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Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis.

Overview

Authors: Jiangliu Xia1, Jia Zheng2, Shengmei Zou3, Hua Zhao1, Qiang Liu2, Ruoyu Zhang2, Lei Xu2
ORCID iDs: Lei Xu
  1. Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
  2. Department of Medical Geriatrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
  3. Department of Medical Genetics and Center for Rare Diseases, Second Affiliated Hospital, Zhejiang University School of Medicine and Zhejiang Key Laboratory of Rare Diseases for Precision Medicine and Clinical Translation, Hangzhou, Zhejiang, China
Institutions: Second Affiliated Hospital of Zhejiang University (China); Zhejiang University (China)
Journal: Medicine, volume 105, issue 19, article e48634
Dates: received 14 September 2025; accepted 22 January 2026; published online 8 May 2026; in print May 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1097/md.0000000000048634 · PMID 42116389 · PMCID PMC13166711 · OpenAlex W7160913978
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: genetics / omics (modality), human (organism), stroke (population), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions
Keywords: bioinformatics, druggable genes, Mendelian randomization, protein–protein interaction, small-molecule drugs, stroke
MeSH: Mendelian Randomization Analysis*, Stroke*, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Protein Interaction Maps, Quantitative Trait Loci (* major topic)
Topic: Genetic Associations and Epidemiology (Genetics, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Science and Technology Plan Project of Zhejiang Provincial Health Department (2025KY874)
Citations: not cited yet (Europe PMC); 93 references in the paper

Abstract

Stroke remains a major cause of mortality and disability, highlighting the need for new therapeutic targets. This study aimed to systematically identify druggable genes causally associated with stroke risk using genetic and transcriptomic data. A total of 5883 druggable genes were compiled from the Drug–Gene Interaction Database and previous reviews. We integrated data from a large-scale stroke GWAS with blood and brain expression quantitative trait loci (eQTLs) for druggable genes and performed a two-sample Mendelian randomization analysis using eQTLs as genetic instruments for gene expression. Significant findings were validated using colocalization analysis. Expression of prioritized genes was further examined in external bulk (GSE140275) and single-cell (GSE174574) RNA-seq datasets. Finally, protein–protein interaction networks and the Drug Signature Database were employed for downstream functional and therapeutic prediction. The intersection of eQTL data identified 3453 genes in blood and 3150 genes in brain tissues. Mendelian randomization analysis identified ten gene-stroke associations (3 in blood, 7 in brain). Colocalization analysis supported a shared causal variant for 5 of these genes, indicated by high posterior probability of hypothesis 4 values, suggesting potential pathogenic roles. The protein–protein interaction network highlighted 5 core druggable genes (protein tyrosine kinase 2, cyclin-dependent kinase 6, ring finger protein 43, papilin proteoglycan-like sulfated glycoprotein, and coagulation factor II) interacting with 20 predicted genes. Myosin light chain kinase inhibitor 7 and staurosporine were the 2 most significant compounds interacting with these genes, followed by simvastatin and cortisol succinate. This study uncovered potential stroke mechanisms and therapeutic targets using integrated multi-omics data, providing a foundation for future clinical applications and drug development strategies. Five druggable genes were identified in stroke (protein tyrosine kinase 2, cyclin-dependent kinase 6, ring finger protein 43, papilin proteoglycan-like sulfated glycoprotein, and coagulation factor II). Myosin light chain kinase inhibitor 7, staurosporine, simvastatin, and cortisol succinate were identified as potential drug candidates for stroke. These results could add additional tools to manage stroke.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 6 keywords, 7 MeSH terms, 1 funder, 90 references.

Cite

This paper

Xia, J., Zheng, J., Zou, S., Zhao, H., Liu, Q., Zhang, R., & Xu, L. (2026). Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis. Medicine, 105(19), e48634. https://doi.org/10.1097/md.0000000000048634

BibTeX

@article{xia2026identifying,
author = {Xia, Jiangliu and Zheng, Jia and Zou, Shengmei and Zhao, Hua and Liu, Qiang and Zhang, Ruoyu and Xu, Lei},
title = {{Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis}},
journal = {Medicine},
year = {2026},
month = may,
volume = {105},
number = {19},
pages = {e48634},
publisher = {Wolters Kluwer Health},
issn = {0304-5412},
doi = {10.1097/md.0000000000048634},
url = {https://doi.org/10.1097/md.0000000000048634},
pmid = {42116389},
pmcid = {PMC13166711}
}

RIS

TY - JOUR
AU - Xia, Jiangliu
AU - Zheng, Jia
AU - Zou, Shengmei
AU - Zhao, Hua
AU - Liu, Qiang
AU - Zhang, Ruoyu
AU - Xu, Lei
TI - Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis
T2 - Medicine
J2 - Medicine (Baltimore)
PY - 2026
DA - 2026/05/01
VL - 105
IS - 19
SP - e48634
SN - 0304-5412
PB - Wolters Kluwer Health
DO - 10.1097/md.0000000000048634
UR - https://doi.org/10.1097/md.0000000000048634
LA - en
ER -

CSL-JSON

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