Cognitively unimpaired individuals with a low burden of Aβ pathology have a distinct CSF biomarker profile

Marta Milà-Alomà, Mahnaz Shekari, Gemma Salvadó, Juan Domingo Gispert, Eider M Arenaza-Urquijo, Grégory Operto, Carles Falcon, Natalia Vilor-Tejedor, Oriol Grau-Rivera, Aleix Sala-Vila, Gonzalo Sánchez-Benavides, José Maria González-de-Echávarri, Carolina Minguillon, Karine Fauria, Aida Niñerola-Baizán, Andrés Perissinotti, Maryline Simon, Gwendlyn Kollmorgen, Henrik Zetterberg, Kaj Blennow, Marc Suárez-Calvet, José Luis Molinuevo, ALFA study, Marta Milà-Alomà, Mahnaz Shekari, Gemma Salvadó, Juan Domingo Gispert, Eider M Arenaza-Urquijo, Grégory Operto, Carles Falcon, Natalia Vilor-Tejedor, Oriol Grau-Rivera, Aleix Sala-Vila, Gonzalo Sánchez-Benavides, José Maria González-de-Echávarri, Carolina Minguillon, Karine Fauria, Aida Niñerola-Baizán, Andrés Perissinotti, Maryline Simon, Gwendlyn Kollmorgen, Henrik Zetterberg, Kaj Blennow, Marc Suárez-Calvet, José Luis Molinuevo, ALFA study

Abstract

Background: Understanding the changes that occur in the transitional stage between absent and overt amyloid-β (Aβ) pathology within the Alzheimer's continuum is crucial to develop therapeutic and preventive strategies. The objective of this study is to test whether cognitively unimpaired individuals with a low burden of Aβ pathology have a distinct CSF, structural, and functional neuroimaging biomarker profile.

Methods: Cross-sectional study of 318 middle-aged, cognitively unimpaired individuals from the ALFA+ cohort. We measured CSF Aβ42/40, phosphorylated tau (p-tau), total tau (t-tau), neurofilament light (NfL), neurogranin, sTREM2, YKL40, GFAP, IL6, S100B, and α-synuclein. Participants also underwent cognitive assessments, APOE genotyping, structural MRI, [18F]-FDG, and [18F]-flutemetamol PET. To ensure the robustness of our results, we used three definitions of low burden of Aβ pathology: (1) positive CSF Aβ42/40 and < 30 Centiloids in Aβ PET, (2) positive CSF Aβ42/40 and negative Aβ PET visual read, and (3) 20-40 Centiloid range in Aβ PET. We tested CSF and neuroimaging biomarker differences between the low burden group and the corresponding Aβ-negative group, adjusted by age and sex.

Results: The prevalence and demographic characteristics of the low burden group differed between the three definitions. CSF p-tau and t-tau were increased in the low burden group compared to the Aβ-negative in all definitions. CSF neurogranin was increased in the low burden group definitions 1 and 3, while CSF NfL was only increased in the low burden group definition 1. None of the defined low burden groups showed signs of atrophy or glucose hypometabolism. Instead, we found slight increases in cortical thickness and metabolism in definition 2.

Conclusions: There are biologically meaningful Aβ-downstream effects in individuals with a low burden of Aβ pathology, while structural and functional changes are still subtle or absent. These findings support considering individuals with a low burden of Aβ pathology for clinical trials.

Trial registration: NCT02485730.

Keywords: Alzheimer’s disease; Biomarkers; CSF; Cognitively unimpaired; Preclinical; Subthreshold.

Conflict of interest statement

MS is a full-time employee of the Roche Diagnostics International Ltd. GK is a full-time employee of the Roche Diagnostics GmbH. HZ has served at scientific advisory boards for Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics, and CogRx; has given lectures in symposia sponsored by Fujirebio, Alzecure, and Biogen; and is a co-founder of the 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, Roche Diagnostics, and Siemens Healthineers and is a co-founder of the Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. MSC has served as a consultant and at advisory boards for the Roche Diagnostics International Ltd. and has given lectures in symposia sponsored by the Roche Diagnostics, S.L.U, and Roche Farma, S.A. JLM is currently a full-time employee of H. Lundbeck A/S and priory has served as a consultant or at advisory boards for the following for-profit companies, or has given lectures in symposia sponsored by the following for-profit companies: Roche Diagnostics, Genentech, Novartis, Lundbeck, Oryzon, Biogen, Lilly, Janssen, Green Valley, MSD, Eisai, Alector, BioCross, GE Healthcare, and ProMIS Neurosciences. The other authors declare that they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Comparison of CSF p-tau, t-tau, NfL, and neurogranin between Aβ groups. The boxplots depict the median (horizontal bar), interquartile range (IQR hinges), and 1.5 × IQR (whiskers). Group differences were assessed by a one-way analysis of covariance (ANCOVA) adjusted by age and sex, followed by Dunnett-corrected pairwise post hoc comparisons. We show the percentage of increase in the mean of each biomarker in the low burden group compared to the Aβ- group. The percentage is shown in bold if the difference is statistically significant. “Low burden” refers to “low burden of Aβ pathology”. NS, not significant. *P <0.05; **P <0.01; ***P <0.001; ****P <0.0001

References

    1. 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 MO, 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. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol. 2014;13(6):614–629. doi: 10.1016/S1474-4422(14)70090-0.
    1. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, Iwatsubo T, Jack CR, Jr, Kaye J, Montine TJ, Park DC, Reiman EM, Rowe CC, Siemers E, Stern Y, Yaffe K, Carrillo MC, Thies B, Morrison-Bogorad M, Wagster MV, Phelps CH. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):280–292. doi: 10.1016/j.jalz.2011.03.003.
    1. Jack CR, Bennett DA, Blennow K, Carrillo MC, Feldman HH, Frisoni GB, et al. A / T / N : An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016:1–10.
    1. Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14:535–562. doi: 10.1016/j.jalz.2018.02.018.
    1. Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, Bakardjian H, Benali H, Bertram L, Blennow K, Broich K, Cavedo E, Crutch S, Dartigues JF, Duyckaerts C, Epelbaum S, Frisoni GB, Gauthier S, Genthon R, Gouw AA, Habert MO, Holtzman DM, Kivipelto M, Lista S, Molinuevo JL, O'Bryant SE, Rabinovici GD, Rowe C, Salloway S, Schneider LS, Sperling R, Teichmann M, Carrillo MC, Cummings J, Jack CR., Jr Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12(3):292–323. doi: 10.1016/j.jalz.2016.02.002.
    1. Milà-Alomà M, Suárez-Calvet M, Molinuevo JL. Latest advances in cerebrospinal fluid and blood biomarkers of Alzheimer’s disease. Ther Adv Neurol Disord. 2019;12:175628641988881. doi: 10.1177/1756286419888819.
    1. Bos I, Vos S, Verhey F, Scheltens P, Teunissen C, Engelborghs S, Sleegers K, Frisoni G, Blin O, Richardson JC, Bordet R, Tsolaki M, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Lleó A, Johannsen P, Freund-Levi Y, Frölich L, Vandenberghe R, Westwood S, Dobricic V, Barkhof F, Legido-Quigley C, Bertram L, Lovestone S, Streffer J, Andreasson U, Blennow K, Zetterberg H, Visser PJ. Cerebrospinal fluid biomarkers of neurodegeneration, synaptic integrity, and astroglial activation across the clinical Alzheimer’s disease spectrum. Alzheimers Dement. 2019;15(5):644–654. doi: 10.1016/j.jalz.2019.01.004.
    1. 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. 2016;15(7):673–684. doi: 10.1016/S1474-4422(16)00070-3.
    1. Fagan AM, Xiong C, Jasielec MS, Bateman RJ, Goate AM, Benzinger TLS, et al. Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer’s disease. Sci Transl Med. 2014;6:226ra30. doi: 10.1126/scitranslmed.3007901.
    1. Bateman RJ, Xiong C, Benzinger TLS, Fagan AM, Goate A, Fox NC, Marcus DS, Cairns NJ, Xie X, Blazey TM, Holtzman DM, Santacruz A, Buckles V, Oliver A, Moulder K, Aisen PS, Ghetti B, Klunk WE, McDade E, Martins RN, Masters CL, Mayeux R, Ringman JM, Rossor MN, Schofield PR, Sperling RA, Salloway S, Morris JC, Dominantly Inherited Alzheimer Network Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med. 2012;367(9):795–804. doi: 10.1056/NEJMoa1202753.
    1. Villeneuve S, Rabinovici GD, Cohn-Sheehy BI, Madison C, Ayakta N, Ghosh PM, la Joie R, Arthur-Bentil SK, Vogel JW, Marks SM, Lehmann M, Rosen HJ, Reed B, Olichney J, Boxer AL, Miller BL, Borys E, Jin LW, Huang EJ, Grinberg LT, DeCarli C, Seeley WW, Jagust W. Existing Pittsburgh Compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation. Brain. 2015;138(7):2020–2033. doi: 10.1093/brain/awv112.
    1. Bischof GN, Jacobs HIL. Subthreshold amyloid and its biological and clinical meaning. Neurology. 2019;93(2):72–79. doi: 10.1212/WNL.0000000000007747.
    1. Leal SL, Lockhart SN, Maass A, Bell RK, Jagust WJ. Subthreshold amyloid predicts tau deposition in aging. J Neurosci. 2018;38(19):4482–4489. doi: 10.1523/JNEUROSCI.0485-18.2018.
    1. Landau SM, Horng A, Jagust WJ. Memory decline accompanies subthreshold amyloid accumulation. Neurology. 2018;90(17):e1452–e1460. doi: 10.1212/WNL.0000000000005354.
    1. Bischof GN, Rodrigue KM, Kennedy KM, Devous MD, Park DC. Amyloid deposition in younger adults is linked to episodic memory performance. Neurology. 2016;87:2562–2566. doi: 10.1212/WNL.0000000000003425.
    1. 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. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. Lancet Neurol. 2013;12(4):357–367. doi: 10.1016/S1474-4422(13)70044-9.
    1. Jack CR, Wiste HJ, Lesnick TG, Weigand SD, Knopman DS, Vemuri P, Pankratz VS, Senjem ML, Gunter JL, Mielke MM, Lowe VJ, Boeve BF, Petersen RC. Brain β-amyloid load approaches a plateau. Neurology. 2013;80(10):890–896. doi: 10.1212/WNL.0b013e3182840bbe.
    1. Jack CR, Wiste HJ, Weigand SD, Therneau TM, Lowe VJ, Knopman DS, et al. Defining imaging biomarker cut points for brain aging and Alzheimer’s disease. Alzheimers Dement. 2017;13:205–216. doi: 10.1016/j.jalz.2016.08.005.
    1. Sutphen CL, McCue L, Herries EM, Xiong C, Ladenson JH, Holtzman DM, Fagan AM, On behalf of ADNI Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer’s disease. Alzheimers Dement. 2018;14(7):869–879. doi: 10.1016/j.jalz.2018.01.012.
    1. Molinuevo JL, Gramunt N, Gispert JD, Fauria K, Esteller M, Minguillon C, et al. The ALFA project: a research platform to identify early pathophysiological features of Alzheimer’s disease. Alzheimers Dement. 2016;2:82–92. doi: 10.1016/j.trci.2016.02.003.
    1. Teunissen CE, Tumani H, Engelborghs S, Mollenhauer B. Biobanking of CSF: international standardization to optimize biomarker development. Clin Biochem. 2014;47:288–292. doi: 10.1016/j.clinbiochem.2013.12.024.
    1. Milà-Alomà M, Salvadó G, Gispert JD, Vilor-Tejedor N, Grau-Rivera O, Sala-Vila A, Sánchez-Benavides G, Arenaza-Urquijo EM, Crous-Bou M, González-de-Echávarri JM, Minguillon C, Fauria K, Simon M, Kollmorgen G, Zetterberg H, Blennow K, Suárez-Calvet M, Molinuevo JL, for the ALFA study Amyloid beta, tau, synaptic, neurodegeneration, and glial biomarkers in the preclinical stage of the Alzheimer’s continuum. Alzheimers Dement. 2020;16(10):1358–1371. doi: 10.1002/alz.12131.
    1. Lifke V, Kollmorgen G, Manuilova E, Oelschlaegel T, Hillringhaus L, Widmann M, et al. Elecsys® Total-Tau and Phospho-Tau (181P) CSF assays: analytical performance of the novel, fully automated immunoassays for quantification of tau proteins in human cerebrospinal fluid. Clin Biochem. 2019;72:30–38. doi: 10.1016/j.clinbiochem.2019.05.005.
    1. Bittner T, Zetterberg H, Teunissen CE, Ostlund RE, Militello M, Andreasson U, et al. Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β-amyloid (1-42) in human cerebrospinal fluid. Alzheimers Dement. 2016;12:517–526. doi: 10.1016/j.jalz.2015.09.009.
    1. Agency EM. ANNEX I SUMMARY OF PRODUCT CHARACTERISTICS. Available from:
    1. Klunk WE, Koeppe RA, Price JC, Benzinger TL, Devous MD, Jagust WJ, et al. The Centiloid project: standardizing quantitative amyloid plaque estimation by PET. Alzheimers Dement. 2015;11:1–15.e4. doi: 10.1016/j.jalz.2014.07.003.
    1. Salvadó G, Molinuevo JL, Brugulat-Serrat A, Falcon C, Grau-Rivera O, Suárez-Calvet M, et al. Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers. Alzheimers Res Ther. 2019;11:27. doi: 10.1186/s13195-019-0478-z.
    1. Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, Weiner MW, Jagust WJ, Alzheimer's Disease Neuroimaging Initiative Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging. 2011;32(7):1207–1218. doi: 10.1016/j.neurobiolaging.2009.07.002.
    1. Fischl B. FreeSurfer. Neuroimage. 2012:774–81.
    1. Jack CR, Wiste HJ, Weigand SD, Therneau TM, Knopman DS, Lowe V, et al. Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50–95 years: a cross-sectional study. Lancet Neurol. 2017;16(6):435–444. doi: 10.1016/S1474-4422(17)30077-7.
    1. Landau SM, Lu M, Joshi AD, Pontecorvo M, Mintun MA, Trojanowski JQ, Shaw LM, Jagust WJ, for the Alzheimer's Disease Neuroimaging Initiative Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid. Ann Neurol. 2013;74(6):826–836. doi: 10.1002/ana.23908.
    1. Fortea J, Sala-Llonch R, Bartrés-Faz D, Lladó A, Solé-Padullés C, Bosch B, et al. Cognitively preserved subjects with transitional cerebrospinal fluid ß-amyloid 1-42 values have thicker cortex in Alzheimer’s disease vulnerable areas. Biol Psychiatry. 2011;70:183–190. doi: 10.1016/j.biopsych.2011.02.017.
    1. La Joie R, Ayakta N, Seeley WW, Borys E, Boxer AL, DeCarli C, et al. Multisite study of the relationships between antemortem [11 C]PIB-PET Centiloid values and postmortem measures of Alzheimer’s disease neuropathology. Alzheimers Dement. 2019;15:205–216. doi: 10.1016/j.jalz.2018.09.001.
    1. Amadoru S, Doré V, McLean CA, Hinton F, Shepherd CE, Halliday GM, et al. Comparison of amyloid PET measured in Centiloid units with neuropathological findings in Alzheimer’s disease. Alzheimers Res Ther. 2020;12:22. doi: 10.1186/s13195-020-00587-5.
    1. Leuzy A, Chiotis K, Hasselbalch SG, Rinne JO, de Mendonça A, Otto M, Lleó A, Castelo-Branco M, Santana I, Johansson J, Anderl-Straub S, von Arnim CAF, Beer A, Blesa R, Fortea J, Herukka SK, Portelius E, Pannee J, Zetterberg H, Blennow K, Nordberg A. Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study. Brain. 2016;139(9):2540–2553. doi: 10.1093/brain/aww160.
    1. Rowe CC, Doré V, Jones G, Baxendale D, Mulligan RS, Bullich S, et al. 18F-Florbetaben PET beta-amyloid binding expressed in Centiloids. Eur J Nucl Med Mol Imaging. 2017;44:2053–2059. doi: 10.1007/s00259-017-3749-6.
    1. AHEAD 3-45 study: a study to evaluate efficacy and safety of treatment with BAN2401 in participants with preclinical Alzheimer’s disease and elevated amyloid and also in participants with early preclinical Alzheimer’s disease and intermediate amyloid - Fu [Internet]. [cited 2020 Oct 15]. Available from:
    1. Benjamini, Yoav ; Hochberg Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57:289–300.
    1. Palmqvist S, Mattsson N, Hansson O. Cerebrospinal fluid analysis detects cerebral amyloid-β accumulation earlier than positron emission tomography. Brain. 2016;139(4):1226–1236. doi: 10.1093/brain/aww015.
    1. Mattsson N, Insel PS, Donohue M, Landau S, Jagust WJ, Shaw LM, Trojanowski JQ, Zetterberg H, Blennow K, Weiner MW, Alzheimer's Disease Neuroimaging Initiative* Independent information from cerebrospinal fluid amyloid-β and florbetapir imaging in Alzheimer’s disease. Brain. 2015;138(3):772–783. doi: 10.1093/brain/awu367.
    1. Milà-Alomà M, Salvadó G, Shekari M, Grau-Rivera O, Sala-Vila A, Sánchez-Benavides G, Arenaza-Urquijo EM, González-de-Echávarri JM, Simon M, Kollmorgen G, Zetterberg H, Blennow K, Gispert JD, Suárez-Calvet M, Molinuevo JL. Comparative analysis of different definitions of Amyloid-B positivity to detect early downstream pathophysiological alterations in preclinical Alzheimer. J Prev Alzheimer’s Dis. 2021;8(1):68–77. doi: 10.14283/jpad.2020.51.
    1. Chen CPC, Chen RL, Preston JE. The influence of ageing in the cerebrospinal fluid concentrations of proteins that are derived from the choroid plexus, brain, and plasma. Exp Gerontol. 2012;47(4):323–328. doi: 10.1016/j.exger.2012.01.008.
    1. Masseguin C, LePanse S, Corman B, Verbavatz JM, Gabrion J. Aging affects choroidal proteins involved in CSF production in Sprague-Dawley rats. Neurobiol Aging. 2005;26:917–927. doi: 10.1016/j.neurobiolaging.2004.07.013.
    1. Chiu C, Miller MC, Caralopoulos IN, Worden MS, Brinker T, Gordon ZN, et al. Temporal course of cerebrospinal fluid dynamics and amyloid accumulation in the aging rat brain from three to thirty months. Fluids Barriers CNS. 2012;9:3. doi: 10.1186/2045-8118-9-3.
    1. Van Harten AC, Wiste HJ, Weigand SD, Mielke MM, Kremers WK, Eichenlaub U, et al. CSF biomarkers in Olmsted County: evidence of 2 subclasses and associations with demographics. Neurology. 2020;95(3):E256–E267. doi: 10.1212/WNL.0000000000009874.
    1. Toledo JB, Zetterberg H, Van Harten AC, Glodzik L, Martinez-Lage P, Bocchio-Chiavetto L, et al. Alzheimer’s disease cerebrospinal fluid biomarker in cognitively normal subjects. Brain. 2015;138:2701–2715. doi: 10.1093/brain/awv199.

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