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Cerebrospinal Fluid Aβ 42/40 Corresponds Better than Aβ 42 to Amyloid PET in Alzheimer’s Disease
Abstract
Background: Decreased concentrations of amyloid-β 1-42 (Aβ 42 ) in cerebrospinal fluid (CSF) and increased retention of Aβ tracers in the brain on positron emission tomography (PET) are considered the earliest biomarkers of Alzheimer’s disease (AD). However, a proportion of cases show discrepancies between the results of the two biomarker modalities which may reflect inter-individual differences in Aβ metabolism. The CSF Aβ 42/40 ratio seems to be a more accurate biomarker of clinical AD than CSF Aβ 42 alone. Objective: We tested whether CSF Aβ 42 alone or the Aβ 42/40 ratio corresponds better with amyloid PET status and analyzed the distribution of cases with discordant CSF-PET results. Methods: CSF obtained from a mixed cohort ( n = 200) of cognitively normal and abnormal research participants who had undergone amyloid PET within 12 months ( n = 150 PET-negative, n = 50 PET-positive according to a previously published cut-off) was assayed for Aβ 42 and Aβ 40 using two recently developed immunoassays. Optimal CSF cut-offs for amyloid positivity were calculated, and concordance was tested by comparison of the areas under receiver operating characteristic (ROC) curves (AUC) and McNemar’s test for paired proportions. Results: CSF Aβ 42/40 corresponded better than Aβ 42 with PET results, with a larger proportion of concordant cases (89.4% versus 74.9%, respectively, p < 0.0001) and a larger AUC (0.936 versus 0.814, respectively, p < 0.0001) associated with the ratio. For both CSF biomarkers, the percentage of CSF-abnormal/PET-normal cases was larger than that of CSF-normal/PET-abnormal cases. Conclusion: The CSF Aβ 42/40 ratio is superior to Aβ 42 alone as a marker of amyloid-positivity by PET. We hypothesize that this increase in performance reflects the ratio compensating for general between-individual variations in CSF total Aβ.
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The Aβ42/40 ratio is decreased in AD patients reflecting increased brain amyloid plaque load, and has been helpful in the diagnosis of AD.
“The Aβ42/40 ratio is decreased in AD patients reflecting increased brain amyloid plaque load, and has been helpful in the diagnosis of AD [34, 35].”
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Cites
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
Self-citationClinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814
Self-citationAPOE predicts amyloid‐beta but not tau Alzheimer pathology in cognitively normal aging
Morris, J. C., Roe, C. M., Xiong, C., Fagan, A. M., Goate, A. M., Holtzman, D. M., & Mintun, M. A. (2010) · Annals of Neurology · doi:10.1002/ana.21843 · Cited by 830
Self-citationRelationships between biomarkers in aging and dementia
Jagust, W. J., Landau, S. M., Shaw, L. M., Trojanowski, J. Q., Koeppe, R. A., Reiman, E. M., Foster, N. L., Petersen, R. C., Weiner, M. W., Price, J. C., et al. (2009) · Neurology · doi:10.1212/wnl.0b013e3181bc010c · Cited by 456
Palmqvist, S., Mattsson, N., Hansson, O., & Initiative, F. T. A. D. N. (2016) · Brain · doi:10.1093/brain/aww015 · Cited by 400
Partial volume correction in quantitative amyloid imaging
Su, Y., Blazey, T. M., Snyder, A. Z., Raichle, M. E., Marcus, D. S., Ances, B. M., Bateman, R. J., Cairns, N. J., Aldea, P., Cash, L., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.058 · Cited by 247
Self-citationQuantitative Analysis of PiB-PET with FreeSurfer ROIs
Su, Y., D'Angelo, G. M., Vlassenko, A. G., Zhou, G., Snyder, A. Z., Marcus, D. S., Blazey, T. M., Christensen, J. J., Vora, S., Morris, J. C., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073377 · Cited by 246 · cited 3×
“anatomic reference as described previously [25, 26].”
MethodSelf-citationMattsson, N., Insel, P. S., Donohue, M., Landau, S., Jagust, W. J., Shaw, L. M., Trojanowski, J. Q., Zetterberg, H., Blennow, K., & Weiner, M. W. (2015) · Brain · doi:10.1093/brain/awu367 · Cited by 237
Self-citationApolipoprotein Eε4 modifies Alzheimer's disease onset in an E280A PS1 kindred
Pastor, P., Roe, C. M., Villegas, A., Bedoya, G., Chakraverty, S., García, G., Tirado, V., Norton, J., Ríos, S., Martínez, M., et al. (2003) · Annals of Neurology · doi:10.1002/ana.10636 · Cited by 194
Imaging and cerebrospinal fluid biomarkers in early preclinical alzheimer disease
Vlassenko, A. G., McCue, L., Jasielec, M. S., Su, Y., Gordon, B. A., Xiong, C., Holtzman, D. M., Benzinger, T. L. S., Morris, J. C., & Fagan, A. M. (2016) · Annals of Neurology · doi:10.1002/ana.24719 · Cited by 106
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Flagged first, then by citations
Research works printed but not linked: 29
- 10.1002/ana.20730 · DOI · Paper page
- 10.1016/j.neurobiolaging.2007.03.029 · DOI
- 10.1016/j.biopsych.2009.01.027 · DOI · Paper page
- 10.2967/jnumed.109.064360 · DOI
- 10.1001/archgenpsychiatry.2011.155 · DOI · Paper page
- 10.1001/jamaneurol.2015.1285 · DOI
- 10.1002/emmm.200900048 · DOI · Paper page
- 10.1016/j.tips.2015.03.002 · DOI · Paper page
- 10.1111/j.1471-4159.2006.04404.x · DOI
- 10.3233/JAD-140771 · DOI
- 10.1159/000100926 · DOI
- 10.3233/JAD-130107 · DOI
- 10.3233/JAD-2012-121267 · DOI
- 10.1373/clinchem.2005.058776 · DOI
- 10.1016/S0197-4580(03)00086-1 · DOI
- 10.1016/0022-3956(75)90026-6 · DOI · Paper page
- 10.1007/s00401-011-0808-0 · DOI
- 10.1002/ana.20009 · DOI · Paper page
- 10.1038/jcbfm.1990.127 · DOI
- 10.1212/01.wnl.0000228230.26044.a4 · DOI · Paper page
- 10.1002/ana.22608 · DOI
- 10.1093/cercor/bhg087 · DOI
- 10.3389/fneur.2015.00247 · DOI
- 10.1093/brain/aww168 · DOI
- 10.1002/acn3.274 · DOI · Paper page
- 10.1186/s13195-015-0159-5 · DOI
- 10.1016/j.dadm.2015.11.006 · DOI
- 10.1001/archneurol.2009.279 · DOI
- 10.1159/000225376 · DOI
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Blennow, K., & Zetterberg, H. (2018) · Journal of Internal Medicine · doi:10.1111/joim.12816 · Cited by 1,000
Self-citationCurrent state of Alzheimer’s fluid biomarkers
Molinuevo, J. L., Ayton, S., Batrla, R., Bednar, M. M., Bittner, T., Cummings, J., Fagan, A. M., Hampel, H., Mielke, M. M., Mikulskis, A., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1932-x · Cited by 518
Self-citationPalmqvist, S., Janelidze, S., Stomrud, E., Zetterberg, H., Karl, J., Zink, K., Bittner, T., Mattsson, N., Eichenlaub, U., Blennow, K., et al. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2019.1632 · Cited by 435
Self-citationEmerging diagnostics and therapeutics for Alzheimer disease
Self, W. K., & Holtzman, D. M. (2023) · Nature Medicine · doi:10.1038/s41591-023-02505-2 · Cited by 381
Palmqvist, S., Insel, P. S., Stomrud, E., Janelidze, S., Zetterberg, H., Brix, B., Eichenlaub, U., Dage, J. L., Chai, X., Blennow, K., et al. (2019) · EMBO Molecular Medicine · doi:10.15252/emmm.201911170 · Cited by 353
Self-citationHampel, H., Hu, Y., Cummings, J., Mattke, S., Iwatsubo, T., Nakamura, A., Vellas, B., O’Bryant, S., Shaw, L. M., Cho, M., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.05.017 · Cited by 283
Self-citationMoving fluid biomarkers for Alzheimer’s disease from research tools to routine clinical diagnostics
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Alcolea, D., Pegueroles, J., Muñoz, L., Camacho, V., López‐Mora, D., Fernández‐León, A., Le Bastard, N., Huyck, E., Nadal, A., Olmedo, V., et al. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50873 · Cited by 183
Cano, A., Turowski, P., Ettcheto, M., Duskey, J. T., Tosi, G., Sánchez-López, E., García, M. L., Camins, A., Souto, E. B., Ruiz, A., et al. (2021) · Journal of Nanobiotechnology · doi:10.1186/s12951-021-00864-x · Cited by 122
MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
ten Kate, M., Redolfi, A., Peira, E., Bos, I., Vos, S. J., Vandenberghe, R., Gabel, S., Schaeverbeke, J., Scheltens, P., Blin, O., et al. (2018) · Alzheimer's Research & Therapy · doi:10.1186/s13195-018-0428-1 · Cited by 78
Self-citationCilento, E. M., Jin, L., Stewart, T., Shi, M., Sheng, L., & Zhang, J. (2019) · Journal of Neurochemistry · doi:10.1111/jnc.14635 · Cited by 60
Medawar, E., Benway, T. A., Liu, W., Hanan, T. A., Haslehurst, P., James, O. T., Yap, K., Muessig, L., Moroni, F., Nahaboo Solim, M. A., et al. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2018.12.006 · Cited by 26
Gossye, H., Van Broeckhoven, C., & Engelborghs, S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00757 · Cited by 34
Biomarker-based signature of alzheimer's disease in pre-MCI individuals
Chipi, E., Salvadori, N., Farotti, L., & Parnetti, L. (2019) · Brain Sciences · doi:10.3390/brainsci9090213 · Cited by 27
Self-citationDi Caro, V., Cho, E., Thiel, J., Lizama, B. N., Koel-Simmelink, M. J. A., Pandey, K., Duong, D., Seyfried, N. T., Grundman, M., Teunissen, C. E., et al. (2026) · Alzheimer's Research & Therapy · doi:10.1186/s13195-026-02025-4 · Cited by 1
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Metadata
- Authors
- Lewczuk, P., Matzen, A., Blennow, K., Parnetti, L., Molinuevo, J. L., Eusebi, P., Kornhuber, J., Morris, J. C., & Fagan, A. M.
- Affiliations
- Universitätsklinikum Erlangen
- IBL International GmbH, Hamburg, Germany
- the Sahlgrenska Academy at the University of Gothenburg
- University of Perugia
- Hospital Clínic de Barcelona – Universitat de Barcelona
- Washington University School of Medicine
- Venue
- Journal of Alzheimer’s Disease
- Publisher
- SAGE Publications
- Published
- 2016-10-14
- Volume
- 55
- Issue
- 2
- Pages
- 813-822
- ISSN
- 1387-2877
- 1875-8908
- PMC
- PMC5147502
- Cited by
- 253
- References
- 12
- Language
- en
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