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Sci Data. 2017 Oct 17;4:170140. doi: 10.1038/sdata.2017.140.

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

Author information

1
Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA.
2
Duke Molecular Physiology Institute, Duke University, Durham, NC 27701, USA.
3
Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
4
Department of Neurology, Houston Methodist Hospital, Houston, TX 77030, USA.
5
Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC 27607, USA.
6
Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
7
Department of Electrical and Computer Engineering, State University of New York, Oswego, NY 13126, USA.
8
BIOCRATES Life Sciences AG, Innsbruck 6020, Austria.
9
Rosa and Co LLC, San Carlos, CA 94070, USA.
10
Sanford Burnham Prebys Medical Discovery Institute, Orlando, FL 32827, USA.
11
Department of Psychiatry and Behavioral Sciences, and the Duke Institute for Brain Sciences, Duke University, Durham, NC 27710, USA.
12
Duke Social Sciences Research Institute, Duke University, Durham, NC 27708, USA.
13
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg D-85764, Germany.
14
German Center for Diabetes Research, Neuherberg D-85764, Germany.
15
Sage Bionetworks, Seattle, WA 98109, USA.
16
Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA.

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.

PMID:
29039849
PMCID:
PMC5644370
DOI:
10.1038/sdata.2017.140
[Indexed for MEDLINE]
Free PMC Article

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