Evidence map›Paper›PMID 35633815›Full record

ArticleFrontiers in psychiatry2022

A Whole Transcriptome Analysis in Peripheral Blood Suggests That Energy Metabolism and Inflammation Are Involved in Major Depressive Disorder.

Yu Wang, Jinxue Wei, Ting Chen, Xiao Yang, Liansheng Zhao, Min Wang, Yikai Dou, Yue Du, Rongjun Ni, Tao Li and 1 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Circulating long noncoding RNA: New frontiers in biomarker research for mood disorders.Genomic psychiatry : advancing science from genes to society · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. 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

11 authors at 2 institutions in 1 country.

Yu WangPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Jinxue WeiPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Ting ChenPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Xiao YangPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Liansheng ZhaoPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Min WangPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Yikai DouPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Yue DuPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Rongjun NiPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Tao LiPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Xiaohong MaPsychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Previous studies on transcriptional profiles suggested dysregulation of multiple RNA species in major depressive disorder (MDD). However, the interaction between different types of RNA was neglected. Therefore, integration of different RNA species in transcriptome analysis would be helpful for interpreting the functional readout of the transcriptome in MDD. Methods: A whole transcriptome sequencing were performed on the peripheral blood of 15 patients with MDD and 15 matched healthy controls (HCs). The differential expression of miRNAs, lncRNAs, circRNAs, and mRNAs was examined between MDD and HCs using empirical analysis of digital gene expression data in R (edgeR). Weighted correlation network analysis (WGCNA) was used to identify RNA co-expression modules associated with MDD. A ceRNA network was constructed for interpretation of interactions between different RNA species. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore potential biological mechanisms associated with MDD. Results: Multiple RNAs and co-expression modules were identified to be significantly dysregulated in MDD compared to HCs. Based on the differential RNAs, a ceRNA network that were dysregulated in MDD were constructed. The pathway networks that related to oxidative phosphorylation and the chemokine signaling were found to be associated with MDD. Conclusion: Our results suggested that the processes of energy metabolism and inflammation may be involved in the pathophysiology of MDD.

Indexed as

ceRNA networkco-expression modulesKEGG pathwaysmajor depressive disorderwhole transcriptome analysis

Identifiers

PMID35633815
PMCPMC9136012
OpenAlexW4280600311

What OpenQuestion holds

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LicenceCC BY
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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.