Abstract
Observational studies have revealed that ischemic heart disease (IHD) has a unique manifestation on electrocardiographic (ECG). However, the genetic relationships between IHD and ECG remain unclear. We took 12-lead ECG as phenotypes to conduct genome-wide association studies (GWAS) for 41,960 samples from UK-Biobank (UKB). By leveraging large-scale GWAS summary of ECG and IHD (downloaded from FinnGen database), we performed LD score regression (LDSC), Mendelian randomization (MR), and polygenic risk score (PRS) regression to explore genetic relationships between IHD and ECG. Finally, we constructed an XGBoost model to predict IHD by integrating PRS and ECG. The GWAS identified 114 independent SNPs significantly (P value < 5 × 10–8/800, where 800 denotes the number of ECG features) associated with ECG. LDSC analysis indicated significant (P value < 0.05) genetic correlations between 39 ECG features and IHD. MR analysis performed by five approaches showed a putative causal effect of IHD on four S wave related ECG features at lead III. Integrating PRS for these ECG features with age and gender, the XGBoost model achieved Area Under Curve (AUC) 0.72 in predicting IHD. Here, we provide genetic evidence supporting S wave related ECG features at lead III to monitor the IHD risk, and open up a unique approach to integrate ECG with genetic factors for pre-warning IHD.
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Data availability
The datasets analyzed during the current study are available in the FinnGen, https://www.finngen.fi/en, and UK Biobank https://www.ukbiobank.ac.uk/.
Abbreviations
- IHD:
-
Ischemic heart disease
- ECG:
-
Electrocardiographic
- UKB:
-
UK Biobank
- SMR:
-
Summary databased Mendelian randomization
- GWAS:
-
Genome-wide association studies
- LDSC:
-
Linkage disequilibrium score regression
- SNP:
-
Single nucleotide polymorphism
- MR:
-
Mendelian randomization
- IVW:
-
Inverse variance-weighted
- GSMR:
-
Generalized summary data-based Mendelian randomization
- CAUSE:
-
Causal analysis using summary effect estimates
- LCV:
-
Latent causal variable
- HEIDI:
-
Heterogeneity in dependent instruments
- GCP:
-
Genetic causality proportion
- CI:
-
Confidence intervals
- PRS:
-
Polygenic risk score
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Acknowledgements
We’d like to thank the UK Biobank (application #65805) and the FinnGen project for making the data available.
Funding
The work was funded by the National Key Research and Development Program of China (2020YFB0204803), the Natural Science Foundation of China (81801132, 81971190, 61772566), Guangdong Key Field Research and Development Plan (2019B020228001,2018B010109006, and 2021A1515010256), Introducing Innovative and Entrepreneurial Teams (2016ZT06D211), Guangzhou Science and Technology Research Plan (202007030010), and Mater Foundation.
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H. Zhao and Y.Yang designed the study. X.Wang performed the analyses with assistance from H. Zhang, M.Qi. X.Wang and H.Zhao wrote the manuscript. Y. Yang and H. Zhao supervised the study. All authors discussed the results and interpretation, and contributed to the final version of the paper.
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Wang, X., Qi, M., Zhang, H. et al. Genome-wide association and Mendelian randomization analysis provide insights into the shared genetic architecture between high-dimensional electrocardiographic features and ischemic heart disease. Hum. Genet. 143, 49–58 (2024). https://doi.org/10.1007/s00439-023-02614-5
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DOI: https://doi.org/10.1007/s00439-023-02614-5