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已发表论文
利用孟德尔随机化和整合的 eQTL/pQTL 分析鉴定脓毒症潜在治疗靶点
Authors Yue H, Tian J, Yin W, Zhao H
Received 29 May 2025
Accepted for publication 2 October 2025
Published 9 October 2025 Volume 2025:18 Pages 6137—6152
DOI https://doi.org/10.2147/IJGM.S535716
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Héctor M. Mora-Montes
Haigui Yue,1 Jinping Tian,2,3 Wei Yin,4 Houyu Zhao2
1Department of Clinical Pharmacy, Taizhou Bone Wound Hospital, Taizhou, Zhejiang, People’s Republic of China; 2Department of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, People’s Republic of China; 3Department of Radiology, The Affiliated Hospital of Hubei Provincial Government, Wuhan, Hubei, People’s Republic of China; 4Department of Radiology, Xianning Central Hospital, The First Affiliated Hospital of Hubei University of Science and Technology, Xianning, Hubei, People’s Republic of China
Correspondence: Wei Yin, Email yinwei19901019@163.com Houyu Zhao, Email zhynaq09080043@163.com
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.
Keywords: sepsis, drug target, Mendelian randomization, bioinformatics, CLP model
1Department of Clinical Pharmacy, Taizhou Bone Wound Hospital, Taizhou, Zhejiang, People’s Republic of China; 2Department of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Weihui, People’s Republic of China; 3Department of Radiology, The Affiliated Hospital of Hubei Provincial Government, Wuhan, Hubei, People’s Republic of China; 4Department of Radiology, Xianning Central Hospital, The First Affiliated Hospital of Hubei University of Science and Technology, Xianning, Hubei, People’s Republic of China
Correspondence: Wei Yin, Email yinwei19901019@163.com Houyu Zhao, Email zhynaq09080043@163.com
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.
Keywords: sepsis, drug target, Mendelian randomization, bioinformatics, CLP model