Summary of Study ST001964

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 PR001095. The data can be accessed directly via it's Project DOI: 10.21228/M85976 This work is supported by NIH grant, U2C- DK119886.

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Study IDST001964
Study TitleQuantitative genome-scale analysis of human liver reveals dysregulation of glycosphingolipid pathways in progressive nonalcoholic fatty liver disease
Study SummaryNonalcoholic fatty liver disease (NAFLD) is a well-defined chronic liver diseases closely related with metabolic disorders. The prevalence of NAFLD is rapidly increasing worldwide, while the pathology and the underlying mechanisms driving NAFLD are not fully understood. In NAFLD, a series of metabolic changes takes place in the liver. However, the alteration of the metabolic pathways in the human liver along the progression of NAFLD, i.e., the transition from nonalcoholic steatosis (NAFL) to steatohepatitis (NASH) through cirrhosis remains to be discovered. Here, we sought to examine the metabolic pathways of the human liver across the full histological spectrum of NAFLD. We analyzed the whole liver tissue transcriptomic (RNA-Seq) and serum metabolomics data obtained from a large, prospectively enrolled cohort of histologically characterized patients derived from the European NAFLD Registry (n=206), and developed genome-scale metabolic models (GEMs) of human hepatocytes at different stages of NAFLD. The integrative approach employed in this study has enabled us to understand the regulation of the metabolic pathways of human liver in NAFL, and with progressive NASH-associated fibrosis (F0–F4). Our study identified several metabolic signatures in the liver and blood of these patients, specifically highlighting the alteration of vitamins (A, E) and glycosphingolipids (GSLs), and their link with complex glycosaminoglycans (GAGs) in advanced fibrosis. The study provides insights into the underlying pathways of the progressive fibrosing steatohepatitis. Furthermore, by applying genome-scale metabolic modeling (GSMM), we were able to identify the metabolic differences among carriers of widely validated genetic variants associated with NAFLD / NASH disease severity in three genes (PNPLA3, TM6SF2 and HSD17B13).
Institute
University of Turku
Last NameSen
First NamePartho
AddressSystems Medicine group, Turku Bioscience, University of Turku (UTU), Tykistökatu 6B, P.O. Box 123 FIN-20521 Turku, Finland
Emailpartho.sen@utu.fi
PhonePhone: +358 469608145
Submit Date2021-02-18
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailGC-MS
Release Date2022-01-03
Release Version1
Partho Sen Partho Sen
https://dx.doi.org/10.21228/M85976
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001095
Project DOI:doi: 10.21228/M85976
Project Title:Metabolomic signatures of NAFLD
Project Summary:Background and Aims: Nonalcoholic fatty liver disease (NAFLD) is a progressive liver disease that is strongly associated with type 2 diabetes. Accurate, non-invasive diagnostic tests to delineate the different stages: degree of steatosis, grade of nonalcoholic steatohepatitis (NASH) and stage fibrosis represent an unmet medical need. In our previous studies, we successfully identified specific serum molecular lipid signatures which associate with the amount of liver fat as well as with NASH. Here we report underlying associations between clinical data, lipidomic profiles, metabolic profiles and clinical outcomes, including downstream identification of potential biomarkers for various stages of the disease. Method: We leverage several statistical and machine-learning approaches to analyse clinical, lipidomic and metabolomic profiles of individuals from the European Horizon 2020 project: Elucidating Pathways of Steatohepatitis (EPoS). We interrogate data on patients representing the full spectrum of NAFLD/NASH derived from the EPoS European NAFLD Registry (n = 627). We condense the EPoS lipidomic data into lipid clusters and subsequently apply non-rejection-rate-pruned partial correlation network techniques to facilitate network analysis between the datasets of lipidomic, metabolomic and clinical data. For biomarker identification, a random forest ensemble classification approach was used to both search for valid disease biomarkers and to compare classification performance of lipids, metabolites and clinical factors in combination. Results: We found that steatosis and fibrosis grades were strongly associated with (1) an increase of triglycerides with low carbon number and double bond count as well as (2) a decrease of specific phospholipids, including lysophosphatidylcholines. In addition to the network topology as a result itself, we also present lipid clusters (LCs) of interest to the derived network of proposed interactions in our NAFLD data from the EPoS cohort, along with preliminary metabolite and lipid biomarkers to classify NAFLD fibrosis. Conclusions: Our findings suggest that dysregulation of lipid metabolism in progressive stages of NAFLD is reflected in circulation and may thus hold diagnostic value as well as offer new insights about NAFLD pathogenesis. Using this cohort as a proof-of-concept, we demonstrate current progress in tuning the accuracy random forest approaches with a view to predicting various subtypes of NAFLD patient using a minimal set of lipidomic and metabolic markers. For the first time, a detailed network-based picture emerges between lipids, polar metabolites and clinical variables. Lipidomic / metabolomic markers may provide an alternative method of NAFLD patient classification and risk stratification to guide therapy.
Institute:Örebro University
Last Name:McGlinchey
First Name:Aidan
Address:School of Medical Sciences, Örebro, Örebro, 70281, Sweden
Email:aidan.mcglinchey@oru.se
Phone:+46736485638

Subject:

Subject ID:SU002044
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Male and female

Factors:

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

mb_sample_id local_sample_id NAFLD.Status
SA1848351022385877NAFL
SA1848361022386427NAFL
SA1848371022386463NAFL
SA1848381022385860NAFL
SA1848391022386190NAFL
SA1848401022386958NAFL
SA1848411022386202NAFL
SA1848421022385788NAFL
SA1848431022385839NAFL
SA1848441022385926NASH_F0/1
SA1848451022386429NASH_F0/1
SA1848461022386914NASH_F0/1
SA1848471022386933NASH_F2
SA1848481022386978NASH_F2
SA1848491022386912NASH_F2
SA1848501022386446NASH_F2
SA1848511022386907NASH_F2
SA1848521022386453NASH_F2
SA1848531022386485NASH_F2
SA1848541022386214NASH_F2
SA1848551022385934NASH_F2
SA1848561022385844NASH_F2
SA1848571022385893NASH_F2
SA1848581022386136NASH_F2
SA1848591022384032NASH_F2
SA1848601022386192NASH_F2
SA1848611022386960NASH_F3
SA1848621022386981NASH_F3
SA1848631022385756NASH_F3
SA1848641022385774NASH_F3
SA1848651022385911NASH_F3
SA1848661022386508NASH_F3
SA1848671022385928NASH_F3
SA1848681022386159NASH_F3
SA1848691022386364NASH_F3
SA1848701022386899NASH_F3
SA1848711022385916NASH_F3
SA1848721022385855NASH_F4 / cirrhosis
SA1848731022387276NASH_F4 / cirrhosis
SA1848741022387147NASH_F4 / cirrhosis
SA1848751022386957NASH_F4 / cirrhosis
Showing results 1 to 41 of 41

Collection:

Collection ID:CO002037
Collection Summary:Serum samples were randomized and sample preparation was carried out as described previously (Castilloet al. 2011). In summary, 400 µL of MeOH containing ISTDs (heptadecanoic acid, deuterium-labeled DL-valine, deuterium-labeled succinic acid, and deuterium-labeled glutamic acid, c = 1 µg/mL) was added to 30 µl of the serum samples which were vortex mixed and incubated on ice for 30 min after which they were centrifuged (9400 × g, 3 min) and 350 µL of the supernatant was collected after centrifugation. The solvent was evaporated to dryness and 25 µL of MOX reagent was added and the sample was incubated for 60 min at 45 °C. 25 µL of MSTFA was added and after 60 min incubation at 45 °C 25 µL of the retention index standard mixture (n-alkanes, c=10 µg/mL) was added. The analyses were carried out on an Agilent 7890B GC coupled to 7200 QTOF MS. Injection volume was 1 µL with 100:1 cold solvent split on PTV at 70 °C, heating to 300 °C at 120 °C/minute. Column: Zebron ZB-SemiVolatiles. Length: 20m, I.D. 0.18mm, film thickness: 0.18 µm. With initial Helium flow 1.2 mL/min, increasing to 2.4 mL/min after 16 mins. Oven temperature program: 50 °C (5 min), then to 270°C at 20 °C/min and then to 300 °C at 40 °C/min (5 min). EI source: 250 °C, 70 eV electron energy, 35µA emission, solvent delay 3 min. Mass range 55 to 650 amu, acquisition rate 5 spectra/s, acquisition time 200 ms/spectrum. Quad at 150 °C, 1.5 mL/min N2 collision flow, aux-2 temperature: 280 °C. Calibration curves were constructed using alanine, citric acid, fumaric acid, glutamic acid, glycine, lactic acid, malic acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, linoleic acid, oleic acid, palmitic acid, stearic acid, cholesterol, fructose, glutamine, indole-3-propionic acid, isoleucine, leucine, proline, succinic acid, valine, asparagine, aspartic acid, arachidonic acid, glycerol-3-phosphate, lysine, methionine, ornithine, phenylalanine, serine and threonine purchased from Sigma-Aldrich (St. Louis, MO, USA) at concentration range of 0.1 to 80 µg/mL. An aliquot of each sample was collected and pooled and used as quality control samples, together with a NIST SRM 1950 serum sample and an in-house pooled serum sample. Relative standard deviations (% RSDs) of the metabolite concentrations in control serum samples showed % RSDs within accepted analytical limits at averages of 27.2% and 29.2% for in-house QC abd pooled QC samples.
Sample Type:Blood (serum)

Treatment:

Treatment ID:TR002056
Treatment Summary:No treatment applied.

Sample Preparation:

Sampleprep ID:SP002050
Sampleprep Summary:Serum samples were randomized and sample preparation was carried out as described previously (Castilloet al. 2011). In summary, 400 µL of MeOH containing ISTDs (heptadecanoic acid, deuterium-labeled DL-valine, deuterium-labeled succinic acid, and deuterium-labeled glutamic acid, c = 1 µg/mL) was added to 30 µl of the serum samples which were vortex mixed and incubated on ice for 30 min after which they were centrifuged (9400 × g, 3 min) and 350 µL of the supernatant was collected after centrifugation. The solvent was evaporated to dryness and 25 µL of MOX reagent was added and the sample was incubated for 60 min at 45 °C. 25 µL of MSTFA was added and after 60 min incubation at 45 °C 25 µL of the retention index standard mixture (n-alkanes, c=10 µg/mL) was added. The analyses were carried out on an Agilent 7890B GC coupled to 7200 QTOF MS. Injection volume was 1 µL with 100:1 cold solvent split on PTV at 70 °C, heating to 300 °C at 120 °C/minute. Column: Zebron ZB-SemiVolatiles. Length: 20m, I.D. 0.18mm, film thickness: 0.18 µm. With initial Helium flow 1.2 mL/min, increasing to 2.4 mL/min after 16 mins. Oven temperature program: 50 °C (5 min), then to 270°C at 20 °C/min and then to 300 °C at 40 °C/min (5 min). EI source: 250 °C, 70 eV electron energy, 35µA emission, solvent delay 3 min. Mass range 55 to 650 amu, acquisition rate 5 spectra/s, acquisition time 200 ms/spectrum. Quad at 150 °C, 1.5 mL/min N2 collision flow, aux-2 temperature: 280 °C. Calibration curves were constructed using alanine, citric acid, fumaric acid, glutamic acid, glycine, lactic acid, malic acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, linoleic acid, oleic acid, palmitic acid, stearic acid, cholesterol, fructose, glutamine, indole-3-propionic acid, isoleucine, leucine, proline, succinic acid, valine, asparagine, aspartic acid, arachidonic acid, glycerol-3-phosphate, lysine, methionine, ornithine, phenylalanine, serine and threonine purchased from Sigma-Aldrich (St. Louis, MO, USA) at concentration range of 0.1 to 80 µg/mL. An aliquot of each sample was collected and pooled and used as quality control samples, together with a NIST SRM 1950 serum sample and an in-house pooled serum sample. Relative standard deviations (% RSDs) of the metabolite concentrations in control serum samples showed % RSDs within accepted analytical limits at averages of 27.2% and 29.2% for in-house QC abd pooled QC samples.
Processing Storage Conditions:-20?
Extract Storage:-80?

Combined analysis:

Analysis ID AN003202
Analysis type MS
Chromatography type GC
Chromatography system Agilent 7890B
Column Zebron ZB-SemiVolatiles (20m x 0.18mm,0.18m)
MS Type EI
MS instrument type GC x GC-TOF
MS instrument name Agilent 7200 QTOF
Ion Mode UNSPECIFIED
Units log2 autoscaled abundance

Chromatography:

Chromatography ID:CH002367
Chromatography Comments:Zebron ZB-SemiVolatiles (20m, I.D. 0.18mm, film thickness 0.18µm)
Instrument Name:Agilent 7890B
Column Name:Zebron ZB-SemiVolatiles (20m x 0.18mm,0.18m)
Chromatography Type:GC

MS:

MS ID:MS002980
Analysis ID:AN003202
Instrument Name:Agilent 7200 QTOF
Instrument Type:GC x GC-TOF
MS Type:EI
MS Comments:In summary, 400 µL of MeOH containing ISTDs (heptadecanoic acid, deuterium-labeled DL-valine, deuterium-labeled succinic acid, and deuterium-labeled glutamic acid, c = 1 µg/mL) was added to 30 µl of the serum samples which were vortex mixed and incubated on ice for 30 min after which they were centrifuged (9400 × g, 3 min) and 350 µL of the supernatant was collected after centrifugation. The solvent was evaporated to dryness and 25 µL of MOX reagent was added and the sample was incubated for 60 min at 45 °C. 25 µL of MSTFA was added and after 60 min incubation at 45 °C 25 µL of the retention index standard mixture (n-alkanes, c=10 µg/mL) was added. The analyses were carried out on an Agilent 7890B GC coupled to 7200 QTOF MS. Injection volume was 1 µL with 100:1 cold solvent split on PTV at 70 °C, heating to 300 °C at 120 °C/minute. Column: Zebron ZB-SemiVolatiles. Length: 20m, I.D. 0.18mm, film thickness: 0.18 µm. With initial Helium flow 1.2 mL/min, increasing to 2.4 mL/min after 16 mins. Oven temperature program: 50 °C (5 min), then to 270°C at 20 °C/min and then to 300 °C at 40 °C/min (5 min). EI source: 250 °C, 70 eV electron energy, 35µA emission, solvent delay 3 min. Mass range 55 to 650 amu, acquisition rate 5 spectra/s, acquisition time 200 ms/spectrum. Quad at 150 °C, 1.5 mL/min N2 collision flow, aux-2 temperature: 280 °C. Calibration curves were constructed using alanine, citric acid, fumaric acid, glutamic acid, glycine, lactic acid, malic acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, linoleic acid, oleic acid, palmitic acid, stearic acid, cholesterol, fructose, glutamine, indole-3-propionic acid, isoleucine, leucine, proline, succinic acid, valine, asparagine, aspartic acid, arachidonic acid, glycerol-3-phosphate, lysine, methionine, ornithine, phenylalanine, serine and threonine purchased from Sigma-Aldrich (St. Louis, MO, USA) at concentration range of 0.1 to 80 µg/mL. An aliquot of each sample was collected and pooled and used as quality control samples, together with a NIST SRM 1950 serum sample and an in-house pooled serum sample. Relative standard deviations (% RSDs) of the metabolite concentrations in control serum samples showed % RSDs within accepted analytical limits at averages of 27.2% and 29.2% for in-house QC abd pooled QC samples. Data values for final analysis were log2-transformed and scaled to zero mean and unit variance.
Ion Mode:UNSPECIFIED
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