Evidence map›Paper›PMID 35599275›Full record

ArticleMolecular neurobiology2022

Identification of Peripheral Blood miRNA Biomarkers in First-Episode Drug-Free Schizophrenia Patients Using Bioinformatics Strategy.

Mengdi Jin, Xiaojing Zhu, Yaoyao Sun, Zhijun Li, Xinwei Li, Lizhe Ai, Yang He, Yane Liu, Ningning Jia, Guoyan Hu and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular neurobiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 11% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. MicroRNAs as biomarkers and molecular mediators of cognitive dysfunction in schizophrenia.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  4. LncRNA-miRNA‒mRNA Network in Schizophrenia.Journal of molecular neuroscience : MN · 2025
    Article
  5. miRNA-Based Diagnosis of Schizophrenia Using Machine Learning.International journal of molecular sciences · 2025
    Article
  6. Article
  7. Article
  8. The Role of microRNA in Schizophrenia: A Scoping Review.International journal of molecular sciences · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Mapping miRNA Research in Schizophrenia: A Scientometric Review.International journal of molecular sciences · 2022
    Review
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

14 authors at 1 institution in 1 country.

Mengdi JinDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Xiaojing ZhuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Yaoyao SunDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Zhijun LiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Xinwei LiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Lizhe AiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Yang HeDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Yane LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Ningning JiaDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Guoyan HuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Xingyao CuiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Mengtong XieDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Yuqing YangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China.
Qiong YuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, China. yuqiong@jlu.edu.cn.ORCID http://orcid.org/0000-0003-1143-1749
Jilin University · CN

Funding

National Natural Science Foundation of China 81673253the Jilin Provincial Ministry of Education S & T Project JJKH20190091KJ
6 · The paper itself

Abstract

Schizophrenia (SCZ) is a polygenic, complex mental disorder of which a diagnosis is often made based on psychiatric history and clinical observation with few available objectives and detectable biomarkers. To identify co-expressed miRNA modules in schizophrenia patients and verify the possibility of using peripheral blood miRNAs as novel biomarkers, high-throughput sequencing was performed on 15 first-episode schizophrenia patients (FES) and 15 healthy controls (CTL). We found 79 differential expressed miRNAs (DEMs) in FES patients and three FES-related co-expression miRNA modules by miRNA-seq data standardized difference analysis and weighted gene co-expression network analysis (WGCNA). Then, 41 hub miRNAs were screened from the intersection of key modules and DEMs, among which miR-9-5p, miR-144-3p, miR-328-3p, and miR-4467 were selected for qRT-PCR verification in a larger sample (FES = 35, CTL = 60). The level of miR-9-5p in FES patients was downregulated, and miR-4467 was upregulated with better diagnostic performance (AUC = 0.719). The target genes of miR-9-5p engage in the biological processes (BP) such as body behaviour, neuronal differentiation regulation, nervous system development, and neurotrophin signaling pathways. Their hub target genes were also located, including NEDD4, EIF4G1, FBXL16, and FBXL3. Summarily, miR-9-5p and miR-4467 hold promise in blood diagnosis for SCZ, and miR-9-5p might affect the onset and development of SCZ through target regulation of neurodevelopment-related mRNAs. Our findings revealed the complex relationship between the miRNA co-expression network and FES, providing more verifiable biomarkers for SCZ early diagnosis and clues for the etiology of schizophrenia.

Indexed as

MicroRNAsSchizophreniaBiomarkersComputational BiologyGene Expression ProfilingHumansBiomarkersMicroRNAsFirst-episode schizophreniaHigh-throughput sequencing analysismiRNAsqRT-PCRWeighted gene co-expression network analysis (WGCNA)

Identifiers

PMID35599275
OpenAlexW4281290079

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Registered trials

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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.