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Targeted metabolomics and medication classification data from participants in the ADNI1 cohort.

Authors :
St John-Williams L
Blach C
Toledo JB
Rotroff DM
Kim S
Klavins K
Baillie R
Han X
Mahmoudiandehkordi S
Jack J
Massaro TJ
Lucas JE
Louie G
Motsinger-Reif AA
Risacher SL
Saykin AJ
Kastenmüller G
Arnold M
Koal T
Moseley MA
Mangravite LM
Peters MA
Tenenbaum JD
Thompson JW
Kaddurah-Daouk R
Source :
Scientific data [Sci Data] 2017 Oct 17; Vol. 4, pp. 170140. Date of Electronic Publication: 2017 Oct 17.
Publication Year :
2017

Abstract

Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.

Details

Language :
English
ISSN :
2052-4463
Volume :
4
Database :
MEDLINE
Journal :
Scientific data
Publication Type :
Academic Journal
Accession number :
29039849
Full Text :
https://doi.org/10.1038/sdata.2017.140