Evidence map›Paper›PMID 39759509›Full record

ArticleFrontiers in immunology2024

Exploration of molecular biomarkers in ankylosing spondylitis transcriptomics.

Yuanpiao Ni, Linrui Zhong, Yanhui Li, Zeng Zhang, Bin Ming, Yufeng Qing, Quanbo Zhang

Abstract read
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Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuanpiao NiResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Linrui ZhongResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Yanhui LiResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Zeng ZhangResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Bin MingResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Yufeng QingResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Quanbo ZhangResearch Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammation of the spine and sacroiliac joints is a hallmark of the chronic, progressive inflammatory illness known as ankylosing spondylitis (AS). The insidious onset and non-specific early symptoms of AS often lead to delays in diagnosis and treatment, which may result in the onset of disability. It is therefore imperative to identify new biomarkers. Methods: In this study, datasets GSE73754 and GSE25101 were derived from the Gene Expression Omnibus (GEO). Key genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA). A model was then established using LASSO regression, and then it was subjected to the receiver operating characteristic (ROC) curve analysis for evaluation of the diagnostic accuracy of the genes. Subsequently, immune infiltration analysis was conducted to demonstrate the immune infiltration status of the samples and the correlation between key genes and immune infiltration. Finally, the expression levels of key genes in peripheral blood mononuclear cells (PBMCs) and their correlation with clinical indicators were validated via RT-qPCR assay. Results: Through WGCNA and differential expression analysis, 6 genes were identified. Ultimately, five key genes (ACSL1, SLC40A1, GZMM, TRIB1, XBP1) were determined using LASSO regression. The area under the ROC curve (AUC) for these genes was greater than 0.7, indicating favorable diagnostic performance. Immune infiltration analysis showed that AS was associated with infiltration levels of various immune cells. RT-qPCR validated that the expression of ACSL1, SLC40A1, GZMM, and XBP1 was consistent with the predictive model, whereas TRIB1 expression was contrary to the predictive model. Clinical correlation analysis of key genes revealed that ACSL1 was positively linked to hsCRP levels, GZMM was negatively linked to, hsCRP levels, and neutrophil absolute values, SLC40A1 was positively linked to ESR, hsCRP levels and neutrophil absolute values, and XBP1 was negatively linked to ESR, hsCRP levels, and neutrophil absolute values. Conclusion: This study identified key genes that may reveal a potential association between AS and ferroptosis, demonstrating high diagnostic value. Furthermore, the expression levels of these genes in peripheral blood mononuclear cells (PBMCs) are strongly correlated with disease activity. These findings not only suggest potential biomarkers for the diagnosis of AS but also offer important references for exploring new therapeutic targets, highlighting their substantial clinical applicability.

Indexed as

BiomarkersGene Expression ProfilingSpondylitis, AnkylosingTranscriptomeDatabases, GeneticFemaleGene Regulatory NetworksHumansLeukocytes, MononuclearMaleROC CurveBiomarkersankylosing spondylitisdifferential gene expressionferroptosisimmune infiltration analysistranscriptomicsweighted gene co-expression network analysis

Identifiers

PMID39759509
PMCPMC11695275

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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.