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Fluid biomarker agreement and interrelation in dementia due to Alzheimer’s disease

  • Psychiatry and Preclinical Psychiatric Studies - Original Article
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Abstract

The cerebrospinal fluid (CSF) levels of β-amyloid 42, total tau, and phosphorylated tau 181 are supposed to be all continuously abnormal in dementia due to Alzheimer’s disease (AD), being the most advanced disease stage. The aim of the present study, which included a monocentric and a multicentric sample (N = 119 and 178, respectively), was to investigate the degree of CSF biomarker agreement and interrelation in AD dementia. Based on previously published cut-off values, biomarker values were categorized as positive or negative for AD (dichotomization strategy) and as either positive, negative, or borderline (trichotomization strategy). The statistical analyses relied on distance correlation analysis and kappa (k) statistics. Poor agreement (k < 0.4) and low interrelations between the studied biomarkers were detected in all cases with the exception of the interrelation between the markers total tau and phosphorylated tau 181, especially in the monocentric sample. Interestingly, lower interrelation and agreement degrees were observed in carriers of the Apolipoprotein E ε4 allele compared to non-carriers. The clinical phenotype currently referred to as “AD dementia” is characterized by an inhomogeneous CSF biomarker profile, possibly mirroring the complex genesis of AD-typical dementia symptoms and pointing to the necessity of shedding more light on the hypothesis of biomarker stability over time in symptomatic AD.

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References

  • Aisen PS, Cummings J, Jack CR Jr, Morris JC, Sperling R, Frolich L, Jones RW, Dowsett SA, Matthews BR, Raskin J, Scheltens P, Dubois B (2017) On the path to 2025. Understanding the Alzheimer’s disease continuum. Alzheimer’s Res Ther 9(1):60

    Article  Google Scholar 

  • Alexopoulos P, Guo L-H, Jiang M, Bujo H, Grimmer T, Forster S, Drzezga A, Kurz A, Perneczky R (2013) Amyloid cascade and tau pathology cerebrospinal fluid markers in mild cognitive impairment with regards to Alzheimer’s disease cerebral metabolic signature. J Alzheimer’s Dis 36(2):401–408

    CAS  Google Scholar 

  • Alexopoulos P, Kriett L, Haller B, Klupp E, Gray K, Grimmer T, Laskaris N, Forster S, Perneczky R, Kurz A, Drzezga A, Fellgiebel A, Yakushev I (2014) Limited agreement between biomarkers of neuronal injury at different stages of Alzheimer’s disease. Alzheimer’s Dement J Alzheimer’s Assoc 10(6):684–689

    Article  Google Scholar 

  • Alexopoulos P, Roesler J, Thierjung N, Werle L, Buck D, Yakushev I, Gleixner L, Kagerbauer S, Ortner M, Grimmer T, Kubler H, Martin J, Laskaris N, Kurz A, Perneczky R (2016) Mapping CSF biomarker profiles onto NIA-AA guidelines for Alzheimer’s disease. Eur Arch Psychiatry Clin Neurosci 266(7):587–597

    Article  PubMed  Google Scholar 

  • Bertens D, Knol DL, Scheltens P, Visser PJ (2015) Temporal evolution of biomarkers and cognitive markers in the asymptomatic, MCI, and dementia stage of Alzheimer’s disease. Alzheimer’s Dement J Alzheimer’s Assoc 11(5):511–522

    Article  Google Scholar 

  • Bier J-C, Verschraegen J, Vandenberghe R, Guillaume B, Picard G, Otte G, Mormont E, Gilles C, Segers K, Sieben A, Thiery E, Ventura M, de Deyn P, Deryck O, Versijpt J, Salmon E, Engelborghs S, Ivanoiu A (2015) Clinical utility and applicability of biomarker-based diagnostic criteria for Alzheimer’s disease. A BeDeCo survey. Acta Neurol Belg 115(4):547–555

    Article  PubMed  Google Scholar 

  • Bocchetta M, Galluzzi S, Kehoe PG, Aguera E, Bernabei R, Bullock R, Ceccaldi M, Dartigues J-F, de Mendonca A, Didic M, Eriksdotter M, Felician O, Frolich L, Gertz H-J, Hallikainen M, Hasselbalch SG, Hausner L, Heuser I, Jessen F, Jones RW, Kurz A, Lawlor B, Lleo A, Martinez-Lage P, Mecocci P, Mehrabian S, Monsch A, Nobili F, Nordberg A, Rikkert MO, Orgogozo J-M, Pasquier F, Peters O, Salmon E, Sanchez-Castellano C, Santana I, Sarazin M, Traykov L, Tsolaki M, Visser PJ, Wallin AK, Wilcock G, Wilkinson D, Wolf H, Yener G, Zekry D, Frisoni GB (2015) The use of biomarkers for the etiologic diagnosis of MCI in Europe. An EADC survey. Alzheimer’s Dement J Alzheimer’s Assoc 11(2):195.e1–206.e1

    Google Scholar 

  • Boyle PA, Wilson RS, Yu L, Barr AM, Honer WG, Schneider JA, Bennett DA (2013) Much of late life cognitive decline is not due to common neurodegenerative pathologies. Ann Neurol 74(3):478–489

    Article  PubMed  Google Scholar 

  • Brenowitz WD, Hubbard RA, Keene CD, Hawes SE, Longstreth WT Jr, Woltjer RL, Kukull WA (2017) Mixed neuropathologies and estimated rates of clinical progression in a large autopsy sample. Alzheimer’s Dement J Alzheimer’s Assoc 13(6):654–662

    Article  Google Scholar 

  • Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, DeKosky ST, Gauthier S, Selkoe D, Bateman R, Cappa S, Crutch S, Engelborghs S, Frisoni GB, Fox NC, Galasko D, Habert M-O, Jicha GA, Nordberg A, Pasquier F, Rabinovici G, Robert P, Rowe C, Salloway S, Sarazin M, Epelbaum S, de Souza LC, Vellas B, Visser PJ, Schneider L, Stern Y, Scheltens P, Cummings JL (2014) Advancing research diagnostic criteria for Alzheimer’s disease. The IWG-2 criteria. Lancet Neurol 13(6):614–629

    Article  PubMed  Google Scholar 

  • Dumurgier J, Schraen S, Gabelle A, Vercruysse O, Bombois S, Laplanche J-L, Peoc’h K, Sablonniere B, Kastanenka KV, Delaby C, Pasquier F, Touchon J, Hugon J, Paquet C, Lehmann S (2015) Cerebrospinal fluid amyloid-beta 42/40 ratio in clinical setting of memory centers. A multicentric study. Alzheimer’s Res Ther 7(1):30

    Article  Google Scholar 

  • Fagan AM, Mintun MA, Mach RH, Lee S-Y, Dence CS, Shah AR, LaRossa GN, Spinner ML, Klunk WE, Mathis CA, DeKosky ST, Morris JC, Holtzman DM (2006) Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 59(3):512–519

    Article  CAS  PubMed  Google Scholar 

  • Fleiss JL, Levin BA, Paik MC (2003) Statistical methods for rates and proportions. In: Fleiss JL, Levin B, Paik MC (eds) Wiley series in probability and statistics, 3rd edn. Wiley, Hoboken

    Google Scholar 

  • Gendron TF, Petrucelli L (2009) The role of tau in neurodegeneration. Mol Neurodegener 4:13

    Article  PubMed  PubMed Central  Google Scholar 

  • Guo L-H, Alexopoulos P, Wagenpfeil S, Kurz A, Perneczky R (2013) Brain size and the compensation of Alzheimer’s disease symptoms. A longitudinal cohort study. Alzheimer’s Dement J Alzheimer’s Assoc 9(5):580–586

    Article  Google Scholar 

  • Herukka S-K, Simonsen AH, Andreasen N, Baldeiras I, Bjerke M, Blennow K, Engelborghs S, Frisoni GB, Gabryelewicz T, Galluzzi S, Handels R, Kramberger MG, Kulczynska A, Molinuevo JL, Mroczko B, Nordberg A, Oliveira CR, Otto M, Rinne JO, Rot U, Saka E, Soininen H, Struyfs H, Suardi S, Visser PJ, Winblad B, Zetterberg H, Waldemar G (2017) Recommendations for cerebrospinal fluid Alzheimer’s disease biomarkers in the diagnostic evaluation of mild cognitive impairment. Alzheimer’s Dement J Alzheimer’s Assoc 13(3):285–295

    Article  Google Scholar 

  • Hulstaert F, Blennow K, Ivanoiu A, Schoonderwaldt HC, Riemenschneider M, de Deyn PP, Bancher C, Cras P, Wiltfang J, Mehta PD, Iqbal K, Pottel H, Vanmechelen E, Vanderstichele H (1999) Improved discrimination of AD patients using beta-amyloid(1-42) and tau levels in CSF. Neurology 52(8):1555–1562

    Article  CAS  PubMed  Google Scholar 

  • Iturria-Medina Y, Carbonell FM, Sotero RC, Chouinard-Decorte F, Evans AC (2017) Multifactorial causal model of brain (dis)organization and therapeutic intervention. Application to Alzheimer’s disease. NeuroImage 152:60–77

    Article  PubMed  Google Scholar 

  • Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue MC, Trojanowski JQ (2013) Tracking pathophysiological processes in Alzheimer’s disease. An updated hypothetical model of dynamic biomarkers. Lancet Neurol 12(2):207–216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jagust WJ, Landau SM, Shaw LM, Trojanowski JQ, Koeppe RA, Reiman EM, Foster NL, Petersen RC, Weiner MW, Price JC, Mathis CA (2009) Relationships between biomarkers in aging and dementia. Neurology 73(15):1193–1199

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kim S, Swaminathan S, Shen L, Risacher SL, Nho K, Foroud T, Shaw LM, Trojanowski JQ, Potkin SG, Huentelman MJ, Craig DW, DeChairo BM, Aisen PS, Petersen RC, Weiner MW, Saykin AJ (2011) Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort. Neurology 76(1):69–79

    Article  CAS  PubMed  Google Scholar 

  • Korczyn AD (2013) Is Alzheimer’s disease a homogeneous disease entity? J Neural Transm (Vienna Austria) 120(10):1475–1477

    Article  Google Scholar 

  • Landau SM, Harvey D, Madison CM, Reiman EM, Foster NL, Aisen PS, Petersen RC, Shaw LM, Trojanowski JQ, Jack CR Jr, Weiner MW, Jagust WJ (2010) Comparing predictors of conversion and decline in mild cognitive impairment. Neurology 75(3):230–238

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Landau SM, Lu M, Joshi AD, Pontecorvo M, Mintun MA, Trojanowski JQ, Shaw LM, Jagust WJ (2013) Comparing positron emission tomography imaging and cerebrospinal fluid measurements of beta-amyloid. Ann Neurol 74(6):826–836

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lehmann S, Dumurgier J, Schraen S, Wallon D, Blanc F, Magnin E, Bombois S, Bousiges O, Campion D, Cretin B, Delaby C, Hannequin D, Jung B, Hugon J, Laplanche J-L, Miguet-Alfonsi C, Peoc’h K, Philippi N, Quillard-Muraine M, Sablonniere B, Touchon J, Vercruysse O, Paquet C, Pasquier F, Gabelle A (2014) A diagnostic scale for Alzheimer’s disease based on cerebrospinal fluid biomarker profiles. Alzheimer’s Res Ther 6(3):38

    Article  Google Scholar 

  • Leuzy A, Carter SF, Chiotis K, Almkvist O, Wall A, Nordberg A (2015) Concordance and diagnostic accuracy of 11CPIB PET and cerebrospinal fluid biomarkers in a sample of patients with mild cognitive impairment and Alzheimer’s disease. J Alzheimer’s Dis 45(4):1077–1088

    CAS  Google Scholar 

  • Leuzy A, Chiotis K, Hasselbalch SG, Rinne JO, de Mendonca A, Otto M, Lleo A, Castelo-Branco M, Santana I, Johansson J, Anderl-Straub S, von Arnim CAF, Beer A, Blesa R, Fortea J, Herukka S-K, Portelius E, Pannee J, Zetterberg H, Blennow K, Nordberg A (2016) Pittsburgh compound B imaging and cerebrospinal fluid amyloid-beta in a multicentre European memory clinic study. Brain J Neurol 139(Pt 9):2540–2553

    Article  Google Scholar 

  • Lista S, Toschi N, Baldacci F, Zetterberg H, Blennow K, Kilimann I, Teipel SJ, Cavedo E, Dos Santos AM, Epelbaum S, Lamari F, Dubois B, Floris R, Garaci F, Hampel H (2017) Diagnostic accuracy of CSF neurofilament light chain protein in the biomarker-guided classification system for Alzheimer’s disease. Neurochem Int 108:355–360

    Article  CAS  PubMed  Google Scholar 

  • McDade E, Bateman RJ (2017) Stop Alzheimer’s before it starts. Nature 547(7662):153–155

    Article  CAS  PubMed  Google Scholar 

  • McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984) Clinical diagnosis of Alzheimer’s disease. Report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34(7):939–944

    Article  CAS  PubMed  Google Scholar 

  • McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH (2011) The diagnosis of dementia due to Alzheimer’s disease. Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement J Alzheimer’s Assoc 7(3):263–269

    Article  Google Scholar 

  • Molinuevo JL, Blennow K, Dubois B, Engelborghs S, Lewczuk P, Perret-Liaudet A, Teunissen CE, Parnetti L (2014) The clinical use of cerebrospinal fluid biomarker testing for Alzheimer’s disease diagnosis. A consensus paper from the Alzheimer’s Biomarkers Standardization Initiative. Alzheimer’s Dement J Alzheimer’s Association 10(6):808–817

    Article  Google Scholar 

  • Persson T, Lattanzio F, Calvo-Garrido J, Rimondini R, Rubio-Rodrigo M, Sundstrom E, Maioli S, Sandebring-Matton A, Cedazo-Minguez A (2017) Apolipoprotein E4 elicits lysosomal cathepsin D release, decreased thioredoxin-1 levels, and apoptosis. J Alzheimer’s Dis 56(2):601–617

    Article  CAS  Google Scholar 

  • Reitz C (2016) Toward precision medicine in Alzheimer’s disease. Annals of translational medicine 4(6):107

    Article  PubMed  PubMed Central  Google Scholar 

  • Rosenmann H (2012) CSF biomarkers for amyloid and tau pathology in Alzheimer’s disease. J Mol Neurosci 47(1):1–14

    Article  CAS  PubMed  Google Scholar 

  • Saykin AJ, Shen L, Foroud TM, Potkin SG, Swaminathan S, Kim S, Risacher SL, Nho K, Huentelman MJ, Craig DW, Thompson PM, Stein JL, Moore JH, Farrer LA, Green RC, Bertram L, Jack CR, Weiner MW (2010) Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes. Genetics core aims, progress, and plans. Alzheimer’s Dement J Alzheimer’s Assoc 6(3):265–273

    Article  CAS  Google Scholar 

  • Schjonning Nielsen M, Simonsen AH, Siersma V, Hasselbalch SG, Hogh P (2016) Are CSF biomarkers useful as prognostic indicators in diagnostically unresolved cognitively impaired patients in a normal clinical setting. Dement Geriatr Cogn Disord Extra 6(3):465–476

    Article  Google Scholar 

  • Schoonenboom NSM, Reesink FE, Verwey NA, Kester MI, Teunissen CE, van de Ven PM, Pijnenburg YAL, Blankenstein MA, Rozemuller AJ, Scheltens P, van der Flier WM (2012) Cerebrospinal fluid markers for differential dementia diagnosis in a large memory clinic cohort. Neurology 78(1):47–54

    Article  CAS  PubMed  Google Scholar 

  • Shaw LM, Vanderstichele H, Knapik-Czajka M, Clark CM, Aisen PS, Petersen RC, Blennow K, Soares H, Simon A, Lewczuk P, Dean R, Siemers E, Potter W, Lee VM-Y, Trojanowski JQ (2009) Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 65(4):403–413

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Simonsen AH, Herukka S-K, Andreasen N, Baldeiras I, Bjerke M, Blennow K, Engelborghs S, Frisoni GB, Gabryelewicz T, Galluzzi S, Handels R, Kramberger MG, Kulczynska A, Molinuevo JL, Mroczko B, Nordberg A, Oliveira CR, Otto M, Rinne JO, Rot U, Saka E, Soininen H, Struyfs H, Suardi S, Visser PJ, Winblad B, Zetterberg H, Waldemar G (2017) Recommendations for CSF AD biomarkers in the diagnostic evaluation of dementia. Alzheimer’s Dement J Alzheimer’s Assoc 13(3):274–284

    Article  Google Scholar 

  • Skillback T, Farahmand BY, Rosen C, Mattsson N, Nagga K, Kilander L, Religa D, Wimo A, Winblad B, Schott JM, Blennow K, Eriksdotter M, Zetterberg H (2015) Cerebrospinal fluid tau and amyloid-beta1-42 in patients with dementia. Brain J Neurol 138(Pt 9):2716–2731

    Article  Google Scholar 

  • Székely GJ, Rizzo ML, Bakirov NK (2007) Measuring and testing dependence by correlation of distances. Ann Stat 35(6):2769–2794

    Article  Google Scholar 

  • Vandermeeren M, Mercken M, Vanmechelen E, Six J, van de Voorde A, Martin JJ, Cras P (1993) Detection of tau proteins in normal and Alzheimer’s disease cerebrospinal fluid with a sensitive sandwich enzyme-linked immunosorbent assay. J Neurochem 61(5):1828–1834

    Article  CAS  PubMed  Google Scholar 

  • Vanderstichele H, van Kerschaver E, Hesse C, Davidsson P, Buyse MA, Andreasen N, Minthon L, Wallin A, Blennow K, Vanmechelen E (2000) Standardization of measurement of beta-amyloid(1-42) in cerebrospinal fluid and plasma. Amyloid Int J Exp Clin Investig 7(4):245–258

    CAS  Google Scholar 

  • Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, Szoeke C, Macaulay SL, Martins R, Maruff P, Ames D, Rowe CC, Masters CL (2013) Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease. A prospective cohort study. Lancet Neurol 12(4):357–367

    Article  CAS  PubMed  Google Scholar 

  • Wallin AK, Blennow K, Andreasen N, Minthon L (2006) CSF biomarkers for Alzheimer’s Disease. Levels of beta-amyloid, tau, phosphorylated tau relate to clinical symptoms and survival. Dement Geriatr Cogn Disord 21(3):131–138

    Article  CAS  PubMed  Google Scholar 

  • Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR Jr, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ (2017) Recent publications from the Alzheimer’s disease neuroimaging initiative. Reviewing progress toward improved AD clinical trials. Alzheimer’s Dement J Alzheimer’s Assoc 13(4):e1–e85

    Article  Google Scholar 

  • Wenham PR, Price WH, Blandell G (1991) Apolipoprotein E genotyping by one-stage PCR. Lancet (Lond, Engl) 337(8750):1158–1159

    Article  CAS  Google Scholar 

  • Yakushev I, Muller MJ, Buchholz H-G, Lang U, Rossmann H, Hampel H, Schreckenberger M, Fellgiebel A (2012) Stage-dependent agreement between cerebrospinal fluid proteins and FDG-PET findings in Alzheimer’s disease. Curr Alzheimer Res 9(2):241–247

    Article  CAS  PubMed  Google Scholar 

  • Yamazaki Y, Painter MM, Bu G, Kanekiyo T (2016) Apolipoprotein E as a therapeutic target in Alzheimer’s disease. A review of basic research and clinical evidence. CNS Drugs 30(9):773–789

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhao N, Liu C-C, Qiao W, Bu G (2017) Apolipoprotein E, receptors, and modulation of Alzheimer’s disease. Neuron 96(1):115–129.e5. https://doi.org/10.1016/j.neuron.2017.09.003

    Article  CAS  PubMed  Google Scholar 

  • Zivelin A, Rosenberg N, Peretz H, Amit Y, Kornbrot N, Seligsohn U (1997) Improved method for genotyping apolipoprotein E polymorphisms by a PCR-based assay simultaneously utilizing two distinct restriction enzymes. Clin Chem 43(9):1657–1659

    CAS  PubMed  Google Scholar 

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Acknowledgements

Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (http://www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

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Correspondence to Panagiotis Alexopoulos.

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All procedures performed in the study were in accordance with the ethical standards of the institutional research committees and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

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Alexopoulos, P., Roesler, J., Werle, L. et al. Fluid biomarker agreement and interrelation in dementia due to Alzheimer’s disease. J Neural Transm 125, 193–201 (2018). https://doi.org/10.1007/s00702-017-1810-z

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