Summary of study ST001690

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


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.

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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."
Duke University
DepartmentDuke Molecular Physiology Institute, School of Medicine
Last NameBain
First NameJames
Address300 N Duke St, Durham, NC, 27701, USA
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 application/zip

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Project ID:PR001086
Project DOI:doi: 10.21228/M8B123
Project Title:Parallel multi-omics in high-risk subjects for the identification of integrated biomarker signatures of type 1 diabetes
Project Type:Untargeted metabolomics: MS qualitative analysis
Project Summary:MS qualitative analysis of human blood samples to identify early-identification biomarkers for type 1 diabetes
Institute:Duke University
Department:Duke Molecular Physiology Institute, School of Medicine
Last Name:Bain
First Name:James
Address:300 N Duke Street, Durham, NC, 27701, USA
Phone:919 479 2320
Funding Source:NIH, NIDDK
Project Comments:This data represents the untargeted metabolomic analysis of the samples
Contributors:O. Alcazar, L.F. Hernandez, E.S. Nakayasu, C. Ansong, C.D. Nicora, C. Ansong, M.J. Muehlbauer, J.R. Bain, C.J. Myer, S.J. Bhattacharya, P. Buchwald, and M.H. Abdulreda