Evidence map›Paper›PMID 36274827›Full record

ArticleJournal of inflammation research2022

The Construction of ITP Diagnostic Modeling Based on the Expressions of Hub Genes Associated with M1 Polarization of Macrophages.

Ming-Jing Wang, Ying Song, Xiao-Qing Guo, Diu Wei, Xin-Tian Cao, Yan Sun, Yong-Gang Xu, Xiao-Mei Hu

Open access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

8 authors at 2 institutions in 1 country.

Ming-Jing Wang *Department of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.ORCID 0000-0002-9899-7595
Ying Song *Department of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Xiao-Qing Guo *Department of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Diu WeiDepartment of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Xin-Tian CaoDepartment of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Yan SunDepartment of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Yong-Gang XuDepartment of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Xiao-Mei HuDepartment of Hematology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, People's Republic of China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Primary immune thrombocytopenia (ITP) is an immune disease with a diagnosis of exclusion, since no validated biomarkers have been identified. In this study, we explored biomarkers associated with the development of ITP from an immune perspective to inform the clinical diagnosis. Patients and Methods: Differentially expressed genes (DEGs) between normal and ITP samples were analyzed using limma package. Random forest algorithm and LASSO regression were further used to screen for DEGs associated with ITP. The expression of these hub genes was validated by PCR. The relationship between DEGs and immunity was explored by enrichment analysis. Immune cell infiltration in ITP was analyzed by CIBERSORT and ssGSEA, and the relationship between DEGs and infiltrating immune cells was analyzed by Spearman's rank correlation analysis. Finally, a diagnostic model related to DEGs was constructed by the neural network, and its efficiency was detected by the ROC curve. Results: After screening the GEO database and validation by PCR analysis, The expression of CTH and TAF8 were higher and while OSBP2 expression was lower in ITP patients compared to normal subjects (P<0.05). GO enrichment analysis showed that these DEGs were associated with inflammatory immune-related diseases, and KEGG analysis showed that they mainly regulated signaling pathways such as JAK-STAT. CIBERSORT and ssGSEA analyses showed that these DEGs were mainly associated with macrophage M1 polarization. The expression of CTH and TAF8 were positively correlated with M1 expression, while OSBP2 was negatively correlated with M1 expression. The ROC curve showed high accuracy of the neural network model [AUC= 0.939, 95% CI (0.8-1)]. Conclusion: Our results suggest that CTH, TAF8, and OSBP2 can be used as effective diagnostic biomarkers of ITP.

Indexed as

bioinformaticsdiagnostic biomarkersimmune cell infiltrationmacrophage M1 polarizationprimary immune thrombocytopenia

Identifiers

PMID36274827
PMCPMC9581081
OpenAlexW4306790604

What OpenQuestion holds

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LicenceCC BY-NC
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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.