Evidence map›Paper›PMID 40481130›Full record

ArticleScientific reports2025

Identification of immune-associated genes and single-cell sequencing analysis in diagnosing Behçet's disease.

Qiyi Yu, Yidong Zhang, Yifan Wu, Meinuo Li, Tianyue Pan

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
–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

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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.

  1. Article
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.

Qiyi Yu *Carnegie Mellon University, Pittsburgh, USA. qiyiy@andrew.cmu.edu.
Yidong Zhang *Queen's Belfast University, Northern Ireland, UK.
Yifan Wu *China Pharmaceutical University, Nanjing, Jiangsu, China.
Meinuo LiThe University of Hongkong, Hongkong, China.
Tianyue PanChina Pharmaceutical University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Behçet's Disease (BD) is diagnosed as continuing systematic inflammation, lacking clarified etiology and pertinent detection of clinical usage. We screened bulk-seq and single-cell seq data of BD from GEO database, then investigated immune infiltration landscape in BD and further explored main immune cells in a single-cell resolution. It was inferred that monocytes might be the trigger cell of BD occurrence and development. On the other hand, we performed differentially expression analysis and weighted correlation network analysis, and intersected the selected genes with immune-related genes from ImmPort database. After KEGG/GO-enrichment, Protein-Protein Interaction network and miRNA-mRNA regulatory network were constructed. Meanwhile, we utilized the Least Absolute Shrinkage and Selection Operator to filtrate 5 significant intersected genes for BD's diagnosis (NRTN, TRDJ1, IGLV4-69, PDIA2 and AVPR1A), then drew Operating Characteristic curve to analyze diagnosis value. For experimental validation, the BD mice models were constructed and qRT-PCR experiment was performed to validate the expression level of selected genes. In conclusion, we investigated the immune landscape in BD and explored the role of monocyte in BD occurrence and development. Through gene selection and machine learning, five new potential diagnostic biomarkers were discovered and validated in both external dataset and experiment assay levels.

Indexed as

Behcet SyndromeSingle-Cell AnalysisAnimalsBiomarkersDisease Models, AnimalGene Expression ProfilingGene Regulatory NetworksHumansMiceMonocytesProtein Interaction MapsBiomarkersBehçet’s diseaseBiomarkerImmunitySingle-cell sequencing analysis

Identifiers

PMID40481130
PMCPMC12144115

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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.