Summary of Study ST001151

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR000770. The data can be accessed directly via it's Project DOI: 10.21228/M8509V This work is supported by NIH grant, U2C- DK119886.


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Study IDST001151
Study Title4-day dietary effect of fast food vs Mediterranean diet to HDL lipidome
Study TypeDietary intervention study
Study SummaryIn this randomized order cross-over study, ten healthy subjects consumed a Mediterranean (Med) and a fast food (FF) diet for 4 days, with a 4-day wash-out between treatments. Lipidomic composition was analyzed in isolated HDL fractions by an untargeted LC-MS method with 15 internal standards. HDL PE content was increased by FF diet, and 41 out of 170 lipid species were differentially affected by diet. Saturated fatty acids (FA) and odd chain FA were enriched after FF diet, while very-long chain FA and unsaturated FA were enriched after Med diet. The composition of PC, TG and CE were significantly altered to reflect the FA composition of the diet whereas the composition of SM and ceramides were generally unaffected, indicating that glycerolipids may be sensitive markers of dietary intake, whereas sphingolipids are more indicative of non-dietary factors. Results from this study indicate that the HDL lipidome is widely remodeled within 4 days of diet change and that certain lipid classes are more sensitive markers of diet whereas other lipid classes are better indicators of non-dietary factors
University of California, Davis
Last NameZivkovic
First NameAngela
Address3402 Meyer hall, Davis, CA, 95616, USA
Submit Date2019-03-14
Num Groups4
Total Subjects10
Num Males5
Num Females5
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2019-09-23
Release Version1
Angela Zivkovic Angela Zivkovic application/zip

Select appropriate tab below to view additional metadata details:


Project ID:PR000770
Project DOI:doi: 10.21228/M8509V
Project Title:Fast Food Project
Project Type:Dietary intervention study
Project Summary:A human study looks at 4-day effect of fast food vs Mediterranean to HDL composition and function, host metabolome and gut microbiome
Institute:University of California, Davis
Department:Department of nutrition
Last Name:Zivkovic
First Name:Angela
Address:3402 Meyer hall, Davis, CA, 95616, USA


Subject ID:SU001216
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:19 - 26 yr
Weight Or Weight Range:50.6 - 94.1 kg
Height Or Height Range:1.6 - 1.85 m
Gender:Male and female
Human Smoking Status:Non-smoker
Human Exclusion Criteria:Subjects with anemia, diabetes, thyroid disease, MetS, cancer, previous cardiovascular events or other disease diagnoses were excluded. Subjects were also excluded if they had extreme dietary or exercise patterns, or were taking prescription medications or other supplements known to alter lipoprotein metabolism such as isoflavones.


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

mb_sample_id local_sample_id Treatment Timepoint
SA079872FFS111BFF Post
SA079873FFS114DFF Post
SA079874FFS113DFF Post
SA079875FFS116DFF Post
SA079876FFS109DFF Post
SA079877FFS108BFF Post
SA079878FFS118DFF Post
SA079879FFS112BFF Post
SA079880FFS110DFF Post
SA079881FFS107BFF Post
SA079882FFS107AFF Pre
SA079883FFS116CFF Pre
SA079884FFS118CFF Pre
SA079885FFS114CFF Pre
SA079886FFS113CFF Pre
SA079887FFS112AFF Pre
SA079888FFS109CFF Pre
SA079889FFS108AFF Pre
SA079890FFS111AFF Pre
SA079891FFS110CFF Pre
SA079892FFS116BMed Post
SA079893FFS109BMed Post
SA079894FFS118BMed Post
SA079895FFS114BMed Post
SA079896FFS113BMed Post
SA079897FFS111DMed Post
SA079898FFS108DMed Post
SA079899FFS110BMed Post
SA079900FFS107DMed Post
SA079901FFS112DMed Post
SA079902FFS107CMed Pre
SA079903FFS118AMed Pre
SA079904FFS108CMed Pre
SA079905FFS114AMed Pre
SA079906FFS112CMed Pre
SA079907FFS111CMed Pre
SA079908FFS113AMed Pre
SA079909FFS110AMed Pre
SA079910FFS109AMed Pre
SA079911FFS116AMed Pre
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Collection ID:CO001210
Collection Summary:HDL fractions were isolated from plasma using a 2-step sequential density-based ultracentrifugation method
Sample Type:Blood (plasma)
Storage Conditions:-80℃


Treatment ID:TR001231
Treatment Summary:Each subject was given either a fast food or a Mediterranean for 4 days in randomized order.

Sample Preparation:

Sampleprep ID:SP001224
Sampleprep Summary:Lipids were extracted using methanol-MTBE method.
Sampleprep Protocol Filename:zivkovic_protocol.pdf

Combined analysis:

Analysis ID AN001899
Analysis type MS
Chromatography type Reversed phase
Chromatography system Waters Acquity
Column Waters Acquity CSH C18 (100 x 2.1mm, 1.7um)
MS instrument type QTOF
MS instrument name Agilent 6550 QTOF
Units ug/ml


Chromatography ID:CH001375
Methods Filename:zivkovic_protocol.pdf
Instrument Name:Waters Acquity
Column Name:Waters Acquity CSH C18 (100 x 2.1mm, 1.7um)
Column Temperature:65°C
Flow Gradient:0 min 15% (B), 0–2 min 30% (B), 2–2.5 min 48% (B), 2.5–11 min 82% (B), 11–11.5 min 99% (B), 11.5–12 min 99% (B), 12–12.1 min 15% (B), 12.1–15 min 15% (B)
Flow Rate:0.6 mL/min
Injection Temperature:4°C
Solvent A:60:40 acetonitrile:water + 10 mM ammonium formiate + 0.1% formic acid
Solvent B:90:10 v/v isopropanol:acetonitrile + 10 mM ammonium formiate + 0.1% formic acid
Chromatography Type:Reversed phase


MS ID:MS001755
Analysis ID:AN001899
Instrument Name:Agilent 6550 QTOF
Instrument Type:QTOF
MS Comments:Data are analyzed in a four-stage process. First, raw data are processed in an untargeted (qualitative) manner by Agilent’s software MassHunter Qual to find peaks in up to 300 chromatograms. Peak features are then imported into MassProfilerProfessional for peak alignments to seek which peaks are present in multiple chromatograms, using exclusion criteria by the minimum percentage of chromatograms in which these peaks are positively detected. We usually use 30% as minimum criterion. In a tedious manual process, these peaks are then collated and constrained into a MassHunter quantification method on the accurate mass precursor ion level, using the MS/MS information and the LipidBlast library to identify lipids with manual confirmation of adduct ions and spectral scoring accuracy. MassHunter enables back-filling of quantifications for peaks that were missed in the primary peak finding process, hence yielding data sets without missing values.