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      Sex and APOE ε4 genotype modify the Alzheimer’s disease serum metabolome

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      1 , 2 , 3 , 1 , 4 , 5 , 2 , 1 , 1 , 6 , 6 , 6 , 7 , 8 , 9 , 9 , 10 , 11 , 12 , 13 , 14 , 14 , 15 , 16 , 17 , 18 , 19 , 14 , 20 , 5 , 21 , 22 , 1 , 23 , 24 , 3 , 1 , 23 , 24 , , 2 , 25 ,
      Nature Communications
      Nature Publishing Group UK
      Metabolomics, Alzheimer's disease, Predictive markers

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          Abstract

          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.

          Abstract

          Sex and the APOE ε4 genotype are important risk factors for late-onset Alzheimer’s disease. In the current study, the authors investigate how sex and APOE ε4 genotype modify the association between Alzheimer’s disease biomarkers and metabolites in serum.

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          Most cited references47

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          USING THE CORRECT STATISTICAL TEST FOR THE EQUALITY OF REGRESSION COEFFICIENTS

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            Religious Orders Study and Rush Memory and Aging Project.

            The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).
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              Sex modifies the APOE-related risk of developing Alzheimer disease.

              The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer disease (AD). Case-control studies suggest the APOE4 link to AD is stronger in women. We examined the APOE4-by-sex interaction in conversion risk (from healthy aging to mild cognitive impairment (MCI)/AD or from MCI to AD) and cerebrospinal fluid (CSF) biomarker levels. Cox proportional hazards analysis was used to compute hazard ratios (HRs) for an APOE-by-sex interaction on conversion in controls (n = 5,496) and MCI patients (n = 2,588). The interaction was also tested in CSF biomarker levels of 980 subjects from the Alzheimer's Disease Neuroimaging Initiative. Among controls, male and female carriers were more likely to convert to MCI/AD, but the effect was stronger in women (HR = 1.81 for women; HR = 1.27 for men; interaction: p = 0.011). The interaction remained significant in a predefined subanalysis restricted to APOE3/3 and APOE3/4 genotypes. Among MCI patients, both male and female APOE4 carriers were more likely to convert to AD (HR = 2.16 for women; HR = 1.64 for men); the interaction was not significant (p = 0.14). In the subanalysis restricted to APOE3/3 and APOE3/4 genotypes, the interaction was significant (p = 0.02; HR = 2.17 for women; HR = 1.51 for men). The APOE4-by-sex interaction on biomarker levels was significant for MCI patients for total tau and the tau-to-Aβ ratio (p = 0.009 and p = 0.02, respectively; more AD-like in women). APOE4 confers greater AD risk in women. Biomarker results suggest that increased APOE-related risk in women may be associated with tau pathology. These findings have important clinical implications and suggest novel research approaches into AD pathogenesis. © 2014 American Neurological Association.
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                Author and article information

                Contributors
                kaddu001@mc.duke.edu
                g.kastenmueller@helmholtz-muenchen.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                2 March 2020
                2 March 2020
                2020
                : 11
                : 1148
                Affiliations
                [1 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Department of Psychiatry and Behavioral Sciences, , Duke University, ; Durham, NC USA
                [2 ]ISNI 0000 0004 0483 2525, GRID grid.4567.0, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, ; Neuherberg, Germany
                [3 ]ISNI 0000 0001 2287 3919, GRID grid.257413.6, Department of Radiology and Imaging Sciences and the Indiana Alzheimer Disease Center, , Indiana University School of Medicine, ; Indianapolis, IN USA
                [4 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Duke Clinical Research Institute, , Duke University, ; Durham, NC USA
                [5 ]ISNI 0000 0000 9760 5620, GRID grid.1051.5, Metabolomics Laboratory, Baker Heart and Diabetes Institute, ; Melbourne, VIC Australia
                [6 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, , Duke University, ; Durham, NC USA
                [7 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Department of Biostatistics and Bioinformatics, , Duke University, ; Durham, NC USA
                [8 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Duke Molecular Physiology Institute, , Duke University, ; Durham, NC USA
                [9 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Center for Innovation in Brain Science, , University of Arizona, ; Tucson, AZ USA
                [10 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Pharmacology, College of Medicine, , University of Arizona, ; Tucson, AZ USA
                [11 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Neurology, College of Medicine, , University of Arizona, ; Tucson, AZ USA
                [12 ]Rosa & Co LLC, San Carlos, CA USA
                [13 ]ISNI 0000 0001 0629 5880, GRID grid.267309.9, University of Texas Health Science Center at San Antonio, ; San Antonio, TX USA
                [14 ]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Pathology & Laboratory Medicine, , University of Pennsylvania, ; Philadelphia, PA USA
                [15 ]ISNI 0000 0004 0389 4302, GRID grid.1038.a, School of Medical and Health Sciences, , Edith Cowan University, ; Joondalup, WA Australia
                [16 ]ISNI 0000 0001 2158 5405, GRID grid.1004.5, Department of Biomedical Sciences, , Macquarie University, ; North Ryde, NSW Australia
                [17 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Center for Imaging of Neurodegenerative Diseases, Department of Radiology, , San Francisco VA Medical Center/University of California San Francisco, ; San Francisco, CA USA
                [18 ]ISNI 0000 0004 0459 167X, GRID grid.66875.3a, Department of Neurology, , Mayo Clinic, ; Rochester, MN USA
                [19 ]ISNI 0000 0004 0459 167X, GRID grid.66875.3a, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, ; Rochester, MN USA
                [20 ]ISNI 0000 0004 0445 0041, GRID grid.63368.38, Department of Neurology, , Houston Methodist Hospital, ; Houston, TX USA
                [21 ]ISNI 0000 0001 0705 3621, GRID grid.240684.c, Rush Alzheimer’s Disease Center, , Rush University Medical Center, ; Chicago, IL USA
                [22 ]ISNI 000000041936877X, GRID grid.5386.8, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, ; New York, NY USA
                [23 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Duke Institute of Brain Sciences, , Duke University, ; Durham, NC USA
                [24 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Department of Medicine, , Duke University, ; Durham, NC USA
                [25 ]GRID grid.452622.5, German Center for Diabetes Research (DZD), ; Neuherberg, Germany
                Author information
                http://orcid.org/0000-0002-4666-0923
                http://orcid.org/0000-0002-3267-7070
                http://orcid.org/0000-0003-3532-565X
                http://orcid.org/0000-0003-3966-6320
                http://orcid.org/0000-0002-8615-2413
                http://orcid.org/0000-0002-9239-8794
                http://orcid.org/0000-0002-2593-4665
                http://orcid.org/0000-0002-1376-8532
                http://orcid.org/0000-0003-1858-5732
                http://orcid.org/0000-0002-2368-7322
                Article
                14959
                10.1038/s41467-020-14959-w
                7052223
                32123170
                2196ee40-0bda-403b-b0f3-e34068fbedd6
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 May 2019
                : 4 February 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000049, U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging);
                Award ID: RF1 AG058942
                Award ID: R01 AG057452
                Award ID: R03 AG054936
                Award ID: R01 LM012535
                Award ID: RF1 AG061872
                Award ID: P30AG10161
                Award ID: R01AG15819
                Award ID: U01AG46152
                Award ID: U01AG61356
                Award ID: R01 AG046171
                Award ID: RF1 AG051550
                Award ID: 3U01 AG024904-09S4
                Award ID: RF1 AG058942
                Award ID: RF1 AG058942
                Award ID: R01 AG057452
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: FundRef https://doi.org/10.13039/100008982, Qatar National Research Fund (QNRF);
                Award ID: NPRP8-061-3-011
                Award ID: NPRP8-061-3-011
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Categories
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                © The Author(s) 2020

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                metabolomics,alzheimer's disease,predictive markers
                Uncategorized
                metabolomics, alzheimer's disease, predictive markers

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