Evidence map›Paper›PMID 41089542›Full record

ArticleInternational journal of general medicine2025

Identification of Potential Therapeutic Targets for Sepsis Using Mendelian Randomization and Integrated eQTL/pQTL Analysis.

Haigui Yue, Jinping Tian, Wei Yin, Houyu Zhao

Abstract read
In one paragraph

Article in International journal of general medicine, 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Haigui YueDepartment of Clinical Pharmacy, Taizhou Orthopedics Hospital, Taizhou, Zhejiang, People's Republic of China.
Jinping TianDepartment of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, People's Republic of China.
Wei YinDepartment of Radiology, Xianning Central Hospital, The First Affiliated Hospital of Hubei University of Science and Technology, Xianning, Hubei, People's Republic of China.
Houyu ZhaoDepartment of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, People's Republic of China.ORCID 0009-0008-3104-087X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis significantly contributes to global morbidity, yet effective treatments remain limited. Mendelian randomization (MR), integrated with genetic data, offers promise for uncovering novel therapeutic targets. Methods: We utilized eQTL (eQTLGen) and pQTL (DECODE) data as exposures, and GWAS summaries for sepsis (UK Biobank, FinnGen) as outcomes. GEO datasets (GSE57065, GSE95233) underwent batch correction via PCA clustering using the "sva" R package. Differentially expressed genes (DEGs, |log2FC|>1, adjusted P<0.05) intersected with druggable genes were identified. MR analyses were performed using TwoSampleMR and MR-PRESSO, followed by drug-target predictions using DGIdb. Key genes (BCL6, PTX3, IL7R, BTN3A2, LGALS1) were validated experimentally through qRT-PCR and Western blot in a mouse sepsis model induced by cecal ligation and puncture (CLP). Results: Intersection analyses yielded 398 therapeutic candidates. MR revealed 6 genes and 21 proteins significantly associated with sepsis risk, including protective (eg, HDC, IFI27) and harmful factors (eg, CTSO, BTN3A2). Furthermore, 13 druggable genes correlated with sepsis-related factors, such as BTN3A2 with diabetes, and IL7R, BCL6, PTX3, among others, linked to vitamin D deficiency and cancer. DGIdb identified 34 potential drugs targeting these hub genes, with KEGG and GO analyses highlighting immune regulation and FoxO signaling pathways. qRT-PCR and Western blot confirmed consistent downregulation (BCL6, PTX3, IL7R) and upregulation (BTN3A2, LGALS1) at both mRNA and protein levels in septic mice compared to controls, supporting MR-based predictions. Conclusion: We identified and experimentally validated 6 sepsis-associated genes and 21 proteins, providing crucial insights into potential therapeutic targets and enhancing understanding of the molecular pathogenesis of sepsis.

Indexed as

bioinformaticsCLP modeldrug targetMendelian randomizationsepsis

Identifiers

PMID41089542
PMCPMC12517198

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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.