TY - JOUR
T1 - Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts
AU - Alzheimer's Disease Neuroimaging Initiative
AU - Alzheimer’s Disease Metabolomics Consortium
AU - St. John-Williams, Lisa
AU - Mahmoudiandehkordi, Siamak
AU - Arnold, Matthias
AU - Massaro, Tyler
AU - Blach, Colette
AU - Kastenmüller, Gabi
AU - Louie, Gregory
AU - Kueider-Paisley, Alexandra
AU - Han, Xianlin
AU - Baillie, Rebecca
AU - Motsinger-Reif, Alison A.
AU - Rotroff, Daniel
AU - Nho, Kwangsik
AU - Saykin, Andrew J.
AU - Risacher, Shannon L.
AU - Koal, Therese
AU - Moseley, M. Arthur
AU - Tenenbaum, Jessica D.
AU - Thompson, J. Will
AU - Kaddurah-Daouk, Rima
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41597-019-0181-8
DO - 10.1038/s41597-019-0181-8
M3 - Article
C2 - 31624257
AN - SCOPUS:85073632308
SN - 2052-4463
VL - 6
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 212
ER -