Evidence map›Paper›PMID 36733342›Full record

ArticleFrontiers in genetics2023

Identification of immune signatures in Parkinson's disease based on co-expression networks.

Xiaolin Dong, Yanping Li, Qingyun Li, Wenhao Li, Gang Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2023. 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
0.6field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Xiaolin DongDepartment of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Yanping LiDepartment of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Qingyun LiDepartment of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Wenhao LiDepartment of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Gang WuDepartment of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Yan'an Hospital Affiliated To Kunming Medical University · CNKunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is a common neurodegenerative disease in middle-aged and elderly people, and there is less research on the relationship between immunity and PD. In this study, the protein-protein interaction networks (PPI) data, 2747 human immune-related genes (HIRGs), 2078 PD-related genes (PDRGs), and PD-related datasets (GSE49036 and GSE20292) were downloaded from the Human Protein Reference Database (HPRD), Amigo 2, DisGeNET, and Gene Expression Omnibus (GEO) databases, respectively. An immune- or PD-directed neighbor co-expressed network construction (IOPDNC) was drawn based on the GSE49036 dataset and HPRD database. Furthermore, a PD-directed neighbor co-expressed network was constructed. Modular clustering analysis was performed on the genes of the gene interaction network obtained in the first step to obtain the central core genes using the GraphWeb online website. The modules with the top 5 functional scores and the number of core genes greater than six were selected as PD-related gene modules. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of different module genes were performed. The single sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to calculate the immune cell infiltration of the PD and the normal samples. The quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) was performed to investigate the expression of module genes. An IOPDNC and PD-directed neighbor co-expressed network (PDNC network) were constructed. Furthermore, a total of 5 immune-PD modules were identified which could distinguish between PD and normal samples, and these module genes were strongly related to PD in protein interaction level or gene expression level. In addition, functional analysis indicated that module genes were involved in various neurodegenerative diseases, such as Alzheimer disease, Huntington disease, Parkinson disease, and Long-term depression. In addition, the genes of the 6 modules were significantly associated with these 4 differential immune cells (aDC cells, eosinophils, neutrophils, and Th2 cells). Finally, the result of qRT-PCR manifested that the expression of 6 module genes was significantly higher in normal samples than in PD samples. In our study, the immune-related genes were found to be strongly related to PD and might play key roles in PD.

Indexed as

bioinformatics analysisco-expression networkdiagnostic markersimmunityParkinon’s disease

Identifiers

PMID36733342
PMCPMC9886886
OpenAlexW4316670310

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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.