Evidence mapPaperPMID 40794250Full record

ArticleJournal of molecular neuroscience : MN2025

LncRNA-miRNA‒mRNA Network in Schizophrenia.

Jianxiong Long, Weiwei Lan, Bing Shen, Fangping Liao, Hong Cai, Jiale Li, Rumei Lu, Zhicheng Zhong, Zukang Gong, Jianfeng Xu

Abstract read
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In one paragraph

Article in Journal of molecular neuroscience : MN, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

10 authors.

Jianxiong Long *Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Weiwei Lan *Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Bing Shen *Epidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Fangping LiaoKey Laboratory of Basic Research on Regional Diseases (Guangxi Medical University), School of Basic Medical Science, Guangxi Medical University, Nanning, Guangxi, China.
Hong CaiUnit of Medical Psychology and Behavior Medicine, School of public health, Guangxi Medical University, Nanning, Guangxi, China.
Jiale LiEpidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Rumei LuEpidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Zhicheng ZhongEpidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Zukang GongNanning Fifth People's Hospital, Nanning, Guangxi, China. 976016780@qq.com.
Jianfeng XuEpidemiology and Biostatistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China. jxu8088@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schizophrenia (SCZ) is a severe mental disorder that significantly impacts the social functioning of patients and can reduce their life expectancy and quality of life. However, the specific causes of SCZ remain unknown, and the evidence indicates that long noncoding RNAs (lncRNAs) play critical roles in its pathogenesis. Analyzing lncRNA expression in peripheral blood samples from patients could reveal the biological mechanisms underlying the disease and help in the identification of biomarkers for early diagnosis and treatment. This study utilized whole-transcriptome sequencing to analyze lncRNA expression in 5 SCZ patients and 5 healthy controls. We constructed lncRNA‒microRNA (miRNA) and miRNA‒messenger RNA (mRNA) interaction pairs and established a competing endogenous RNA (ceRNA) network. Additionally, a weighted gene coexpression network analysis (WGCNA) and lncRNA‒RNA binding protein (RBP) network construction were performed. The potential functions of the mRNAs were predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A total of 438 differentially expressed lncRNAs (DElncRNAs) were identified in patients with SCZ compared with controls, with 260 upregulated and 178 downregulated. The ceRNA network comprised 383 DElncRNAs, 304 miRNAs, and 1849 mRNAs. GO and KEGG analyses indicated that these genes are involved in pathways such as the HIF-1 signaling pathway and oxidative phosphorylation, both of which are relevant to SCZ. Based on the ceRNA network-derived mRNAs, WGCNA identified three disease-associated modules. Furthermore, interactions between RBPs and DElncRNAs may play a significant role in the pathophysiology of SCZ. This study identifies 438 dysregulated lncRNAs in SCZ, constructs a ceRNA network implicating HIF-1 signaling and oxidative phosphorylation pathways, and reveals disease-associated coexpression modules and RBP-lncRNA interactions, providing novel insights into SCZ pathogenesis and potential diagnostic biomarkers.

Indexed as

Gene Regulatory NetworksMicroRNAsRNA, Long NoncodingRNA, MessengerSchizophreniaAdultFemaleHumansMaleMiddle AgedMicroRNAsRNA, Long NoncodingRNA, MessengerCase‒control studyCeRNA networkLncRNARBP networkSchizophreniaWGCNA

Identifiers

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Registered trials

None linked

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 Socratic graph.