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Integrative genetic analysis of shared genetic architecture of stroke and coronary artery disease: implications for pharmacist-led precision medicine

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Abstract

Introduction

Coronary artery disease (CAD) and stroke are leading causes of global morbidity and mortality. Their frequent comorbidities and overlapping risk profiles highlight the importance of understanding shared genetic mechanisms, particularly in identifying therapeutic targets relevant to personalized pharmacotherapy.

Aim

This study aimed to explore the shared genetic architecture between stroke and CAD, identify common therapeutic targets, and provide implications for clinical pharmacy practice.

Method

We integrated multi-ancestry genome-wide association study (GWAS) summary statistics (stroke: 110,182 cases; CAD: 210,842 cases) and employed linkage disequilibrium score regression to assess genetic correlations. Bidirectional two-sample Mendelian randomization (MR) was employed to infer causal inference. Shared genetic variants were identified through cross-trait meta-analyses (MTAG and CPASSOC) and validated using Bayesian colocalization. Pharmacogenomic pathways associated with shared genes were linked to approved drugs using a pathway-pairing score to assess the therapeutic alignment. A score of ≥ 0.5 indicated a strong alignment between a drug’s pharmacological mechanism and the disease’s genetic pathophysiology.

Results

A significant genetic correlation was observed between stroke and CAD (rg = 0.48, P = 3.38 × 10−34). Eight pleiotropic SNPs and five colocalized causal variants were identified, implicating ten disease-shared genes. Drug-target analyses prioritized the 19 approved cardiovascular agents. Beta-blockers (e.g., bisoprolol, esmolol) and antihypertensives (e.g., fenoldopam bromide/mesylate) demonstrated strong therapeutic potential (pathway score ≥ 0.5).

Conclusion

This study provides genomic evidence to support integrated therapeutic strategies for stroke and CAD. Pharmacogenomic insights into shared genetic determinants can assist clinical pharmacists in optimizing treatment selection, mitigating polypharmacy risks, and guiding precision medicine in patients with dual cardiocerebrovascular risks.

Explore related subjects

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  • Cardiovascular Genetics
  • Genetic Interaction
  • Genetic association study
  • Genome-wide association studies
  • Pharmacogenetics
  • Pharmacogenomics

Data availability

All data used in this study were obtained from publicly accessible genome-wide association study (GWAS) summary statistics. Stroke data were sourced from the GIGASTROKE consortium via the GWAS Catalog (https://www.ebi.ac.uk/gwas/publications/36180795), and coronary artery disease data were retrieved from the CARDIoGRAMplusC4D and associated datasets (https://www.ebi.ac.uk/gwas/studies/GCST90132315). No individual-level data were used. All analyses were performed using open-source tools as cited in the Methods section.

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Funding

This study was supported by the Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support (code: ZLRK202508).

Author information

Author notes

  1. Weizhong Shi and Luofei Zhang contributed equally to this work and share first authorship.
  2. Kefu Yu is the corresponding author.

Authors and Affiliations

  1. Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China

    Weizhong Shi, Luofei Zhang, Zhigang Zhao & Kefu Yu

  2. Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, China

    Luofei Zhang & Zhigang Zhao

Contributions

WS: Data curation; Formal analysis; Investigation; Methodology; Software; Validation; Visualization; Writing – review and editing LZ: Data curation; Formal analysis; Validation; Visualization; Writing–original draft; Writing–review and editing ZZ: Conceptualization; Data curation; Supervision; Writing – review and editing KY: Conceptualization; Data curation; Supervision; Writing – review and editing.

Corresponding author

Correspondence to Kefu Yu.

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Competing interests

The authors declare no competing interests.

Ethics approval

This study was entirely based on publicly available, de-identified, and summary-level data from previously published genome-wide association studies. As no human participants were directly involved and no individual-level data were used, institutional review board (IRB) approval and informed consent were not required.

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Shi, W., Zhang, L., Zhao, Z. et al. Integrative genetic analysis of shared genetic architecture of stroke and coronary artery disease: implications for pharmacist-led precision medicine. Int J Clin Pharm (2025). https://doi.org/10.1007/s11096-025-01952-w

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  • DOI  https://doi.org/10.1007/s11096-025-01952-w

Keywords

  • Clinical pharmacy
  • Coronary artery disease
  • Genetic correlation
  • Pharmacogenomics
  • Precision therapeutics
  • Stroke

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