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

Application of omics in hypertension and resistant hypertension

Hypertension is a major modifiable risk factor that affects the global health burden. Despite the availability of multiple antihypertensive drugs, blood pressure is often not optimally controlled. The prevalence of true resistant hypertension in treated hypertensive patients is ~2-20%, and these patients are at higher risk for adverse events and poor clinical outcomes. Therefore, an in-depth dissection of the pathophysiological mechanisms of hypertension and resistant hypertension is needed to identify more effective targets for regulating blood pressure. Omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and microbiomics, can accurately present the characteristics of organisms at varying molecular levels. Integrative omics can further reveal the network of interactions between molecular levels and provide a complete dynamic view of the organism. In this review, we describe the applications, progress, and challenges of omics technologies in hypertension. Specifically, we discuss the application of omics in resistant hypertension. We believe that omics approaches will produce a better understanding of the pathogenesis of hypertension and resistant hypertension and improve diagnostic and therapeutic strategies, thus increasing rates of blood pressure control and reducing the public health burden of hypertension.

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly

Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the global burden of the disease. Artificial intelligence and machine learning, which have made a substantial impact on our everyday lives over the last decade may be the route to this transformation. However, artificial intelligence in health care is still in its nascent stages and realizing its potential requires numerous challenges to be overcome. In this review, we provide a clinician-centric perspective on artificial intelligence and machine learning as applied to medicine and hypertension. We focus on the main roadblocks impeding implementation of this technology in clinical care and describe efforts driving potential solutions. At the juncture, there is a critical requirement for clinical and scientific expertise to work in tandem with algorithmic innovation followed by rigorous validation and scrutiny to realize the promise of artificial intelligence-enabled health care for hypertension and other chronic diseases.

Genomics of hypertension: the road to precision medicine

The known genetic architecture of blood pressure now comprises >30 genes, with rare variants resulting in monogenic forms of hypertension or hypotension and >1,477 common single-nucleotide polymorphisms (SNPs) being associated with the blood pressure phenotype. Monogenic blood pressure syndromes predominantly involve the renin-angiotensin-aldosterone system and the adrenal glucocorticoid pathway, with a smaller fraction caused by neuroendocrine tumours of the sympathetic and parasympathetic nervous systems. The SNPs identified in genome-wide association studies (GWAS) as being associated with the blood pressure phenotype explain only approximately 27% of the 30-50% estimated heritability of blood pressure, and the effect of each SNP on the blood pressure phenotype is small. A paucity of SNPs from GWAS are mapped to known genes causing monogenic blood pressure syndromes. For example, a GWAS signal mapped to the gene encoding uromodulin has been shown to affect blood pressure by influencing sodium homeostasis, and the effects of another GWAS signal were mediated by endothelin. However, the majority of blood pressure-associated SNPs show pleiotropic associations. Unravelling these associations can potentially help us to understand the underlying biological pathways. In this Review, we appraise the current knowledge of blood pressure genomics, explore the causal pathways for hypertension identified in Mendelian randomization studies and highlight the opportunities for drug repurposing and pharmacogenomics for the treatment of hypertension.

A Pooling Genome-Wide Association Study Identifies Susceptibility Loci and Signaling Pathways of Immune Thrombocytopenia in Chinese Han Population

Immune thrombocytopenia (ITP) is an acquired bleeding disease due to immune-mediated destruction of antilogous platelets and ineffective thrombopoiesis. Although the etiology of ITP remains unknown, genetic variants are thought to predispose individuals to the disease. Several candidate gene analyses have identified several loci that increased ITP susceptibility, but no systematic genetic analysis on a genome-wide scope. To extend the genetic evidence and to identify novel candidates of ITP, we performed a pooling genome-wide association study (GWAS) by IlluminaHumanOmniZhongHua-8 combining pathway analysis in 200 ITP cases and 200 controls from Chinese Han population (CHP). The results revealed that 4 novel loci (rs117503120, rs5998634, rs4483616, and rs16866133) were strongly associated with ITP (P < 1.0 × 10⁻⁷). Expect for rs4483616, other three loci were validated by the TaqMan probe genotyping assay (P < 0.05) in another cohort including 250 ITP cases and 250 controls. And rs5998634 T allele was more sensitive to glucocorticoids for ITP patients (χ² = 7.30, P < 0.05). Moreover, we identified three overrepresented signaling pathways including the neuroactive ligand-receptor interaction, pathways in cancer, and the JAK-STAT pathway, which involved in the etiology of ITP. In conclusion, our results revealed four novel loci and three pathways related to ITP and provided new clues to explore the pathogenesis of ITP.

Genomics of Blood Pressure and Hypertension: Extending the Mosaic Theory Toward Stratification

The genetic architecture of blood pressure (BP) now includes more than 30 genes, with rare mutations resulting in inherited forms of hypertension or hypotension, and 1477 common single-nucleotide polymorphisms (SNPs). These signify the heterogeneity of the BP phenotype and support the mosaic theory of hypertension. The majority of monogenic syndromes involve the renin-angiotensin-aldosterone system and the adrenal glucocorticoid pathway, and a smaller fraction are due to rare neuroendocrine tumours of the adrenal glands and the sympathetic and parasympathetic paraganglia. Somatic mutations in genes coding for ion channels (KCNJ5 and CACNA1D) and adenosine triphosphatases (ATP1A1 and ATP2B3) highlight the central role of calcium signalling in autonomous aldosterone production by the adrenal gland. The per-SNP BP effect is small for SNPs according to genome-wide association studies (GWAS), and all of the GWAS-identified BP SNPs explain ∼ 27% of the 30%-50% estimated heritability of BP. Uromodulin is a novel pathway identified by GWAS, and it has now progressed to a genotype-directed clinical trial. The majority of the GWAS-identified BP SNPs show pleiotropic associations, and unravelling those signals and underpinning biological pathways offers potential opportunities for drug repurposing. The GWAS signals are predominantly from Europe-centric studies with other ancestries underrepresented, however, limiting the generalisability of the findings. In this review, we leverage the burgeoning list of polygenic and monogenic variants associated with BP regulation along with phenome-wide studies in the context of the mosaic theory of hypertension, and we explore potential translational aspects that underlie different hypertension subtypes.

Over 1000 genetic loci influencing blood pressure with multiple systems and tissues implicated

High blood pressure (BP) remains the major heritable and modifiable risk factor for cardiovascular disease. Persistent high BP, or hypertension, is a complex trait with both genetic and environmental interactions. Despite swift advances in genomics, translating new discoveries to further our understanding of the underlying molecular mechanisms remains a challenge. More than 500 loci implicated in the regulation of BP have been revealed by genome-wide association studies (GWAS) in 2018 alone, taking the total number of BP genetic loci to over 1000. Even with the large number of loci now associated to BP, the genetic variance explained by all loci together remains low (~5.7%). These genetic associations have elucidated mechanisms and pathways regulating BP, highlighting potential new therapeutic and drug repurposing targets. A large proportion of the BP loci were discovered and reported simultaneously by multiple research groups, creating a knowledge gap, where the reported loci to date have not been investigated in a harmonious way. Here, we review the BP-associated genetic variants reported across GWAS studies and investigate their potential impact on the biological systems using in silico enrichment analyses for pathways, tissues, gene ontology and genetic pleiotropy.