Genetics of Hypertension

2018 ◽  
Author(s):  
Matthew A. Sparks ◽  
Paul J Phelan
Keyword(s):  
Association Studies ◽  
Large Population ◽  
Antihypertensive Agents ◽  
Population Based ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Monogenic Diseases ◽  
High Prevalence ◽  
Shared Risk

Despite the high prevalence of hypertension and its resulting morbidity and mortality, our knowledge of its pathogenesis remains limited. Strong evidence for a genetic role in blood pressure (BP) variability was first provided by familial segregation studies and the identification of mendelian disorders causing marked hypertension. These monogenic diseases, largely involving genes in sodium homeostatic pathways, have reinforced the Guytonian principle that BP is largely governed by renal sodium excretion. More recently, large population based genome wide association studies (GWAS) have attempted to fill in the missing heritability of the BP trait, with mixed results. Although many variants have been identified that are robustly associated with BP variability, they are mostly rare and together are responsible for a tiny percentage of total trait variability. Observations from GWAS include shared risk variants for cardiovascular and kidney disease, including polymorphisms in UMOD. Mutations in this gene are known to cause monogenic renal disease. GWAS data may be employed for pathway analysis to discover the etiology of hypertension as well providing the potential to interrogate drug responses to antihypertensive agents depending on genotype. The chapter concludes with describing future directions in BP genetics including evidence of the role of epigenetic mechanisms in BP pathogenesis. As we enter the era of whole genome sequencing, the possibility exists to discover the missing hereditability of BP variation although this technology will present its own challenges. This review contains 6 figures, 2 tables and 94 references Key words: adrenocorticotropic hormone, autosomal dominant,  autosomal recessive, cytosine-phosphate-guanine, epithelial sodium channel

scholarly journals Pan-Cancer Study Detects Novel Genetic Risk Variants and Shared Genetic Basis in Two Large Cohorts

2019 ◽  
Author(s):  
Sara R. Rashkin ◽  
Rebecca E. Graff ◽  
Linda Kachuri ◽  
Khanh K. Thai ◽  
Stacey E. Alexeeff ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Large Population ◽  
Regulatory Elements ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Pan Cancer ◽  
Shared Genetic

AbstractDeciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. However, no studies have investigated pan-cancer pleiotropy within single, well-defined populations unselected for phenotype. We undertook novel genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (413,870 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detected 21 novel genome-wide significant risk variants. In addition, numerous cancer sites exhibited clear heritability. Investigations of pleiotropy identified 12 cancer pairs exhibiting either positive or negative genetic correlations and 43 pleiotropic loci. We identified 158 pleiotropic variants, many of which were enriched for regulatory elements and influenced cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

scholarly journals Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Neurology ◽  
2019 ◽  
Vol 92 (5) ◽  
pp. e486-e503 ◽  
Author(s):  
Ganesh Chauhan ◽  
Hieab H.H. Adams ◽  
Claudia L. Satizabal ◽  
Joshua C. Bis ◽  
Alexander Teumer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Association Studies ◽  
Large Population ◽  
Population Based ◽  
Genome Wide Association Studies ◽  
Lifestyle Risk Factors ◽  
Brain Infarcts ◽  
Genome Wide ◽  
Lifestyle Risk

ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10−8; and LINC00539/ZDHHC20, p = 5.82 × 10−9. Both have been associated with blood pressure (BP)–related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10−25; p[SSBI] = 5.23 × 10−14 for hypertension), smoking (p[BI] = 4.4 × 10−10; p[SSBI] = 1.2 × 10−4), diabetes (p[BI] = 1.7 × 10−8; p[SSBI] = 2.8 × 10−3), previous cardiovascular disease (p[BI] = 1.0 × 10−18; p[SSBI] = 2.3 × 10−7), stroke (p[BI] = 3.9 × 10−69; p[SSBI] = 3.2 × 10−24), and MRI-defined white matter hyperintensity burden (p[BI] = 1.43 × 10−157; p[SSBI] = 3.16 × 10−106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

scholarly journals Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

scholarly journals Characterizing the mechanism behind the progression of NAFLD to hepatocellular carcinoma

2020 ◽  
pp. HEP36
Author(s):  
Pierre Nahon ◽  
Manon Allaire ◽  
Jean-Charles Nault ◽  
Valérie Paradis
Keyword(s):  
Hepatocellular Carcinoma ◽  
Fatty Liver Disease ◽  
Association Studies ◽  
Cost Effective ◽  
Genome Wide Association Studies ◽  
Alcoholic Fatty Liver ◽  
Genome Wide ◽  
High Prevalence ◽  
Prevalence Of Obesity ◽  
Alcoholic Fatty Liver Disease

Hepatocellular carcinoma (HCC) developed in non-alcoholic fatty liver disease (NAFLD) individuals presents substantial clinical and biological characteristics, which remain to be elucidated. Its occurrence in noncirrhotic patients raises issues regarding surveillance strategies, which cannot be considered as cost-effective given the high prevalence of obesity and metabolic syndrome, and furthermore delineates specific oncogenic process that could be targeted in the setting of primary or secondary prevention. In this context, the identification of a genetic heterogeneity modulating HCC risk as well as specific biological pathways have been made possible through genome-wide association studies, development of animal models and in-depth analyses of human samples at the pathological and genomic levels. These advances must be confirmed and pursued to pave the way for personalized management of NAFLD-related HCC.

scholarly journals Polygenic Susceptibility of Aortic Aneurysms Associates to the Diameter of the Aneurysm Sac: the Aneurysm-Express Biobank Cohort

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Constance J. H. C. M. van Laarhoven ◽  
Jessica van Setten ◽  
Joost A. van Herwaarden ◽  
Gerard Pasterkamp ◽  
Dominique P. V. de Kleijn ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Association Studies ◽  
Significant Risk ◽  
Aortic Aneurysms ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Best Fit ◽  
Genetic Risk Variants

AbstractRecent genome-wide association studies (GWAS) have discovered ten genetic risk variants for abdominal aortic aneurysms (AAA). To what extent these genetic variants contribute to the pathology of aneurysms is yet unknown. The present study aims to investigate whether genetic risk variants are associated with three clinical features: diameter of aneurysm sac, type of artery and aneurysm related-symptoms in aortic and peripheral aneurysm patients. Aneurysm tissue of 415 patients included in the Aneurysm-Express biobank was used. A best-fit polygenic risk score (PRS) based on previous GWAS effect estimates was modeled for each clinical phenotype. The best-fit PRS (including 272 variants at PT = 0.01015) showed a significant correlation with aneurysm diameter (R2 = 0.019, p = 0.001). No polygenic association was found with clinical symptoms or artery type. In addition, the ten genome-wide significant risk variants for AAA were tested individually, but no associations were observed with any of the clinical phenotypes. All models were corrected for confounders and data was normalized. In conclusion, a weighted PRS of AAA susceptibility explained 1.9% of the phenotypic variation (p = 0.001) in diameter in aneurysm patients. Given our limited sample size, future biobank collaborations need to confirm a potential causal role of susceptibility variants on aneurysmal disease initiation and progression.

scholarly journals Genomic Variations in Susceptibility to Intracranial Aneurysm in the Korean Population

2019 ◽  
Vol 8 (2) ◽  
pp. 275 ◽  
Author(s):  
Eun Hong ◽  
Bong Kim ◽  
Steve Cho ◽  
Jin Yang ◽  
Hyuk Choi ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Association Studies ◽  
Large Population ◽  
Genome Wide Association ◽  
Korean Population ◽  
Genome Wide Association Studies ◽  
Medicine Research ◽  
Genome Wide ◽  
A Genome ◽  
Significant Difference

Genome-wide association studies found genetic variations with modulatory effects for intracranial aneurysm (IA) formations in European and Japanese populations. We aimed to identify the susceptibility of single nucleotide polymorphisms (SNPs) to IA in a Korean population consisting of 250 patients, and 294 controls using the Asian-specific Axiom Precision Medicine Research Array. Twenty-nine SNPs reached a genome-wide significance threshold (5 × 10−8). The rs371331393 SNP, with a stop-gain function of ARHGAP32 (11q24.3), showed the most significant association with the risk of IA (OR = 43.57, 95% CI: 21.84–86.95; p = 9.3 × 10−27). Eight out of 29 SNPs—GBA (rs75822236), TCF24 (rs112859779), OLFML2A (rs79134766), ARHGAP32 (rs371331393), CD163L1 (rs138525217), CUL4A (rs74115822), LOC102724084 (rs75861150), and LRRC3 (rs116969723)—demonstrated sufficient statistical power greater than or equal to 0.8. Two previously reported SNPs, rs700651 (BOLL, 2q33.1) and rs6841581 (EDNRA, 4q31.22), were validated in our GWAS (Genome-wide association study). In a subsequent analysis, three SNPs showed a significant difference in expressions: the rs6741819 (RNF144A, 2p25.1) was down-regulated in the adrenal gland tissue (p = 1.5 × 10−6), the rs1052270 (TMOD1. 9q22.33) was up-regulated in the testis tissue (p = 8.6 × 10−10), and rs6841581 (EDNRA, 4q31.22) was up-regulated in both the esophagus (p = 5.2 × 10−12) and skin tissues (1.2 × 10−6). Our GWAS showed novel candidate genes with Korean-specific variations in IA formations. Large population based studies are thus warranted.

scholarly journals Proportion of idiopathic pulmonary fibrosis risk explained by known genetic loci

2020 ◽  
Author(s):  
Olivia C Leavy ◽  
Shwu-Fan Ma ◽  
Philip L Molyneaux ◽  
Toby M Maher ◽  
Justin M Oldham ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Genetic Architecture ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
The Impact ◽  
Insight Into

Genome-wide association studies have identified 14 genetic loci associated with susceptibility to idiopathic pulmonary fibrosis (IPF), a devastating lung disease with poor prognosis. Of these, the variant with the strongest association, rs35705950, is located in the promoter region of the MUC5B gene and has a risk allele (T) frequency of 30-35% in IPF cases. Here we present estimates of the proportion of disease liability explained by each of the 14 IPF risk variants as well as estimates of the proportion of cases that can be attributed to each variant. We estimate that rs35705950 explains 5.9-9.4% of disease liability, which is much lower than previously reported estimates. Of every 100,000 individuals with the rs35705950_GG genotype we estimate 30 will have IPF, whereas for every 100,000 individuals with the rs35705950_GT genotype 152 will have IPF. Quantifying the impact of genetic risk factors on disease liability improves our understanding of the underlying genetic architecture of IPF and provides insight into the impact of genetic factors in risk prediction modelling.

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