Large-scale proteome and metabolome analysis of CSF implicates altered glucose metabolism and succinylcarnitine in Alzheimer’s disease

A major hallmark of Alzheimer’s disease (AD) is the aggregation of proteins (β-amyloid (A) and hyperphosphorylated tau (T)) in the brain, which makes the AD proteome in cerebrospinal fluid (CSF) of particular interest. Here, we conducted a CSF proteome-wide analysis among participants with and without AD pathology (n = 137 total participants: 56 A-T-, 39 A+T-, and 42 A+T+; 915 proteins analyzed), using a panel of 9 CSF biomarkers for neurodegeneration and neuroinflammation. We identified 61 proteins significantly associated with AT category (P < 5.46 x 10-5; strongest was SMOC1, P = 1.87 x 10-12) and 636 significant protein-biomarker associations (P < 6.07 x 10-6; strongest was a positive association between neurogranin and EPHA4, P = 2.42 x 10-25). Community network and pathway enrichment analyses highlighted three biomarker-associated protein networks centered around amyloid and tau measures, neurogranin, and the remaining biomarkers. Glucose metabolic pathways were enriched primarily among the amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, both of which were associated with CSF phosphorylated tau levels in an independent replication cohort of 717 participants (P = 8.65 x 10-56 and P = 1.35 x 10-45). Follow-up interrogation of related CSF metabolite levels in the same samples as the discovery proteomics analysis identified increasing levels of succinylcarnitine with ptau and numerous other CSF biomarkers (P < 0.00056) that were replicated in an independent sample of 363 participants. Together, these results implicate glucose metabolic dysregulation and increased CSF succinylcarnitine levels as amyloid and tau pathology emerge in AD. One Sentence Summary: Combining cerebrospinal fluid proteomics data with neurodegeneration and neuroinflammation biomarkers, genomics, and cerebrospinal fluid metabolomics, we identify and replicate a theme of altered glucose metabolism proteins and the metabolite succinylcarnitine across amyloid and tau progression in Alzheimer’s disease. ### Competing Interest Statement Author CC receives research support from Biogen, EISAI, Alector, GSK and Parabon; these funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. Author CC is a member of the advisory board of Vivid Genomics, Halia Therapeutics and ADx Healthcare. Author HZ has served at scientific advisory boards and/or as a consultant for Alector, Eisai, Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics, Nervgen, AZTherapies, CogRx and Red Abbey Labs, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure and Biogen, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. Author 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, 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. Author GK is a full-time employee of Roche Diagnostics GmbH. Author IS is a full-time employee and shareholder of Roche Diagnostics International Ltd. Author AB is a full-time employee and shareholder of Roche Diagnostics GmbH. Author SCJ serves as a consultant to Roche Diagnostics and receives research funding from Cerveau Technologies. Other authors have no competing interests to declare. ### Funding Statement This research is supported by 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), P41GM108538 (National Center for Quantitative Biology of Complex Systems), R01AG037639 (White Matter Degeneration: Biomarkers in Preclinical Alzheimer's Disease), R01AG021155 (The Longitudinal Course of Imaging Biomarkers in People at Risk of AD), and P50AG033514 and P30AG062715 (Wisconsin Alzheimer's Disease Research Center Grant), 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 a core grant to the Center for Demography and Ecology at the University of Wisconsin-Madison (P2CHD047873). We also acknowledge use of the facilities of the Center for Demography of Health and Aging at the University of Wisconsin-Madison, funded by NIA Center grant P30AG017266. Author DJP was supported by NLM training grants to the Bio-Data Science Training Program (T32LM012413) and the Interdisciplinary Training Program in Cardiovascular and Pulmonary Biostatistics (5T32HL83806). Author YKD was supported by a training grant from the National Institute on Aging (T32AG000213). Author GEE was supported by an Alzheimer's Association Research Fellowship (2019-AARF-643973). Author 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), and the UK Dementia Research Institute at UCL. Author KB was supported by the Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (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), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), and the NIH, USA, (grant #1R01AG068398-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author CC receives support from the National Institutes of Health (R01AG044546, R01AG064877, RF1AG053303, R01AG058501, U01AG058922, R01AG064614, 1RF1AG074007), and the Chuck Zuckerberg Initiative (CZI). The recruitment and clinical characterization of research participants at Washington University were supported by NIH P30AG066444, and P01AG003991. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the NeuroGenomics and Informatics Center (NGI: ) and the Departments of Neurology and Psychiatry at Washington University School of Medicine. ELECSYS, COBAS and COBAS E are trademarks of Roche. The Roche NeuroToolKit robust prototype assays are for investigational purposes only and are not approved for clinical use. We thank the University of Wisconsin Madison Biotechnology Center Gene Expression Center for providing Illumina Infinium genotyping services. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: For the University of Wisconsin data: this study used the STROBE cohort reporting guidelines and was performed as part of the GeneRations Of WRAP (GROW) study, which was approved by the University of Wisconsin Health Sciences Institutional Review Board. Participants in the ADRC and WRAP studies provided written informed consent. For the Washington University in St. Louis data: the Institutional Review Boards of Washington University School of Medicine in St. Louis approved the study; research was performed in accordance with the approved protocols and participants provided informed consent. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The data sets generated and analyzed in this study from the Wisconsin ADRC may be requested at . The Knight-ADRC proteomic data is available at NIAGADS: NG00102 collection and can be interactively explored at .