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Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease

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Higginbotham, Lenora, Ping, Lingyan, Dammer, Eric B., Duong, Duc M., Zhou, Maotian, Gearing, Marla, Hurst, Cheyenne, Glass, Jonathan D. +6 more·2020·Science Advances
DOI 10.1126/sciadv.aaz9360PMC PMC7577712

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Abstract

Integrative proteomic analysis identifies CSF biomarker panels linked to brain-based pathophysiologies in Alzheimer’s disease.

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Crossref · 10.1126/sciadv.aaz9360

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  • SMOC1, NTN1, and MDK are strongly associated with amyloid plaques and are considered hub proteins in both AsymAD and AD.

    “These proteins are strongly associated with amyloid plaques and are considered hub proteins in both AsymAD and AD. 43 , 51 , 80”

    From Unraveling sex differences in Alzheimer's disease and related endophenotypes with brain proteomes (2025) · cites this paper as [80]

    The Results sections ‘Disease-related brain modules are preserved in AsymAD’ and ‘Overlap between brain protein and RNA networks’ report changes in SMOC1 and MDK in AsymAD and AD, and describe strong amyloid-plaque associations as a likely explanation for changes that include NTN1 and MDK. They do not identify the three proteins as hub proteins in both conditions, establish a plaque association for SMOC1, or specifically report an AsymAD change for NTN1. Page numbers are unavailable in our copy. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • There is important overlap between brain and CSF proteomes.

    “Given the important overlap between brain and CSF proteomes, 80 , 81 , 82 further studies could investigate these proteins as potential sex‐specific biomarkers in AD.”

    From Unraveling sex differences in Alzheimer's disease and related endophenotypes with brain proteomes (2025) · cites this paper as [80]

  • Levels of pro-inflammatory cytokines (including IL-1β, IL-6, IL-8, IL-18 and TNF) are upregulated in serum, cerebrospinal fluid, and post-mortem brain tissue of Alzheimer's disease patients.

    “Levels of these pro-inflammatory cytokines (including IL-1β, IL-6, IL-8, IL-18 and TNF) are upregulated in serum, cerebrospinal fluid (CSF) and post-mortem brain tissue of AD patients [23–25].”

    From Microglial function, INPP5D/SHIP1 signaling, and NLRP3 inflammasome activation: implications for Alzheimer’s disease (2023) · cites this paper as [24]

    The Results section reports altered CSF proteins and identifies osteopontin as a pro-inflammatory cytokine linked to AD, but it does not establish increases in the five cytokines named in the claim. Searches for IL-1β, IL-6, IL-8, IL-18, TNF, and the serum/CSF/post-mortem-brain comparison found no passage addressing that specific claim. Page numbers were not available in our copy. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 53

  1. [1]Lista S., Zetterberg H., O’Bryant S. E., Blennow K., Hampel H., Evolving relevance of neuroproteomics in Alzheimer’s disease. Methods Mol. Biol. 1598, 101– 115 (2017). 28508359
  2. [2]Castrillo J. I., Lista S., Hampel H., Ritchie C. W., Systems biology methods for Alzheimer’s disease research toward molecular signatures, subtypes, and stages and precision medicine: Application in cohort studies and trials. Methods Mol. Biol. 1750, 31– 66 (2018). 29512064
  3. [6]Olsson B., Lautner R., Andreasson U., Öhrfelt A., Portelius E., Bjerke M., Hölttä M., Rosén C., Olsson C., Strobel G., Wu E., Dakin K., Petzold M., Blennow K., Zetterberg H., CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: A systematic review and meta-analysis. Lancet Neurol. 15, 673– 684 (2016). 27068280
  4. [7]Blennow K., Zetterberg H., Biomarkers for Alzheimer’s disease: Current status and prospects for the future. J. Intern. Med. 284, 643– 663 (2018). 30051512
  5. [8]Armstrong R. A., Lantos P. L., Cairns N. J., Overlap between neurodegenerative disorders. Neuropathology 25, 111– 124 (2005). 15875904
  6. [9]Kapasi A., DeCarli C., Schneider J. A., Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol. 134, 171– 186 (2017). 28488154 PMC5663642
  7. [10]Hodes R. J., Buckholtz N., Accelerating Medicines Partnership: Alzheimer’s disease (AMP-AD) knowledge portal aids Alzheimer’s drug discovery through open data sharing. Expert Opin. Ther. Targets 20, 389– 391 (2016). 26853544
  8. [11]Langfelder P., Horvath S., WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008). 19114008 PMC2631488
  9. [13]Seyfried N. T., Dammer E. B., Swarup V., Nandakumar D., Duong D. M., Yin L., Deng Q., Nguyen T., Hales C. M., Wingo T., Glass J., Gearing M., Thambisetty M., Troncoso J. C., Geschwind D. H., Lah J. J., Levey A. I., A multi-network approach identifies protein-specific co-expression in asymptomatic and symptomatic Alzheimer’s disease. Cell Syst. 4, 60– 72.e4 (2017). 27989508 PMC5269514
  10. [16]Higginbotham L., Ping L., Dammer E. B., Duong D. M., Zhou M., Gearing M., Johnson E. C. B., Hajjar I., Lah J. J., Levey A. I., Seyfried N. T., Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease. bioRxiv, 806752 (2019). PMC7577712 33087358
  11. [17]Johnson E. C. B., Dammer E. B., Duong D. M., Ping L., Zhou M., Yin L., Higginbotham L. A., Guajardo A., White B., Troncoso J. C., Thambisetty M., Montine T. J., Lee E. B., Trojanowski J. Q., Beach T. G., Reiman E. M., Haroutunian V., Wang M., Schadt E., Zhang B., Dickson D. W., Ertekin-Taner N., Golde T. E., Petyuk V. A., de Jager P. L., Bennett D. A., Wingo T. S., Rangaraju S., Hajjar I., Shulman J. M., Lah J. J., Levey A. I., Seyfried N. T., Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat. Med. 26, 769– 780 (2020). 32284590 PMC7405761
  12. [21]Wingo A. P., Fan W., Duong D. M., Gerasimov E. S., Dammer E. B., Liu Y., Harerimana N. V., White B., Thambisetty M., Troncoso J. C., Kim N., Schneider J. A., Hajjar I. M., Lah J. J., Bennett D. A., Seyfried N. T., Levey A. I., Wingo T. S., Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain. Nat. Neurosci. 23, 696– 700 (2020). 32424284 PMC7269838
  13. [22]Zhang Q., Ma C., Gearing M., Wang P. G., Chin L.-S., Li L., Integrated proteomics and network analysis identifies protein hubs and network alterations in Alzheimer’s disease. Acta Neuropathol. Commun. 6, 19 (2018). 29490708 PMC5831854
  14. [24]Roche S., Gabelle A., Lehmann S., Clinical proteomics of the cerebrospinal fluid: Towards the discovery of new biomarkers. Proteomics Clin. Appl. 2, 428– 436 (2008). 21136844
  15. [25]Ping L., Duong D. M., Yin L., Gearing M., Lah J. J., Levey A. I., Seyfried N. T., Global quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s disease. Sci. Data 5, 180036 (2018). 29533394 PMC5848788
  16. [26]Umoh M. E., Dammer E. B., Dai J., Duong D. M., Lah J. J., Levey A. I., Gearing M., Glass J. D., Seyfried N. T., A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain. EMBO Mol. Med. 10, 48– 62 (2018). 29191947 PMC5760858
  17. [27]Pottiez G., Yang L., Stewart T., Song N., Aro P., Galasko D. R., Quinn J. F., Peskind E. R., Shi M., Zhang J., Mass-spectrometry-based method to quantify in parallel tau and amyloid β 1–42 in CSF for the diagnosis of Alzheimer’s disease. J. Proteome Res. 16, 1228– 1238 (2017). 28112948 PMC5679294
  18. [28]Mawuenyega K. G., Kasten T., Sigurdson W., Bateman R. J., Amyloid-beta isoform metabolism quantitation by stable isotope-labeled kinetics. Anal. Biochem. 440, 56– 62 (2013). 23714261 PMC3749773
  19. [32]Okada I., Hamanoue H., Terada K., Tohma T., Megarbane A., Chouery E., Abou-Ghoch J., Jalkh N., Cogulu O., Ozkinay F., Horie K., Takeda J., Furuichi T., Ikegawa S., Nishiyama K., Miyatake S., Nishimura A., Mizuguchi T., Niikawa N., Hirahara F., Kaname T., Yoshiura K. I., Tsurusaki Y., Doi H., Miyake N., Furukawa T., Matsumoto N., Saitsu H., SMOC1 is essential for ocular and limb development in humans and mice. Am. J. Hum. Genet. 88, 30– 41 (2011). 21194678 PMC3014372
  20. [33]Kerzerho J., Adotevi O., Castelli F. A., Dosset M., Bernardeau K., Szely N., Lang F., Tartour E., Maillere B., The angiogenic growth factor and biomarker midkine is a tumor-shared antigen. J. Immunol. 185, 418– 423 (2010). 20511550
  21. [36]Rader D. J., Dugi K. A., The endothelium and lipoproteins: Insights from recent cell biology and animal studies. Semin. Thromb. Hemost. 26, 521– 528 (2000). 11129408
  22. [37]Yi L., Tsai C. F., Dirice E., Swensen A. C., Chen J., Shi T., Gritsenko M. A., Chu R. K., Piehowski P. D., Smith R. D., Rodland K. D., Atkinson M. A., Mathews C. E., Kulkarni R. N., Liu T., Qian W.-J., Boosting to amplify signal with isobaric labeling (BASIL) strategy for comprehensive quantitative phosphoproteomic characterization of small populations of cells. Anal. Chem. 91, 5794– 5801 (2019). 30843680 PMC6596310
  23. [38]Hebert A. S., Prasad S., Belford M. W., Bailey D. J., McAlister G. C., Abbatiello S. E., Huguet R., Wouters E. R., Dunyach J. J., Brademan D. R., Westphall M. S., Coon J. J., Comprehensive single-shot proteomics with FAIMS on a hybrid orbitrap mass spectrometer. Anal. Chem. 90, 9529– 9537 (2018). 29969236 PMC6145172
  24. [39]Sun Y., Yin X. S., Guo H., Han R. K., He R. D., Chi L. J., Elevated osteopontin levels in mild cognitive impairment and Alzheimer’s disease. Mediators Inflamm. 2013, 615745 (2013). 23576854 PMC3612435
  25. [40]Rentsendorj A., Sheyn J., Fuchs D. T., Daley D., Salumbides B. C., Schubloom H. E., Hart N. J., Li S., Hayden E. Y., Teplow D. B., Black K. L., Koronyo Y., Koronyo-Hamaoui M., A novel role for osteopontin in macrophage-mediated amyloid-β clearance in Alzheimer’s models. Brain Behav. Immun. 67, 163– 180 (2018). 28860067 PMC5865478
  26. [41]Comi C., Carecchio M., Chiocchetti A., Nicola S., Galimberti D., Fenoglio C., Cappellano G., Monaco F., Scarpini E., Dianzani U., Osteopontin is increased in the cerebrospinal fluid of patients with Alzheimer’s disease and its levels correlate with cognitive decline. J. Alzheimers Dis. 19, 1143– 1148 (2010). 20308780
  27. [43]Kester M. I., Teunissen C. E., Crimmins D. L., Herries E. M., Ladenson J. H., Scheltens P., van der Flier W. M., Morris J. C., Holtzman D. M., Fagan A. M., Neurogranin as a cerebrospinal fluid biomarker for synaptic loss in symptomatic Alzheimer disease. JAMA Neurol. 72, 1275– 1280 (2015). 26366630 PMC4694558
  28. [44]Thorsell A., Bjerke M., Gobom J., Brunhage E., Vanmechelen E., Andreasen N., Hansson O., Minthon L., Zetterberg H., Blennow K., Neurogranin in cerebrospinal fluid as a marker of synaptic degeneration in Alzheimer’s disease. Brain Res. 1362, 13– 22 (2010). 20875798
  29. [45]Dayon L., Núñez Galindo A., Wojcik J., Cominetti O., Corthésy J., Oikonomidi A., Henry H., Kussmann M., Migliavacca E., Severin I., Bowman G. L., Popp J., Alzheimer disease pathology and the cerebrospinal fluid proteome. Alzheimers Res. Ther. 10, 66 (2018). 30021611 PMC6052524
  30. [46]Dayon L., Nuñez Galindo A., Corthésy J., Cominetti O., Kussmann M., Comprehensive and scalable highly automated MS-based proteomic workflow for clinical biomarker discovery in human plasma. J. Proteome Res. 13, 3837– 3845 (2014). 25058407
  31. [47]Driscoll I., Troncoso J., Asymptomatic Alzheimer’s disease: A prodrome or a state of resilience? Curr. Alzheimer Res. 8, 330– 335 (2011). 21222594 PMC3286868
  32. [50]Ly C. V., Verstreken P., Mitochondria at the synapse. Neuroscientist 12, 291– 299 (2006). 16840705
  33. [52]Malm T., Loppi S., Kanninen K. M., Exosomes in Alzheimer’s disease. Neurochem. Int. 97, 193– 199 (2016). 27131734
  34. [53]Rajendran L., Honsho M., Zahn T. R., Keller P., Geiger K. D., Verkade P., Simons K., Alzheimer’s disease β-amyloid peptides are released in association with exosomes. Proc. Natl. Acad. Sci. U.S.A. 103, 11172– 11177 (2006). 16837572 PMC1544060
  35. [54]Bellingham S. A., Guo B. B., Coleman B. M., Hill A. F., Exosomes: Vehicles for the transfer of toxic proteins associated with neurodegenerative diseases? Front. Physiol. 3, 124 (2012). 22563321 PMC3342525
  36. [55]Dinkins M. B., Dasgupta S., Wang G., Zhu G., Bieberich E., Exosome reduction in vivo is associated with lower amyloid plaque load in the 5XFAD mouse model of Alzheimer’s disease. Neurobiol. Aging 35, 1792– 1800 (2014). 24650793 PMC4035236
  37. [57]Nelson A. R., Sweeney M. D., Sagare A. P., Zlokovic B. V., Neurovascular dysfunction and neurodegeneration in dementia and Alzheimer’s disease. Biochim. Biophys. Acta 1862, 887– 900 (2016). 26705676 PMC4821735
  38. [58]Aluganti Narasimhulu C., Mitra C., Bhardwaj D., Burge K. Y., Parthasarathy S., Alzheimer’s disease markers in aged ApoE-PON1 deficient mice. J. Alzheimers Dis. 67, 1353– 1365 (2019). 30714958
  39. [59]Chistiakov D. A., Melnichenko A. A., Orekhov A. N., Bobryshev Y. V., Paraoxonase and atherosclerosis-related cardiovascular diseases. Biochimie 132, 19– 27 (2017). 27771368
  40. [60]Shu Y., Li R., Yang Y., Dai Y., Qiu W., Chen Y., Zhao Z., Lu Z., Hu X., Urinary trypsin inhibitor levels are reduced in cerebrospinal fluid of multiple sclerosis and neuromyelitis optica patients during relapse. Neurochem. Int. 81, 28– 31 (2015). 25555815
  41. [61]Feng M., Shu Y., Yang Y., Zheng X., Li R., Wang Y., Dai Y., Qiu W., Lu Z., Hu X., Ulinastatin attenuates experimental autoimmune encephalomyelitis by enhancing anti-inflammatory responses. Neurochem. Int. 64, 64– 72 (2014). 24274996
  42. [62]Zhou M., Duong D. M., Johnson E. C. B., Dai J., Lah J. J., Levey A. I., Seyfried N. T., Mass spectrometry-based quantification of tau in human cerebrospinal fluid using a complementary tryptic peptide standard. J. Proteome Res. 18, 2422– 2432 (2019). 30983353
  43. [64]Bader J. M., Geyer P. E., Müller J. B., Strauss M. T., Koch M., Leypoldt F., Koertvelyessy P., Bittner D., Schipke C. G., Incesoy E. I., Peters O., Deigendesch N., Simons M., Jensen M. K., Zetterberg H., Mann M., Proteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer’s disease. Mol. Syst. Biol. 16, e9356 (2020). 32485097 PMC7266499
  44. [65]Olsson A., Vanderstichele H., Andreasen N., de Meyer G., Wallin A., Holmberg B., Rosengren L., Vanmechelen E., Blennow K., Simultaneous measurement of β-amyloid(1–42), total tau, and phosphorylated tau (Thr181) in cerebrospinal fluid by the xMAP technology. Clin. Chem. 51, 336– 345 (2005). 15563479
  45. [66]Hulstaert F., Blennow K., Ivanoiu A., Schoonderwaldt H. C., Riemenschneider M., Deyn P. P. D., Bancher C., Cras P., Wiltfang J., Mehta P. D., Iqbal K., Pottel H., Vanmechelen E., Vanderstichele H., Improved discrimination of AD patients using β-amyloid(1–42) and tau levels in CSF. Neurology 52, 1555– 1562 (1999). 10331678
  46. [68]Winiarska A., Zareba L., Krolczyk G., Czyzewicz G., Zabczyk M., Undas A., Decreased levels of histidine-rich glycoprotein in advanced lung cancer: Association with prothrombotic alterations. Dis. Markers 2019, 8170759 (2019). 30944671 PMC6421726
  47. [69]Russell C. L., Heslegrave A., Mitra V., Zetterberg H., Pocock J. M., Ward M. A., Pike I., Combined tissue and fluid proteomics with tandem mass tags to identify low-abundance protein biomarkers of disease in peripheral body fluid: An Alzheimer’s disease case study. Rapid Commun. Mass Spectrom. 31, 153– 159 (2017). 27813239
  48. [70]Li J., Van Vranken J. G., Vaites L. P., Schweppe D. K., Huttlin E. L., Etienne C., Nandhikonda P., Viner R., Robitaille A. M., Thompson A. H., Kuhn K., Pike I., Bomgarden R. D., Rogers J. C., Gygi S. P., Paulo J. A., TMTpro reagents: A set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples. Nat. Methods 17, 399– 404 (2020). 32203386 PMC7302421
  49. [71]Mertins P., Tang L. C., Krug K., Clark D. J., Gritsenko M. A., Chen L., Clauser K. R., Clauss T. R., Shah P., Gillette M. A., Petyuk V. A., Thomas S. N., Mani D. R., Mundt F., Moore R. J., Hu Y., Zhao R., Schnaubelt M., Keshishian H., Monroe M. E., Zhang Z., Udeshi N. D., Mani D., Davies S. R., Townsend R. R., Chan D. W., Smith R. D., Zhang H., Liu T., Carr S. A., Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry. Nat. Protoc. 13, 1632– 1661 (2018). 29988108 PMC6211289
  50. [72]Mirra S. S., Heyman A., McKeel D., Sumi S. M., Crain B. J., Brownlee L. M., Vogel F. S., Hughes J. P., van Belle G., Berg L.; participating CERAD neuropathologists, The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease. Neurology 41, 479– 486 (1991). 2011243
  51. [74]Hyman B. T., Trojanowski J. Q., Editorial on consensus recommendations for the postmortem diagnosis of Alzheimer disease from the national institute on aging and the reagan institute working group on diagnostic criteria for the neuropathological assessment of Alzheimer disease. J. Neuropathol. Exp. Neurol. 56, 1095– 1097 (1997). 9329452
  52. [75]Brown D. F., Dababo M. A., Bigio E. H., Risser R. C., Eagan K. P., Hladik C. L., White C. L. III, Neuropathologic evidence that the Lewy body variant of Alzheimer disease represents coexistence of Alzheimer disease and idiopathic Parkinson disease. J. Neuropathol. Exp. Neurol. 57, 39– 46 (1998). 9600196
  53. [77]Zambon A. C., Gaj S., Ho I., Hanspers K., Vranizan K., Evelo C. T., Conklin B. R., Pico A. R., Salomonis N., GO-Elite: A flexible solution for pathway and ontology over-representation. Bioinformatics 28, 2209– 2210 (2012). 22743224 PMC3413395

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Authors
Higginbotham, L., Ping, L., Dammer, E. B., Duong, D. M., Zhou, M., Gearing, M., Hurst, C., Glass, J. D., Factor, S. A., Johnson, E. C. B., Hajjar, I., Lah, J. J., Levey, A. I., & Seyfried, N. T.
Affiliations
Emory University (US)
Corresponding author
  • Levey, Allan I.
  • Seyfried, Nicholas T.
ORCID
Venue
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Published
2020-10-23
Volume
6
Issue
43
ISSN
2375-2548 (ISSN-L)
DOI
10.1126/sciadv.aaz9360
PMC
PMC7577712
OpenAlex
W3093903285
Cited by
367
References
38
Citations by year
2026: 37 · 2025: 77 · 2024: 71 · 2023: 84 · 2022: 50 · 2021: 29 · 2020: 16 · 2019: 1 · 2012: 1
FWCI
27.22
Type
journal article
Language
en
Open access
Licence
Locations
  • Science Advances (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
  • Foundation for the National Institutes of Health
  • National Institute on Aging (R01AG053960, R01AG057911, R01AG061800, RF1AG057471, RF1AG057470, R01AG057339)
  • Accelerating Medicine Partnership for AD (U01AG046161, U01AG061357)
  • Emory Goizueta Alzheimer’s Disease Research Center (P50AG025688)
  • NINDS Emory Neuroscience Core (P30NS055077)
  • Michael J. Fox Foundation for Parkinson’s Research
  • Alzheimer’s Association
  • Weston Brain Institute (11060)
  • Alzheimer’s Research UK
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
Alzheimer's disease, cerebrospinal fluid biomarkers, brain proteome, protein panels, network analysis, synaptic proteins, metabolic proteins, glial proteins, myelination, neuroinflammation, asymptomatic Alzheimer's disease
MeSH terms
Alzheimer Disease, Brain, Humans, Biomarkers, Proteome, Proteomics

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