Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer’s disease
Open accessAbstract
Introduction: Alzheimer’s disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including β-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment. Method: We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time. Results: Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/β-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD. Conclusion: Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.
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?
MDK, SMOC1, and NTN1 have been shown to colocalize with Aβ plaque and are promising biomarkers associated with AD pathology.
“These proteins have been shown to colocalize with Aβ plaque and are promising biomarkers associated with AD pathology.”
From Unraveling sex differences in Alzheimer's disease and related endophenotypes with brain proteomes (2025) · cites this paper as [52]
The Results and Discussion identify SMOC1 as a promising CSF biomarker associated with AD pathology. Our copy does not report that SMOC1 colocalizes with Aβ plaques, or establish the stated findings for MDK and NTN1 (searched: colocalization, plaques, MDK, and NTN1). (LLM, conf=0.87)
Experimental — accuracy not yet measuredSMOC1, YWHAZ, ALDOA, and MAP1B emerged as biomarkers that could best discriminate between individuals with AD and non-AD cognitive impairment, correlating well with Aβ and tau levels.
“SMOC1, YWHAZ, ALDOA, and MAP1B emerged as biomarkers that could best discriminate between individuals with AD and non-AD cognitive impairment, correlating well with Aβ and tau levels [192].”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [192]
Several proteins, including tau and neurofilaments, were significantly increased in AD CSF and capable of distinguishing AD cases from controls and non-AD dementia.
“Several proteins, including tau and neurofilaments, were significantly increased in AD CSF and capable of distinguishing AD cases from controls and non-AD dementia.”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [192]
Zhou and colleagues used PRM to quantify a panel of brain-derived proteins significantly altered in a discovery-driven proteomic analysis of AD CSF.
“In this study, Zhou and colleagues used PRM to quantify a panel of brain-derived proteins significantly altered in a discovery-driven proteomic analysis of AD CSF.”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [192]
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
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
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155 · see citing works
2016 Alzheimer's disease facts and figures
Alzheimer's Association (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.03.001 · Cited by 5,069 · see citing works
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875 · see citing works
Skyline: an open source document editor for creating and analyzing targeted proteomics experiments
MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., & MacCoss, M. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq054 · Cited by 4,697 · see citing works
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295 · see citing works
Olsson, B., Lautner, R., Andreasson, U., Öhrfelt, A., Portelius, E., Bjerke, M., Hölttä, M., Rosén, C., Olsson, C., Strobel, G., et al. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)00070-3 · Cited by 2,049 · see citing works
A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Feldman, H. H., Frisoni, G. B., Hampel, H., Jagust, W. J., Johnson, K. A., Knopman, D. S., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000002923 · Cited by 1,864 · see citing works
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Ping, L., Zhou, M., Yin, L., Higginbotham, L. A., Guajardo, A., White, B., Troncoso, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0815-6 · Cited by 1,001 · see citing works
Self-citationBiomarkers for Alzheimer's disease: current status and prospects for the future
Blennow, K., & Zetterberg, H. (2018) · Journal of Internal Medicine · doi:10.1111/joim.12816 · Cited by 1,000 · see citing works
Undulating changes in human plasma proteome profiles across the lifespan
Lehallier, B., Gate, D., Schaum, N., Nanasi, T., Lee, S. E., Yousef, H., Moran Losada, P., Berdnik, D., Keller, A., Verghese, J., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0673-2 · Cited by 981 · see citing works
Revisiting biomarker discovery by plasma proteomics
Geyer, P. E., Holdt, L. M., Teupser, D., & Mann, M. (2017) · Molecular Systems Biology · doi:10.15252/msb.20156297 · Cited by 917 · see citing works
Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression
Bai, B., Wang, X., Li, Y., Chen, P.-C., Yu, K., Dey, K. K., Yarbro, J. M., Han, X., Lutz, B. M., Rao, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.015 · Cited by 632 · see citing works
Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics
Rauniyar, N., & Yates, J. R. (2014) · Journal of Proteome Research · doi:10.1021/pr500880b · Cited by 597 · see citing works
Tau Kinetics in Neurons and the Human Central Nervous System
Sato, C., Barthélemy, N. R., Mawuenyega, K. G., Patterson, B. W., Gordon, B. A., Jockel-Balsarotti, J., Sullivan, M., Crisp, M. J., Kasten, T., Kirmess, K. M., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.02.015 · Cited by 586 · see citing works
Person-specific contribution of neuropathologies to cognitive loss in old age
Boyle, P. A., Yu, L., Wilson, R. S., Leurgans, S. E., Schneider, J. A., & Bennett, D. A. (2018) · Annals of Neurology · doi:10.1002/ana.25123 · Cited by 508 · see citing works
YKL-40: A Novel Prognostic Fluid Biomarker for Preclinical Alzheimer's Disease
Craig-Schapiro, R., Perrin, R. J., Roe, C. M., Xiong, C., Carter, D., Cairns, N. J., Mintun, M. A., Peskind, E. R., Li, G., Galasko, D. R., et al. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.08.025 · Cited by 504 · see citing works
Seyfried, N. T., Dammer, E. B., Swarup, V., Nandakumar, D., Duong, D. M., Yin, L., Deng, Q., Nguyen, T., Hales, C. M., Wingo, T., et al. (2017) · Cell Systems · doi:10.1016/j.cels.2016.11.006 · Cited by 477 · see citing works
Self-citationHigginbotham, L., Ping, L., Dammer, E. B., Duong, D. M., Zhou, M., Gearing, M., Johnson, E. C. B., Hajjar, I., Lah, J. J., Levey, A. I., et al. (2019) · doi:10.1101/806752 · Cited by 367 · see citing works
Self-citationHigginbotham, L., Ping, L., Dammer, E. B., Duong, D. M., Zhou, M., Gearing, M., Hurst, C., Glass, J. D., Factor, S. A., Johnson, E. C. B., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz9360 · Cited by 367 · see citing works
Self-citationAdvances in targeted proteomics and applications to biomedical research
Shi, T., Song, E., Nie, S., Rodland, K., Liu, T., Qian, W., & Smith, R. D. (2016) · PROTEOMICS · doi:10.1002/pmic.201500449 · Cited by 259 · see citing works
Olsson, B., Portelius, E., Cullen, N. C., Sandelius, Å., Zetterberg, H., Andréasson, U., Höglund, K., Irwin, D. J., Grossman, M., Weintraub, D. A., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2018.3746 · Cited by 255 · see citing works
Hoofnagle, A. N., Whiteaker, J. R., Carr, S. A., Kuhn, E. W., Liu, T., Massoni, S. A., Thomas, S. N., Townsend, R. R., Zimmerman, L. J., Boja, E. S., et al. (2015) · Clinical Chemistry · doi:10.1373/clinchem.2015.250563 · Cited by 230 · see citing works
Andreasen, N. C., Vanmechelen, E., VOORDE, A. V. D., Davidsson, P., Hesse, C., Tarvonen-Schröder, S., Räihä, I. J., Sourander, L., Winblad, B. G., & Blennow, K. (1998) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.64.3.298 · Cited by 227 · see citing works
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Yin, L., Thambisetty, M., Troncoso, J. C., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0282-4 · Cited by 225 · see citing works
Self-citationGlobal quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s Disease
Ping, L., Duong, D. M., Yin, L., Gearing, M., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Scientific Data · doi:10.1038/sdata.2018.36 · Cited by 221 · see citing works
Self-citationSynaptic markers of cognitive decline in neurodegenerative diseases: a proteomic approach
Bereczki, E., Branca, R. M., Francis, P. T., Pereira, J. B., Baek, J.-H., Hortobágyi, T., Winblad, B., Ballard, C., Lehtiö, J., & Aarsland, D. (2018) · Brain · doi:10.1093/brain/awx352 · Cited by 220 · see citing works
Comprehensive Label-Free Method for the Relative Quantification of Proteins from Biological Samples
Higgs, R. E., Knierman, M. D., Gelfanova, V., Butler, J. P., & Hale, J. E. (2005) · Journal of Proteome Research · doi:10.1021/pr050109b · Cited by 219 · see citing works
Wingo, A. P., Dammer, E. B., Breen, M. S., Logsdon, B. A., Duong, D. M., Troncosco, J. C., Thambisetty, M., Beach, T. G., Serrano, G. E., Reiman, E. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09613-z · Cited by 211 · see citing works
Self-citationDendritic spines provide cognitive resilience against <scp>A</scp> lzheimer's disease
Boros, B. D., Greathouse, K. M., Gentry, E. G., Curtis, K. A., Birchall, E. L., Gearing, M., & Herskowitz, J. H. (2017) · Annals of Neurology · doi:10.1002/ana.25049 · Cited by 198 · see citing works
Elevated CSF GAP‐43 is Alzheimer's disease specific and associated with tau and amyloid pathology
Sandelius, Å., Portelius, E., Källén, Å., Zetterberg, H., Rot, U., Olsson, B., Toledo, J. B., Shaw, L. M. J., Lee, V. M. ‐., Irwin, D. J., et al. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.08.006 · Cited by 191 · see citing works
Fagan, A. M., Shaw, L. M. J., Xiong, C., Vanderstichele, H., Mintun, M. A., Trojanowski, J. Q., Coart, E., Morris, J. C., & Holtzman, D. M. (2011) · Archives of Neurology · doi:10.1001/archneurol.2011.105 · Cited by 190 · see citing works
14-3-3 proteins in neurological disorders.
Foote, M. M., & Zhou, Y. (2012) · PubMed · Cited by 140 · see citing works
Barthélemy, N. R., Gabelle, A., Hirtz, C., Fenaille, F., Sergeant, N., Schraen-Maschke, S., Vialaret, J., Buée, L., Junot, C., Becher, F., et al. (2016) · Journal of Alzheimer’s Disease · doi:10.3233/jad-150962 · Cited by 139 · see citing works
Label-free mass spectrometry-based protein quantification technologies in proteomic analysis
Wang, M., You, J., Bemis, K. G., Tegeler, T. J., & Brown, D. P. G. (2008) · Briefings in Functional Genomics and Proteomics · doi:10.1093/bfgp/eln031 · Cited by 130 · see citing works
Mouton‐Barbosa, E., Roux‐Dalvai, F., Bouyssié, D., Berger, F. R., Schmidt, E. A., Righetti, P. G., Guerrier, L., Boschetti, E., Burlet‐Schiltz, O., Monsarrat, B., et al. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900513-mcp200 · Cited by 129 · see citing works
Sathe, G., Na, C. H., Renuse, S., Madugundu, A. K., Albert, M., Moghekar, A., & Pandey, A. (2019) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201800105 · Cited by 126 · see citing works
Barthélemy, N. R., Fenaille, F., Hirtz, C., Sergeant, N., Schraen-Maschke, S., Vialaret, J., Buée, L., Gabelle, A., Junot, C., Lehmann, S., et al. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b01001 · Cited by 123 · see citing works
Characterization of SMOC-1, a Novel Modular Calcium-binding Protein in Basement Membranes
Vannahme, C., Smyth, N. R., Miosge, N., Gösling, S., Frie, C., Paulsson, M., Maurer, P., & Hartmann, U. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m203830200 · Cited by 121 · see citing works
SMOC1 Is Essential for Ocular and Limb Development in Humans and Mice
Okada, I., Hamanoue, H., Terada, K., Tohma, T., Mégarbané, A., Chouery, É., Ghoch, J. A., Jalkh, N., Çoğulu, Ö., Özkınay, F., et al. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.012 · Cited by 112 · see citing works
Chitotriosidase - a putative biomarker for sporadic amyotrophic lateral sclerosis
Varghese, A. M., Sharma, A., Mishra, P. S., Vijayalakshmi, K., Harsha, H. C., Sathyaprabha, T. N., Bharath, S., Nalini, A., Alladi, P. A., & Raju, T. R. (2013) · Clinical Proteomics · doi:10.1186/1559-0275-10-19 · Cited by 109 · see citing works
Alzheimer disease pathology and the cerebrospinal fluid proteome
Dayon, L., Núñez Galindo, A., Wojcik, J., Cominetti, O., Corthésy, J., Oikonomidi, A., Henry, H., Kussmann, M., Migliavacca, E., Severin, I., et al. (2018) · Alzheimer's Research & Therapy · doi:10.1186/s13195-018-0397-4 · Cited by 101 · see citing works
Boros, B. D., Greathouse, K. M., Gearing, M., & Herskowitz, J. H. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.09.003 · Cited by 90 · see citing works
Heart fatty acid binding protein as a potential diagnostic marker for neurodegenerative diseases
Steinacker, P., Mollenhauer, B., Bibl, M., Cepek, L., Esselmann, H., Brechlin, P., Lewczuk, P., Poser, S., Kretzschmar, H. A., Wiltfang, J., et al. (2004) · Neuroscience Letters · doi:10.1016/j.neulet.2004.07.061 · Cited by 85 · see citing works
Begcevic, I., Brinc, D., Brown, M., Martinez-Morillo, E., Goldhardt, O., Grimmer, T., Magdolen, V., Batruch, I., & Diamandis, E. P. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.04.027 · Cited by 81 · see citing works
The Role of Osteopontin in Neurodegenerative Diseases
Carecchio, M., & Comi, C. (2011) · Journal of Alzheimer's Disease · doi:10.3233/jad-2011-102151 · Cited by 79 · see citing works
Awwad, K., Hu, J., Shi, L., Mangels, N., Abdel Malik, R., Zippel, N., Fisslthaler, B., Eble, J. A., Pfeilschifter, J., Popp, R., et al. (2015) · Cardiovascular Research · doi:10.1093/cvr/cvv098 · Cited by 77 · see citing works
Andersson, A. K., Remnestål, J., Nellgård, B., Vunk, H., Kotol, D., Edfors, F., Uhlén, M., Schwenk, J. M., Ilag, L. L., Zetterberg, H., et al. (2019) · Clinica Chimica Acta · doi:10.1016/j.cca.2019.03.243 · Cited by 50 · see citing works
Antibody-free quantification of seven tau peptides in human CSF using targeted mass spectrometry
Bros, P., Vialaret, J., Barthélemy, N. R., Delatour, V., Gabelle, A., Lehmann, S., & Hirtz, C. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00302 · Cited by 45 · see citing works
Jankovska, E., Svitek, M., Holada, K., & Petrák, J. (2019) · Clinical Proteomics · doi:10.1186/s12014-019-9229-1 · Cited by 42 · see citing works
Chitotriosidase in Patients with Acute Ischemic Stroke
Sotgiu, S., Barone, R., Zanda, B., Arru, G., Fois, M., Arru, A., Rosati, G., Marchetti, B., & Musumeci, S. (2005) · European Neurology · doi:10.1159/000089935 · Cited by 37 · see citing works
Yi, M., Stromswold, J., Wilson, K., Holder, D., Sur, C., Laterza, O., Savage, M. J., Struyk, A. F., Scheltens, P., Teunissen, C. E., et al. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.02.004 · Cited by 23 · see citing works
A unified model of dementias and age‐related neurodegeneration
Fossel, M. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12012 · Cited by 16 · see citing works
Zhou, M., Duong, D. M., Johnson, E. C. B., Dai, J., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00920 · Cited by 13 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [10]Johnson ECB Dammer EB Duong DM Ping L Zhou M Yin L Higginbotham LA Guajardo A White B Troncoso JC Thambisetty M Montine TJ Lee EB Trojanowski JQ Beach TG Reiman EM Haroutunian V Wang M Schadt E Zhang B Dickson DW Ertekin-Taner N Golde TE Petyuk VA De Jager PL Bennett DA Wingo TS Rangaraju S Hajjar I Shulman JM Lah JJ Levey AI Seyfried NT Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation Nat Med 2020 26 5 769 780 32284590 PMC7405761
Cited by
Sorted by citations
Johnson, E. C. B., Carter, E. K., Dammer, E. B., Duong, D. M., Gerasimov, E. S., Liu, Y., Liu, J., Betarbet, R., Ping, L., Yin, L., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00999-y · Cited by 561 · see citing works
Self-citationHigginbotham, L., Ping, L., Dammer, E. B., Duong, D. M., Zhou, M., Gearing, M., Hurst, C., Glass, J. D., Factor, S. A., Johnson, E. C. B., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz9360 · Cited by 367 · see citing works
Self-citationCerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer’s disease
Johnson, E. C. B., Bian, S., Haque, R. U., Carter, E. K., Watson, C. M., Gordon, B. A., Ping, L., Duong, D. M., Epstein, M. P., McDade, E., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02476-4 · Cited by 170 · see citing works
Self-citationSystems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau
Rayaprolu, S., Higginbotham, L., Bagchi, P., Watson, C. M., Zhang, T., Levey, A. I., Rangaraju, S., & Seyfried, N. T. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00840-3 · Cited by 118 · see citing works
Self-citationClark, C., Dayon, L., Masoodi, M., Bowman, G. L., & Popp, J. (2021) · Alzheimer s Research & Therapy · doi:10.1186/s13195-021-00814-7 · Cited by 116 · see citing works
Spurrier, J. M., Nicholson, L., Fang, X. T., Stoner, A. J., Toyonaga, T., Holden, D., Siegert, T. R., Laird, W., Allnutt, M. A., Chiasseu, M., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abi8593 · Cited by 102 · see citing works
Guo, Y. X., Chen, S.-D., You, J., Huang, S.-Y., Chen, Y., Zhang, Y., Wang, L., He, X., Deng, Y., Zhang, Y.-R., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01924-6 · Cited by 65 · see citing works
Modeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00638-z · Cited by 62 · see citing works
Self-citationHaque, R., Watson, C. M., Liu, J., Carter, E. K., Duong, D. M., Lah, J. J., Wingo, A. P., Roberts, B. R., Johnson, E. C. B., Saykin, A. J., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adg4122 · Cited by 64 · see citing works
Self-citationWatson, C. M., Dammer, E. B., Ping, L., Duong, D. M., Modeste, E. S., Carter, E. K., Johnson, E. C. B., Levey, A. I., Lah, J. J., Roberts, B. R., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02158-3 · Cited by 58 · see citing works
Self-citationCSF proteomics in autosomal dominant Alzheimer’s disease highlights parallels with sporadic disease
van der Ende, E. L., Veld, S. G. J. G. I. ‘., Hanskamp, I., van der Lee, S. J., Dijkstra, J. I. R., Hok‐A‐Hin, Y. S., Blujdea, E. R., Swieten, J. C. V., Irwin, D. J., Chen‐Plotkin, A. S., et al. (2023) · Brain · doi:10.1093/brain/awad213 · Cited by 55 · see citing works
Wang, Q., Lu, M., Zhu, X., Gu, X., Zhang, T., Xia, C., Yang, L., Xu, Y., & Zhou, M. (2022) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2022.113412 · Cited by 52 · see citing works
Self-citationWojtas, A., Dammer, E. B., Guo, Q., Ping, L., Shantaraman, A., Duong, D. M., Yin, L., Fox, E. J., Seifar, F., Lee, E. B., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13821 · Cited by 53 · see citing works
Self-citationYu, W., Yu, W., Yang, Y., & Lü, Y. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.602781 · Cited by 50 · see citing works
Cary, G. A., Wiley, J. C., Gockley, J., Keegan, S., Amirtha Ganesh, S. S., Heath, L., Butler, R. R., Mangravite, L. M., Logsdon, B. A., Longo, F. M., et al. (2024) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12461 · Cited by 49 · see citing works
Self-citationKulkarni, A. S., Huang, L., & Qian, K. (2021) · Journal of Materials Chemistry B · doi:10.1039/d1tb00289a · Cited by 49 · see citing works
Wan, J., Zhou, S., Mea, H. J., Guo, Y., Ku, H., & Urbina, B. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00480 · Cited by 43 · see citing works
Frick, E. A., Emilsson, V., Jónmundsson, Þ., Steindorsdottir, A. E., Johnson, E. C. B., Puerta, R., Dammer, E. B., Shantaraman, A., Cano, A. C., Boada, M., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00693-1 · Cited by 45 · see citing works
Self-citationA new generation of AD biomarkers: 2019 to 2021
Hawksworth, J. I., Fernández, E., & Gevaert, K. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2022.101654 · Cited by 34 · see citing works
SMOC1 colocalizes with Alzheimer’s disease neuropathology and delays Aβ aggregation
Balcomb, K., Johnston, C., Kavanagh, T., Leitner, D., Schneider, J. A., Halliday, G. M., Wısnıewskı, T., Sunde, M., & Drummond, E. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02819-6 · Cited by 32 · see citing works
Zhao, Y. G., Xie, Y., & Liu, Y. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.949074 · Cited by 29 · see citing works
Giangrande, C., Delatour, V., Andréasson, U., Blennow, K., Gobom, J., & Zetterberg, H. (2023) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12465 · Cited by 29 · see citing works
Impact of Depression and Stress on Placental DNA Methylation in Ethnically Diverse Pregnant Women
Tesfaye, M., Chatterjee, S., Zeng, X., Joseph, P. V., & Ayele, F. T. (2021) · Epigenomics · doi:10.2217/epi-2021-0192 · Cited by 27 · see citing works
de Geus, M. B., Leslie, S. N., Lam, T. T., Wang, W., Roux‐Dalvai, F., Droit, A., Kivisäkk, P., Nairn, A. C., Arnold, S. E., & Carlyle, B. C. (2023) · Scientific Reports · doi:10.1038/s41598-023-49440-3 · Cited by 26 · see citing works
Guo, Q., Dammer, E. B., Zhou, M., Kundinger, S. R., Gearing, M., Lah, J. J., Levey, A. I., Shulman, J. M., & Seyfried, N. T. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.623659 · Cited by 23 · see citing works
Self-citationKnowledge gaps in Alzheimer's disease immune biomarker research
Morgan, D., & Mielke, M. M. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12342 · Cited by 25 · see citing works
Llano, D. A., Devanarayan, P., & Devanarayan, V. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.07.015 · Cited by 22 · see citing works
Roberts, J. A., Varma, V. R., Candia, J., Tanaka, T., Ferrucci, L., Bennett, D. A., & Thambisetty, M. (2023) · npj Aging · doi:10.1038/s41514-023-00112-6 · Cited by 22 · see citing works
Osteopontin: A novel marker of pre‐symptomatic sporadic Alzheimer's disease
Quesnel, M. J., Labonté, A., Picard, C., Bowie, D. C., Zetterberg, H., Blennow, K., Brinkmalm, A., Villeneuve, S., Poirier, J., & Initiative, A. D. N. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14065 · Cited by 20 · see citing works
Navas-Carrillo, D., Rivera‐Caravaca, J. M., Sampedro-Andrada, A., & Orenes‐Piñero, E. (2020) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2020.1833298 · Cited by 19 · see citing works
Paciotti, S., Wojdała, A. L., Bellomo, G., Toja, A., Chipi, E., Piersma, S. R., Pham, T. V., Gaetani, L., Jiménez, C. R., Parnetti, L., et al. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01269-8 · Cited by 19 · see citing works
Proteomics Landscape of Alzheimer’s Disease
Jain, A., & Sathe, G. J. (2021) · Proteomes · doi:10.3390/proteomes9010013 · Cited by 18 · see citing works
van Zalm, P., Ahmed, S., Fatou, B., Schreiber, R., Barnaby, O. S., Boxer, A. L., Zetterberg, H., Steen, J. A. J., & Steen, H. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101005 · Cited by 17 · see citing works
Kamalian, A., Ho, S. G., Patel, M. A., Lewis, A., Bakker, A., Albert, M., O’Brien, R., Moghekar, A., & Lutz, M. W. (2023) · Biomolecules · doi:10.3390/biom13071094 · Cited by 16 · see citing works
“Advances in biomarker discovery and diagnostics for alzheimer’s disease”
Bhatia, V., Chandel, A., Minhas, Y., & Kushawaha, S. K. (2025) · Neurological Sciences · doi:10.1007/s10072-025-08023-y · Cited by 21 · see citing works
APOE4 Copy Number-Dependent Proteomic Changes in the Cerebrospinal Fluid1
Berger, M., Cooter, M., Roesler, A. S., Chung, S., Park, J., Modliszeski, J. L., VanDusen, K. W., Thompson, J. W., Moseley, M. A., Devinney, M. J., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200747 · Cited by 15 · see citing works
Fard, G. H., & Anastasova, S. (2024) · Sensors · doi:10.3390/s24113294 · Cited by 15 · see citing works
Montoliu‐Gaya, L., Bian, S., Dammer, E. B., Alcolea, D. A., Sauer, M., Martá-Ariza, M., Ashton, N. J., Belbin, O., Fuchs, J., Watson, C. M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61054-z · Cited by 14 · see citing works
Self-citationWeiner, S., Blennow, K., Zetterberg, H., & Gobom, J. (2023) · Expert Review of Proteomics · doi:10.1080/14789450.2023.2255752 · Cited by 14 · see citing works
Hou, X., Qiu, Y., Li, H., Yan, Y., Zhao, D., Ji, S., Ni, J., Zhang, J., Liu, K., Qing, H., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01789-5 · Cited by 14 · see citing works
UCH-L1 in Alzheimer’s Disease: A Crucial Player in Dementia-Associated Mechanisms
Porchietto, E., Morello, G., Cicilese, G., Rainero, I., Rubino, E., Tamagno, E., Boschi, S., & Guglielmotto, M. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26189012 · Cited by 13 · see citing works
Yu, H., Li, M., Pan, Q., Liu, Y., Zhang, Y., He, T., Yang, H., Xiao, Y., Weng, Y., Gao, Y., et al. (2022) · MedComm · doi:10.1002/mco2.180 · Cited by 11 · see citing works
Huhe, H., Shapley, S. M., Duong, D. M., Wu, F., Ha, S.-K., Choi, S., Kofler, J., Mou, Y., Guimarães, T. R., Thathiah, A., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14366 · Cited by 12 · see citing works
Self-citationEffect of Thrombin on the Metabolism and Function of Murine Macrophages
Ukan, Ü., Lagos, F. D., Kempf, S., Günther, S., Siragusa, M., Fißlthaler, B., & Fleming, I. (2022) · Cells · doi:10.3390/cells11101718 · Cited by 13 · see citing works
Feasibility of detecting snake envenomation biomarkers from dried blood spots
Smith, C. F., Brandehoff, N., Pepin, L. C., McCabe, M. C., Castoe, T. A., Mackessy, S. P., Nemkov, T. G., Hansen, K. C., & Saviola, A. J. (2023) · Analytical Science Advances · doi:10.1002/ansa.202200050 · Cited by 13 · see citing works
Giangrande, C., Vaneeckhoutte, H., Bœuf, A., Lalère, B., Hirtz, C., Lehmann, S., Quaglia, M., & Delatour, V. (2023) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2022-1250 · Cited by 13 · see citing works
Arioz, B. I., Cotuk, A., Yaka, E. C., & Genç, Ş. (2023) · European Journal of Neuroscience · doi:10.1111/ejn.16226 · Cited by 12 · see citing works
Agrawal, I., Tripathi, P., & Biswas, S. (2022) · Drug Metabolism Reviews · doi:10.1080/03602532.2022.2029475 · Cited by 12 · see citing works
Stachiv, I., Machů, Z., Ševeček, O., Jeng, Y., Li, W.-L., Kotoul, M., & Prášek, J. (2022) · International Journal of Mechanical Sciences · doi:10.1016/j.ijmecsci.2022.107353 · Cited by 12 · see citing works
Quantitative proteomics profiling of plasma from children with asthma
Zhou, Y., Kuai, S., Pan, R., Li, Q., Zhang, J., Gu, X., Ren, H., & Cui, Y. (2023) · International Immunopharmacology · doi:10.1016/j.intimp.2023.110249 · Cited by 12 · see citing works
Unraveling sex differences in Alzheimer's disease and related endophenotypes with brain proteomes
Mei, Z., Liu, J., Bennett, D. A., Seyfried, N., Wingo, A. P., & Wingo, T. S. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70206 · Cited by 11 · see citing works
Self-citationPlasma and cerebrospinal fluid biomarkers in aged dogs with cognitive decline
Alsulami, A., Boland, S. W., McGrath, S., MacLean, E. L., Latimer, C. S., Darvas, M., & Moreno, J. A. (2025) · BMC Veterinary Research · doi:10.1186/s12917-025-05027-w · Cited by 11 · see citing works
Barbalace, M. C., Freschi, M., Rinaldi, I., Zallocco, L., Malaguti, M., Manera, C., Ortore, G., Zuccarini, M., Ronci, M., Cuffaro, D., et al. (2024) · Antioxidants · doi:10.3390/antiox13091074 · Cited by 12 · see citing works
Defining Alzheimer’s Disease through Proteomic CSF Profiling
Peña‐Bautista, C., Álvarez‐Sánchez, L., Balaguer, Á., Raga, L., García, L., Baquero, M., & Cháfer‐Pericás, C. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00590 · Cited by 13 · see citing works
Pedrero-Prieto, C. M., Frontiñán-Rubio, J., Alcain, F. J., Durán‐Prado, M., Peinado, J. R., & Rabanal‐Ruiz, Y. (2021) · Diagnostics · doi:10.3390/diagnostics11091655 · Cited by 12 · see citing works
A 3-Gene-Based Diagnostic Signature in Alzheimer’s Disease
Wang, H., Zhang, Y., Zheng, C., Yang, S., Chen, X., Wang, H., & Gao, S. (2021) · European Neurology · doi:10.1159/000518727 · Cited by 11 · see citing works
Morató, X., Puerta, R., Cano, A. C., Orellana, A., de Rojas, I., Capdevila, M., Montrreal, L., Rosende‐Roca, M., García‐González, P., Olivé, C., et al. (2024) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2024.100899 · Cited by 10 · see citing works
Neurofilament light chain in Alzheimer’s disease
Fuloria, N. K., Sekar, M., Porwal, O., Ansari, M. T., Biswas, A., Narain, K., Biswas, S., Bhatia, S., Dhanalekshmi, U. M., & Fuloria, S. (2025) · Clinica Chimica Acta · doi:10.1016/j.cca.2025.120580 · Cited by 10 · see citing works
Advances and applications of clinical proteomics in precision medicine
Alshehri, S., Vitorino, R. M. P., Saleh, O., Al-Harthi, S., Alahmadi, A., Alotibi, R., Rosa, S. C. D. S., Osama, A., Magedeldin, S., Alhattab, D. M., et al. (2025) · Expert Review of Proteomics · doi:10.1080/14789450.2025.2560919 · Cited by 11 · see citing works
Faldu, K. G., & Shah, J. (2022) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2022.2104639 · Cited by 9 · see citing works
Ferreira, A., Timmerman, E., Staes, A., Vuylsteke, M., Muynck, L. D., & Gevaert, K. (2023) · Scientific Data · doi:10.1038/s41597-023-02009-1 · Cited by 7 · see citing works
Abiose, O., Rutledge, J., Losada, P. M., Belloy, M. E., Wilson, E. N., He, Z., Trelle, A. N., Channappa, D., Romero, A., Park, J., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13576 · Cited by 6 · see citing works
Stratifying risk of Alzheimer’s disease in healthy middle-aged individuals with machine learning
Tandon, R., Zhao, L., Watson, C. M., Sarkar, N., Elmor, M. B., Heilman, C. J., Sanders, K., Hales, C. M., Yang, H., Loring, D. W., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf121 · Cited by 6 · see citing works
Self-citationCurrent Methods in Clinical Alzheimer’s Disease Research and Diagnosis
Kodosaki, E., Zetterberg, H., & Heslegrave, A. (2025) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-025-00789-3 · Cited by 5 · see citing works
Bellver‐Sanchís, A., Valle‐García, D., Barbaraci, C., Romero-Becerra, F., Singh, R. K., Jarné‐Ferrer, J., Vasilopoulou, F., Irisarri, A., Martínez-Fernández, C., Fafián-Labora, J. A., et al. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.12.038 · Cited by 4 · see citing works
You, T., Wang, Y., Xu, J., Zhao, Y., Peng, S., Han, Q., Wang, X., Zhang, M., Shen, W., Guo, M., et al. (2026) · Nature Aging · doi:10.1038/s43587-026-01117-y · Cited by 4 · see citing works
CSF proteomics reveals changes in myelin and synaptic biology after Spectris treatment
Hajós, M., Pandey, K., Singer, A. C., Duong, D. M., Bitarafan, S., Shpokayte, M., Malchano, Z., Kern, R. Z., Lah, J. J., Levey, A. I., et al. (2025) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70051 · Cited by 4 · see citing works
Self-citationYin, S., Qian, G.-Y., Yang, J., Lee, J., & Park, Y. (2021) · Protein and Peptide Letters · doi:10.2174/0929866528666211105112927 · Cited by 4 · see citing works
Lah, J. J., Tandon, R., Zhao, L., Watson, C. M., Elmor, M. B., Heilman, C. J., Sanders, K., Hales, C. M., Yang, H., Loring, D. W., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2577025/v1 · Cited by 4 · see citing works
Self-citationFrick, E. A., Emilsson, V., Jonmundsson, T., Steindorsdottir, A. E., Johnson, E. C. B., Puerta, R., Dammer, E. B., Shantaraman, A., Cano, A., Boada, M., et al. (2023) · doi:10.1101/2023.11.08.23298251 · Cited by 3 · see citing works
Self-citationLiu, M., Hu, H., Fu, Y., Chi, H., Huang, L.-Y., Tan, L., & Hu, H. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05442-y · Cited by 2 · see citing works
CSF proteomics and machine learning reveal distinct stages across the Alzheimer’s disease continuum
Rathore, S., Dammer, E. B., Shantaraman, A., Wu, F., Duong, D. M., Fox, E. J., Johnson, E. C. B., Lah, J. J., Initiative, A. D. N., Levey, A. I., et al. (2026) · Molecular Neurodegeneration · doi:10.1186/s13024-026-00983-9 · Cited by 2 · see citing works
Self-citationProteomics As A Valid Tool In Biomarker Discovery For Alzheimer's DiseasePreprint
Magnelli, V. (2024) · Preprints.org · doi:10.20944/preprints202401.1595.v1 · Cited by 1 · see citing works
Shahnaee, A., Liu, C. S., Ngo, T., Palmer, C. R., Ziomek, D., Park, C. S., Tan, V. P., Jimenez, N. A., & Chun, J. J. M. (2026) · Communications Biology · doi:10.1038/s42003-026-09759-9 · Cited by 1 · see citing works
Jiang, Q., Hu, J.-N., Dong, H.-M., Xin, J., Shi, A., Zeng, G., Liu, J., & Wang, Y. (2026) · Molecular Neurodegeneration · doi:10.1186/s13024-026-00956-y · Cited by 1 · see citing works
Potential prognostic value of CSF-targeted proteomics across the Alzheimer’s disease continuum
Xu, B., Ling, Y., Liu, L., Liu, Y., Lin, Y., Lyu, J., & Zhang, Y. (2024) · BMC Geriatrics · doi:10.1186/s12877-024-05104-z · Cited by 1 · see citing works
Adeola, H. A., & Robinson, R. A. S. (2025) · ACS Bio & Med Chem Au · doi:10.1021/acsbiomedchemau.5c00074 · Cited by 1 · see citing works
UT's Project Quest Reaches Deep into Instruction and Research
Danielson, W. A. (1988) · T.H.E. Journal Technological Horizons in Education
Biobanking and Biomarkers in the Alzheimer’s Disease Drug-Development Ecosystem
Kinney, J. W., & Salazar, A. (2022) · Cambridge University Press eBooks · doi:10.1017/9781108975759.011
Proximity extension assay-based proteomic studies in Alzheimer’s disease
Yaka, E. C., & Genç, Ş. (2024) · Turkish Journal Of Neurology · doi:10.55697/tnd.2024.96
Griñán‐Ferré, C., Bellver‐Sanchís, A., Valle‐García, D., Barbaraci, C., Romero-Beccera, F., Singh, R., Vasilopoulou, F., Irisarri, A., Martı́nez, C., Fafián‐Labora, J., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-6940373/v1
Fluid and Imaging Markers of Glial Reactivity
Suárez‐Calvet, M. (2025) · Springer eBooks · doi:10.1007/978-3-031-80849-4_6
Modeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2024) · Figshare · doi:10.6084/m9.figshare.26605045
Self-citationPaciotti, S., Wojdała, A. L., Bellomo, G., Toja, A., Chipi, E., Piersma, S. R., Pham, T. V., Gaetani, L., Jiménez, C. R., Parnetti, L., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23691223
Xu, B., Ling, Y., Liu, L., Liu, Y., Lin, Y., Lyu, J., & Zhang, Y. (2024) · Figshare · doi:10.6084/m9.figshare.25989206
Modeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2024) · Figshare · doi:10.6084/m9.figshare.26605036
Self-citationModeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2024) · Figshare · doi:10.6084/m9.figshare.26605042
Self-citationClark, C., Dayon, L., Masoodi, M., Bowman, G. L., & Popp, J. (2021) · Figshare · doi:10.6084/m9.figshare.14361431
Clark, C., Dayon, L., Masoodi, M., Bowman, G. L., & Popp, J. (2021) · Figshare · doi:10.6084/m9.figshare.14361437
Clark, C., Dayon, L., Masoodi, M., Bowman, G. L., & Popp, J. (2021) · Figshare · doi:10.6084/m9.figshare.14361434
Modeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2024) · Figshare · doi:10.6084/m9.figshare.26605048
Self-citationModeste, E. S., Ping, L., Watson, C. M., Duong, D. M., Dammer, E. B., Johnson, E. C. B., Roberts, B. R., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2024) · Figshare · doi:10.6084/m9.figshare.26605039
Self-citationKataoka, C., Li, Y., Minić, Z., Inoue, T., Yurimoto, T., Sasaki, E., Komohara, Y., Eto, K., Ogihara, N., 中村政明, et al. (2026) · Neurotoxicity Research · doi:10.1007/s12640-026-00832-z
- Authors
- Zhou, M., Haque, R. U., Dammer, E. B., Duong, D. M., Ping, L., Johnson, E. C. B., Lah, J. J., Levey, A. I., & Seyfried, N. T.
- Affiliations
- Emory University (US)
- Corresponding author
- Seyfried, Nicholas T.
- ORCID
- Venue
- Clinical Proteomics
- Published
- 2020-05-29
- Volume
- 17
- Issue
- 1
- Pages
- 19-19
- ISSN
- 1542-6416 (ISSN-L)
- 1559-0275
- PMC
- PMC7257173
- OpenAlex
- W3029074972
- Cited by
- 92
- References
- 53
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 19 · 2023: 21 · 2022: 13 · 2021: 13 · 2020: 4
- FWCI
- 4.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Clinical Proteomics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (R01AG053960, R01AG061800, RF1AG057471, RF1AG057470, R01AG057339, RF1AG062181, U01AG046161, U01AG061357, P50AG025688)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, cerebrospinal fluid biomarkers, targeted mass spectrometry, parallel reaction monitoring, CSF proteomics, tau protein, SMOC1, 14-3-3ζ, non-AD dementia, diagnostic biomarkers, protein quantification, reproducibility, dementia classification
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
