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Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer’s disease pathology

  • NEURO-EPIDEMIOLOGY
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Abstract

Modifiable factors can influence the risk for Alzheimer’s disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer’s prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

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Data availability

Data available on request. The data underlying this article can be requested through the WRAP Application for Resources link on the following website: https://wrap.wisc.edu/data-requests-2/.

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Acknowledgements

The authors especially thank the WRAP participants and staff for their contributions to the studies. Without their efforts, this research would not be possible. We would like to thank Roche for providing the NTK kits for this study. The Roche NeuroToolKit is a panel of exploratory prototype assays designed to robustly evaluate biomarkers associated with key pathologic events characteristic of AD and other neurological disorders, used for research purposes only and not approved for clinical use. COBAS, COBAS E and ELECSYS are trademarks of Roche.

Funding

This study was supported by the National Institutes of Health (NIH) grants [R01AG27161 (Wisconsin Registry for Alzheimer Prevention: Biomarkers of Preclinical AD), R01AG054047 (Genomic and Metabolomic Data Integration in a Longitudinal Cohort at Risk for Alzheimer’s Disease), and R21AG067092 (Identifying Metabolomic Risk Factors in Plasma and Cerebrospinal Fluid for Alzheimer's Disease)], the Helen Bader Foundation, Northwestern Mutual Foundation, Extendicare Foundation, State of Wisconsin, the Clinical and Translational Science Award (CTSA) program through the NIH National Center for Advancing Translational Sciences (NCATS) grant [UL1TR000427], and the University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation. Computational resources were supported by core grants to the Center for Demography and Ecology [P2CHD047873] and the Center for Demography of Health and Aging [P30AG017266]. HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C), the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), European Union Joint Program for Neurodegenerative Disorders (JPND2021-00694), and the UK Dementia Research Institute at UCL. KB is supported by the Swedish Research Council (#2017-00915), ADDF, USA [#RDAPB-201809-2016615], the Swedish Alzheimer Foundation [#AF-742881], Hjärnfonden, Sweden [#FO2017-0243], the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement [#ALFGBG-715986], and European Union Joint Program for Neurodegenerative Disorders [JPND2019-466–236].

Author information

Authors and Affiliations

  1. Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA

    Ruocheng Dong, Diandra N. Denier-Fields & Corinne D. Engelman

  2. Department of Nutrition Science, University of Wisconsin-Madison, Madison, WI, 53706, USA

    Diandra N. Denier-Fields

  3. Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA

    Carol A. Van Hulle, Rozalyn M. Anderson, Cynthia M. Carlsson & Sterling C. Johnson

  4. Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA

    Carol A. Van Hulle, Cynthia M. Carlsson, Sterling C. Johnson & Corinne D. Engelman

  5. Roche Diagnostics International Ltd, CH-6346, Rotkreuz, Switzerland

    Gwendlyn Kollmorgen

  6. Roche Diagnostics GmbH, 82377, Penzberg, Germany

    Ivonne Suridjan & Norbert Wild

  7. Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA

    Qiongshi Lu

  8. Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, 53705, USA

    Rozalyn M. Anderson, Cynthia M. Carlsson & Sterling C. Johnson

  9. Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, S-43180, Mölndal, Sweden

    Henrik Zetterberg & Kaj Blennow

  10. Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-43180, Mölndal, Sweden

    Henrik Zetterberg & Kaj Blennow

  11. UK Dementia Research Institute at UCL, London, WC1E 6BT, UK

    Henrik Zetterberg

  12. Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1H 0AL, UK

    Henrik Zetterberg

  13. Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China

    Henrik Zetterberg

  14. Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53719, USA

    Sterling C. Johnson & Corinne D. Engelman

Authors
  1. Ruocheng Dong
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  2. Diandra N. Denier-Fields
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  3. Carol A. Van Hulle
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  4. Gwendlyn Kollmorgen
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  5. Ivonne Suridjan
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  6. Norbert Wild
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  7. Qiongshi Lu
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  8. Rozalyn M. Anderson
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  9. Henrik Zetterberg
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  13. Corinne D. Engelman
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Contributions

RD conceived and designed the analysis, performed the analysis, and wrote the paper. DF helped interpret the findings and write the discussion. CV conducted the Cerebrolspinal fluid NeuroToolKit biomarker data quality control and reviewed the paper. GK, IS, NW generated the Cerebrolspinal fluid NeuroToolKit biomarker data and reviewed the paper. QL, RA contributed to the analysis design and reviewed the paper. HZ, KB contributed the Cerebrialspinal fluid NeuroToolKit biomarker data generation and reviewed the paper. CC, SJ directed the WRAP study and reviewed the paper. CE contributed to the analysis design, helped interpret the findings, and reviewed and edited the paper.

Corresponding author

Correspondence to Corinne D. Engelman.

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Gwendlyn Kollmorgen and Norbert Wild are full-time employees of Roche Diagnostics GmbH. Ivonne Suridjan is a full-time employee of Roche Diagnostics International Ltd and holds non-voting equities in F. Hoffmann-La Roche. HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). KB has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Pharmatrophix, Prothena, Roche Diagnostics, and Siemens Healthineers, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, all unrelated to the work presented in this paper. SJ received grants from the NIH during the conduct of the study and personal fees from Roche Diagnostics outside the submitted work.

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Dong, R., Denier-Fields, D.N., Van Hulle, C.A. et al. Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer’s disease pathology. Eur J Epidemiol 38, 559–571 (2023). https://doi.org/10.1007/s10654-023-00988-4

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