SA125464	13200761	Baseline
SA125465	13200738	Baseline
SA125466	13200811	Baseline
SA125467	13200357	Baseline
SA125468	13200852	Baseline
SA125469	13200753	Baseline
SA125470	13200837	Baseline
SA125471	13200795	Baseline
SA125472	13200621	Baseline
SA125473	13200456	Baseline
SA125474	13200589	Baseline
SA125475	13200829	Baseline
SA125476	13200571	Baseline
SA125477	13200522	Baseline
SA125478	13200282	Baseline
SA125479	13200498	Baseline
SA125480	13200365	Baseline
SA125481	13200241	Baseline
SA125482	13200480	Baseline
SA125483	13200373	Baseline
SA125484	13200530	Baseline
SA125485	13200266	Baseline
SA125486	13200126	Baseline
SA125487	13200134	Baseline
SA125488	13200233	Baseline
SA125489	13200118	Baseline
SA125490	13200472	Baseline
SA125491	13200308	Baseline
SA125492	13200290	Baseline
SA125493	13200431	Baseline
SA125494	13200407	Baseline
SA125495	13200324	Baseline
SA125496	13200639	Baseline
SA125497	13200894	Baseline
SA125498	13200514	Baseline
SA125499	13200381	Baseline
SA125500	13200258	Baseline
SA125501	13200340	Baseline
SA125502	13200274	Baseline
SA125503	13200555	Baseline
SA125504	13200332	Baseline
SA125505	13200217	Baseline
SA125506	13200605	Baseline
SA125507	13200670	Baseline
SA125508	13200928	Baseline
SA125509	13200969	Baseline
SA125510	13200704	Baseline
SA125511	13200076	Baseline
SA125512	13200019	Baseline
SA125513	13200027	Baseline
SA125514	13200910	Baseline
SA125515	13200084	Baseline
SA125516	13200936	Baseline
SA125517	13200845	Baseline
SA125518	13200043	Baseline
SA125519	13200951	Baseline
SA125520	13200068	Baseline
SA125521	13200886	Baseline
SA125522	13200548	Baseline
SA125523	13200902	Baseline
SA125524	13200464	Baseline
SA125525	13200050	Baseline
SA125526	13200977	Baseline
SA125527	13200423	Baseline
SA125528	13206172	HGL
SA125529	13202593	HGL
SA125530	13206230	HGL
SA125531	13206735	HGL
SA125532	13206628	HGL
SA125533	13202643	HGL
SA125534	13206362	HGL
SA125535	13202544	HGL
SA125536	13202346	HGL
SA125537	13206107	HGL
SA125538	13206412	HGL
SA125539	13206347	HGL
SA125540	13202221	HGL
SA125541	13202957	HGL
SA125542	13202775	HGL
SA125543	13206339	HGL
SA125544	13206909	HGL
SA125545	13206370	HGL
SA125546	13206727	HGL
SA125547	13206867	HGL

Showing page 1 of 3 Results: 1 2 3 Next Showing results 1 to 100 of 240

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)

Treatment:

Treatment ID:	TR001579
Treatment Summary:	A 7-day rotating menu was created for each diet. At baseline, participants completed a 3-d food record to estimate mean daily calorie intake. Energy intake from the food records along with weight, height, sex and activity level were used to estimate each participant’s daily energy needs necessary to maintain the current weight. The estimated calorie intake was used to adjust the 7-day rotating menu to meet each participant’s needs so that they would remain weight stable during the study. The percentage energy from macronutrients of the two diets were identical: 15% energy from protein, 30% energy from fat, and 55% energy from carbohydrate. The LGL diet provided on average 55 g/d of fiber and 77 g/d of fructose, with a GL of 125 (Table 1). The HGL diet substituted refined grains for whole grains, included other carbohydrates from high-glycemic index food sources and provided on average 28 g/d of fiber and 26 g/d of fructose, with a GL of 250. All food was prepared and provided by the Fred Hutch Human Nutrition Laboratory (HNL) during the intervention. Weekday dinners were consumed under supervision at the HNL, and the next day’s breakfast, lunch and snacks were portioned, packaged and taken home for consumption. Examples of study menus and detail on diet consumption have been published previously (Neuhouser et al. 2012).

Treatment ID:

TR001579

Treatment Summary:

A 7-day rotating menu was created for each diet. At baseline, participants completed a 3-d food record to estimate mean daily calorie intake. Energy intake from the food records along with weight, height, sex and activity level were used to estimate each participant’s daily energy needs necessary to maintain the current weight. The estimated calorie intake was used to adjust the 7-day rotating menu to meet each participant’s needs so that they would remain weight stable during the study. The percentage energy from macronutrients of the two diets were identical: 15% energy from protein, 30% energy from fat, and 55% energy from carbohydrate. The LGL diet provided on average 55 g/d of fiber and 77 g/d of fructose, with a GL of 125 (Table 1). The HGL diet substituted refined grains for whole grains, included other carbohydrates from high-glycemic index food sources and provided on average 28 g/d of fiber and 26 g/d of fructose, with a GL of 250. All food was prepared and provided by the Fred Hutch Human Nutrition Laboratory (HNL) during the intervention. Weekday dinners were consumed under supervision at the HNL, and the next day’s breakfast, lunch and snacks were portioned, packaged and taken home for consumption. Examples of study menus and detail on diet consumption have been published previously (Neuhouser et al. 2012).

Sample Preparation:

Sampleprep ID:	SP001572
Sampleprep Summary:	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.

Sampleprep ID:

SP001572

Sampleprep Summary:

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.

Combined analysis:

Analysis ID	AN002468	AN002469
Analysis type	MS	MS
Chromatography type	None (Direct infusion)	None (Direct infusion)
Chromatography system	Triple quadrupole	Triple quadrupole
Column	ESI	ESI
MS Type	ESI	ESI
MS instrument type	Triple quadrupole	Triple quadrupole
MS instrument name	ABI Sciex 5500 QTrap	ABI Sciex 5500 QTrap
Ion Mode	UNSPECIFIED	UNSPECIFIED
Units	mM	mM

Chromatography:

Chromatography ID:	CH001809
Chromatography Summary:	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 analysis at 8 uL/min aka direct infusion. Each sample was injected twice, once with the DMS on Method 1 (PC/PE/LPC/LPE/SM), and once with the DMS off Method 2 (CE/CER/DAG/DCER/FFA/HCER/LCER/TAG). The lipid molecular species were measured using multiple reaction monitoring (MRM) and positive/negative polarity switching. Positive ion mode detected lipid classes SM/DAG/CE/CER/DCER/HCER/LCER/TAG and negative ion mode detected lipid classes LPE/LPC/PC/PE/FFA. A total of 1070 lipids and fatty acids were targeted in the analysis.
Instrument Name:	Triple quadrupole
Column Name:	ESI
Chromatography Type:	None (Direct infusion)

MS:

MS ID:	MS002288
Analysis ID:	AN002468
Instrument Name:	ABI Sciex 5500 QTrap
Instrument Type:	Triple quadrupole
MS Type:	ESI
MS Comments:	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 analysis at 8 uL/min aka direct infusion. Each sample was injected twice, once with the DMS on Method 1 (PC/PE/LPC/LPE/SM)
Ion Mode:	UNSPECIFIED

MS ID:	MS002289
Analysis ID:	AN002469
Instrument Name:	ABI Sciex 5500 QTrap
Instrument Type:	Triple quadrupole
MS Type:	ESI
MS Comments:	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 analysis at 8 uL/min aka direct infusion. Each sample was injected twice once with the DMS off Method 2 (CE/CER/DAG/DCER/FFA/HCER/LCER/TAG)
Ion Mode:	UNSPECIFIED