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Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts

Authors :
Lisa St. John-Williams
Siamak Mahmoudiandehkordi
Matthias Arnold
Tyler Massaro
Colette Blach
Gabi Kastenmüller
Gregory Louie
Alexandra Kueider-Paisley
Xianlin Han
Rebecca Baillie
Alison A. Motsinger-Reif
Daniel Rotroff
Kwangsik Nho
Andrew J. Saykin
Shannon L. Risacher
Therese Koal
M. Arthur Moseley
Jessica D. Tenenbaum
J. Will Thompson
Rima Kaddurah-Daouk
Alzheimer’s Disease Neuroimaging Initiative
Alzheimer’s Disease Metabolomics Consortium
Source :
Scientific Data, Vol 6, Iss 1, Pp 1-8 (2019), Scientific Data
Publication Year :
2019
Publisher :
Springer Science and Business Media LLC, 2019.

Abstract

Alzheimer’s disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.<br />Measurement(s)bile acid • MedicationTechnology Type(s)ultra high performance liquid chromatography with mass spectrometer • Resource InformaticsFactor Type(s)age • biological sex • cognitive stateSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9724652

Details

Language :
English
ISSN :
20524463
Volume :
6
Database :
OpenAIRE
Journal :
Scientific Data
Accession number :
edsair.doi.dedup.....f350826f21709028b4d053d4bbe9d41d
Full Text :
https://doi.org/10.1038/s41597-019-0181-8