Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics
Open accessAbstract
Introduction Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive.Objectives To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls.Methods CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set.Results 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism.Conclusion Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as candidate biomarkers in parkinsonism.
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NPTXR and NPTX1 were decreased in atypical parkinsonian disorders (progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration) in comparison with controls.
“Further to this, NPTXR and NPTX1 were decreased in atypical parkinsonian disorders (progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration) in comparison with controls (Magdalinou et al. 2017).”
From Neuronal pentraxins as biomarkers of synaptic activity: from physiological functions to pathological changes in neurodegeneration (2022) · cites this paper as Magdalinou et al. 2017
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447 · see citing works
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., & Müller, M. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-77 · Cited by 13,697 · see citing works
Hughes, A. J., Daniel, S. E., Kilford, L., & Lees, A. J. (1992) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.55.3.181 · Cited by 10,378 · see citing works
Self-citationMutations in the parkin gene cause autosomal recessive juvenile parkinsonism
Kitada, T., Asakawa, S., Hattori, N., Matsumine, H., Yamamura, Y., Minoshima, S., Yokochi, M., Mizuno, Y., & Shimizu, N. (1998) · Nature · doi:10.1038/33416 · Cited by 5,227 · see citing works
Second consensus statement on the diagnosis of multiple system atrophy
Gilman, S., Wenning, G. K., Low, P. A., Brooks, D. J., Mathias, C. J., Trojanowski, J. Q., Wood, N. W., Colosimo, C., Dürr, A., Fowler, C. J., et al. (2008) · Neurology · doi:10.1212/01.wnl.0000324625.00404.15 · Cited by 3,140 · see citing works
Self-citationWalport, M. J. (2001) · New England Journal of Medicine · doi:10.1056/nejm200104053441406 · Cited by 2,921 · see citing works
Litvan, I., Agid, Y., Calne, D., Campbell, G., Dubois, B., Duvoisin, R. C., Goetz, C. G., Golbe, L. I., Grafman, J., Growdon, J. H., et al. (1996) · Neurology · doi:10.1212/wnl.47.1.1 · Cited by 2,538 · see citing works
Wiklund, R. A., & Rosenbaum, S. H. (1997) · New England Journal of Medicine · doi:10.1056/nejm199710163371606 · Cited by 2,159 · see citing works
The current and projected economic burden of Parkinson's disease in the United States
Kowal, S. L., Dall, T. M., Chakrabarti, R., Storm, M. V., & Jain, A. (2013) · Movement Disorders · doi:10.1002/mds.25292 · Cited by 667 · see citing works
Identification of common variants influencing risk of the tauopathy progressive supranuclear palsy
PSP Genetics Study Group, Höglinger, G. U., Melhem, N. M., Dickson, D. W., Sleiman, P. M. A., Wang, L.-S., Klei, L., Rademakers, R., de Silva, R., Litvan, I., et al. (2011) · Nature Genetics · doi:10.1038/ng.859 · Cited by 603 · see citing works
Self-citationDayon, L., Hainard, A., Licker, V., Turck, N., Kuhn, K., Hochstrasser, D. F., Burkhard, P. R., & Sanchez, J. (2008) · Analytical Chemistry · doi:10.1021/ac702422x · Cited by 565 · see citing works
Hall, S., Öhrfelt, A., Constantinescu, R., Andreasson, U., Surova, Y., Bostrom, F., Nilsson, C., Widner, H., Decraemer, H., Nägga, K., et al. (2012) · Archives of Neurology · doi:10.1001/archneurol.2012.1654 · Cited by 473 · see citing works
Self-citationClinical outcomes of progressive supranuclear palsy and multiple system atrophy
O’Sullivan, S. S., Massey, L. A., Williams, D. R., Silveira‐Moriyama, L., Kempster, P. A., Holton, J. L., Révész, T., & Lees, A. J. (2008) · Brain · doi:10.1093/brain/awn065 · Cited by 423 · see citing works
Self-citationVeeriah, S., Taylor, B. S., Meng, S., Fang, F., Yilmaz, E., Vivanco, I., Janakiraman, M., Schultz, N. D., Hanrahan, A. J., Pao, W. J., et al. (2009) · Nature Genetics · doi:10.1038/ng.491 · Cited by 407 · see citing works
Abdi, F. A., Quinn, J. F., Jankovic, J. J., McIntosh, M. W., Leverenz, J. B., Peskind, E. R., Nixon, R., Nutt, J. G., Chung, K., Zabetian, C. P., et al. (2006) · Journal of Alzheimer s Disease · doi:10.3233/jad-2006-9309 · Cited by 385 · see citing works
A mitochondrial etiology of Alzheimer and Parkinson disease
Coskun, P. E., Wyrembak, J., Schriner, S. E., Chen, H.-W., Marciniack, C., LaFerla, F. M., & Wallace, D. C. (2011) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2011.08.008 · Cited by 297 · see citing works
CSF Multianalyte Profile Distinguishes Alzheimer and Parkinson Diseases
Zhang, J., Sokal, I., Peskind, E. R., Quinn, J. F., Jankovic, J. J., Kenney, C., Chung, K. A., Millard, S. P., Nutt, J. G., & Montine, T. J. (2008) · American Journal of Clinical Pathology · doi:10.1309/w01y0b808emeh12l · Cited by 263 · see citing works
Magdalinou, N. K., Paterson, R. W., Schott, J. M., Fox, N. C., Mummery, C. J., Blennow, K., Bhatia, K. P., Morris, H. R., Giunti, P., Warner, T. T., et al. (2015) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2014-309562 · Cited by 250 · see citing works
Self-citationDiagnostic criteria for corticobasal syndrome: a comparative study
Mathew, R., Bak, T. H., & Hodges, J. R. (2011) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2011-300875 · Cited by 195 · see citing works
Cancer and Neurodegeneration: Between the Devil and the Deep Blue Sea
Plun‐Favreau, H., Lewis, P. A., Hardy, J., Martins, L. M., & Wood, N. W. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001257 · Cited by 173 · see citing works
Yin, G. N., Lee, H. W., Cho, J.-Y., & Suk, K. (2009) · Brain Research · doi:10.1016/j.brainres.2009.01.058 · Cited by 143 · see citing works
Goldknopf, I., Sheta, E., Bryson, J., Folsom, B., Wilson, C., Duty, J., Yen, A., & Appel, S. (2006) · Biochemical and Biophysical Research Communications - BBRC · doi:10.1016/j.bbrc.2006.02.051 · Cited by 125 · see citing works
Cerebrospinal fluid biomarkers in parkinsonian conditions: an update and future directions
Magdalinou, N. K., Lees, A. J., & Zetterberg, H. (2014) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2013-307539 · Cited by 93 · see citing works
Self-citationKim, T., Wu, K. M., Xu, J., McAuliffe, G., Tanzi, R. E., Wasco, W., & Black, I. B. (1995) · Molecular Brain Research · doi:10.1016/0169-328x(95)00328-p · Cited by 75 · see citing works
Shi, M. Y., Movius, J., Dator, R., Aro, P., Zhao, Y., Pan, C., Lin, X., Bammler, T. K., Stewart, T., Zabetian, C. P., et al. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.040576 · Cited by 68 · see citing works
Lehnert, S., Jesse, S., Rist, W., Steinacker, P., Soininen, H. S., Herukka, S., Tumani, H., Lenter, M., Oeckl, P., Ferger, B., et al. (2012) · Experimental Neurology · doi:10.1016/j.expneurol.2012.01.024 · Cited by 63 · see citing works
Proteomic profiling of cerebrospinal fluid in parkinsonian disorders
Constantinescu, R., Andréasson, U., Li, S., Podust, V. N., Mattsson, N., Anckarsäter, R., Anckarsäter, H. S., Rosengren, L., Holmberg, B., Blennow, K., et al. (2010) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2010.06.011 · Cited by 43 · see citing works
Self-citationα-1-Antichymotrypsin gene polymorphism and susceptibility to multiple system atrophy (MSA)
Furiya, Y., Hirano, M., Kurumatani, N., Nakamuro, T., Matsumura, R., Futamura, N., & Ueno, S. (2005) · Molecular Brain Research · doi:10.1016/j.molbrainres.2005.04.011 · Cited by 36 · see citing works
Cerebrospinal fluid proteomic patterns discriminate Parkinson's disease and multiple system atrophy
Ishigami, N., Tokuda, T., Ikegawa, M., Komori, M., Kasai, T., Kondo, T., Matsuyama, Y., Nirasawa, T., Thiele, H., Tashiro, K., et al. (2012) · Movement Disorders · doi:10.1002/mds.24994 · Cited by 32 · see citing works
Cramer, H., Rißler, K., Rösler, N., et al. (2008) · European Neurology · doi:10.1159/000116366 · Cited by 29 · see citing works
Towards proteome standards: The use of absolute quantitation in high-throughput biomarker discovery
Chao, T., Hansmeier, N., & Halden, R. U. (2010) · Journal of Proteomics · doi:10.1016/j.jprot.2010.04.004 · Cited by 24 · see citing works
The secretogranin II gene is a signal integrator of glutamate and dopamine inputs
Iwase, K., Ishihara, A., Yoshimura, S., Andoh, Y., Kato, M., Seki, N., Matsumoto, E., Hiwasa, T., Müller, D., Fukunaga, K., et al. (2013) · Journal of Neurochemistry · doi:10.1111/jnc.12467 · Cited by 18 · see citing works
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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-citationAlirezaei, Z., Pourhanifeh, M. H., Borran, S., Nejati, M., Mirzaei, H., & Hamblin, M. R. (2020) · Molecular Neurobiology · doi:10.1007/s12035-019-01698-3 · Cited by 142 · see citing works
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- Authors
- Magdalinou, N. K., Noyce, A. J., Pinto, R., Lindstrom, E., Holmén-Larsson, J., Holtta, M., Blennow, K., Morris, H. R., Skillbäck, T., Warner, T. T., Lees, A. J., Pike, I., Ward, M., Zetterberg, H., & Gobom, J.
- Affiliations
- National Hospital for Neurology and Neurosurgery (GB)
- Umeå University (SE)
- University of Gothenburg (SE)
- The Royal Free Hospital (GB)
- Proteome Sciences (United Kingdom) (GB)
- Corresponding author
- Magdalinou, N.K.
- ORCID
- Venue
- Parkinsonism & Related Disorders
- Publisher
- Elsevier BV
- Published
- 2017-04
- Volume
- 37
- Pages
- 65-71
- ISSN
- 1353-8020 (ISSN-L)
- OpenAlex
- W2583303566
- Cited by
- 49
- References
- 33
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 5 · 2023: 3 · 2022: 9 · 2021: 4 · 2020: 7 · 2019: 5 · 2018: 4 · 2017: 2
- FWCI
- 3.43
- Type
- journal article
- Language
- en
- Open access
- green
- qmro.qmul.ac.uk
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Parkinsonism & Related Disorders (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by-nc-nd)
- Funders
- Swedish Research Council (521-2011-4709)
- Gun och Bertil Stohnes Stiftelse
- the Leonard Wolfson Experimental Neurology Centre
- Demensförbundet
- Stiftelsen för Gamla Tjänarinnor
- Topics
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- cerebrospinal fluid biomarkers, parkinsonism
- MeSH terms
- Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Cohort Studies, Biomarkers, Neurofilament Proteins, Parkinsonian Disorders, Proteomics, alpha-Synuclein
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