Evidence map›Paper›PMID 31786691›Full record

ArticleJournal of neural transmission (Vienna, Austria : 1996)2020

Profiling of schizophrenia-associated serum peptides by MALDI-TOF-MS.

Yingli Fu, Na Zhou, Yaqin Yu, Huiping Zhang, Yaoyao Sun, Mingyuan Zhang, Xin Chen, Yueying Wang, Qiong Yu

Abstract read
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In one paragraph

Article in Journal of neural transmission (Vienna, Austria : 1996), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yingli FuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Na ZhouDepartment of Pharmacy, School and Hospital of Stomatology, Jilin University, Changchun, Jilin, China.
Yaqin YuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Huiping ZhangDepartments of Psychiatry and Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
Yaoyao SunDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Mingyuan ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Xin ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Yueying WangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China.
Qiong YuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin, China. yuqiong@jlu.edu.cn.ORCID http://orcid.org/0000-0003-1143-1749

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schizophrenia is a psychiatric condition characterized by poor prognosis and severe symptoms that decrease the quality of life of patients. It is therefore important to develop rapid and reliable methods for early diagnosis. To achieve this aim, identification of accurate biomarkers will promote research into the mechanisms of schizophrenia and the design of effective diagnosis tools. Discriminative peptides in the serum of participants (277 schizophrenia patients and 294 healthy controls) were detected using the matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF-MS). The diagnostic model for schizophrenia was validated using the ClinProTool software. Discrimination models were tested in the training set (200 schizophrenia patients and 200 healthy controls), and the robustness of the models was evaluated using the independent test set (77 cases and 94 controls). A total of 77 peaks were significantly different between schizophrenia patients and healthy controls with a signal-to-noise ratio of over 5. Among them, 35 peptides were down-regulated and 42 peptides were up-regulated in schizophrenia patients. With a cross-validation rate of 92.7% and a recognition capability rate of 96.5%, the supervised neural network comprising 25 discriminative peaks was found to be the most efficient model for schizophrenia diagnosis (sensitivity = 96.10%, specificity = 94.68%). Peptides at m/z = 2022.18 corresponded to complement C3f, and peptides at m/z = 1020.89, 1351.02, 1466.1 were identified as fragments of fibrinopeptide A. These two peptides may be potential biomarkers for schizophrenia in the Chinese population. The serum peptide levels present a potential clinical diagnostic tool for schizophrenia.

Indexed as

AlgorithmsProteomeSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTandem Mass SpectrometryAdultBiomarkersComplement C3bDown-RegulationFemaleFibrinopeptide AHumansMaleMiddle AgedNeural Networks, ComputerPeptidesSchizophreniaBiomarkersComplement C3bcomplement C3fFibrinopeptide APeptidesProteomeBiomarkerDiagnosis modelProtein peptide profilingSchizophrenia

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.