Shared genetic etiology of hypertension and stroke: evidence from bioinformatics analysis of genome-wide association studies

Abstract

Hypertension is the most significant modifiable risk factor for cerebrovascular disease. It has been estimated that about 54% of strokes worldwide can be attributed to hypertension. However, there has not been a systematic study assessing the shared genetic susceptibility to hypertension and stroke on a genome-wide level. In this study, SNPs associated with essential hypertension and stroke were collected from the NHGRI-EBI GWAS catalog, and genotype imputation were conducted using information from the 1000 Genomes Project. Subsequently, the SNPs and the mapped genes were compared between the two diseases. Finally, functional clustering was performed, and the enriched GO terms and KEGG pathways were further compared between hypertension and stroke. Comparison of these two groups of SNPs and genes identified only one shared SNP (rs3184504) and 11 shared genes. After genotype imputation, 129 shared SNPs and 16 shared genes were identified. These genes were significantly enriched in 10 GO terms, which were mainly involved in lipoprotein and triglyceride metabolism. Additionally, KEGG analysis identified one pathway, glycerolipid metabolism, as being significantly enriched in both diseases. The present study strongly suggests that the gene network regulating lipid metabolism and blood circulation is the major shared genetic etiology of hypertension and stroke.

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Acknowledgements

This study was supported by the grants from National Natural Science Foundation of China (81402747), Ningbo Natural Science Foundation (2016A610085, 2017A610199), as well as the KC Wong Magna Fund in Ningbo University.

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Correspondence to QJ Shen or J Xu.

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The authors declare that they have no competing interests.

Additional information

LD Ji and SP Hu contributed equally to this work.

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Ji, L., Hu, S., Li, J. et al. Shared genetic etiology of hypertension and stroke: evidence from bioinformatics analysis of genome-wide association studies. J Hum Hypertens 32, 34–39 (2018). https://doi.org/10.1038/s41371-017-0012-3

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