The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Plasma Protein Biomarkers for Depression and Schizophrenia by Multi Analyte Profiling of Case-Control Collections
Open accessAbstract
Despite significant research efforts aimed at understanding the neurobiological underpinnings of psychiatric disorders, the diagnosis and the evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms. Therefore, biological markers which could improve the current classification of psychiatry disorders, and in perspective stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. In order to identify novel candidate biological markers for major depression and schizophrenia, we have applied a focused proteomic approach using plasma samples from a large case-control collection. Patients were diagnosed according to DSM criteria using structured interviews and a number of additional clinical variables and demographic information were assessed. Plasma samples from 245 depressed patients, 229 schizophrenic patients and 254 controls were submitted to multi analyte profiling allowing the evaluation of up to 79 proteins, including a series of cytokines, chemokines and neurotrophins previously suggested to be involved in the pathophysiology of depression and schizophrenia. Univariate data analysis showed more significant p-values than would be expected by chance and highlighted several proteins belonging to pathways or mechanisms previously suspected to be involved in the pathophysiology of major depression or schizophrenia, such as insulin and MMP-9 for depression, and BDNF, EGF and a number of chemokines for schizophrenia. Multivariate analysis was carried out to improve the differentiation of cases from controls and identify the most informative panel of markers. The results illustrate the potential of plasma biomarker profiling for psychiatric disorders, when conducted in large collections. The study highlighted a set of analytes as candidate biomarker signatures for depression and schizophrenia, warranting further investigation in independent collections.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
An introduction to ROC analysis
Fawcett, T. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.10.010 · Cited by 21,879
Inflammation and Its Discontents: The Role of Cytokines in the Pathophysiology of Major Depression
Miller, A. H., Maletic, V., & Raison, C. L. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.11.029 · Cited by 3,848
Cytokines sing the blues: inflammation and the pathogenesis of depression
Raison, C. L., Capuron, L., & Miller, A. H. (2006) · Trends in Immunology · doi:10.1016/j.it.2005.11.006 · Cited by 3,009
Associations of depression with C-reactive protein, IL-1, and IL-6: a meta-analysis.
Howren, M. B., Lamkin, D. M., & Suls, J. (2009) · Psychosomatic Medicine · doi:10.1097/psy.0b013e3181907c1b · Cited by 2,766
Sen, S., Duman, R., & Sanacora, G. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.05.005 · Cited by 1,232
Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins
Ray, S., Britschgi, M., Herbert, C., Takeda-Uchimura, Y., Boxer, A., Blennow, K., Friedman, L. F., Galasko, D. R., Jutel, M., Karydas, A., et al. (2007) · Nature Medicine · doi:10.1038/nm1653 · Cited by 1,048
Cytokine Production and Treatment Response in Major Depressive Disorder
Lanquillon, S. (2000) · Neuropsychopharmacology · doi:10.1016/s0893-133x(99)00134-7 · Cited by 735
Maes, M., Bosmans, E., De Jongh, R., Kenis, G., Vandoolaeghe, E., & Neels, H. (1997) · Cytokine · doi:10.1006/cyto.1997.0238 · Cited by 728
Wittchen, H.-U., Lachner, G., Wunderlich, U., & Pfister, H. (1998) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s001270050095 · Cited by 668
Cited by
Depression as a Microglial Disease
Yirmiya, R., Rimmerman, N., & Reshef, R. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2015.08.001 · Cited by 944
Kim, Y.-K., Na, K.-S., Myint, A.-M., & Leonard, B. E. (2016) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.06.008 · Cited by 620
Treatment-resistant depression and peripheral C-reactive protein.
Chamberlain, S. R., Cavanagh, J., de Boer, P., Mondelli, V., Jones, D. N. C., Drevets, W. C., Cowen, P. J., Harrison, N. A., Pointon, L., Pariante, C. M., et al. (2019) · British Journal of Psychiatry · doi:10.1192/bjp.2018.66 · Cited by 400
Self-citationHashimoto, K. (2010) · Psychiatry and Clinical Neurosciences · doi:10.1111/j.1440-1819.2010.02113.x · Cited by 388
Leighton, S. P., Nerurkar, L., Krishnadas, R., Johnman, C., Graham, G. J., & Cavanagh, J. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.205 · Cited by 291
Metadata
- Authors
- Domenici, E., Willé, D. R., Tozzi, F., Prokopenko, I., Miller, S., McKeown, A., Brittain, C., Rujescu, D., Giegling, I., Turck, C. W., Holsboer, F., Bullmore, E. T., Middleton, L., Merlo-Pich, E., Alexander, R. C., & Muglia, P.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-02-11
- Volume
- 5
- Issue
- 2
- Pages
- e9166
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2007353040
- Cited by
- 347
- References
- 54
- FWCI
- 6.69
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Plasma Protein Biomarkers for Depression and Schizophrenia by Multi Analyte Profiling of Case-Control Collections. https://app.cochat.ai/papers/10.1371/journal.pone.0009166
- The paper
- Domenici, E., Willé, D. R., Tozzi, F., Prokopenko, I., Miller, S., McKeown, A., Brittain, C., Rujescu, D., Giegling, I., Turck, C. W., Holsboer, F., Bullmore, E. T., Middleton, L., Merlo-Pich, E., Alexander, R. C., & Muglia, P. (2010). Plasma Protein Biomarkers for Depression and Schizophrenia by Multi Analyte Profiling of Case-Control Collections. PLoS ONE. https://doi.org/10.1371/journal.pone.0009166
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
