Association Between Longitudinal Plasma Neurofilament Light and Neurodegeneration in Patients With Alzheimer Disease
Open accessAbstract
Importance: Plasma neurofilament light (NfL) has been suggested as a noninvasive biomarker to monitor neurodegeneration in Alzheimer disease (AD), but studies are lacking. Objective: To examine whether longitudinal plasma NfL levels are associated with other hallmarks of AD. Design, Setting, and Participants: This North American cohort study used data from 1583 individuals in the multicenter Alzheimer's Disease Neuroimaging Initiative study from September 7, 2005, through June 16, 2016. Patients were eligible for inclusion if they had NfL measurements. Annual plasma NfL samples were collected for up to 11 years and were analyzed in 2018. Exposures: Clinical diagnosis, Aβ and tau cerebrospinal fluid (CSF) biomarkers, imaging measures (magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography), and tests on cognitive scores. Main Outcomes and Measures: The primary outcome was the association between baseline exposures (diagnosis, CSF biomarkers, imaging measures, and cognition) and longitudinal plasma NfL levels, analyzed by an ultrasensitive assay. The secondary outcomes were the associations between a multimodal classification scheme with Aβ, tau, and neurodegeneration (ie, the ATN system) and plasma NfL levels and between longitudinal changes in plasma NfL levels and changes in the other measures. Results: Of the included 1583 participants, 716 (45.2%) were women, and the mean (SD) age was 72.9 (7.1) years; 401 had no cognitive impairment, 855 had mild cognitive impairment, and 327 had AD dementia. The NfL level was increased at baseline in patients with mild cognitive impairment and AD dementia (mean levels: cognitive unimpairment, 32.1 ng/L; mild cognitive impairment, 37.9 ng/L; and AD dementia, 45.9 ng/L; P < .001) and increased in all diagnostic groups, with the greatest increase in patients with AD dementia. A longitudinal increase in NfL level correlated with baseline CSF biomarkers (low Aβ42 [P = .001], high total tau [P = .02], and high phosphorylated tau levels [P = .02]), magnetic resonance imaging measures (small hippocampal volumes [P < .001], thin regional cortices [P = .009], and large ventricular volumes [P = .002]), low fluorodeoxyglucose-positron emission tomography uptake (P = .01), and poor cognitive performance (P < .001) for a global cognitive score. With use of the ATN system, increased baseline NfL levels were seen in A-T+N+ (P < .001), A+T-N+ (P < .001), and A+T+N+ (P < .001), and increased rates of NfL levels were seen in A-T+N- (P = .009), A-T+N+ (P = .02), A+T-N+ (P = .04), and A+T+N+ (P = .002). Faster increase in NfL levels correlated with faster increase in CSF biomarkers of neuronal injury, faster rates of atrophy and hypometabolism, and faster worsening in global cognition (all P < .05 in patients with mild cognitive impairment; associations differed slightly in cognitively unimpaired controls and patients with AD dementia). Conclusions and Relevance: The findings suggest that plasma NfL can be used as a noninvasive biomarker associated with neurodegeneration in patients with AD and may be useful to monitor effects in trials of disease-modifying drugs.
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
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?
Biomarkers of neurodegeneration (hippocampal atrophy, medial cortex thinning, low FDG-PET glucose uptake, raised CSF neurofilament light) are more closely associated temporally with cognitive decline than amyloid and tau fluid biomarkers.
“Biomarkers of neurodegeneration, such as hippocampal atrophy, medial cortex thinning, low glucose uptake on fluorodeoxyglucose (FDG)-PET, or raised CSF neurofilament light (NFL- a non-specific marker of neurodegeneration), are more closely associated temporally with cognitive decline than amyloid and tau fluid biomarkers.(444)”
From Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission (2024) · cites this paper as [444]
The Abstract and Discussion (pages unavailable) report that neurofilament light tracks worsening cognition and atrophy, and the paper measures hippocampal volume, cortical thickness, and FDG-PET uptake. But its longitudinal neurofilament findings concern plasma, not CSF, and it does not establish that these neurodegeneration markers are more closely associated in time with cognitive decline than amyloid and tau fluid biomarkers. (LLM, conf=0.85)
Experimental — accuracy not yet measuredNfL in blood shows a clear increase in AD and tracks neurofibrillary tangle load and cognitive decline.
“Whereas blood t-tau shows no diagnostic potential for AD, 13 NfL in blood shows a clear increase in AD, 4 and also tracks neurofibrillary tangle load and cognitive decline.14,15”
From Plasma Tau and Neurofilament Light in Frontotemporal Lobar Degeneration and Alzheimer Disease (2021) · cites this paper as [15]
The Abstract and Discussion report that changes in plasma NfL correlate with worsening cognition, and the Abstract reports associations with CSF tau biomarkers. The paper does not report measuring neurofibrillary tangle load, so the claim that NfL tracks tangle load is not established by this source. (LLM, conf=0.87)
Experimental — accuracy not yet measuredIn Alzheimer disease, elevated plasma neurofilament light tracks with quicker global cognitive decline and faster atrophy.
“This study also replicated the findings of previous investigations supporting that, in AD, high plasma NfL correlates with faster worsening in global cognition and faster atrophy rates.4,15”
From Plasma Tau and Neurofilament Light in Frontotemporal Lobar Degeneration and Alzheimer Disease (2021) · cites this paper as [15]
Several studies have demonstrated that plasma Aβ40, Aβ42, P-tau and NfL are to some extent correlated with PET scan and CSF detection results.
“Several studies have demonstrated that plasma Aβ40, Aβ42, phosphorylated tau (P-tau) and neurofilament light (NfL) are to some extent correlated with PET scan and CSF detection results6–8.”
From Integrated algorithm combining plasma biomarkers and cognitive assessments accurately predicts brain β-amyloid pathology (2023) · cites this paper as [8]
NfL is elevated in AD and provides prognostic insight into ongoing neurodegeneration.
“In addition, plasma Aβ42/Aβ40 ratios have demonstrated potential for reflecting cerebral amyloid burden88, while NfL, a marker of axonal damage, is elevated in AD and provides prognostic insight into ongoing neurodegeneration89.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [89]
Studies correlating transcriptomic profiles with proteomic, metabolomic, and epigenomic data have revealed key discrepancies between RNA and protein expression in AD.
“Studies correlating transcriptomic profiles with proteomic, metabolomic, and epigenomic data have already revealed key discrepancies between RNA and protein expression in AD89,159,160.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [89]
The Statistical Analysis and Discussion sections describe correlations between plasma neurofilament light and AD biomarkers, imaging, and cognition; page numbers are unavailable in our copy. Searches for transcriptomic profiles and RNA–protein expression discrepancies found no passage addressing the claim. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn ADAD and LOAD, the rate of change in CSF and plasma NfL correlates with cortical thickness on structural MRI and cognitive performance.
“Studies of both ADAD and LOAD have demonstrated that rate of change in CSF and plasma NfL levels correlate with cortical thickness on structural MRI and cognitive performance”
From Alzheimer Disease: An Update on Pathobiology and Treatment Strategies (2019) · cites this paper as Mattsson et al., 2019
Plasma NfL, a measure of neuronal degeneration, is increasingly elevated as AD progresses.
“Plasma NfL, a measure of neuronal degeneration, is increasingly elevated as AD progresses. 30”
From Alzheimer’s disease drug development pipeline: 2021 (2021) · cites this paper as [30]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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 · see citing works
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020 · see citing works
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007) · The Lancet · doi:10.1016/s0140-6736(07)61602-x · Cited by 21,320 · see citing works
Correspondence - Tranexamic acid for traumatic brain injury
(2005) · London School of Economics and Political Science Theses Online (London School of Economics and Political Science) · doi:10.1016/s0140-6736 · Cited by 11,894 · see citing works
NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.02.018 · Cited by 10,537 · see citing works
Self-citationThe Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods
Jack, C. R., Bernstein, M. A., Fox, N. C., Thompson, P., Alexander, G., Harvey, D., Borowski, B., Britson, P. J., L. Whitwell, J., Ward, C., et al. (2008) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21049 · Cited by 4,347 · see citing works
Scheltens, P., Blennow, K., Breteler, M. M. B., de Strooper, B., Frisoni, G. B., Salloway, S., & Van der Flier, W. M. (2016) · The Lancet · doi:10.1016/s0140-6736(15)01124-1 · Cited by 3,125 · see citing works
Self-citationAlzheimer's Disease Neuroimaging Initiative (ADNI)
Petersen, R. C., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Shaw, L. M., Toga, A. W., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181cb3e25 · Cited by 2,572 · see citing works
Serum neurofilament light: a biomarker of neuronal damage in multiple sclerosis
Disanto, G., Barro, C., Benkert, P., Naegelin, Y., Schädelin, S., Giardiello, A., Zecca, C., Blennow, K., Zetterberg, H., Leppert, D., et al. (2017) · Annals of Neurology · doi:10.1002/ana.24954 · Cited by 1,164 · see citing works
Self-citationAssociation of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease
Mattsson, N., Andreasson, U., Zetterberg, H., Blennow, K., & Initiative, F. T. A. D. N. (2017) · JAMA Neurology · doi:10.1001/jamaneurol.2016.6117 · Cited by 1,070 · see citing works
Self-citationHansson, O., Seibyl, J., Stomrud, E., Zetterberg, H., Trojanowski, J. Q., Bittner, T., Lifke, V., Corradini, V., Eichenlaub, U., Batrla, R., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.01.010 · Cited by 808 · see citing works
Self-citationAmyloid Deposition, Hypometabolism, and Longitudinal Cognitive Decline
Landau, S. M., Mintun, M., Joshi, A. D., Koeppe, R., Petersen, R. C., Aisen, P., Weiner, M., & Jagust, W. J. (2012) · Annals of Neurology · doi:10.1002/ana.23650 · Cited by 723 · see citing works
Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic
Hampel, H., O’Bryant, S. E., Molinuevo, J. L., Zetterberg, H., Masters, C. L., Lista, S., Kiddle, S. J., Batrla, R., & Blennow, K. (2018) · Nature Reviews Neurology · doi:10.1038/s41582-018-0079-7 · Cited by 716 · see citing works
Self-citationJournal of Magnetic Resonance Imaging
Illes, J., Kirschen, M. P., Karetsky, K., Kelly, M., Saha, A., Desmond, J. E., Raffin, T. A., Glover, G. H., & Atlas, S. W. (2006) · Journal of Magnetic Resonance Imaging · doi:10.1002/(issn)1522-2586 · Cited by 667 · see citing works
Gisslén, M., Price, R. W., Andreasson, U., Norgren, N., Nilsson, S., Hagberg, L., Fuchs, D., Spudich, S., Blennow, K., & Zetterberg, H. (2016) · EBioMedicine · doi:10.1016/j.ebiom.2015.11.036 · Cited by 481 · see citing works
Self-citationSerum neurofilament light chain protein is a measure of disease intensity in frontotemporal dementia
Rohrer, J. D., Woollacott, I., Dick, K. M., Brotherhood, E., Gordón, E., Fellows, A. D., Toombs, J., Druyeh, R., Cardoso, M. J., Sebastien Ourselin, A., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000003154 · Cited by 431 · see citing works
Self-citationBittner, T., Zetterberg, H., Teunissen, C. E., Ostlund, R. E., Militello, M., Andreasson, U., Hubeek, I., Gibson, D., Chu, D. C., Eichenlaub, U., et al. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.09.009 · Cited by 374 · see citing works
Serum neurofilament light protein predicts clinical outcome in traumatic brain injury
Shahim, P., Gren, M., Liman, V., Andreasson, U., Norgren, N., Tegner, Y., Mattsson, N., Andreasen, N., Öst, M., Zetterberg, H., et al. (2016) · Scientific Reports · doi:10.1038/srep36791 · Cited by 336 · see citing works
Self-citationSerum Neurofilament Light Chain for Prognosis of Outcome After Cardiac Arrest
Knappe, M. M., Mattsson, N., Nielsen, N., Zetterberg, H., Blennow, K., Dankiewicz, J., Dragancea, I., Friberg, H., Lilja, G., Insel, P. S., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2018.3223 · Cited by 266 · see citing works
Self-citationJack, C. R., Wiste, H. J., Weigand, S. D., Knopman, D. S., Mielke, M. M., Vemuri, P., Lowe, V. J., Senjem, M. L., Gunter, J. L., Reyes, D. A., et al. (2015) · Brain · doi:10.1093/brain/awv283 · Cited by 252 · see citing works
Magnetic resonance imaging in Alzheimer’s disease neuroimaging initiative 2
Jack, C. R., Barnes, J., Bernstein, M. A., Borowski, B. J., Brewer, J., Clegg, S., Dale, A. M., Carmichael, O., Ching, C., DeCarli, C., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.05.002 · Cited by 220 · see citing works
Self-citation18F‐AV‐1451 and CSF T‐tau and P‐tau as biomarkers in Alzheimer's disease
Mattsson, N., Schöll, M., Strandberg, O., Smith, R., Palmqvist, S., Insel, P. S., Hägerström, D., Ohlsson, T., Zetterberg, H., Jögi, J., et al. (2017) · EMBO Molecular Medicine · doi:10.15252/emmm.201707809 · Cited by 177 · see citing works
Self-citationThe Past and the Future of Alzheimer’s Disease Fluid Biomarkers
Blennow, K., & Zetterberg, H. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-170773 · Cited by 148 · see citing works
Self-citationInformation Processing in Medical Imaging
Prince, J. L., Myers, K. J., & Pham, D. L. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02498-6 · Cited by 138 · see citing works
Serum neurofilament light chain in patients with acute cerebrovascular events
Marchis, G. M. D., Mira, K., Barro, C., Fladt, J. C., Traenka, C., Seiffge, D. J., Hert, L., Gensicke, H., Disanto, G., Sutter, R., et al. (2017) · European Journal of Neurology · doi:10.1111/ene.13554 · Cited by 112 · see citing works
Schwarz, C. G., Fletcher, E., DeCarli, C. S., & Carmichael, O. T. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02498-6_20 · Cited by 100 · see citing works
Kovács, G. G., Andreasson, U., Liman, V., Regelsberger, G., Lutz, M. I., Danics, K., Keller, É., Zetterberg, H., & Blennow, K. (2017) · European Journal of Neurology · doi:10.1111/ene.13389 · Cited by 90 · see citing works
Self-citationMolecular imaging in dementia: Past, present, and future
Laforce, R. J., Soucy, J., Sellami, L., Dallaire‐Théroux, C., Brunet, F., Bergeron, D., Miller, B. L., & Ossenkoppele, R. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.06.2855 · Cited by 87 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission
Livingston, G., Huntley, J., Liu, K. Y., Costafreda, S. G., Selbæk, G., Alladi, S., Ames, D., Banerjee, S., Burns, A., Brayne, C., et al. (2024) · The Lancet · doi:10.1016/s0140-6736(24)01296-0 · Cited by 3,860 · see citing works
Alzheimer Disease: An Update on Pathobiology and Treatment Strategies
Long, J. M., & Holtzman, D. M. (2019) · Cell · doi:10.1016/j.cell.2019.09.001 · Cited by 3,204 · see citing works
Karikari, T. K., Pascoal, T. A., Ashton, N. J., Janelidze, S., Benedet, A. L., Rodriguez, J. L., Chamoun, M., Savard, M., Kang, M. S., Therriault, J., et al. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30071-5 · Cited by 1,316 · see citing works
Self-citationJanelidze, S., Mattsson, N., Palmqvist, S., Smith, R., Beach, T. G., Serrano, G. E., Chai, X., Proctor, N. K., Eichenlaub, U., Zetterberg, H., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0755-1 · Cited by 1,247 · see citing works
Self-citationAdvancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) investigators, Thijssen, E. H., La Joie, R., Wolf, A., Strom, A., Wang, P., Iaccarino, L., Bourakova, V., Cobigo, Y., Heuer, H., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0762-2 · Cited by 761 · see citing works
Self-citationBlood-based biomarkers for Alzheimer disease: mapping the road to the clinic
Hampel, H., O’Bryant, S. E., Molinuevo, J. L., Zetterberg, H., Masters, C. L., Lista, S., Kiddle, S. J., Batrla, R., & Blennow, K. (2018) · Nature Reviews Neurology · doi:10.1038/s41582-018-0079-7 · Cited by 716 · see citing works
Self-citationA multicentre validation study of the diagnostic value of plasma neurofilament light.
Ashton, N. J., Janelidze, S., Al Khleifat, A., Leuzy, A., van der Ende, E. L., Karikari, T. K., Benedet, A. L., Pascoal, T. A., Lleó, A., Parnetti, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23620-z · Cited by 545 · see citing works
Self-citationAlzheimer’s disease drug development pipeline: 2021
Cummings, J., Lee, G., Zhong, K., Fonseca, J., & Taghva, K. (2021) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12179 · Cited by 539 · see citing works
Ashton, N. J., Janelidze, S., Mattsson-Carlgren, N., Binette, A. P., Strandberg, O., Brum, W. S., Karikari, T. K., González-Ortiz, F., Di Molfetta, G., Meda, F. J., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-02074-w · Cited by 436 · see citing works
Self-citationPalmqvist, 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 · see citing works
Self-citationTolar, M., Abushakra, S., Hey, J. A., Porsteinsson, A., & Sabbagh, M. (2020) · Alzheimer's Research & Therapy · doi:10.1186/s13195-020-00663-w · Cited by 354 · see citing works
Lantero Rodriguez, J., Karikari, T. K., Suárez-Calvet, M., Troakes, C., King, A., Emersic, A., Aarsland, D., Hye, A., Zetterberg, H., Blennow, K., et al. (2020) · Acta Neuropathologica · doi:10.1007/s00401-020-02195-x · Cited by 350 · see citing works
Self-citationMolecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease
Otero-Garcia, M., Mahajani, S. U., Wakhloo, D., Tang, W., Xue, Y.-Q., Morabito, S., Pan, J., Oberhauser, J., Madira, A. E., Shakouri, T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.06.021 · Cited by 262 · see citing works
Pontecorvo, M. J., Lu, M., Burnham, S. C., Schade, A. E., Dage, J. L., Shcherbinin, S., Collins, E. C., Sims, J. R., & Mintun, M. A. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2022.3392 · Cited by 261 · see citing works
Advances in the development of new biomarkers for Alzheimer’s disease
Klyucherev, T. O., Olszewski, P., Shalimova, A. A., Chubarev, V. N., Tarasov, V. V., Attwood, M. M., Syvänen, S., & Schiöth, H. B. (2022) · Translational Neurodegeneration · doi:10.1186/s40035-022-00296-z · Cited by 241 · see citing works
Pichet Binette, A., Janelidze, S., Cullen, N., Dage, J. L., Bateman, R. J., Zetterberg, H., Blennow, K., Stomrud, E., Mattsson‐Carlgren, N., & Hansson, O. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12787 · Cited by 226 · see citing works
Self-citationTime course of phosphorylated-tau181 in blood across the Alzheimer’s disease spectrum
Moscoso, A., Grothe, M. J., Ashton, N. J., Karikari, T. K., Rodriguez, J. L., Snellman, A., Suárez-Calvet, M., Zetterberg, H., Blennow, K., Schöll, M., et al. (2021) · Brain · doi:10.1093/brain/awaa399 · Cited by 229 · see citing works
Self-citationLarge-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk
Walker, K. A., Chen, J., Zhang, J., Fornage, M., Yang, Y., Zhou, L., Grams, M. E., Tin, A., Daya, N., Hoogeveen, R. C., et al. (2021) · Nature Aging · doi:10.1038/s43587-021-00064-0 · Cited by 212 · see citing works
Moving fluid biomarkers for Alzheimer’s disease from research tools to routine clinical diagnostics
Zetterberg, H., & Blennow, K. (2021) · Molecular Neurodegeneration · doi:10.1186/s13024-021-00430-x · Cited by 219 · see citing works
Self-citationMielke, M. M., Aggarwal, N. T., Vila‐Castelar, C., Agarwal, P., Arenaza‐Urquijo, E. M., Brett, B., Brugulat‐Serrat, A., DuBose, L. E., Eikelboom, W. S., Flatt, J., et al. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12662 · Cited by 198 · see citing works
van der Ende, E. L., Meeter, L. H., Poos, J. M., Panman, J. L., Jiskoot, L. C., Dopper, E. G. P., Papma, J. M., de Jong, F. J., Verberk, I. M. W., Teunissen, C., et al. (2019) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30354-0 · Cited by 181 · see citing works
Cullen, N. C., Leuzy, A., Palmqvist, S., Janelidze, S., Stomrud, E., Pesini, P., Sarasa, L., Allué, J. A., Proctor, N. K., Zetterberg, H., et al. (2020) · Nature Aging · doi:10.1038/s43587-020-00003-5 · Cited by 187 · see citing works
Self-citationVeitch, D. P., Weiner, M. W., Aisen, P. S., Beckett, L. A., DeCarli, C., Green, R. C., Harvey, D., Jack, C. R., Jagust, W., Landau, S. M., et al. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12422 · Cited by 184 · see citing works
Fluid Biomarkers for Synaptic Dysfunction and Loss
Camporesi, E., Nilsson, J., Brinkmalm, A., Becker, B., Ashton, N. J., Blennow, K., & Zetterberg, H. (2020) · Biomarker Insights · doi:10.1177/1177271920950319 · Cited by 165 · see citing works
Self-citationForgrave, L. M., Ma, M., Best, J. R., & DeMarco, M. L. (2019) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1016/j.dadm.2019.08.009 · Cited by 177 · see citing works
Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain
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., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0635-5 · Cited by 161 · see citing works
An Update on Blood-Based Markers of Alzheimer’s Disease Using the SiMoA Platform
Li, D., & Mielke, M. M. (2019) · Neurology and Therapy · doi:10.1007/s40120-019-00164-5 · Cited by 147 · see citing works
Quiroz, Y. T., Zetterberg, H., Reiman, E. M., Chen, Y., Su, Y., Fox-Fuller, J. T., Garcia, G., Villegas, A., Sepulveda-Falla, D., Villada, M., et al. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30137-x · Cited by 159 · see citing works
Self-citationBiomarker-Based Prediction of Longitudinal Tau Positron Emission Tomography in Alzheimer Disease
Leuzy, A., Smith, R., Cullen, N. C., Strandberg, O., Vogel, J. W., Binette, A. P., Borroni, E., Janelidze, S., Ohlsson, T., Jögi, J., et al. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2021.4654 · Cited by 149 · see citing works
Self-citationPlasma Tau and Neurofilament Light in Frontotemporal Lobar Degeneration and Alzheimer Disease
Illán-Gala, I., Lleo, A., Karydas, A., Staffaroni, A. M., Zetterberg, H., Sivasankaran, R., Grinberg, L. T., Spina, S., Kramer, J. H., Ramos, E. M., et al. (2021) · Neurology · doi:10.1212/wnl.0000000000011226 · Cited by 150 · see citing works
Self-citationClark, C., Lewczuk, P., Kornhuber, J., Richiardi, J., Maréchal, B., Karikari, T. K., Blennow, K., Zetterberg, H., & Popp, J. (2021) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00805-8 · Cited by 88 · see citing works
Self-citationThe dynamics of biomarkers across the clinical spectrum of Alzheimer's disease
Hadjichrysanthou, C., Evans, S., Bajaj, S., Siakallis, L. C., McRae-McKee, K., de Wolf, F., Anderson, R. M., & Initiative, T. A. D. N. (2020) · Alzheimer's Research & Therapy · doi:10.1186/s13195-020-00636-z · Cited by 86 · see citing works
“…a promising marker that can indicate pathological changes at early stages in disease development, and therefore, although not specific for AD, it could potentially be considered as a biomarker for the screening of related neurodegeneration and disease prognosis, monitoring and assessment [68 – 71].”
Salivary Biomarkers for Alzheimer’s Disease and Related Disorders
Ashton, N. J., Ide, M., Zetterberg, H., & Blennow, K. (2019) · Neurology and Therapy · doi:10.1007/s40120-019-00168-1 · Cited by 89 · see citing works
Self-citationRen, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
Frisoni, G. B., Molinuevo, J. L., Altomare, D., Carrera, E., Barkhof, F., Berkhof, J., Delrieu, J., Dubois, B., Kivipelto, M., Nordberg, A., et al. (2020) · Alzheimer's & Dementia · doi:10.1002/alz.12132 · Cited by 78 · see citing works
Associations of longitudinal plasma p-tau181 and NfL with tau-PET, Aβ-PET and cognition
Rauchmann, B. S., Schneider-Axmann, T., & Perneczky, R. (2021) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2020-325537 · Cited by 74 · see citing works
Chhatwal, J. P., Schultz, A. P., Dang, Y., Ostaszewski, B., Liu, L., Yang, H.-S., Johnson, K. A., Sperling, R. A., & Selkoe, D. J. (2020) · Nature Communications · doi:10.1038/s41467-020-19543-w · Cited by 60 · see citing works
Quantitative phosphoproteomics uncovers dysregulated kinase networks in Alzheimer’s disease
Morshed, N., Lee, M. J., Rodriguez, F. H., Lauffenburger, D. A., Mastroeni, D., & White, F. M. (2021) · Nature Aging · doi:10.1038/s43587-021-00071-1 · Cited by 58 · see citing works
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 · see citing works
Pan, F., Huang, Y., Cai, X., Wang, Y., Guan, Y., Deng, J., Yang, D., Zhu, J., Zhao, Y., Xie, F., et al. (2023) · Communications Medicine · doi:10.1038/s43856-023-00295-9 · Cited by 27 · see citing works
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 · see citing works
Lim, B., Fowler, C., Li, Q.-X., Rowe, C., Dhiman, K., Gupta, V. B., Masters, C. L., Doecke, J. D., Martins, R. N., Collins, S., et al. (2020) · Neuroscience Letters · doi:10.1016/j.neulet.2020.135078 · Cited by 10 · see citing works
- Authors
- Mattsson, N., Cullen, N. C., Andreasson, U., Zetterberg, H., & Blennow, K.
- Affiliations
- Lund University (SE)
- University of Pennsylvania (US)
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Sahlgrenska University Hospital (SE)
- Corresponding author
- Mattsson, Niklas
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2019-07-01
- Volume
- 76
- Issue
- 7
- Pages
- 791
- ISSN
- 2168-6149 (ISSN-L)
- PMC
- PMC6583067
- OpenAlex
- W2938221890
- Semantic Scholar
- e03cd0578f82e38c8991601ce30e4f0393ae5c64
- Cited by
- 726
- References
- 28
- Citations by year
- 2026: 67 · 2025: 113 · 2024: 126 · 2023: 100 · 2022: 84 · 2021: 115 · 2020: 90 · 2019: 30 · 2018: 1
- FWCI
- 63.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Neurology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Greta och Johan Kocks stiftelser
- National Institutes of Health (5u01ag024904-10)
- Canadian Institutes of Health Research
- National Institute on Aging (U01-AG-024904)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- neurofilament light chain, Alzheimer's disease, neurodegeneration, plasma biomarkers, amyloid-beta, tau protein, phosphorylated tau, hippocampal volume, cortical thinning, FDG-PET, mild cognitive impairment, Alzheimer's dementia, longitudinal biomarker changes, neuroimaging biomarkers, cerebrospinal fluid biomarkers, cognitive decline, neuroinflammation
- MeSH terms
- Mental Status and Dementia Tests, Aged, Aged, 80 and over, Alzheimer Disease, Cerebral Cortex, Cerebral Ventricles, Female, Hippocampus, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Organ Size, Peptide Fragments, Phosphoproteins, Cohort Studies, Biomarkers, Case-Control Studies, Amyloid beta-Peptides, tau Proteins, Neurofilament Proteins, Disease Progression, Radiopharmaceuticals, Fluorodeoxyglucose F18, Positron-Emission Tomography, Cognitive Dysfunction
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
