Evidence map›Paper›PMID 35449567›Full record

ArticleFrontiers in psychiatry2022

MicroRNA-Messenger RNA Regulatory Network Mediates Disrupted TH17 Cell Differentiation in Depression.

Haiyang Wang, Lanxiang Liu, Xueyi Chen, Chanjuan Zhou, Xuechen Rao, Wenxia Li, Wenwen Li, Yiyun Liu, Liang Fang, Hongmei Zhang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Therapeutic Implications of microRNAs in Depressive Disorders: A 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

13 authors at 2 institutions in 1 country.

Haiyang WangKey Laboratory of Psychoseomadsy, Stomatological Hospital of Chongqing Medical University, Chongqing, China.
Lanxiang LiuNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xueyi ChenNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Chanjuan ZhouNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xuechen RaoNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenxia LiNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenwen LiDepartment of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing, China.
Yiyun LiuNational Health Commission Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Liang FangDepartment of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Hongmei ZhangKey Laboratory of Psychoseomadsy, Stomatological Hospital of Chongqing Medical University, Chongqing, China.
Jinlin SongKey Laboratory of Psychoseomadsy, Stomatological Hospital of Chongqing Medical University, Chongqing, China.
Ping JiKey Laboratory of Psychoseomadsy, Stomatological Hospital of Chongqing Medical University, Chongqing, China.
Peng XieKey Laboratory of Psychoseomadsy, Stomatological Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulating evidence indicates an important role for microRNA (miRNA)-messenger RNA (mRNA) regulatory networks in human depression. However, the mechanisms by which these networks act are complex and remain poorly understood. We used data mining to identify differentially expressed miRNAs from GSE81152 and GSE152267 datasets, and differentially expressed mRNAs were identified from the Netherlands Study of Depression and Anxiety, the GlaxoSmithKline-High-Throughput Disease-specific target Identification Program, and the Janssen-Brain Resource Company study. We constructed a miRNA-mRNA regulatory network based on differentially expressed mRNAs that intersected with target genes of differentially expressed miRNAs, and then performed bioinformatics analysis of the network. The key candidate genes were assessed in the prefrontal cortex of chronic social defeat stress (CSDS) depression mice by quantitative real-time polymerase chain reaction (qRT-PCR). Three differentially expressed miRNAs were commonly identified across the two datasets, and 119 intersecting differentially expressed mRNAs were identified. A miRNA-mRNA regulatory network including these three key differentially expressed miRNAs and 119 intersecting differentially expressed mRNAs was constructed. Functional analysis of the intersecting differentially expressed mRNAs revealed that an abnormal inflammatory response characterized by disturbed T-helper cell 17 (Th17) differentiation was the primary altered biological function. qRT-PCR validated the decreased expression of Th17 cell differentiation-related genes, including

Indexed as

CSDSdepressionmiRNAsmRNAsTh17 cell differentiation

Identifiers

PMID35449567
PMCPMC9017773
OpenAlexW4226143532

What OpenQuestion holds

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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.