Alzheimer disease pathology and the cerebrospinal fluid proteome
Open accessAbstract
Altered proteome profiles have been reported in both postmortem brain tissues and body fluids of subjects with Alzheimer disease (AD), but their broad relationships with AD pathology, amyloid pathology, and tau-related neurodegeneration have not yet been fully explored. Using a robust automated MS-based proteomic biomarker discovery workflow, we measured cerebrospinal fluid (CSF) proteomes to explore their association with well-established markers of core AD pathology. Cross-sectional analysis was performed on CSF collected from 120 older community-dwelling adults with normal ( n = 48) or impaired cognition ( n = 72). LC-MS quantified hundreds of proteins in the CSF. CSF concentrations of β-amyloid 1–42 (Aβ 1–42 ), tau, and tau phosphorylated at threonine 181 (P-tau181) were determined with immunoassays. First, we explored proteins relevant to biomarker-defined AD. Then, correlation analysis of CSF proteins with CSF markers of amyloid pathology, neuronal injury, and tau hyperphosphorylation (i.e., Aβ 1–42 , tau, P-tau181) was performed using Pearson’s correlation coefficient and Bonferroni correction for multiple comparisons. We quantified 790 proteins in CSF samples with MS. Four CSF proteins showed an association with CSF Aβ 1–42 levels ( p value ≤ 0.05 with correlation coefficient ( R ) ≥ 0.38). We identified 50 additional CSF proteins associated with CSF tau and 46 proteins associated with CSF P-tau181 ( p value ≤ 0.05 with R ≥ 0.37). The majority of those proteins that showed such associations were brain-enriched proteins. Gene Ontology annotation revealed an enrichment for synaptic proteins and proteins originating from reelin-producing cells and the myelin sheath. We used an MS-based proteomic workflow to profile the CSF proteome in relation to cerebral AD pathology. We report strong evidence of previously reported CSF proteins and several novel CSF proteins specifically associated with amyloid pathology or neuronal injury and tau hyperphosphorylation.
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?
Four proteins (GPNMB, SMOC1, NPTX2, VGF) were previously reported in AD CSF.
“In the list, 4 proteins (GPNMB, SMOC1, NPTX2 and VGF) have previously been reported in AD CSF (Dayon et al., 2018; Huttenrauch et al., 2018; Llano et al., 2019; Xiao et al., 2017)”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Dayon et al., 2018
The Results and Discussion report NPTX2 and SMOC1 as CSF proteins associated with biomarkers of Alzheimer pathology. Our copy does not report GPNMB or VGF, so it supports only two of the four proteins attributed to this citation. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSMOC1 and GPNMB were reported to be CSF biomarker candidates for Alzheimer's disease in other recent biomarker studies.
“Consistently, SMOC1 and GPNMB were reported to be CSF biomarker candidates for AD in other recent biomarker studies [62, 69].”
From Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer’s disease (2020) · cites this paper as [69]
The Results section (page not available) identifies SMOC1 among CSF proteins that differed significantly between AD biomarker-profile groups, supporting its description as a candidate biomarker. The passages from our copy do not identify GPNMB as a CSF biomarker candidate; a search for GPNMB and its expanded name found no matching passage. (LLM, conf=0.88)
Experimental — accuracy not yet measured
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
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282 · see citing works
The Hospital Anxiety and Depression Scale
Zigmond, A. S., & Snaith, R. P. (1983) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.1983.tb09716.x · Cited by 47,139 · see citing works
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · PubMed · Cited by 21,010 · see citing works
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589 · see citing works
Regularization Paths for Generalized Linear Models via Coordinate Descent
Friedman, J., Hastie, T., & Tibshirani, R. (2010) · Journal of Statistical Software · doi:10.18637/jss.v033.i01 · Cited by 19,927 · see citing works
Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J., & Wouters, E. (2015) · Gerontology · doi:10.1159/000430949 · Cited by 19,803 · see citing works
Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly
Kangas, M., Korpelainen, R., Vikman, I., Nyberg, L., & Jämsä, T. J. (2014) · Gerontology · doi:10.1159/000362720 · Cited by 19,003 · see citing works
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657 · see citing works
Tissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286 · see citing works
Depression and quality of life in older persons: A review
Sivertsen, H., Bjørkløf, G. H., Engedal, K., Selbæk, G., & Helvik, A.-S. (2015) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000437299 · Cited by 14,152 · see citing works
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.008 · Cited by 10,152 · see citing works
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882 · see citing works
KEGG: new perspectives on genomes, pathways, diseases and drugs
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., & Morishima, K. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1092 · Cited by 8,865 · see citing works
UniProt: the Universal Protein knowledgebase
Apweiler, R. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh131 · Cited by 7,535 · 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
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946 · see citing works
UniProt: the universal protein knowledgebase
The UniProt Consortium (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1099 · Cited by 4,436 · see citing works
Regression Shrinkage and Selection via The Lasso: A Retrospective
Tibshirani, R. J. (2011) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2011.00771.x · Cited by 3,601 · see citing works
Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
Dubois, B., Feldman, H. H., Jacova, C., Hampel, H., Molinuevo, J. L., Blennow, K., DeKosky, S. T., Gauthier, S., Selkoe, D., Bateman, R., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70090-0 · Cited by 3,321 · see citing works
Albert, M., DeKosky, S. T., Dickson, D. W., Dubois, B., Feldman, H., Fox, N. C., Gamst, A. C., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2013) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.11.1.96 · Cited by 2,630 · 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
Expansion of the Gene Ontology knowledgebase and resources
The Gene Ontology Consortium (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1108 · Cited by 1,850 · see citing works
Jorm, A. F., & Jacomb, P. A. (1989) · Psychological Medicine · doi:10.1017/s0033291700005742 · Cited by 1,104 · 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
Somatostatin regulates brain amyloid β peptide Aβ42 through modulation of proteolytic degradation
Saito, T., Iwata, N., Tsubuki, S., Takaki, Y., Takano, J., Huang, S.-M., Suemoto, T., Higuchi, M., & Saido, T. C. (2005) · Nature Medicine · doi:10.1038/nm1206 · Cited by 361 · see citing works
Quantitative variability of 342 plasma proteins in a human twin population
Liu, Y., Buil, A., Collins, B. C., Gillet, L. C., Blum, L. C., Cheng, L., Vitek, O., Mouritsen, J., Lachance, G., Spector, T. D., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20145728 · Cited by 328 · see citing works
The cerebrospinal fluid “Alzheimer profile”: Easily said, but what does it mean?
Duits, F. H., Teunissen, C. E., Bouwman, F. H., Visser, P. J., Mattsson, N., Zetterberg, H., Blennow, K., Hansson, O., Minthon, L., Andreasen, N., et al. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2013.12.023 · Cited by 300 · see citing works
A Review of Fluid Biomarkers for Alzheimer’s Disease: Moving from CSF to Blood
Blennow, K. (2017) · Neurology and Therapy · doi:10.1007/s40120-017-0073-9 · Cited by 295 · see citing works
Association of Amyloid Pathology With Myelin Alteration in Preclinical Alzheimer Disease
Dean, D. C., Hurley, S. A., Kecskemeti, S. R., O’Grady, J. P., Canda, C., Davenport-Sis, N. J., Carlsson, C. M., Zetterberg, H., Blennow, K., Asthana, S., et al. (2017) · JAMA Neurology · doi:10.1001/jamaneurol.2016.3232 · Cited by 252 · cited 1× · see citing works
“, lower concentrations of Aβ1–42 and higher concentrations of tau and P-tau181), but mainly in association with amyloid pathology [59].”
BackgroundProteomics reveals the effects of sustained weight loss on the human plasma proteome
Geyer, P. E., Albrechtsen, N. J. W., Tyanova, S., Graßl, N., Iepsen, E. W., Lundgren, J. R., Madsbad, S., Holst, J. J., Torekov, S. S., & Mann, M. (2016) · Molecular Systems Biology · doi:10.15252/msb.20167357 · Cited by 235 · see citing works
Kim, M., Suh, J., Romano, D., Truong, M. H., Mullin, K., Hooli, B., Norton, D., Tesco, G., Elliott, K., Wagner, S. L., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp323 · Cited by 234 · see citing works
Diagnosis of early dementia by the Double Memory Test
Herman Buschke, L., Sliwinski, M. J., Kuslansky, G., & Lipton, R. B. (1997) · Neurology · doi:10.1212/wnl.48.4.989 · Cited by 222 · see citing works
Establishing the Proteome of Normal Human Cerebrospinal Fluid
Schutzer, S. E., Liu, T., Natelson, B. H., Angel, T. E., Schepmoes, A., Purvine, S. O., Hixson, K. K., Lipton, M. S. W., Camp, D., Coyle, P. K., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010980 · Cited by 217 · see citing works
The endocannabinoid system as a target for the treatment of neurodegenerative disease
Scotter, E. L., Abood, M. E., & Glass, M. (2010) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2010.00735.x · Cited by 181 · see citing works
Molecular diagnostics of neurodegenerative disorders
Agrawal, M., & Biswas, A. (2015) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2015.00054 · Cited by 164 · see citing works
Guldbrandsen, A., Vethe, H., Farag, Y. M., Oveland, E., Garberg, H., Berle, M., Myhr, K., Opsahl, J. A., Barsnes, H., & Berven, F. S. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.038554 · Cited by 163 · see citing works
The Role of ADAM10 in Alzheimer’s Disease
Yuan, X., Sun, S., Tan, C., Yu, J., & Tan, L. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170061 · Cited by 160 · see citing works
Vos, A. D., Jacobs, D., Struyfs, H., Fransén, E., Andersson, K., Portelius, E., Andréasson, U., Surgeloose, D. D., Hernalsteen, D., Sleegers, K., et al. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.05.012 · Cited by 158 · see citing works
Markers of neuroinflammation associated with Alzheimer’s disease pathology in older adults
Popp, J., Oikonomidi, A., Tautvydaitė, D., Dayon, L., Bacher, M., Migliavacca, E., Henry, H., Kirkland, R., Severin, I., Wojcik, J., et al. (2017) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2017.01.020 · Cited by 136 · see citing works
Self-citationKocherhans, S., Madhusudan, A., Doehner, J., Breu, K. S., Nitsch, R. M., Fritschy, J.-M., & Knuesel, I. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.0418-10.2010 · Cited by 132 · see citing works
Blood-Based Proteomic Biomarkers of Alzheimer’s Disease Pathology
Baird, A. L., Westwood, S., & Lovestone, S. (2015) · Frontiers in Neurology · doi:10.3389/fneur.2015.00236 · Cited by 118 · see citing works
Wang, J., Xu, J., Finnerty, J., Furuta, M., Steiner, D. F., & Verchere, C. B. (2001) · Diabetes · doi:10.2337/diabetes.50.3.534 · Cited by 112 · see citing works
Biomarker discovery in neurodegenerative diseases: A proteomic approach
Shi, M. Y., Caudle, W. M., & Zhang, J. (2008) · Neurobiology of Disease · doi:10.1016/j.nbd.2008.09.004 · Cited by 111 · see citing works
Aebersold, R. H., Bader, G. D., Edwards, A. M., Eyk, J. E. V., Kussmann, M., Qin, J., & Omenn, G. S. (2012) · Journal of Proteome Research · doi:10.1021/pr301151m · Cited by 102 · see citing works
Self-citationQuantification of the Brain Proteome in Alzheimer’s Disease Using Multiplexed Mass Spectrometry
Musunuri, S., Wetterhall, M., Ingelsson, M., Lannfelt, L., Artemenko, K. A., Bergquist, J., Kultima, K., & Shevchenko, G. (2014) · Journal of Proteome Research · doi:10.1021/pr401202d · Cited by 102 · see citing works
Remnestål, J., Just, D., Mitsios, N., Fredolini, C., Mulder, J., Schwenk, J. M., Uhlén, M., Kultima, K., Ingelsson, M., Kilander, L., et al. (2016) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201500150 · Cited by 97 · see citing works
Brain-specific Proteins Decline in the Cerebrospinal Fluid of Humans with Huntington Disease
Fang, Q., Strand, A. D., Law, W., Faça, V. M., Fitzgibbon, M., Hamel, N., Houle, B., Liu, X., May, D., Poschmann, G., et al. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800231-mcp200 · Cited by 92 · see citing works
Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry
Cominetti, O., Galindo, A. N., Corthésy, J., Moreno, S. O., Irincheeva, I., Valsesia, A., Astrup, A. V., Saris, W. H. M., Hager, J., Kussmann, M., et al. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00901 · Cited by 91 · see citing works
Self-citationBegcevic, I., Brinc, D., Drabovich, A. P., Batruch, I., & Diamandis, E. P. (2016) · Clinical Proteomics · doi:10.1186/s12014-016-9111-3 · Cited by 84 · see citing works
Identification of genetic variants influencing the human plasma proteome
Johansson, Å., Enroth, S., Palmblad, M., Deelder, A. M., Bergquist, J., & Gyllensten, U. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217238110 · Cited by 82 · see citing works
Nilsson, C. L., Brinkmalm, A., Minthon, L., Blennow, K., & Ekman, R. (2001) · Peptides · doi:10.1016/s0196-9781(01)00571-x · Cited by 79 · see citing works
Swanson, A., & Willette, A. A. (2016) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2016.07.148 · Cited by 79 · see citing works
A comprehensive map and functional annotation of the normal human cerebrospinal fluid proteome
Zhang, Y., Guo, Z., Zou, L., Yang, Y., Zhang, L., Ji, N., Shao, C., Sun, W., & Wang, Y. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.01.017 · Cited by 78 · see citing works
Relative Protein Quantification by MS/MS Using the Tandem Mass Tag Technology
Dayon, L., & Sanchez, J. (2012) · Methods in molecular biology · doi:10.1007/978-1-61779-885-6_9 · Cited by 73 · see citing works
Self-citationDietary patterns and ethnicity are associated with distinct plasma proteomic groups
García‐Bailo, B., Brenner, D. R., Nielsen, D. E., Lee, H., Domański, D., Kuzyk, M. A., Borchers, C. H., Badawi, A. F., Karmali, M. A., & El‐Sohemy, A. (2011) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.111.022657 · Cited by 73 · see citing works
Cole, R. N., Ruczinski, I., Schulze, K. J., Christian, P. S., Herbrich, S. M., Wu, L. S. F., Devine, L. R., O’Meally, R. N., Shrestha, S., Boronina, T. N., et al. (2013) · Journal of Nutrition · doi:10.3945/jn.113.175018 · Cited by 54 · see citing works
Stumm, C., Hiebel, C., Hanstein, R., Purrio, M., Nagel, H., Conrad, A., Lutz, B., Behl, C., & Clement, A. B. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.05.027 · Cited by 53 · see citing works
Dayon, L., Galindo, A. N., Corthésy, J., Cominetti, O., & Kussmann, M. (2014) · Journal of Proteome Research · doi:10.1021/pr500635f · Cited by 51 · see citing works
Self-citationWestwood, S., Liu, B., Baird, A. L., Anand, S. N., Nevado‐Holgado, A. J., Newby, D., Pikkarainen, M., Hallikainen, M., Kuusisto, J., Streffer, J. R., et al. (2017) · Alzheimer s Research & Therapy · doi:10.1186/s13195-017-0258-6 · Cited by 50 · see citing works
Moreno, S. O., Cominetti, O., Galindo, A. N., Irincheeva, I., Corthésy, J., Astrup, A. V., Saris, W. H. M., Hager, J., Kussmann, M., & Dayon, L. (2017) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201600150 · Cited by 45 · see citing works
Self-citationDayon, L., & Kussmann, M. (2013) · EuPA Open Proteomics · doi:10.1016/j.euprot.2013.08.001 · Cited by 40 · see citing works
Self-citationGalindo, A. N., Kussmann, M., & Dayon, L. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b02748 · Cited by 35 · see citing works
Self-citationTautvydaitė, D., Antonietti, J., Henry, H., von Gunten, A., & Popp, J. (2017) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.12.024 · Cited by 35 · see citing works
Self-citationForsova, O. S., & Zakharov, V. V. (2016) · FEBS Journal · doi:10.1111/febs.13692 · Cited by 33 · see citing works
Winsky‐Sommerer, R., Grouselle, D., Rougeot, C., Laurent, V., David, J.-P., Delacourte, A., Dournaud, P., Seidah, N. G., Lindberg, I., Trottier, S., et al. (2003) · Neuroscience · doi:10.1016/s0306-4522(03)00560-8 · Cited by 32 · see citing works
Balogiannis, S. (2005) · International Journal of Neuroscience · doi:10.1080/00207450590901396 · Cited by 31 · see citing works
Plasma Proteome Biomarkers of Inflammation in School Aged Children in Nepal
Lee, S. E., West, K. P., Cole, R. N., Schulze, K. J., Christian, P. S., Wu, L. S., Yager, J. D., Groopman, J. D., & Ruczinski, I. (2015) · PLoS ONE · doi:10.1371/journal.pone.0144279 · Cited by 30 · see citing works
CSF biomarkers for Alzheimer disease — approaching consensus
Galasko, D. R., & Shaw, L. M. J. (2017) · Nature Reviews Neurology · doi:10.1038/nrneurol.2017.11 · Cited by 28 · see citing works
Dayon, L., Galindo, A. N., Cominetti, O., Corthésy, J., & Kussmann, M. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7057-5_30 · Cited by 28 · see citing works
Self-citationAmbulante Durchführung einer diagnostischen Lumbalpunktion in der Gedächtnissprechstunde
Popp, J., Riad, M., Freymann, K., et al. (2006) · Der Nervenarzt · doi:10.1007/s00115-006-2174-z · Cited by 27 · see citing works
Self-citationLee, S. E., Stewart, C. P., Schulze, K. J., et al. (2017) · Journal of Nutrition · doi:10.3945/jn.116.243014 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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
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
“(F) Consistent protein changes of 8 proteins in AD brain tissue and CSF.”
BackgroundInfluentialProteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer's disease
Bader, J. M., Geyer, P. E., Müller, J. B., Strauss, M. T., Koch, M., Leypoldt, F., Koertvelyessy, P., Bittner, D., Schipke, C. G., Incesoy, E. I., et al. (2020) · Molecular Systems Biology · doi:10.15252/msb.20199356 · Cited by 286 · see citing works
Wang, H., Dey, K. K., Chen, P.-C., Li, Y., Niu, M., Cho, J.-H., Wang, X., Bai, B., Jiao, Y., Chepyala, S. R., et al. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00384-6 · Cited by 210 · see citing works
Cerebrospinal 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
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. (2020) · Clinical Proteomics · doi:10.1186/s12014-020-09285-8 · Cited by 92 · see citing works
- Authors
- Dayon, L., Núñez Galindo, A., Wojcik, J., Cominetti, O., Corthésy, J., Oikonomidi, A., Henry, H., Kussmann, M., Migliavacca, E., Severin, I., Bowman, G. L., & Popp, J.
- Affiliations
- Bibliothèque de Genève (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- University of Auckland (NZ)
- ORCID
- Venue
- Alzheimer's Research & Therapy
- Published
- 2018-07-18
- Volume
- 10
- Issue
- 1
- Pages
- 66-66
- ISSN
- 1758-9193 (ISSN-L)
- PMC
- PMC6052524
- OpenAlex
- W2884550682
- Cited by
- 101
- References
- 73
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 18 · 2023: 18 · 2022: 12 · 2021: 24 · 2020: 15 · 2019: 6
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Alzheimer s Research & Therapy (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- SERVAL (Université de Lausanne) (publishedVersion, other-oa)
- IRIS (submittedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF 320030_141179)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- Alzheimer's disease, cerebrospinal fluid proteome, amyloid pathology, tau hyperphosphorylation, p-tau181, amyloid-beta 42, cerebrospinal fluid biomarkers, neuronal injury, synaptic proteins, reelin, cognitive impairment
- MeSH terms
- Reelin Protein, Age Factors, Aged, Aged, 80 and over, Alzheimer Disease, Apolipoproteins E, Chromatography, Liquid, Educational Status, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Peptide Fragments, Phosphorylation, Sex Factors, Amyloid beta-Peptides, tau Proteins, Proteome, Tandem Mass Spectrometry
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
