Evidence map›Paper›PMID 37153570›Full record

ArticleFrontiers in immunology2023

Potential common molecular mechanisms between Sjögren syndrome and inclusion body myositis: a bioinformatic analysis and

Li Zeng, Kai Chen, Feng Xiao, Chun-Yan Zhu, Jia-Ying Bai, Song Tan, Li Long, Yi Wang, Qiao Zhou

Abstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

9 authors.

Li ZengDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Kai ChenDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Feng XiaoDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Chun-Yan ZhuDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Jia-Ying BaiDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Song TanDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Li LongDepartment of Rheumatology and Immunology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Yi WangDepartment of Critical Care Medicine, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Qiao ZhouDepartment of Rheumatology and Immunology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inclusion body myositis (IBM) is a slowly progressive inflammatory myopathy that typically affects the quadriceps and finger flexors. Sjögren's syndrome (SS), an autoimmune disorder characterized by lymphocytic infiltration of exocrine glands has been reported to share common genetic and autoimmune pathways with IBM. However, the exact mechanism underlying their commonality remains unclear. In this study, we investigated the common pathological mechanisms involved in both SS and IBM using a bioinformatic approach. Methods: IBM and SS gene expression profiles were obtained from the Gene Expression Omnibus (GEO). SS and IBM coexpression modules were identified using weighted gene coexpression network analysis (WGCNA), and differentially expressed gene (DEG) analysis was applied to identify their shared DEGs. The hidden biological pathways were revealed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, protein-protein interaction (PPI) networks, cluster analyses, and hub shared gene identification were conducted. The expression of hub genes was validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR). We then analyzed immune cell abundance patterns in SS and IBM using single-sample gene set enrichment analysis (ssGSEA) and investigated their association with hub genes. Finally, NetworkAnalyst was used to construct a common transcription factor (TF)-gene network. Results: Using WGCNA, we found that 172 intersecting genes were closely related to viral infection and antigen processing/presentation. Based on DEG analysis, 29 shared genes were found to be upregulated and enriched in similar biological pathways. By intersecting the top 20 potential hub genes from the WGCNA and DEG sets, three shared hub genes ( Conclusion: Our study identified that IBM shares common immunologic and transcriptional pathways with SS, such as viral infection and antigen processing/presentation. Furthermore, both IBM and SS have almost identical immune infiltration microenvironments, indicating similar immune responses may contribute to their association.

Indexed as

Autoimmune DiseasesMyositis, Inclusion BodySjogren's SyndromeAntigen PresentationComputational BiologyHumansantigen processing and presentationbioinformatic analysisimmune infiltration landscapeinclusion body myositisSjögren syndromeviral infection

Identifiers

PMID37153570
PMCPMC10160489

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