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Recent Findings in the Genetics of Blood Pressure: How to Apply in Practice or Is a Moonshot Required?

Journal

CURRENT HYPERTENSION REPORTS
Volume 20, Issue 6, Pages -

Publisher

SPRINGER
DOI: 10.1007/s11906-018-0863-1

Keywords

Hypertension; Blood pressure; Genetics; Genetic risk score; Global disease burden; Hypertension moonshot

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Hypertension is recognised as the biggest contributor to the global burden of disease, but it is controlled in less than a fifth of patients worldwide, despite being relatively easy to detect and the availability of inexpensive safe generic drugs. Blood pressure is regulated by a complex network of physiologic pathways with currently available drugs targeting key receptors or enzymes in the top pathways. Major advances in the dissection of both monogenic and polygenic determinants of blood pressure regulation and variation have not resulted in rapid translation of these discoveries into clinical applications or precision medicine. Uromodulin is an example of a novel gene for hypertension identified from genome-wide association studies, currently the basis of a clinical trial to reposition loop diuretics in hypertension management. Gene-editing studies have established a genome-wide association studies (GWAS) SNP in chromosome 6p24, implicated in six conditions including hypertension, as a distal regulator of the endothelin-1 gene around 3000 base pairs away. Genomics of aldosterone-producing adenomas bring to focus the paradox in genomic medicine where availability of cheap generic drugs may render precision medicine uneconomical. The speed of technology-driven genomic discoveries and the sluggish traditional pathways of drug development and translation need harmonisation to make a timely and early impact on global public health. This requires a directed collaborative effort for which we propose a hypertension moonshot to make a quantum leap in hypertension management and cardiovascular risk reduction by bringing together traditional bioscience, omics, engineering, digital technology and data science.

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