Summary of study ST001690

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 PR001086. The data can be accessed directly via it's Project DOI: 10.21228/M8B123 This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Perform statistical analysis  |  Show all samples  |  Show named metabolites  |  Download named metabolite data  |  Download all metabolite data  |  Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data (Contains raw data)
Study IDST001690
Study TitleUntargeted metabolomic analysis of human blood samples via qualitative GC-MS for T1D biomarker identification
Study TypeQualitative GC-MS biomarker identification
Study Summary"Blood from human subjects at high risk for T1D (and healthy controls; n=4 each) were subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to the controls. The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of immune cells, particularly, CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. Parallel multi-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and helped identify an associated integrated biomarker signature, which could ultimately facilitate the classification of T1D progressors from non-progressors."
Institute
Duke University
DepartmentDuke Molecular Physiology Institute, School of Medicine
LaboratoryMetabolomics
Last NameBain
First NameJames
Address300 N Duke St, Durham, NC, 27701, USA
Emailjames.bain@duke.edu
Phone919 479 2320
Submit Date2021-02-09
Total Subjects9
Raw Data AvailableYes
Analysis Type DetailGC-MS
Release Date2021-06-10
Release Version1
James Bain James Bain
https://dx.doi.org/10.21228/M8B123
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Factors:

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

mb_sample_id local_sample_id Condition
SA156644RT-
SA1566459Healthy control
SA1566467Healthy control
SA1566476Healthy control
SA1566482Healthy control
SA1566491High-risk T1D
SA1566505High-risk T1D
SA1566518High-risk T1D
SA1566524New-onset (fasting)
SA1566533New-onset (post-prandial)
SA156654Ghost (blank)Process blank
Showing results 1 to 11 of 11
  logo