scholarly journals Genome-Wide Association Studies: Contribution of Genomics to Understanding Blood Pressure and Essential Hypertension

2010 ◽  
Vol 12 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Georg B. Ehret
Keyword(s):  
Blood Pressure ◽  
Essential Hypertension ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals An Academic Clinician’s Road Map to Hypertension Genomics

Hypertension ◽  
2021 ◽  
Author(s):  
Emma F. Magavern ◽  
Helen R. Warren ◽  
Fu L. Ng ◽  
Claudia P. Cabrera ◽  
Patricia B. Munroe ◽  
...  
Keyword(s):  
Big Data ◽  
Essential Hypertension ◽  
Clinical Benefit ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Road Map ◽  
Genome Wide ◽  
Cardiovascular Morbidity And Mortality

At the dawn of the new decade, it is judicious to reflect on the boom of knowledge about polygenic risk for essential hypertension supplied by the wealth of genome-wide association studies. Hypertension continues to account for significant cardiovascular morbidity and mortality, with increasing prevalence anticipated. Here, we overview recent advances in the use of big data to understand polygenic hypertension, as well as opportunities for future innovation to translate this windfall of knowledge into clinical benefit.

Identification of Phosphorylation Associated SNPs for Blood Pressure, Coronary Artery Disease and Stroke from Genome-wide Association Studies

2019 ◽  
Vol 19 (10) ◽  
pp. 731-738
Author(s):  
Xingchen Wang ◽  
Xingbo Mo ◽  
Huan Zhang ◽  
Yonghong Zhang ◽  
Yueping Shen
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Association Studies ◽  
Serum Levels ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Artery Disease

Purpose: Phosphorylation-related SNP (phosSNP) is a non-synonymous SNP that might influence protein phosphorylation status. The aim of this study was to assess the effect of phosSNPs on blood pressure (BP), coronary artery disease (CAD) and ischemic stroke (IS). Methods: We examined the association of phosSNPs with BP, CAD and IS in shared data from genome-wide association studies (GWAS) and tested if the disease loci were enriched with phosSNPs. Furthermore, we performed quantitative trait locus analysis to find out if the identified phosSNPs have impacts on gene expression, protein and metabolite levels. Results: We found numerous phosSNPs for systolic BP (count=148), diastolic BP (count=206), CAD (count=20) and IS (count=4). The most significant phosSNPs for SBP, DBP, CAD and IS were rs1801131 in MTHFR, rs3184504 in SH2B3, rs35212307 in WDR12 and rs3184504 in SH2B3, respectively. Our analyses revealed that the associated SNPs identified by the original GWAS were significantly enriched with phosSNPs and many well-known genes predisposing to cardiovascular diseases contain significant phosSNPs. We found that BP, CAD and IS shared for phosSNPs in loci that contain functional genes involve in cardiovascular diseases, e.g., rs11556924 (ZC3HC1), rs1971819 (ICA1L), rs3184504 (SH2B3), rs3739998 (JCAD), rs903160 (SMG6). Four phosSNPs in ADAMTS7 were significantly associated with CAD, including the known functional SNP rs3825807. Moreover, the identified phosSNPs seemed to have the potential to affect transcription regulation and serum levels of numerous cardiovascular diseases-related proteins and metabolites. Conclusion: The findings suggested that phosSNPs may play important roles in BP regulation and the pathological mechanisms of CAD and IS.

Abstract P142: Meta-analyses Of Genome-wide Association Studies Accounting For Gene-psychosocial Factor Interactions Identify Novel Loci For Blood Pressure Traits

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Myriam Fornage ◽  
Daokun Sun ◽  
Melissa A Richard ◽  
Solomon K Musani ◽  
Yun Ju Sung ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Psychosocial Factors ◽  
Social Factors ◽  
Association Studies ◽  
Psychosocial Factor ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
The Novel ◽  
Genome Wide ◽  
Meta Analyses

Background: Genome-wide association studies (GWAS) have identified hundreds of genetic loci for blood pressure (BP) traits and advanced our understanding of BP regulation and hypertension etiology. Psychological and social factors are known to influence BP and risk of cardiovascular diseases. Accounting for psychosocial factors may help identify BP loci and extend our knowledge of its genetic architecture. Methods: To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptomatology, trait anxiety, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. Results: In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response ( PLCL2 ), synaptic function and neurotransmission ( LIN7A, PFIA2 ), as well as genes previously implicated in neuropsychiatric or stress-related disorders ( FSTL5, CHODL ). Conclusion: These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

scholarly journals The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization

2020 ◽  
Author(s):  
Venexia M Walker ◽  
Sean Harrison ◽  
Alice R Carter ◽  
Dipender Gill ◽  
Ioanna Tzoulaki ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Medication Use ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Empirical Estimates ◽  
Genome Wide

Introduction: Genome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example. Methods: We simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 318,147 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome. Results: The simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios. Conclusions: Given the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, and the reduced sample size of these GWAS, this approach should be deprioritized. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.

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