Browsing by Author "St. John-Williams, Lisa"

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    Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts
    (Nature Research, 2019-10-17) St. John-Williams, Lisa; Mahmoudiandehkordi, Siamak; Arnold, Matthias; Massaro, Tyler; Blach, Colette; Kastenmüller, Gabi; Louie, Gregory; Kueider-Paisley, Alexandra; Han, Xianlin; Baillie, Rebecca; Motsinger-Reif, Alison A.; Rotroff, Daniel; Nho, Kwangsik; Saykin, Andrew J.; Risacher, Shannon L.; Koal, Therese; Moseley, M. Arthur; Tenenbaum, Jessica D.; Thompson, J. Will; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    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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    Sex and APOE ε4 genotype modify the Alzheimer’s disease serum metabolome
    (Springer Nature, 2020) Arnold, Matthias; Nho, Kwangsik; Kueider-Paisley, Alexandra; Massaro, Tyler; Huynh, Kevin; Brauner, Barbara; MahmoudianDehkordi, Siamak; Louie, Gregory; Moseley, M. Arthur; Thompson, J. Will; St. John-Williams, Lisa; Tenenbaum, Jessica D.; Blach, Colette; Chang, Rui; Brinton, Roberta D.; Baillie, Rebecca; Han, Xianlin; Trojanowski, John Q.; Shaw, Leslie M.; Martins, Ralph; Weiner, Michael W.; Trushina, Trushina; Toledo, Jon B.; Meikle, Peter J.; Bennett, David A.; Krumsiek, Jan; Doraiswamy, P. Murali; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Kastenmüller, Gabi; Radiology and Imaging Sciences, School of Medicine
    Late-onset Alzheimer’s disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.