Evidence map›Paper›PMID 40313968›Full record

ArticleFrontiers in immunology2025

Shared circulating diagnostic biomarkers and molecular mechanisms in ischemic stroke and systemic lupus erythematosus.

Xiaoyi Ma, Lifei Huang, Huanhuan Yan

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Article
  2. Stroke in autoimmune rheumatic diseases.Rheumatology international · 2026
    Review
  3. 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

3 authors.

Xiaoyi MaDepartment of Geriatrics, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Lifei HuangMRI Division, Wuhan United Imaging Life Science Instrument Co., Ltd., Wuhan, China.
Huanhuan YanBrain Science Laboratory, Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Ischemic stroke, a prevalent cerebrovascular disorder characterized by reduced cerebral blood flow, and systemic lupus erythematosus (SLE), an autoimmune disease affecting various organs, are suspected to share overlapping etiological mechanisms and genetic predispositions. This study aimed to identify shared diagnostic biomarkers and molecular mechanisms by analyzing datasets from the GEO database. Methods: We pinpointed differentially expressed genes using the limma package and identified co-expression modules associated with both conditions using Weighted Gene Coexpression Network Analysis. Pathway enrichment analysis was conducted using GO and KEGG to identify co-driver genes. LASSO regression was applied to evaluate potential diagnostic markers, and immune cell infiltration was quantified using the CIBERSORT computational method. A middle cerebral artery occlusion (MCAO) mouse model was developed to assess core gene expression Results: We identified 69 shared driver genes linked to stroke and SLE, which were narrowed down to the top 10 genes through a Protein-Protein Interaction network analysis with Cytoscape. LASSO regression selected EIF2AK2, PARP9, and IFI27 as diagnostic biomarkers, supported by ROC curve analysis. Immune cell infiltration profiles were nearly identical between ischemic stroke and SLE. 9.4T MR imaging, H&E and Nissl staining confirmed ischemic stroke in the MCAO model, and qPCR analysis confirmed elevated expression of the three hub genes. Discussion: Our findings provide evidence for common diagnostic indicators and disease mechanisms in ischemic stroke and SLE, offering novel insights for potential therapeutic strategies targeting their shared immune cell infiltration microenvironments.

Indexed as

BiomarkersIschemic StrokeLupus Erythematosus, SystemicAnimalsComputational BiologyDisease Models, AnimalGene Expression ProfilingGene Regulatory NetworksHumansMiceProtein Interaction MapsBiomarkersbioinformaticsdiagnostic biomarkersimmune infiltrationischemic strokesystemic lupus erythematosus

Identifiers

PMID40313968
PMCPMC12043496

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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.