Summary of Study ST001845

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 PR000667. The data can be accessed directly via it's Project DOI: 10.21228/M8FX07 This work is supported by NIH grant, U2C- DK119886.

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Study IDST001845
Study TitleIdentification of unique metabolite networks between Latino and Caucasian patients with nonalcoholic fatty liver disease (NAFLD) (part V)
Study SummaryNonalcoholic fatty liver disease (NAFLD) is a spectrum of liver pathology ranging from simple steatosis to nonalcoholic steatohepatitis (NASH); the latter is characterized by inflammation and fibrosis. Risk factors for NALFD include obesity, diabetes, hyperlipidemia, and hypertension—all of which are features of metabolic syndrome. NAFLD is a very heterogeneous disease, as it presents in different patterns in males and females and in patients from different ethnicities, with unclear predictors for development and severity of disease. Previous studies have shown that NAFLD is 1.4 times more frequent in Hispanics than in Caucasians. One of the major challenges in NAFLD is the lack of accurate, noninvasive biomarkers for the detection of the most aggressive presentation, NASH. The gold standard for the diagnosis is liver biopsy, which is an invasive procedure associated with possible complications. Noninvasive diagnosis of NASH is a major unmet medical need and there are no ethnicity-specific biomarkers that can diagnose this condition and predict its progression. Therefore, the main gap in knowledge that this proposal and line of research will address is the characterizing the different plasma and liver metabolomics profile of patients with fatty liver from two ethnicities (Latinos vs. Caucasians) and of both sexes. The overall hypothesis of the present study is that the higher incidence of nonalcoholic fatty liver (NAFL) in Latino patients is reflected in a different plasma and liver metabolomics profile compared to Caucasian patients with further sex-related differences. Characterization of metabolite networks can aid in identifying the mechanistic underpinnings of sex and ethnic driven differences in NAFL which could help diagnose and establish a prognosis of this condition, especially in the critical transition from NAFL to the more aggressive nonalcoholic steatohepatitis (NASH).To address this hypothesis, plasma metabolomics profile of samples from male and female Latino and Caucasian bariatric surgery patients with NAFL and from healthy subjects will be compared. Metabolomics findings will be related with liver pathology and liver transcriptome profiles from intraoperatively obtained liver biopsies using correlation, network, and pathway analysis.
Institute
University of California, Davis
DepartmentDepartment of Internal Medicine, Division of Gastroenterology and Hepatology
LaboratoryMedici Lab
Last NameMedici
First NameValentina
Address4150 V Street - PSSB Suite 3500 - 95817 Sacramento CA
Emailvmedici@ucdavis.edu
Phone(916) 734 3751
Submit Date2021-06-21
Raw Data AvailableYes
Raw Data File Type(s)wiff
Analysis Type DetailGC-MS
Release Date2021-07-05
Release Version1
Valentina Medici Valentina Medici
https://dx.doi.org/10.21228/M8FX07
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Sample Preparation:

Sampleprep ID:SP001928
Sampleprep Summary:1 Thaw plasma samples on ice 2 Vortex plasma sample and pipette 50µl in polypropylene Eppendorf tube/Plate 3 Add Surrogate Standards of the 3 lipid classes (as needed) and other reagents as in the following table: Plasma Sample 10x Oxylipid Surrogate STDs CUDA + PHAU Anti-oxidant ACN/MeOH SUM 4 Vortex for 30sec 5 Centrifuge at 6°C for 5 min at 15,000 g (or 1,800 g for plates) 6 Take the supernatant (~240µl) into new Eppendorf tube/filter plate 7 Spin Filter (0.1 um) or plate filter (0.2um) for 5 min @ 12,000 g (1,800g for plate) 8 place aliquotes of samples into vials, or plate, and cap vials or seal plates 9 Store in -20°C until analysis
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