The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis
Open accessAbstract
Background Alzheimer's disease biomarkers are important for early diagnosis in routine clinical practice and research. Three core CSF biomarkers for the diagnosis of Alzheimer's disease (Aβ42, T-tau, and P-tau) have been assessed in numerous studies, and several other Alzheimer's disease markers are emerging in the literature. However, there have been no comprehensive meta-analyses of their diagnostic performance. We systematically reviewed the literature for 15 biomarkers in both CSF and blood to assess which of these were most altered in Alzheimer's disease.Methods In this systematic review and meta-analysis, we screened PubMed and Web of Science for articles published between July 1, 1984, and June 30, 2014, about CSF and blood biomarkers reflecting neurodegeneration (T-tau, NFL, NSE, VLP-1, and HFABP), APP metabolism (Aβ42, Aβ40, Aβ38, sAPPα, and sAPPβ), tangle pathology (P-tau), blood-brain-barrier function (albumin ratio), and glial activation (YKL-40, MCP-1, and GFAP). Data were taken from cross-sectional cohort studies as well as from baseline measurements in longitudinal studies with clinical follow-up. Articles were excluded if they did not contain a cohort with Alzheimer's disease and a control cohort, or a cohort with mild cognitive impairment due to Alzheimer's disease and a stable mild cognitive impairment cohort. Data were extracted by ten authors and checked by two for accuracy. For quality assessment, modified QUADAS criteria were used. Biomarker performance was rated by random-effects meta-analysis based on the ratio between biomarker concentration in patients with Alzheimer's disease and controls (fold change) or the ratio between biomarker concentration in those with mild cognitive impariment due to Alzheimer's disease and those with stable mild cognitive impairment who had a follow-up time of at least 2 years and no further cognitive decline.Findings Of 4521 records identified from PubMed and 624 from Web of Science, 231 articles comprising 15 699 patients with Alzheimer's disease and 13 018 controls were included in this analysis. The core biomarkers differentiated Alzheimer's disease from controls with good performance: CSF T-tau (average ratio 2·54, 95% CI 2·44-2·64, p<0·0001), P-tau (1·88, 1·79-1·97, p<0·0001), and Aβ42 (0·56, 0·55-0·58, p<0·0001). Differentiation between cohorts with mild cognitive impairment due to Alzheimer's disease and those with stable mild cognitive impairment was also strong (average ratio 0·67 for CSF Aβ42, 1·72 for P-tau, and 1·76 for T-tau). Furthermore, CSF NFL (2·35, 1·90-2·91, p<0·0001) and plasma T-tau (1·95, 1·12-3·38, p=0·02) had large effect sizes when differentiating between controls and patients with Alzheimer's disease, whereas those of CSF NSE, VLP-1, HFABP, and YKL-40 were moderate (average ratios 1·28-1·47). Other assessed biomarkers had only marginal effect sizes or did not differentiate between control and patient samples.Interpretation The core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer's disease and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer's disease. Emerging CSF biomarkers NSE, VLP-1, HFABP, and YKL-40 were moderately associated with Alzheimer's disease, whereas plasma Aβ42 and Aβ40 were not. Due to their consistency, T-tau, P-tau, Aβ42, and NFL in CSF should be used in clinical practice and clinical research.Funding Swedish Research Council, Swedish State Support for Clinical Research, Alzheimer's Association, Knut and Alice Wallenberg Foundation, Torsten Söderberg Foundation, Alzheimer Foundation (Sweden), European Research Council, and Biomedical Research Forum.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Notably, P-tau181 concentration is the most accurate indicator for differentiating AD from non-AD dementia.372,373”
From Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies. (2024) · cites this paper as [372]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The only disorder that consistently shows an increase in CSF P-tau is AD [143], whereas this biomarker is normal in other neurodegenerative disorders.”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [143]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Increased concentrations of extracellular soluble phosphorylated tau (p-tau) and total tau (t-tau) constitute a reliable index of this intracellular process in mild cognitive impairment due to AD2,3 and AD dementia.2,4”
From Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease (2022) · cites this paper as [2]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The most thoroughly examined P-tau epitope as a CSF biomarker for AD is threonine 181 (P-tau181) [143], but assays for the concentration of P-tau231 and P-tau199 correlate tightly with P-tau181 and show very similar diagnostic accuracy [144].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [143]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“CSF tau levels are not increased in non-AD tauopathies57–60, suggesting that extracellular tau is not a primary target in these conditions.”
From Tau-targeting therapies for Alzheimer disease (2018) · cites this paper as [59]
Experimental — accuracy not yet measured
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The only disorder that consistently shows an increase in CSF P-tau is AD [143], whereas this biomarker is normal in other neurodegenerative disorders.”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [143]
Experimental — accuracy not yet measuredIn the citing paper
“A recent meta-analysis confirmed elevated levels of YKL-40 in AD dementia, although the association with AD was moderate compared with the core CSF AD biomarkers Aβ42, t-tau, and p-tau.25”
From CSF biomarkers of neuroinflammation and cerebrovascular dysfunction in early Alzheimer disease (2018) · cites this paper as [25]
In the citing paper
“along with levels of various additional proteins, the clinical and biological relevance of which remain to be elucidated [216–218].”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [218]
In the citing paper
“CSF tau levels are not increased in non-AD tauopathies57–60, suggesting that extracellular tau is not a primary target in these conditions.”
From Tau-targeting therapies for Alzheimer disease (2018) · cites this paper as [59]
In the citing paper
“Of note, CSF tau levels are increased in AD but not in the other tauopathies57–60, suggesting that extracellular spread of tau pathology is not a prominent feature of non-AD tauopathies.”
From Tau-targeting therapies for Alzheimer disease (2018) · cites this paper as [59]
In the citing paper
“reduced concentrations of Aβ42 in CSF and increased retention of Aβ tracers in the brain have been considered as early biomarkers of AD.255–258”
From Amyloid β-based therapy for Alzheimer’s disease: Challenges, successes and future (2023) · cites this paper as [255]
In the citing paper
“Attempts to discover new biomarkers for the diagnosis of early stages of the disease are ongoing [134–136].”
From Brain-Derived Neurotrophic Factor in Brain Disorders: Focus on Neuroinflammation (2019) · cites this paper as [135]
In the citing paper
“CHI3L1, which encodes YKL-40 protein, is expressed in astrocytes and is a biomarker of inflammation in Alzheimer’s disease [48]”
From Transmembrane protein 97 is a potential synaptic amyloid beta receptor in human Alzheimer’s disease (2024) · cites this paper as [48]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000100 · Cited by 28,164
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gotzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · BMJ · doi:10.1136/bmj.b2700 · Cited by 17,648
Development of AMSTAR: A measurement tool to assess the methodological quality of systematic reviews
Shea, B. J., Grimshaw, J. M., Wells, G. A., Boers, M., Andersson, N., Hamel, C., Porter, A. C., Tugwell, P., Moher, D., & Bouter, L. M. (2007) · BMC Medical Research Methodology · doi:10.1186/1471-2288-7-10 · Cited by 4,374
Clinical 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
Blennow, K., de Leon, M. J., & Zetterberg, H. (2006) · The Lancet · doi:10.1016/s0140-6736(06)69113-7 · Cited by 3,134
Self-citationTwo Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer's Disease
Salloway, S., Sperling, R., Fox, N. C., Blennow, K., Klunk, W., Raskind, M., Sabbagh, M., Honig, L. S., Porsteinsson, A. P., Ferris, S., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1304839 · Cited by 1,960
Self-citationCerebrospinal fluid and plasma biomarkers in Alzheimer disease
Blennow, K., Hampel, H., Weiner, M., & Zetterberg, H. (2010) · Nature Reviews Neurology · doi:10.1038/nrneurol.2010.4 · Cited by 1,863
Self-citationPrevalence of Cerebral Amyloid Pathology in Persons Without Dementia: A Meta-analysis
Jansen, W. J., Ossenkoppele, R., Knol, D. L., Tijms, B. M., Scheltens, P., Verhey, F. R. J., Visser, P. J., Aalten, P., Aarsland, D., Alcolea, D., et al. (2015) · JAMA · doi:10.1001/jama.2015.4668 · Cited by 1,610
Self-citation
Cited by
Sorted by citations
Items 101–128 of 128
Korábečný, J., Nepovimová, E., Cikánková, T., Špilovská, K., Vašková, L., Mezeiová, E., Kuča, K., & Hroudová, J. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2017.06.034 · Cited by 64
Tau-targeting therapy in Alzheimer’s disease: Critical advances and future opportunities
Guo, Y., Li, S., Zeng, L.-H., & Tan, J. (2022) · Ageing and Neurodegenerative Diseases · doi:10.20517/and.2022.16 · Cited by 61
Ali, M., Timsina, J., Western, D., Liu, M., Beric, A., Budde, J., Do, A., Heo, G., Wang, L., Gentsch, J., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.02.014 · Cited by 61
Li, J., Ni, W., Jin, D., Yu, Y., Xiao, M.-M., Zhang, Z.-Y., & Zhang, G.-J. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.2c05751 · Cited by 60
Cerebrospinal fluid vasopressin and symptom severity in children with autism
Oztan, O., Garner, J. P., Partap, S., Sherr, E. H., Hardan, A. Y., Farmer, C., Thurm, A., Swedo, S. E., & Parker, K. J. (2018) · Annals of Neurology · doi:10.1002/ana.25314 · Cited by 59
Cilento, E. M., Jin, L., Stewart, T., Shi, M., Sheng, L., & Zhang, J. (2019) · Journal of Neurochemistry · doi:10.1111/jnc.14635 · Cited by 60
Comparison of CSF phosphorylated tau 181 and 217 for cognitive decline
Mielke, M. M., Aakre, J. A., Algeciras‐Schimnich, A., Proctor, N. K., Machulda, M. M., Eichenlaub, U., Knopman, D. S., Vemuri, P., Graff‐Radford, J., Jack, C. R., et al. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12415 · Cited by 55
Calpain-mediated tau fragmentation is altered in Alzheimer’s disease progression
Chen, H.-H., Liu, P., Auger, P., Lee, S.-H., Adolfsson, O., Rey-Bellet, L., Lafrance-Vanasse, J., Friedman, B. A., Pihlgren, M., Muhs, A., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-35130-y · Cited by 51
Two‐level diagnostic classification using cerebrospinal fluid YKL‐40 in Alzheimer's disease
Baldacci, F., Toschi, N., Lista, S., Zetterberg, H., Blennow, K., Kilimann, I., Teipel, S., Cavedo, E., dos Santos, A. M., Epelbaum, S., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.01.021 · Cited by 53
Self-citationTau and neurofilament light‐chain as fluid biomarkers in spinocerebellar ataxia type 3
Garcia‐Moreno, H., Prudencio, M., Thomas‐Black, G., Solanky, N., Jansen‐West, K. R., Hanna AL‐Shaikh, R., Heslegrave, A., Zetterberg, H., Santana, M. M., Pereira de Almeida, L., et al. (2022) · European Journal of Neurology · doi:10.1111/ene.15373 · Cited by 49
Self-citationMulticenter Alzheimer's and Parkinson's disease immune biomarker verification study
Brosseron, F., Kolbe, C., Santarelli, F., Carvalho, S., Antonell, A., Castro‐Gomez, S., Tacik, P., Namasivayam, A. A., Mangone, G., Schneider, R., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.07.018 · Cited by 47
Vijverberg, E. G. B., Dols, A., Krudop, W. A., Del Campo Milan, M., Kerssens, C. J., Gossink, F., Prins, N. D., Stek, M. L., Scheltens, P., Teunissen, C. E., et al. (2017) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.01.009 · Cited by 46
Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer’s Disease
Rani, S., Dhar, S. B., Khajuria, A., Gupta, D., Jaiswal, P. K., Singla, N., Kaur, M., Singh, G., & Barnwal, R. P. (2023) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-023-01330-y · Cited by 48
Urinary metabolic phenotyping for Alzheimer’s disease
Kurbatova, N., Garg, M., Whiley, L., Chekmeneva, E., Jiménez, B., Gómez-Romero, M., Pearce, J., Kimhofer, T., D’Hondt, E., Soininen, H., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-78031-9 · Cited by 44
Genetic risk factors for Alzheimer disease: emerging roles of microglia in disease pathomechanisms
Takatori, S., Wang, W., Iguchi, A., & Tomita, T. (2019) · Advances in Experimental Medicine and Biology · doi:10.1007/978-3-030-05542-4_5 · Cited by 44
Transmembrane protein 97 is a potential synaptic amyloid beta receptor in human Alzheimer’s disease
Colom-Cadena, M., Toombs, J., Simzer, E., Holt, K., McGeachan, R., Tulloch, J., Jackson, R. J., Catterson, J. H., Spires-Jones, M. P., Rose, J., et al. (2024) · Acta Neuropathologica · doi:10.1007/s00401-023-02679-6 · Cited by 44
Diagnostic biomarkers in Alzheimer’s disease
Andersen, E., Casteigne, B., Chapman, W. D., Creed, A., Foster, F., Lapins, A., Shatz, R., & Sawyer, R. P. (2021) · Biomarkers in Neuropsychiatry · doi:10.1016/j.bionps.2021.100041 · Cited by 42
Blood Biomarkers for Alzheimer’s Disease: Much Promise, Cautious Progress
Keshavan, A., Heslegrave, A., Zetterberg, H., & Schott, J. M. (2017) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-016-0241-0 · Cited by 34
Self-citationAlzheimer’s disease: From basic science to precision medicine approach
Forloni, G. (2020) · BMJ Neurology Open · doi:10.1136/bmjno-2020-000079 · Cited by 33
Progress and challenges in the diagnosis of dementia: a critical review
Paraskevaidi, M., Martin-Hirsch, P. L., & Martin, F. L. (2018) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.8b00007 · Cited by 31
Cerebrospinal Fluid Biomarkers in Alzheimer’s Disease—From Brain Starch to Bench and Bedside
Pawlowski, M., Meuth, S., & Duning, T. (2017) · Diagnostics · doi:10.3390/diagnostics7030042 · Cited by 25
Panza, F., Dibello, V., Sardone, R., Castellana, F., Zupo, R., Lampignano, L., Bortone, I., Stallone, R., Cirillo, N., Damiani, C., et al. (2023) · Expert Opinion on Investigational Drugs · doi:10.1080/13543784.2023.2233892 · Cited by 22
Conrado, D. J., Duvvuri, S., Geerts, H., Burton, J., Biesdorf, C., Ahamadi, M., Macha, S., Hather, G., Francisco Morales, J., Podichetty, J., et al. (2020) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1782 · Cited by 21
Marelli, C., Hourregue, C., Gutierrez, L.-A., Paquet, C., Menjot de Champfleur, N., De Verbizier, D., Jacob, M., Dubois, J., Maleska, A. M., Hirtz, C., et al. (2020) · Journal of Alzheimer's Disease · doi:10.3233/jad-190378 · Cited by 21
Chen, Y., Wang, Y., Tao, Q., Lu, P., Meng, F., Zhuang, L., Qiao, S., Zhang, Y., Luo, B., Liu, Y., et al. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2024.118784 · Cited by 21
Association of brain network dynamics with plasma biomarkers in subjective memory complainers
Chiesa, P. A., Houot, M., Vergallo, A., Cavedo, E., Lista, S., Potier, M. C., Zetterberg, H., Blennow, K., Vanmechelen, E., De Vos, A., et al. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.12.017 · Cited by 7
Self-citationSifting through a failed Alzheimer trial: What biomarkers tell us about what happened
Knopman, D. S. (2018) · Neurology · doi:10.1212/wnl.0000000000005073 · Cited by 5
Generating MRI ‐Derived CSF Proxy‐Markers to Predict and Visualize Alzheimer's Disease Progression
Abrol, A., Calhoun, V. D., & Initiative, T. A. D. N. (2025) · Human Brain Mapping · doi:10.1002/hbm.70391 · Cited by 3
Metadata
- Authors
- 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.
- Affiliations
- University of Gothenburg (SE)
- University of Antwerp (BE)
- Alzforum (US)
- University of the Witwatersrand (ZA)
- UCL Queen Square Institute of Neurology (GB)
- Corresponding author
- Olsson, Bob
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 15
- Issue
- 7
- Pages
- 673-684
- ISSN
- 1474-4422 (ISSN-L)
- OpenAlex
- W2327547544
- Cited by
- 2,049
- References
- 35
- Citations by year
- 2026: 123 · 2025: 200 · 2024: 243 · 2023: 214 · 2022: 240 · 2021: 253 · 2020: 228 · 2019: 198 · 2018: 188 · 2017: 114 · 2016: 42
- FWCI
- 25.79
- Type
- journal article
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Licence
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Chalmers Publication Library (Chalmers University of Technology) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion, other-oa)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- Funders
- Knut och Alice Wallenbergs Stiftelse
- Vetenskapsrådet
- H2020 European Research Council (681712)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Clinical Neurology › Cerebrospinal fluid and hydrocephalus
- Keywords
- Alzheimer's disease, biomarkers, cerebrospinal fluid biomarkers, blood biomarkers, amyloid-beta 42, tau protein, phosphorylated tau, neurofilament light chain, neurotensin, APP metabolism, blood-brain barrier, YKL-40, glial activation, mild cognitive impairment, diagnostic accuracy, early diagnosis, neurodegeneration, amyloid plaques
- MeSH terms
- Alzheimer Disease, Humans, Biomarkers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review