Hypertension and genetic variation in endothelial-specific genes

A Review of Vascular Traits and Assessment Techniques, and Their Heritability

Various tools are available to assess atherosclerosis, arterial stiffening, and endothelial function. They offer utility in the assessment of hypertensive phenotypes, in cardiovascular risk prediction, and as surrogate endpoints in clinical trials. We explore the relative influence of participant genetics, with reference to large-scale genomic studies, population-based cohorts, and candidate gene studies. We find heritability estimates highest for carotid intima-media thickness (CIMT 35–65%), followed by pulse wave velocity as a measure of arterial stiffness (26–43%), and flow mediated dilatation as a surrogate for endothelial function (14–39%); data were lacking for peripheral artery tonometry. We furthermore examine genes and polymorphisms relevant to each technique. We conclude that CIMT and pulse wave velocity dominate the existing evidence base, with fewer published genomic linkages for measures of endothelial function. We finally make recommendations regarding planning and reporting of data relating to vascular assessment techniques, particularly when genomic data are also available, to facilitate integration of these tools into cardiovascular disease research.

A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank

With increasing biobanking efforts connecting electronic health records and national registries to germline genetics, the time-to-event data analysis has attracted increasing attention in the genetics studies of human diseases. In time-to-event data analysis, the Cox proportional hazards (PH) regression model is one of the most used approaches. However, existing methods and tools are not scalable when analyzing a large biobank with hundreds of thousands of samples and endpoints, and they are not accurate when testing low-frequency and rare variants. Here, we propose a scalable and accurate method, SPACox (a saddlepoint approximation implementation based on the Cox PH regression model), that is applicable for genome-wide scale time-to-event data analysis. SPACox requires fitting a Cox PH regression model only once across the genome-wide analysis and then uses a saddlepoint approximation (SPA) to calibrate the test statistics. Simulation studies show that SPACox is 76-252 times faster than other existing alternatives, such as gwasurvivr, 185-511 times faster than the standard Wald test, and more than 6,000 times faster than the Firth correction and can control type I error rates at the genome-wide significance level regardless of minor allele frequencies. Through the analysis of UK Biobank inpatient data of 282,871 white British European ancestry samples, we show that SPACox can efficiently analyze large sample sizes and accurately control type I error rates. We identified 611 loci associated with time-to-event phenotypes of 12 common diseases, of which 38 loci would be missed within a logistic regression framework with a binary phenotype defined as event occurrence status during the follow-up period.

Pharmacogenomics of Hypertension Treatment

Hypertension is one of the strongest modifiable cardiovascular risk factors, affecting an increasing number of people worldwide. Apart from poor medication adherence, the low efficacy of some therapies could also be related to inter-individual genetic variability. Genetic studies of families revealed that heritability accounts for 30% to 50% of inter-individual variation in blood pressure (BP). Genetic factors not only affect blood pressure (BP) elevation but also contribute to inter-individual variability in response to antihypertensive treatment. This article reviews the recent pharmacogenomics literature concerning the key classes of antihypertensive drugs currently in use (i.e., diuretics, β-blockers, ACE inhibitors, ARB, and CCB). Due to the numerous studies on this topic and the sometimes-contradictory results within them, the presented data are limited to several selected SNPs that alter drug response. Genetic polymorphisms can influence drug responses through genes engaged in the pathogenesis of hypertension that are able to modify the effects of drugs, modifications in drug–gene mechanistic interactions, polymorphisms within drug-metabolizing enzymes, genes related to drug transporters, and genes participating in complex cascades and metabolic reactions. The results of numerous studies confirm that genotype-based antihypertension therapies are the most effective and may help to avoid the occurrence of major adverse events, as well as decrease the costs of treatment. However, the genetic heritability of drug response phenotypes seems to remain hidden in multigenic and multifactorial complex traits. Therefore, further studies are required to analyze all associations and formulate final genome-based treatment recommendations.

Genomic Association Analysis Reveals Variants Associated With Blood Pressure Response to Beta-Blockers in European Americans

European Americans (EA) have a better antihypertensive response to β-blockers when compared with African Americans, albeit with some variability. We undertook a genomewide association study to elucidate the underlying genetic determinants in EA contributing to this variability in blood pressure (BP) response. A discovery genomewide association study of change in BP post-metoprolol treatment was performed in EA participants (n = 201) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and tested for replication in the atenolol-treated EA from the PEAR study (n = 233). Rs294610 in the FGD5, which encodes for FYVE, RhoGEF and PH Domain Containing 5, (expression quantitative trait loci for FGD5 in the small intestine) was significantly associated with increased diastolic BP response to β-blockers in the PEAR-2 study (P = 3.41 × 10-6 , β = -2.70) and replicated (P = 0.01, β = -1.17) in the PEAR study. Post-meta-analysis of these studies, an additional single nucleotide polymorphism rs45545233 in the SLC4A1, encoding for Solute Carrier Family 4 Member 1, (expression quantitative trait loci for dual specificity phosphatase 3 in the artery tibial) was identified that was significantly associated with a poor response to β-blockers (P = 3.43 × 10-6 , β = 4.57) and was replicated in the atenolol add-on cohort (P = 0.007, β = 4.97). We identified variants in FGD5 and SLC4A1, which have been previously cited as candidate genes for hypertension, to be associated with a β-blocker BP response in EA. Further elucidation is warranted of the underlying mechanisms of these variants and genes by which they influence the BP response to β-blockers.

Autophagy as an emerging target in cardiorenal metabolic disease: From pathophysiology to management

Although advances in medical technology and health care have improved the early diagnosis and management for cardiorenal metabolic disorders, the prevalence of obesity, insulin resistance, diabetes, hypertension, dyslipidemia, and kidney disease remains high. Findings from numerous population-based studies, clinical trials, and experimental evidence have consolidated a number of theories for the pathogenesis of cardiorenal metabolic anomalies including resistance to the metabolic action of insulin, abnormal glucose and lipid metabolism, oxidative and nitrosative stress, endoplasmic reticulum (ER) stress, apoptosis, mitochondrial damage, and inflammation. Accumulating evidence has recently suggested a pivotal role for proteotoxicity, the unfavorable effects of poor protein quality control, in the pathophysiology of metabolic dysregulation and related cardiovascular complications. The ubiquitin-proteasome system (UPS) and autophagy-lysosomal pathways, two major although distinct cellular clearance machineries, govern protein quality control by degradation and clearance of long-lived or damaged proteins and organelles. Ample evidence has depicted an important role for protein quality control, particularly autophagy, in the maintenance of metabolic homeostasis. To this end, autophagy offers promising targets for novel strategies to prevent and treat cardiorenal metabolic diseases. Targeting autophagy using pharmacological or natural agents exhibits exciting new strategies for the growing problem of cardiorenal metabolic disorders.

Associations of Endothelial System Genes With Blood Pressure Changes and Hypertension Incidence: The GenSalt Study

BACKGROUND

We used single-marker and novel gene-based methods to examine the associations of endothelial system genes with blood pressure (BP) changes and hypertension in a longitudinal family study.

METHODS

The Genetic Epidemiology Network of Salt Sensitivity follow-up study was conducted among 1,768 Chinese participants from 633 families. Nine BP measurements were obtained at baseline and at 2 follow-up visits using a random-zero sphygmomanometer. Mixed-effect models were used to assess the additive associations of 206 single-nucleotide polymorphisms (SNPs) in 15 endothelial system genes with longitudinal BP changes and hypertension incidence. Gene-based analyses were conducted using the truncated product method. The Bonferroni method was used to adjust for multiple testing in all analyses.

RESULTS

Among those free from hypertension at baseline, 512 (32.1%) developed hypertension during the average 7.2 years of follow-up. In single-marker analyses, each copy of the minor alleles of correlated SELE markers rs4656704, rs6427212, and rs5368 were associated with increased risk of developing hypertension (P for trend = 1.48 × 10(-4), 6.69 × 10(-5), and 7.64 × 10(-5), respectively). In addition, the minor allele of SELE marker rs3917436 was associated with smaller diastolic BP (DBP) increases over time. Results of gene-based analyses confirmed associations of the SELE gene with the longitudinal BP phenotypes (P values < 1.00 × 10(-6) for DBP change and hypertension incidence). Furthermore, the DDAH1 and COL18A1 genes were associated with systolic BP change (P < 1.00 × 10(-6) and P = 4.00 × 10(-6), respectively), while EDNRA was associated with hypertension incidence (P = 2.39 × 10(-4)).

CONCLUSIONS

The current study provides strong evidence of a role of endothelial system genes in BP progression and hypertension incidence.

Association between 1019C/T polymorphism in the connexin 37 gene and essential hypertension

OBJECTIVE

To investigate the association between the CX 37 1019C/T polymorphism and the susceptibility to essential hypertension (EH).

METHODS

A total of 1126 cases of EH were diagnosed in the People's Hospital of Wuxi City, China. A control group consisted of 874 healthy people, i.e., non-EH patients. All cases were genotyped by DNA sequencing.

RESULTS

Polymorphism C1019T on the Connexin37 gene was found in the whole population. The distribution of three genotype frequencies in both groups was in accordance with the Hardy-Weinberg equilibrium. The frequency of the CX37C allele was higher in EH patients (57.4% vs. 42.1%, χ(2)=92.5, P<0.01) compared to the control group. The frequency of C carriers (CC+TC) was 80.5% in EH patients compared to 66.7% in the control (χ(2)=49.0, P<0.01). EH risk was significantly increased in carriers of C the allele (CC+TC) over that in the TT homozygote (OR=2.06, 95% CI: 1.68 ∼ 2.52). Subsequent stratified analyses demonstrate that a significant difference exists in the frequency of C carriers between male EH patients and controls (79.2% vs. 69.1%, χ(2)=13.4, P<0.01) and in female EH patients and the control group (81.8% vs. 64.4%, χ(2)=38.7, P<0.01). The carriers of the C allele had higher EH risk compared with the TT homozygote without sex differences (male: OR=1.71, 95% CI: 1.28 ∼ 2.27; female: OR=2.48, 95%CI: 1.85 ∼ 3.31).

CONCLUSION

The C allele in the CX37 gene might be associated with the susceptibility to EH in population of Wuxi, China.

WinHAP2: an extremely fast haplotype phasing program for long genotype sequences

Background

The haplotype phasing problem tries to screen for phenotype associated genomic variations from millions of candidate data. Most of the current computer programs handle this problem with high requirements of computing power and memory. By replacing the computation-intensive step of constructing the maximum spanning tree with a heuristics of estimated initial haplotype, we released the WinHAP algorithm version 1.0, which outperforms the other algorithms in terms of both running speed and overall accuracy.

Results

This work further speeds up the WinHAP algorithm to version 2.0 (WinHAP2) by utilizing the divide-and-conquer strategy and the OpenMP parallel computing mode. WinHAP2 can phase 500 genotypes with 1,000,000 SNPs using just 12.8 MB in memory and 2.5 hours on a personal computer, whereas the other programs require unacceptable memory or running times. The parallel running mode further improves WinHAP2's running speed with several orders of magnitudes, compared with the other programs, including Beagle, SHAPEIT2 and 2SNP.

Conclusions

WinHAP2 is an extremely fast haplotype phasing program which can handle a large-scale genotyping study with any number of SNPs in the current literature and at least in the near future.

Personal genomic information management and personalized medicine: challenges, current solutions, and roles of HIM professionals

In recent years, the term personalized medicine has received more and more attention in the field of healthcare. The increasing use of this term is closely related to the astonishing advancement in DNA sequencing technologies and other high-throughput biotechnologies. A large amount of personal genomic data can be generated by these technologies in a short time. Consequently, the needs for managing, analyzing, and interpreting these personal genomic data to facilitate personalized care are escalated. In this article, we discuss the challenges for implementing genomics-based personalized medicine in healthcare, current solutions to these challenges, and the roles of health information management (HIM) professionals in genomics-based personalized medicine.