Evidence map›Paper›PMID 42677018›Full record

ArticleCentral-European journal of immunology2026

Uncovering common pathways and potential drug targets in COVID-19 and venous thrombosis

Boyang Yu, Rongjian Gao, Wenchao Ma

Abstract read
In one paragraph

Article in Central-European journal of immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Boyang YuThe Fourth Affiliated Hospital of Harbin Medical University, China.
Rongjian GaoThe Third People's Hospital of Shenzhen, China.
Wenchao MaThe Fourth Affiliated Hospital of Harbin Medical University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: COVID-19 and venous thrombosis pose significant global health challenges. Recent studies suggest a potential overlap in their underlying molecular mechanisms, particularly immune responses and inflammation. This study aims to elucidate shared molecular pathways between COVID-19 and venous thrombosis, identify common biomarkers, and propose potential therapeutic targets through a comprehensive multi-dataset analysis. Material and methods: Public datasets (GSE171110, GSE189990, GSE178246, GSE48000, and GSE19151) were analyzed using the "Limma" package in R for differential gene expression analysis. Functional enrichment (GO, KEGG) was conducted via the "ClusterProfiler" package. Protein-protein interaction (PPI) networks, transcription factor (TF)-target, and miRNA-target networks were constructed using TRRUST and miRDB databases. Drug sensitivity was assessed using CellMiner, and feature genes were identified using LASSO regression. Immune infiltration analysis was performed with CIBERSORT, and key genes were validated using qRT-PCR and animal models. Results: Key differentially expressed genes (DEGs), including SELP and CLEC4D, were identified, highlighting their roles in immune regulation and thrombosis. Drug sensitivity analysis revealed correlations with specific chemotherapeutic agents. Immune infiltration analysis demonstrated increased expression of SELP and CLEC4D in certain immune cells, confirmed by qRT-PCR and in animal models. Conclusions: This study uncovered shared molecular mechanisms between COVID-19 and venous thrombosis, identifying potential biomarkers and therapeutic targets such as SELP and CLEC4D. These findings provide new insights into the diagnosis and treatment of both conditions.

Indexed as

CLEC4DCOVID-19immune responseSELPtherapeutic targetsvenous thrombosis

Identifiers

PMID42677018
PMCPMC13527619

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.