NHLBI family blood pressure program: methodology and recruitment in the HyperGEN network. Hypertension genetic epidemiology network

Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations

Key Points

Background

CKD is a risk factor of cardiovascular disease and early death. Recently, polygenic risk scores (PRSs) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European ancestry–derived PRSs demonstrate diminished predictive performance in African ancestry populations.

Methods

This study aimed to develop a PRS for CKD in Black American populations. We obtained score weights from a meta-analysis of genome-wide association studies for eGFR in the Million Veteran Program and Reasons for Geographic and Racial Differences in Stroke Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of participants from the Hypertension Genetic Epidemiology Network. Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine Consortium and Genetics of Hypertension Associated Treatment Study.

Results

The prevalence of CKD—defined as stage 3 or higher—was associated with the PRS as a continuous predictor (odds ratio [95% confidence interval]: 1.35 [1.08 to 1.68]) and in a threshold-dependent manner. Furthermore, including APOL1 risk status—a putative variant for CKD with higher prevalence among those of sub-Saharan African descent—improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable with a European ancestry–derived PRS for kidney traits. However, single-ancestry PRSs were less predictive than multi-ancestry–derived PRSs.

Conclusions

In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.

Sex-Associated Metabolites and Incident Stroke, Incident Coronary Heart Disease, Hypertension, and Chronic Kidney Disease in the REGARDS Cohort

BACKGROUND

Sex disparities exist in cardiometabolic diseases. Metabolomic profiling offers insight into disease mechanisms, as the metabolome is influenced by environmental and genetic factors. We identified metabolites associated with sex and determined if sex-associated metabolites are associated with incident stoke, incident coronary heart disease, prevalent hypertension, and prevalent chronic kidney disease.

METHODS AND RESULTS

Targeted metabolomics was conducted for 357 metabolites in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) case-cohort substudy for incident stroke. Weighted logistic regression models were used to identify metabolites associated with sex in REGARDS. Sex-associated metabolites were replicated in the HyperGEN (Hypertension Genetic Epidemiology Network) and using the literature. Weighted Cox proportional hazard models were used to evaluate associations between metabolites and incident stroke. Cox proportional hazard models were used to evaluate associations between metabolites and incident coronary heart disease. Weighted logistic regression models were used to evaluate associations between metabolites and hypertension and chronic kidney disease. Fifty-one replicated metabolites were associated with sex. Higher levels of 6 phosphatidylethanolamines were associated with incident stroke. No metabolites were associated with incident coronary heart disease. Higher levels of uric acid and leucine and lower levels of a lysophosphatidylcholine were associated with hypertension. Higher levels of indole-3-lactic acid, 7 phosphatidylethanolamines, and uric acid, and lower levels of betaine and bilirubin were associated with chronic kidney disease.

CONCLUSIONS

These findings suggest that the sexual dimorphism of the metabolome may contribute to sex differences in stroke, hypertension, and chronic kidney disease.

Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization

Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.

Organs-on-a-chip: a union of tissue engineering and microfabrication

We review the emergence of the new field of organ-on-a-chip (OOAC) engineering, from the parent fields of tissue engineering and microfluidics. We place into perspective the tools and capabilities brought into the OOAC field by early tissue engineers and microfluidics experts. Liver-on-a-chip and heart-on-a-chip are used as two case studies of systems that heavily relied on tissue engineering techniques and that were amongst the first OOAC models to be implemented, motivated by the need to better assess toxicity to human tissues in preclinical drug development. We review current challenges in OOAC that often stem from the same challenges in the parent fields, such as stable vascularization and drug absorption.

Circulating Metabolites Associated with Albuminuria in a Hispanic/Latino Population

BACKGROUND

Albuminuria is associated with metabolic abnormalities, but these relationships are not well understood. We studied the association of metabolites with albuminuria in Hispanic/Latino people, a population with high risk for metabolic disease.

METHODS

We used data from 3736 participants from the Hispanic Community Health Study/Study of Latinos, of which 16% had diabetes and 9% had an increased urine albumin-to-creatinine ratio (UACR). Metabolites were quantified in fasting serum through nontargeted mass spectrometry (MS) analysis using ultra-performance liquid chromatography-MS/MS. Spot UACR was inverse normally transformed and tested for the association with each metabolite or combined, correlated metabolites, in covariate-adjusted models that accounted for the study design. In total, 132 metabolites were available for replication in the Hypertension Genetic Epidemiology Network study ( n =300), and 29 metabolites were available for replication in the Malmö Offspring Study ( n =999).

RESULTS

Among 640 named metabolites, we identified 148 metabolites significantly associated with UACR, including 18 novel associations that replicated in independent samples. These metabolites showed enrichment for D-glutamine and D-glutamate metabolism and arginine biosynthesis, pathways previously reported for diabetes and insulin resistance. In correlated metabolite analyses, we identified two modules significantly associated with UACR, including a module composed of lipid metabolites related to the biosynthesis of unsaturated fatty acids and alpha linolenic acid and linoleic acid metabolism.

CONCLUSIONS

Our study identified associations of albuminuria with metabolites involved in glucose dysregulation, and essential fatty acids and precursors of arachidonic acid in Hispanic/Latino population.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_02_08_CJN09070822.mp3.

Differentially Methylated DNA Regions and Left Ventricular Hypertrophy in African Americans: A HyperGEN Study

Left ventricular (LV) hypertrophy (LVH) is an independent risk factor for cardiovascular disease, and African Americans experience a disparate high risk of LVH. Genetic studies have identified potential candidate genes and variants related to the condition. Epigenetic modifications may continue to help unravel disease mechanisms. We used methylation and echocardiography data from 636 African Americans selected from the Hypertension Genetic Epidemiology Network (HyperGEN) to identify differentially methylated regions (DMRs) associated with LVH. DNA extracted from whole blood was assayed on Illumina Methyl450 arrays. We fit linear mixed models to examine associations between co-methylated regions and LV traits, and we then conducted single CpG analyses within significant DMRs. We identified associations between DMRs and ejection fraction (XKR6), LV internal diastolic dimension (TRAK1), LV mass index (GSE1, RPS15 A, PSMD7), and relative wall thickness (DNHD1). In single CpG analysis, CpG sites annotated to TRAK1 and DNHD1 were significant. These CpGs were not associated with LV traits in replication cohorts but the direction of effect for DNHD1 was consistent across cohorts. Of note, DNHD1, GSE1, and PSMD7 may contribute to cardiac structural function. Future studies should evaluate relationships between regional DNA methylation patterns and the development of LVH.

Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes

Background:

Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.

Methods:

Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years). First, we identified genetic hypertension components with an unsupervised Bayesian non-negative matrix factorization algorithm using public genome-wide association data for 144 genetic hypertension variants and 16 clinical traits. For these components, we computed their (1) cross-sectional associations with clinical traits in FINRISK using linear regression and (2) longitudinal associations with incident adverse outcomes in FinnGen using Cox regression.

Results:

We observed 4 genetic hypertension components corresponding to recognizable clinical phenotypes: obesity (high body mass index), dyslipidemia (low high-density lipoprotein cholesterol and high triglycerides), hypolipidemia (low low-density lipoprotein cholesterol and low total cholesterol), and short stature. In FINRISK, all hypertension components had robust associations with their respective clinical characteristics. In FinnGen, the Obesity component was associated with increased diabetes risk (hazard ratio per 1 SD increase 1.08 [Bonferroni corrected CI, 1.05–1.10]) and the Hypolipidemia component with increased autoimmune disease risk (hazard ratio per 1 SD increase 1.05 [Bonferroni corrected CI, 1.03–1.07]). In addition, all hypertension components were related to both hypertension and cardiovascular disease.

Conclusions:

Our unsupervised analysis demonstrates that the genetic basis of hypertension can be understood as a mixture of 4 broad, clinically interpretable components capturing disease heterogeneity. These components could be used to stratify individuals into specific genetic subtypes and, therefore, to benefit personalized health care and pharmaceutical research.

Genome-wide polygenic score to predict chronic kidney disease across ancestries

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations.

METHODS

We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.

RESULTS

The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance.

CONCLUSIONS

By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.

Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities

Hypertension, obesity, chronic kidney disease and type 2 diabetes are comorbidities that have very high prevalence among persons with hyperuricemia (serum urate > 6.8 mg/dL) and gout. Here we use multivariate genetic models to test the hypothesis that the co-association of traits representing hyperuricemia and its comorbidities is genetically based. Using Bayesian whole-genome regression models, we estimated the genetic marker-based variance and the covariance between serum urate, serum creatinine, systolic blood pressure (SBP), blood glucose and body mass index (BMI) from two independent family-based studies: The Framingham Heart Study-FHS and the Hypertension Genetic Epidemiology Network study-HyperGEN. The main genetic findings that replicated in both FHS and HyperGEN, were (1) creatinine was genetically correlated only with urate and (2) BMI was genetically correlated with urate, SBP, and glucose. The environmental covariance among the traits was generally highest for trait pairs involving BMI. The genetic overlap of traits representing the comorbidities of hyperuricemia and gout appears to cluster in two separate axes of genetic covariance. Because creatinine is genetically correlated with urate but not with metabolic traits, this suggests there is one genetic module of shared loci associated with hyperuricemia and chronic kidney disease. Another module of shared loci may account for the association of hyperuricemia and metabolic syndrome. This study provides a clear quantitative genetic basis for the clustering of comorbidities with hyperuricemia.

Whole-Exome Sequencing and hiPSC Cardiomyocyte Models Identify MYRIP, TRAPPC11, and SLC27A6 of Potential Importance to Left Ventricular Hypertrophy in an African Ancestry Population

Background: Indices of left ventricular (LV) structure and geometry represent useful intermediate phenotypes related to LV hypertrophy (LVH), a predictor of cardiovascular (CV) disease (CVD) outcomes.

Methods and Results: We conducted an exome-wide association study of LV mass (LVM) adjusted to height^2.7, LV internal diastolic dimension (LVIDD), and relative wall thickness (RWT) among 1,364 participants of African ancestry (AAs) in the Hypertension Genetic Epidemiology Network (HyperGEN). Both single-variant and gene-based sequence kernel association tests were performed to examine whether common and rare coding variants contribute to variation in echocardiographic traits in AAs. We then used a data-driven procedure to prioritize and select genes for functional validation using a human induced pluripotent stem cell cardiomyocyte (hiPSC-CM) model. Three genes [myosin VIIA and Rab interacting protein (MYRIP), trafficking protein particle complex 11 (TRAPPC11), and solute carrier family 27 member 6 (SLC27A6)] were prioritized based on statistical significance, variant functional annotations, gene expression in the hiPSC-CM model, and prior biological evidence and were subsequently knocked down in the hiPSC-CM model. Expression profiling of hypertrophic gene markers in the knockdowns suggested a decrease in hypertrophic expression profiles. MYRIP knockdowns showed a significant decrease in atrial natriuretic factor (NPPA) and brain natriuretic peptide (NPPB) expression. Knockdowns of the heart long chain fatty acid (FA) transporter SLC27A6 resulted in downregulated caveolin 3 (CAV3) expression, which has been linked to hypertrophic phenotypes in animal models. Finally, TRAPPC11 knockdown was linked to deficient calcium handling.

Conclusions: The three genes are biologically plausible candidates that provide new insight to hypertrophic pathways.

Genetic-Based Hypertension Subtype Identification Using Informative SNPs

In this work, we proposed a process to select informative genetic variants for identifying clinically meaningful subtypes of hypertensive patients. We studied 575 African American (AA) and 612 Caucasian hypertensive participants enrolled in the Hypertension Genetic Epidemiology Network (HyperGEN) study and analyzed each race-based group separately. All study participants underwent GWAS (Genome-Wide Association Studies) and echocardiography. We applied a variety of statistical methods and filtering criteria, including generalized linear models, F statistics, burden tests, deleterious variant filtering, and others to select the most informative hypertension-related genetic variants. We performed an unsupervised learning algorithm non-negative matrix factorization (NMF) to identify hypertension subtypes with similar genetic characteristics. Kruskal–Wallis tests were used to demonstrate the clinical meaningfulness of genetic-based hypertension subtypes. Two subgroups were identified for both African American and Caucasian HyperGEN participants. In both AAs and Caucasians, indices of cardiac mechanics differed significantly by hypertension subtypes. African Americans tend to have more genetic variants compared to Caucasians; therefore, using genetic information to distinguish the disease subtypes for this group of people is relatively challenging, but we were able to identify two subtypes whose cardiac mechanics have statistically different distributions using the proposed process. The research gives a promising direction in using statistical methods to select genetic information and identify subgroups of diseases, which may inform the development and trial of novel targeted therapies.

Epigenetic loci for blood pressure are associated with hypertensive target organ damage in older African Americans from the genetic epidemiology network of Arteriopathy (GENOA) study

BACKGROUND

Hypertension is a major modifiable risk factor for arteriosclerosis that can lead to target organ damage (TOD) of heart, kidneys, and peripheral arteries. A recent epigenome-wide association study for blood pressure (BP) identified 13 CpG sites, but it is not known whether DNA methylation at these sites is also associated with TOD.

METHODS

In 1218 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study, a cohort of hypertensive sibships, we evaluated the associations between methylation at these 13 CpG sites measured in peripheral blood leukocytes and five TOD traits assessed approximately 5 years later.

RESULTS

Ten significant associations were found after adjustment for age, sex, blood cell counts, time difference between CpG and TOD measurement, and 10 genetic principal components (FDR q < 0.1): two with estimated glomerular filtration rate (eGFR, cg06690548, cg10601624), six with urinary albumin-to-creatinine ratio (UACR, cg16246545, cg14476101, cg19693031, cg06690548, cg00574958, cg22304262), and two with left ventricular mass indexed to height (LVMI, cg19693031, cg00574958). All associations with eGFR and four associations with UACR remained significant after further adjustment for body mass index (BMI), smoking status, and diabetes. We also found significant interactions between cg06690548 and BMI on UACR, and between 3 CpG sites (cg19693031, cg14476101, and cg06690548) and diabetes on UACR (FDR q < 0.1). Mediation analysis showed that 4.7% to 38.1% of the relationship between two CpG sites (cg19693031 and cg00574958) and two TOD measures (UACR and LVMI) was mediated by blood pressure (Bonferroni-corrected P < 0.05). Mendelian randomization analysis suggests that methylation at two sites (cg16246545 and cg14476101) in PHGDH may causally influence UACR.

CONCLUSIONS

In conclusion, we found compelling evidence for associations between arteriosclerotic traits of kidney and heart and previously identified blood pressure-associated DNA methylation sites. This study may lend insight into the role of DNA methylation in pathological mechanisms underlying target organ damage from hypertension.

A Mendelian randomization study of telomere length and blood-cell traits

Whether telomere attrition reducing proliferative reserve in blood-cell progenitors is causal has important public-health implications. Mendelian randomization (MR) is an analytic technique using germline genetic variants as instrumental variables. If certain assumptions are met, estimates from MR should be free from most environmental sources of confounding and reverse causation. Here, two-sample MR is performed to test whether longer telomeres cause changes to hematological traits. Summary statistics for genetic variants strongly associated with telomere length were extracted from a genome-wide association (GWA) study for telomere length in individuals of European ancestry (n = 9190) and from GWA studies of blood-cell traits, also in those of European ancestry (n ~ 173,000 participants). A standard deviation increase in genetically influenced telomere length increased red blood cell and white blood cell counts, decreased mean corpuscular hemoglobinand mean cell volume, and had no observable impact on mean corpuscular hemoglobin concentration, red cell distribution width, hematocrit, or hemoglobin. Sensitivity tests for pleiotropic distortion were mostly inconsistent with glaring violations to the MR assumptions. Similar to germline mutations in telomere biology genes leading to bone-marrow failure, these data provide evidence that genetically influenced common variation in telomere length impacts hematologic traits in the population.

Detecting fitness epistasis in recently admixed populations with genome-wide data

BACKGROUND

Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population.

RESULTS

We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10- 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of co-expressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment.

CONCLUSIONS

Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Integrating hypertension phenotype and genotype with hybrid non-negative matrix factorization

MOTIVATION

Hypertension is a heterogeneous syndrome in need of improved subtyping using phenotypic and genetic measurements with the goal of identifying subtypes of patients who share similar pathophysiologic mechanisms and may respond more uniformly to targeted treatments. Existing machine learning approaches often face challenges in integrating phenotype and genotype information and presenting to clinicians an interpretable model. We aim to provide informed patient stratification based on phenotype and genotype features.

RESULTS

In this article, we present a hybrid non-negative matrix factorization (HNMF) method to integrate phenotype and genotype information for patient stratification. HNMF simultaneously approximates the phenotypic and genetic feature matrices using different appropriate loss functions, and generates patient subtypes, phenotypic groups and genetic groups. Unlike previous methods, HNMF approximates phenotypic matrix under Frobenius loss, and genetic matrix under Kullback-Leibler (KL) loss. We propose an alternating projected gradient method to solve the approximation problem. Simulation shows HNMF converges fast and accurately to the true factor matrices. On a real-world clinical dataset, we used the patient factor matrix as features and examined the association of these features with indices of cardiac mechanics. We compared HNMF with six different models using phenotype or genotype features alone, with or without NMF, or using joint NMF with only one type of loss We also compared HNMF with 3 recently published methods for integrative clustering analysis, including iClusterBayes, Bayesian joint analysis and JIVE. HNMF significantly outperforms all comparison models. HNMF also reveals intuitive phenotype-genotype interactions that characterize cardiac abnormalities.

AVAILABILITY AND IMPLEMENTATION

Our code is publicly available on github at https://github.com/yuanluo/hnmf.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-wide meta-analysis of SNP and antihypertensive medication interactions on left ventricular traits in African Americans

BACKGROUND

Left ventricular (LV) hypertrophy affects up to 43% of African Americans (AAs). Antihypertensive treatment reduces LV mass (LVM). However, interindividual variation in LV traits in response to antihypertensive treatments exists. We hypothesized that genetic variants may modify the association of antihypertensive treatment class with LV traits measured by echocardiography.

METHODS

We evaluated the main effects of the three most common antihypertensive treatments for AAs as well as the single nucleotide polymorphism (SNP)-by-drug interaction on LVM and relative wall thickness (RWT) in 2,068 participants across five community-based cohorts. Treatments included thiazide diuretics (TDs), angiotensin converting enzyme inhibitors (ACE-Is), and dihydropyridine calcium channel blockers (dCCBs) and were compared in a pairwise manner. We performed fixed effects inverse variance weighted meta-analyses of main effects of drugs and 2.5 million SNP-by-drug interaction estimates.

RESULTS

We observed that dCCBs versus TDs were associated with higher LVM after adjusting for covariates (p = 0.001). We report three SNPs at a single locus on chromosome 20 that modified the association between RWT and treatment when comparing dCCBs to ACE-Is with consistent effects across cohorts (smallest p = 4.7 × 10-8 , minor allele frequency range 0.09-0.12). This locus has been linked to LV hypertrophy in a previous study. A marginally significant locus in BICD1 (rs326641) was validated in an external population.

CONCLUSIONS

Our study identified one locus having genome-wide significant SNP-by-drug interaction effect on RWT among dCCB users in comparison to ACE-I users. Upon additional validation in future studies, our findings can enhance the precision of medical approaches in hypertension treatment.

A Platform for Generation of Chamber-Specific Cardiac Tissues and Disease Modeling

Tissue engineering using cardiomyocytes derived from human pluripotent stem cells holds a promise to revolutionize drug discovery, but only if limitations related to cardiac chamber specification and platform versatility can be overcome. We describe here a scalable tissue-cultivation platform that is cell source agnostic and enables drug testing under electrical pacing. The plastic platform enabled on-line noninvasive recording of passive tension, active force, contractile dynamics, and Ca2+ transients, as well as endpoint assessments of action potentials and conduction velocity. By combining directed cell differentiation with electrical field conditioning, we engineered electrophysiologically distinct atrial and ventricular tissues with chamber-specific drug responses and gene expression. We report, for the first time, engineering of heteropolar cardiac tissues containing distinct atrial and ventricular ends, and we demonstrate their spatially confined responses to serotonin and ranolazine. Uniquely, electrical conditioning for up to 8 months enabled modeling of polygenic left ventricular hypertrophy starting from patient cells.

Clinical correlates and heritability of cardiac mechanics: The HyperGEN study

BACKGROUND

Indices of cardiac mechanics are sensitive markers of subclinical myocardial dysfunction. Improved understanding of the clinical correlates and heritability of cardiac mechanics could result in novel insight into the acquired and genetic risk factors for myocardial dysfunction. Therefore, we sought to determine the clinical correlates and heritability of indices of cardiac mechanics in whites and African Americans (AAs).

METHODS

We examined 2058 participants stratified by race (1104 whites, 954 AA) in the Hypertension Genetic Epidemiology Network (HyperGEN), a population- and family-based study, and performed digitization of analog echocardiograms with subsequent speckle-tracking analysis. We used linear mixed effects models to determine the clinical correlates of indices of cardiac mechanics (longitudinal, circumferential, radial strain; early diastolic strain rate; and early diastolic tissue velocities). Heritability estimates for cardiac mechanics were calculated using maximum-likelihood variance component analyses in Sequential Oligogenic Linkage Analysis Routine (SOLAR), with adjustment for clinical and echocardiographic covariates.

RESULTS

Several clinical characteristics and conventional echocardiographic parameters were found to be associated with speckle-tracking traits of cardiac mechanics. Male sex, blood pressure, and fasting glucose were associated with worse longitudinal strain (LS) (P < 0.05 for all) after multivariable adjustment. After adjustment for covariates, LS, e' velocity, and early diastolic strain rate were found to be heritable; LS and e' velocity had higher heritability estimates in AAs compared to whites.

CONCLUSIONS

Indices of cardiac mechanics are heritable traits even after adjustment for clinical and conventional echocardiographic correlates. These findings provide the basis for future studies of genetic determinants of these traits that may elucidate race-based differences in heart failure development.

Low-grade albuminuria is associated with poor memory performance in the nondemented Chinese elderly with type 2 diabetes

Recent studies have correlated cognitive function with albuminuria. We investigated the association between low-grade albuminuria and cognitive performance in nondemented elderly with type 2 diabetes in Fuzhou, China. Between January, 2013 and December, 2014, a retrospective study was performed in 815 patients with type 2 diabetes (398 female and 417 male patients), ages ≥60 years, with normal urinary albumin to creatinine ratios (UACR <30 mg/g). Patients were stratified into tertiles based on UACR levels (lowest tertile, UACR <5.8 mg/g; highest tertile, UACR ≥18.1 mg/g). Cognitive function was measured using the Mini Mental State Examination. UACR tertiles correlated directly (p < 0.05) with age, duration of diabetes, systolic blood pressure (SBP), and pulse wave velocity (PWV). Patients in the second and highest tertiles performed significantly worse on memory and language than those in the lowest UACR tertile (p < 0.05). The association between UACR and memory loss was stronger in patients younger than 70 years of age and in those with a history of diabetes for less than 10 years. Low-grade albuminuria is associated with poor memory performance, especially in the youngest old (60-69 years) and in those with shorter duration of diabetes (< 10 years). Type 2 diabetics with urinary albumin excretion in the upper normal range were also at risk for declining memory performance.

Association of Estimated Sodium Intake With Adverse Cardiac Structure and Function: From the HyperGEN Study

BACKGROUND

The optimal level of sodium intake remains controversial.

OBJECTIVES

This study sought to determine whether examination of left ventricular longitudinal strain (LS), circumferential strain, and e' velocity can provide insight into thresholds for the detrimental effects of estimated sodium intake (ESI) on subclinical cardiovascular disease.

METHODS

We performed speckle-tracking analysis on HyperGEN (Hypertension Genetic Epidemiology Network) study echocardiograms with available urinary sodium data (N = 2,996). We evaluated the associations among ESI and LS, circumferential strain, and e' velocity using multivariable-adjusted linear mixed-effects models (to account for relatedness among subjects) with linear splines (spline 1: ESI ≤3.7 g/day, spline 2: ESI >3.7 g/day based on visual inspection of fractional polynomial plots of the association between ESI and indices of strain and e' velocity). We performed mediation analysis to understand the indirect effects of systolic blood pressure and serum aldosterone on the relationship between ESI and strain and e' velocity.

RESULTS

Mean age of participants was 49 ± 14 years, 57% were female, 50% were African American, and 54% had hypertension. The median ESI was 3.73 (interquartile range: 3.24, 4.25) g/day. ESI >3.7 g/day was associated with larger left atrial and left ventricular dimensions (p < 0.05). After adjusting for speckle-tracking analyst, image quality, study site, age, sex, smoking status, alcohol use, daily blocks walked, diuretic use, estimated glomerular filtration rate, left ventricular mass, ejection fraction, and wall motion score index, ESI >3.7 g/day was associated with both strain parameters and e' velocity (p < 0.05 for all comparisons), but ESI ≤3.7 g/day was not (p > 0.05 for all comparisons). There were significant interactions by potassium excretion for circumferential strain. Mediation analysis suggested that systolic blood pressure explained 14% and 20% of the indirect effects between ESI and LS and e' velocity, respectively, whereas serum aldosterone explained 19% of the indirect effects between ESI and LS.

CONCLUSIONS

ESI >3.7 g/day is associated with adverse cardiac remodeling and worse systolic strain and diastolic e' velocity.

Association of Central Adiposity With Adverse Cardiac Mechanics: Findings From the Hypertension Genetic Epidemiology Network Study

BACKGROUND

Central obesity, defined by increased waist circumference or waist:hip ratio (WHR), is associated with increased cardiovascular events, including heart failure. However, the pathophysiological link between central obesity and adverse cardiovascular outcomes remains poorly understood. We hypothesized that central obesity and larger WHR are independently associated with worse cardiac mechanics (reduced left ventricular strain and systolic [s'] and early diastolic [e'] tissue velocities).

METHODS AND RESULTS

We performed speckle-tracking analysis of echocardiograms from participants in the Hypertension Genetic Epidemiology Network (HyperGEN) study, a population- and family-based epidemiological study (n=2181). Multiple indices of systolic and diastolic cardiac mechanics were measured. We evaluated the association between central obesity and cardiac mechanics using multivariable-adjusted linear mixed-effects models to account for relatedness among participants. The mean age of the cohort was 51±14 years, 58% were women, and 47% were black. Mean body mass index was 30.8±7.1 kg/m(2), waist circumference was 102±17 cm, WHR was 0.91±0.08, and 80% had central obesity based on waist circumference and WHR criteria. After adjusting for multiple potential confounders (including age, sex, race, physical activity, body mass index, heart rate, smoking status, systolic blood pressure, fasting glucose, total cholesterol, antihypertensive medication use, glomerular filtration rate, left ventricular mass index, wall motion abnormalities, and ejection fraction), central obesity and WHR remained associated with worse global longitudinal strain, early diastolic strain rate, s' velocity, and e' velocity (P<0.05 for all comparisons). There were no significant statistical interactions between WHR and obesity status.

CONCLUSIONS

In this cross-sectional study of participants with multiple comorbidities, central obesity was found to be associated with adverse cardiac mechanics.

Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction

We sought to evaluate whether unbiased machine learning of dense phenotypic data ("phenomapping") could identify distinct hypertension subgroups that are associated with the myocardial substrate (i.e., abnormal cardiac mechanics) for heart failure with preserved ejection fraction (HFpEF). In the HyperGEN study, a population- and family-based study of hypertension, we studied 1273 hypertensive patients utilizing clinical, laboratory, and conventional echocardiographic phenotyping of the study participants. We used machine learning analysis of 47 continuous phenotypic variables to identify mutually exclusive groups constituting a novel classification of hypertension. The phenomapping analysis classified study participants into 2 distinct groups that differed markedly in clinical characteristics, cardiac structure/function, and indices of cardiac mechanics (e.g., phenogroup #2 had a decreased absolute longitudinal strain [12.8 ± 4.1 vs. 14.6 ± 3.5%] even after adjustment for traditional comorbidities [p < 0.001]). The 2 hypertension phenogroups may represent distinct subtypes that may benefit from targeted therapies for the prevention of HFpEF.

Cardiac Imaging in Heart Failure with Comorbidities

Imaging modalities stand at the frontiers for progress in congestive heart failure (CHF) screening, risk stratification and monitoring. Advancements in echocardiography (ECHO) and Magnetic Resonance Imaging (MRI) have allowed for improved tissue characterizations, cardiac motion analysis, and cardiac performance analysis under stress. Common cardiac comorbidities such as hypertension, metabolic syndromes and chronic renal failure contribute to cardiac remodeling, sharing similar pathophysiological mechanisms starting with interstitial changes, structural changes and finally clinical CHF. These imaging techniques can potentially detect changes earlier. Such information could have clinical benefits for screening, planning preventive therapies and risk stratifying patients. Imaging reports have often focused on traditional measures without factoring these novel parameters. This review is aimed at providing a synopsis on how we can use this information to assess and monitor improvements for CHF with comorbidities.

A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction

Cigarette smoking has been shown to be a health hazard. In addition to being considered a negative lifestyle behavior, studies have shown that cigarette smoking has been linked to genetic underpinnings of hypertension. Because African Americans have the highest incidence and prevalence of hypertension, we examined the joint effect of genetics and cigarette smoking on health among this understudied population. The sample included African Americans from the genome wide association studies of HyperGEN (N = 1083, discovery sample) and GENOA (N = 1427, replication sample), both part of the FBPP. Results suggested that 2 SNPs located on chromosomes 14 (NEDD8; rs11158609; raw p = 9.80 × 10⁻⁹, genomic control-adjusted p = 2.09 × 10⁻⁷) and 17 (TTYH2; rs8078051; raw p = 6.28 × 10⁻⁸, genomic control-adjusted p = 9.65 × 10⁻⁷) were associated with SBP including the genetic interaction with cigarette smoking. These two SNPs were not associated with SBP in a main genetic effect only model. This study advances knowledge in the area of main and joint effects of genetics and cigarette smoking on hypertension among African Americans and offers a model to the reader for assessing these risks. More research is required to determine how these genes play a role in expression of hypertension.

Archeological Echocardiography: Digitization and Speckle Tracking Analysis of Archival Echocardiograms in the HyperGEN Study

BACKGROUND

Several large epidemiologic studies and clinical trials have included echocardiography, but images were stored in analog format and these studies predated tissue Doppler imaging (TDI) and speckle tracking echocardiography (STE). We hypothesized that digitization of analog echocardiograms, with subsequent quantification of cardiac mechanics using STE, is feasible, reproducible, accurate, and produces clinically valid results.

METHODS

In the NHLBI HyperGEN study (N = 2234), archived analog echocardiograms were digitized and subsequently analyzed using STE to obtain tissue velocities/strain. Echocardiograms were assigned quality scores and inter-/intra-observer agreement was calculated. Accuracy was evaluated in: (1) a separate second study (N = 50) comparing prospective digital strain versus post hoc analog-to-digital strain, and (2) in a third study (N = 95) comparing prospectively obtained TDI e' velocities with post hoc STE e' velocities. Finally, we replicated previously known associations between tissue velocities/strain, conventional echocardiographic measurements, and clinical data.

RESULTS

Of the 2234 HyperGEN echocardiograms, 2150 (96.2%) underwent successful digitization and STE analysis. Inter/intra-observer agreement was high for all STE parameters, especially longitudinal strain (LS). In accuracy studies, LS performed best when comparing post hoc STE to prospective digital STE for strain analysis. STE-derived e' velocities correlated with, but systematically underestimated, TDI e' velocity. Several known associations between clinical variables and cardiac mechanics were replicated in HyperGEN. We also found a novel independent inverse association between fasting glucose and LS (adjusted β = -2.4 [95% CI -3.6, -1.2]% per 1-SD increase in fasting glucose; P < 0.001).

CONCLUSIONS

Archeological echocardiography, the digitization and speckle tracking analysis of archival echocardiograms, is feasible and generates indices of cardiac mechanics similar to contemporary studies.

The role of rare variants in systolic blood pressure: analysis of ExomeChip data in HyperGEN African Americans

Cardiovascular diseases are among the most significant health problems in the United States today, with their major risk factor, hypertension, disproportionately affecting African Americans (AAs). Although GWAS have identified dozens of common variants associated with blood pressure (BP) and hypertension in European Americans, these variants collectively explain <2.5% of BP variance, and most of the genetic variants remain yet to be identified. Here, we report the results from rare-variant analysis of systolic BP using 94,595 rare and low-frequency variants (minor allele frequency, MAF, <5%) from the Illumina exome array genotyped in 2,045 HyperGEN AAs. In addition to single-variant analysis, 4 gene-level association tests were used for analysis: burden and family-based SKAT tests using MAF cutoffs of 1 and 5%. The gene-based methods often provided lower p values than the single-variant approach. Some consistency was observed across these 4 gene-based analysis options. While neither the gene-based analyses nor the single-variant analysis produced genome-wide significant results, the top signals, which had supporting evidence from multiple gene-based methods, were of borderline significance. Though additional molecular validations are required, 6 of the 16 most promising genes are biologically plausible with physiological connections to BP regulation.

Leukocyte telomere length and coronary artery calcium

Patients with histories of myocardial infarction display shortened leukocyte telomere length (LTL), but conflicting findings have been reported on the relation between LTL and subclinical coronary artery atherosclerosis, as expressed by coronary artery calcium (CAC). The aim of this study was to examine the relation between LTL, measured by Southern blots, and CAC in 3,169 participants in the National Heart, Lung, and Blood Institute Family Heart Study. Participants consisted of 2,556 whites, 613 blacks, 1,790 women, and 1,379 men. The odds of having CAC ≥100 for the shortest LTL tertile versus the longest LTL tertile were 1.95 (95% confidence interval [CI] 1.28 to 3.16) in white men and 1.76 (95% CI 1.18 to 2.45) in white women, after adjusting for multiple covariates of CAC. The corresponding odds ratios for blacks were 1.53 (95% CI 0.67 to 3.50) and 0.87 (95% CI 0.37 to 2.00). Significance levels of tests for trend across LTL tertiles were p = 0.002 in white men, p = 0.006 in white women, p = 0.32 in black men, and p = 0.74 in black women. The associations, or lack of associations, were independent of C-reactive protein levels and other risk factors for CAC. As previously shown in other studies, whites displayed shorter LTLs than blacks (p <0.0001). In conclusion, the higher the coronary artery atherosclerotic burden in whites, the shorter the LTL. This LTL-atherosclerosis connection is not found in blacks. The mechanisms for the racial difference in LTL, CAC, and their interrelations do not seem to be related to inflammation and merit further research.

Admixture mapping of coronary artery calcification in African Americans from the NHLBI family heart study

Background

Coronary artery calcification (CAC) is an imaging biomarker of coronary atherosclerosis. In European Americans, genome-wide association studies (GWAS) have identified several regions associated with coronary artery disease. However, few large studies have been conducted in African Americans. The largest meta-analysis of CAC in African Americans failed to identify genome-wide significant variants despite being powered to detect effects comparable to effects identified in European Americans. Because CAC is different in prevalence and severity in African Americans and European Americans, admixture mapping is a useful approach to identify loci missed by GWAS.

Results

We applied admixture mapping to the African American cohort of the Family Heart Study and identified one genome-wide significant region on chromosome 12 and three potential regions on chromosomes 6, 15, and 19 that are associated with CAC. Follow-up studies using previously reported GWAS meta-analysis data suggest that the regions identified on chromosome 6 and 15 contain variants that are possibly associated with CAC. The associated region on chromosome 6 contains the gene for BMP-6, which is expressed in vascular calcific lesions.

Conclusions

Our results suggest that admixture mapping can be a useful hypothesis-generating tool to identify genomic regions that contribute to complex diseases in genetically admixed populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0196-x) contains supplementary material, which is available to authorized users.

PCSK9 variation and association with blood pressure in African Americans: preliminary findings from the HyperGEN and REGARDS studies

Proprotein convertase subtilisin/kexin type 9 (encoded by PCSK9) plays a well-known role in the regulation of low-density lipoprotein (LDL) receptors, and an inhibitor of this enzyme is a promising new therapeutic for hyperlipidemia. Recently, animal and human studies also implicate PCSK9 genetic variation in the regulation of blood pressure. The goal of this study was to examine if common and rare polymorphisms in PCSK9 are associated with blood pressure in an African-American population at high risk for cardiovascular disease. Using genomic data assayed on the Affymetrix 6.0 array (n = 1199) and the Illumina HumanExome Beadchip (n = 1966) from the Hypertension Genetic Epidemiology Network (HyperGEN), we tested the association of PCSK9 polymorphisms with blood pressure. We used linear mixed models and the sequence kernel association test (SKAT) to assess the association of 31 common and 19 rare variants with blood pressure. The models were adjusted for age, sex, center, smoking status, principal components for ancestry and diabetes as fixed effects and family as a random effect. The results showed a marginally significant effect of two genome-wide association study (GWAS) single-nucleotide polymorphisms (SNPs) (rs12048828: β = 1.8, P = 0.05 and rs9730100: β = 1.0, P = 0.05) with diastolic blood pressure (DBP); however these results were not significant after correction for multiple testing. Rare variants were cumulatively associated with DBP (P = 0.04), an effect that was strengthened by restriction to non-synonymous or stop-gain SNPs (P = 0.02). While gene-based results for DBP did not replicate (P = 0.36), we found an association with SBP (P = 0.04) in the Reasons for Geographic And Racial Differences in Stroke study (REGARDS). The findings here suggest rare variants in PCSK9 may influence blood pressure among African Americans, laying the ground work for further validation studies.

Diastolic wall strain: a simple marker of abnormal cardiac mechanics

BACKGROUND

Diastolic wall strain (DWS), defined using posterior wall thickness (PWT) measurements from standard echocardiographic images (DWS = [PWT(systole)-PWT(diastole)]/PWT(systole)), has been proposed as a marker of left ventricular (LV) diastolic stiffness. However, the equation for DWS is closely related to systolic radial strain, and whether DWS is associated with abnormal cardiac mechanics (reduced systolic strains and diastolic tissue velocities) is unknown. We sought to determine the relationship between DWS and systolic and diastolic cardiac mechanics.

METHODS

We calculated DWS and performed speckle-tracking analysis in a large population- and family-based study (Hypertension Genetic Epidemiology Network [HyperGEN]; N=1907 after excluding patients with ejection fraction [EF] <50% or posterior wall motion abnormalities). We measured global longitudinal, circumferential, and radial strain (GLS, GCS, and GRS, respectively) and early diastolic (e') tissue velocities, and we determined the independent association of DWS with cardiac mechanics using linear mixed effects models to account for relatedness among study participants. We also prospectively performed receiver-operating characteristic (ROC) analysis of DWS for the detection of abnormal cardiac mechanics in a separate, prospective validation study (N=35).

RESULTS

In HyperGEN (age 51 ± 14 years, 59% female, 45% African-American, 57% hypertensive), mean DWS was 0.38 ± 0.05. DWS decreased with increasing comorbidity burden (β-coefficient -0.013 [95% CI -0.015, -0.011]; P<0.0001). DWS was independently associated with GLS, GCS, GRS, and e' velocity (adjusted P<0.05) but not LV chamber compliance (EDV20, P=0.97). On prospective speckle-tracking analysis, DWS correlated well with GLS, GCS, and GRS (R=0.61, 0.57, and 0.73, respectively; P<0.001 for all comparisons). C-statistics for DWS as a diagnostic test for abnormal GLS, GCS, and GRS were: 0.78, 0.79, and 0.84, respectively.

CONCLUSIONS

DWS, a simple parameter than can be calculated from routine 2D echocardiography, is closely associated with systolic strain parameters and early diastolic (e') tissue velocities but not LV chamber compliance.

Social oral epidemi(olog)(2) y where next: one small step or one giant leap?

Since the early 1990s, there has been heated debate critically reflecting on social epidemiology. Yet, very little of this debate has reached oral epidemiology. This is no more noticeable than in the field of oral health inequalities. One of the significant achievements of social oral epidemiology has been the persistent documentation of social patterning of oral disease. Nevertheless, where social oral epidemiology has fallen down is going beyond description to explaining these patterns. Thinking how and in what way things happen, not just in relation to oral health inequalities but also more broadly, requires a more creative approach which links to scholarship outside of dentistry, including the work from critical epidemiologists to that within the social sciences. The aim of this review study is to provide a critical commentary on key aspects of more general epidemiological debates in order to inform and develop social oral epidemiology theory and methodology. In the first section, 'Where are we now?', six key debates are reflected upon: (i) analysis of variance versus analysis of causes, (ii) the fallacy of independent effects, (iii) black box thinking, (iv) theory and the understanding of mechanisms, (v) individualization of risk and (vi) the meaning of 'social'. In the second section, 'Where to next?' we draw on a number of fundamental issues from within the social science literature in order to highlight possible channels of future inquiry. Our overriding goal throughout is to facilitate a critical engagement in order to improve understanding and generate knowledge in relation to population oral health.

Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study

Background

Comorbidities are common in heart failure (HF), and the number of comorbidities has been associated with poor outcomes in HF patients. However, little is known about the effect of multiple comorbidities on cardiac mechanics, which could impact the pathogenesis of HF. We sought to determine the relationship between comorbidity burden and adverse cardiac mechanics.

Methods and Results

We performed speckle‐tracking analysis on echocardiograms from the HyperGEN study (n=2150). Global longitudinal, circumferential, and radial strain, and early diastolic (e') tissue velocities were measured. We evaluated the association between comorbidity number and cardiac mechanics using linear mixed effects models to account for relatedness among subjects. The mean age was 51±14 years, 58% were female, and 47% were African American. Dyslipidemia and hypertension were the most common comorbidities (61% and 58%, respectively). After adjusting for left ventricular (LV) mass index, ejection fraction, and several potential confounders, the number of comorbidities remained associated with all indices of cardiac mechanics except global circumferential strain (eg, β=−0.32 [95% CI −0.44, −0.20] per 1‐unit increase in number of comorbidities for global longitudinal strain; β=−0.16 [95% CI −0.20, −0.11] for e' velocity; P≤0.0001 for both comparisons). Results were similar after excluding participants with abnormal LV geometry (P<0.05 for all comparisons).

Conclusions

Higher comorbidity burden is associated with worse cardiac mechanics, even in the presence of normal LV geometry. The deleterious effect of multiple comorbidities on cardiac mechanics may explain both the high comorbidity burden and adverse outcomes in patients who ultimately develop HF.

An empirical comparison of meta-analysis and mega-analysis of individual participant data for identifying gene-environment interactions

For analysis of the main effects of SNPs, meta-analysis of summary results from individual studies has been shown to provide comparable results as "mega-analysis" that jointly analyzes the pooled participant data from the available studies. This fact revolutionized the genetic analysis of complex traits through large GWAS consortia. Investigations of gene-environment (G×E) interactions are on the rise since they can potentially explain a part of the missing heritability and identify individuals at high risk for disease. However, for analysis of gene-environment interactions, it is not known whether these methods yield comparable results. In this empirical study, we report that the results from both methods were largely consistent for all four tests; the standard 1 degree of freedom (df) test of main effect only, the 1 df test of the main effect (in the presence of interaction effect), the 1 df test of the interaction effect, and the joint 2 df test of main and interaction effects. They provided similar effect size and standard error estimates, leading to comparable P-values. The genomic inflation factors and the number of SNPs with various thresholds were also comparable between the two approaches. Mega-analysis is not always feasible especially in very large and diverse consortia since pooling of raw data may be limited by the terms of the informed consent. Our study illustrates that meta-analysis can be an effective approach also for identifying interactions. To our knowledge, this is the first report investigating meta-versus mega-analyses for interactions.

Association of low-grade albuminuria with adverse cardiac mechanics: findings from the hypertension genetic epidemiology network (HyperGEN) study

BACKGROUND

Albuminuria is a marker of endothelial dysfunction and has been associated with adverse cardiovascular outcomes. The reasons for this association are unclear but may be attributable to the relationship between endothelial dysfunction and intrinsic myocardial dysfunction.

METHODS AND RESULTS

In the Hypertension Genetic Epidemiology Network (HyperGEN) Study, a population- and family-based study of hypertension, we examined the relationship between urine albumin-to-creatinine ratio (UACR) and cardiac mechanics (n=1894, all of whom had normal left ventricular ejection fraction and wall motion). We performed speckle-tracking echocardiographic analysis to quantify global longitudinal, circumferential, and radial strain, and early diastolic (e') tissue velocities. We used E/e' ratio as a marker of increased left ventricular filling pressures. We used multivariable-adjusted linear mixed effect models to determine independent associations between UACR and cardiac mechanics. The mean age was 50±14 years, 59% were female, and 46% were black. Comorbidities were increasingly prevalent among higher UACR quartiles. Albuminuria was associated with global longitudinal strain, global circumferential strain, global radial strain, e' velocity, and E/e' ratio on unadjusted analyses. After adjustment for covariates, UACR was independently associated with lower absolute global longitudinal strain (multivariable-adjusted mean global longitudinal strain [95% confidence interval] for UACR Quartile 1 = 15.3 [15.0-15.5]% versus UACR Q4 = 14.6 [14.3-14.9]%, P for trend <0.001) and increased E/e' ratio (Q1 = 25.3 [23.5-27.1] versus Q4 = 29.0 [27.0-31.0], P=0.003). The association between UACR and global longitudinal strain was present even in participants with UACR < 30 mg/g (P<0.001 after multivariable adjustment).

CONCLUSIONS

Albuminuria, even at low levels, is associated with adverse cardiac mechanics and higher E/e' ratio.

Hemodynamic and echocardiographic profiles in African American compared with White offspring of hypertensive parents: the HyperGEN study

BACKGROUND

Alterations in cardiovascular structure and function have been shown to precede the finding of elevated blood pressure.

METHODS

This study is part of the Hypertension Genetic Epidemiologic Network (HyperGEN) in which genetic and environmental determinants of hypertension were investigated in 5 geographical field centers. All nonhypertensive offspring (n = 1,035) were included from the entire HyperGEN study population that consists of 2,225 hypertensive patients and 1,380 nonhypertensive patients who had adequate echocardiographic left ventricular (LV) mass measurements. Participants were compared by self-declared race (African American and white).

RESULTS

Nonhypertensive African American offspring were younger (aged 31 years vs. 38 years), more likely to be female, and had a higher body mass index (BMI) and higher systolic blood pressure (SBP) than their white counterparts. After adjusting for age, sex, SBP, pulse pressure (PP), BMI, diabetes status, and family effects, we observed statistically significant and potentially pathophysiological differences (all with P ≤ 0.001) with greater LV mass/height, relative wall thickness, and posterior wall thickness and with lesser midwall shortening, PP/stroke volume, and (PP/stroke volume)/fat-free body mass.

CONCLUSION

This study shows that ethnic differences in hemodynamic and echocardiographic profiles exist in a large, population-based cohort of nonhypertensive offspring of hypertensive parents.

The role of SNP-loop diuretic interactions in hypertension across ethnic groups in HyperGEN

Blood pressure (BP) is significantly influenced by genetic factors; however, less than 3% of the BP variance has been accounted for by variants identified from genome-wide association studies (GWAS) of primarily European-descent cohorts. Other genetic influences, including gene-environment (GxE) interactions, may explain more of the unexplained variance in BP. African Americans (AA) have a higher prevalence and earlier age of onset of hypertension (HTN) as compared with European Americans (EA); responses to anti-hypertensive drugs vary across race groups. To examine potential interactions between the use of loop diuretics and HTN traits, we analyzed systolic (SBP) and diastolic (DBP) blood BP from 1222 AA and 1231 EA participants in the Hypertension Genetic Epidemiology Network (HyperGEN). Population-specific score tests were used to test associations of SBP and DBP, using a panel of genotyped and imputed single nucleotide polymorphisms (SNPs) for AA (2.9 million SNPs) and EA (2.3 million SNPs). Several promising loci were identified through gene-loop diuretic interactions, although no SNP reached genome-wide significance after adjustment for genomic inflation. In AA, SNPs in or near the genes NUDT12, CHL1, GRIA1, CACNB2, and PYHIN1 were identified for SBP, and SNPs near ID3 were identified for DBP. For EA, promising SNPs for SBP were identified in ESR1 and for DBP in SPATS2L and EYA2. Among these SNPs, none were common across phenotypes or population groups. Biologic plausibility exists for many of the identified genes, suggesting that these are candidate genes for regulation of BP and/or anti-hypertensive drug response. The lack of genome-wide significance is understandable in this small study employing gene-drug interactions. These findings provide a set of prioritized SNPs/candidate genes for future studies in HTN. Studies in more diversified population samples may help identify previously missed variants.

Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity?

BACKGROUND

It has been suggested that the cardiometabolic risk associated with excess adiposity is particularly related to central obesity.

OBJECTIVE

The objective was to compare the associations between cardiometabolic risk of apparently healthy individuals and measures of central obesity [waist circumference (WC)] and overall obesity [body mass index (BMI)].

DESIGN

In this cross-sectional, observational study, 492 subjects (306 women and 303 non-Hispanic whites) were classified by BMI (in kg/m²) as normal weight (BMI <25) or overweight/obese (BMI = 25.0-34.9) and as having an abnormal WC (≥80 cm in women and ≥94 cm in men) or a normal WC (<80 cm in women and <94 cm in men). Measurements were also made of the cardiometabolic risk factors age, systolic blood pressure (SBP), and fasting plasma glucose (FPG), triglyceride, and high-density lipoprotein (HDL)-cholesterol concentrations. Associations among cardiometabolic risk factors and BMI and WC were evaluated with Pearson correlations.

RESULTS

There was a considerable overlap in the normal and abnormal categories of BMI and WC, and ~81% of the subjects had both an abnormal BMI and WC. In women, BMI and WC correlated with SBP (r = 0.30 and 0.19, respectively), FPG (r = 0.25 and 0.22, respectively), triglycerides (r = 0.17 and 0.20, respectively), and HDL cholesterol (r = -0.23 and -0.20, respectively) (P < 0.01 for all). In men, BMI and WC also correlated with SBP (r = 0.22 and 0.22, respectively), FPG (r = 0.22 and 0.25, respectively), triglycerides (r = 0.21 and 0.18, respectively), and HDL cholesterol (r = -0.20 and -0.13, respectively) [P < 0.05 for all, except for the association of WC with HDL cholesterol (P = 0.08)].

CONCLUSIONS

Most individuals with an abnormal BMI also have an abnormal WC. Both indexes of excess adiposity are positively associated with SBP, FPG, and triglycerides and inversely associated with HDL cholesterol.

SORCS1 contributes to the development of renal disease in rats and humans

Many lines of evidence demonstrate that genetic variability contributes to chronic kidney disease susceptibility in humans as well as rodent models. Little progress has been made in discovering causal kidney disease genes in humans mainly due to genetic complexity. Here, we use a minimal congenic mapping strategy in the FHH (fawn hooded hypertensive) rat to identify Sorcs1 as a novel renal disease candidate gene. We investigated the hypothesis that genetic variation in Sorcs1 influences renal disease susceptibility in both rat and human. Sorcs1 is expressed in the kidney, and knocking out this gene in a rat strain with a sensitized genome background produced increased proteinuria. In vitro knockdown of Sorcs1 in proximal tubule cells impaired protein trafficking, suggesting a mechanism for the observed proteinuria in the FHH rat. Since Sorcs1 influences renal function in the rat, we went on to test this gene in humans. We identified associations between single nucleotide polymorphisms in SORCS1 and renal function in large cohorts of European and African ancestry. The experimental data from the rat combined with association results from different ethnic groups indicates a role for SORCS1 in maintaining proper renal function.

Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained

Genome-wide association studies (GWAS) have identified ∼100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1×10⁻⁴ in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

Lipid traits are heritable, but many of the DNA variants that influence lipid levels remain unknown. In a genomic region, more than one variant may affect gene expression or function, and the frequencies of these variants can differ across populations. Genotyping densely spaced variants in individuals with different ancestries may increase the chance of identifying variants that affect gene expression or function. We analyzed high-density genotyped variants for association with TG, HDL-C, and LDL-C in African Americans, East Asians, and Europeans. At several genomic regions, we provide evidence that two or more variants can influence lipid traits; across loci, these additional signals increase the proportion of trait variation that can be explained by genes. At some association signals shared across populations, combining data from individuals of different ancestries narrowed the set of likely functional variants. At PCSK9 and APOA5, the data suggest that different variants influence trait levels in different populations. Variants previously reported to alter gene expression or function frequently exhibited the strongest association at those signals. The multiple signals and population-specific characteristics of the loci described here may be shared by genetic loci for other complex traits.

Partial normalization of components of metabolic syndrome does not influence prevalent echocardiographic abnormalities: the HyperGEN study

BACKGROUND AND AIMS

Metabolic syndrome (MetS) is a complex condition characterized by different phenotypes, according to the combinations of risk factors and is associated with cardiovascular abnormalities. Whether control of MetS components by treatment produces improvement in the associated cardiovascular abnormalities is unknown. We investigated whether partial control of components of MetS was associated with less echocardiographic abnormalities than the complete presentation of MetS based on measured components.

METHODS AND RESULTS

We evaluated markers of echocardiographic preclinical cardiovascular disease in MetS (ATP III) defined by measured components or by history of treatment, in 1421 African-American and 1195 Caucasian non-diabetic HyperGEN participants, without prevalent cardiovascular disease or serum creatinine >2 mg/dL. Of 2616 subjects, 512 subjects had MetS by measured components and 328 by history. Hypertension was found in 16% of participants without MetS, 6% of those with MetS by history and 42% of those with MetS by measured components. Obesity and central fat distribution had similar prevalence in both MetS groups (both p < 0.0001 vs. No-MetS). Blood pressure was similar in MetS by history and No-MetS, and lower than in MetS by measured components (p < 0.0001). LV mass and midwall shortening, left atrial (LA) dimension and LA systolic force were similarly abnormal in both MetS groups (all p < 0.0001 vs. No-MetS) without difference between them.

CONCLUSIONS

There is a little impact of control by treatment of single components of MetS (namely hypertension) on echocardiographic abnormalities. Lower blood pressure in participants with MetS by history was not associated with substantially reduced alterations in cardiac geometry and function.

Copy number variations associated with obesity-related traits in African Americans: a joint analysis between GENOA and HyperGEN

Obesity is a highly heritable trait and a growing public health problem. African Americans (AAs) are a genetically diverse, yet understudied population with a high prevalence of obesity (BMI >30 kg/m(2)). Recent studies based upon single-nucleotide polymorphisms (SNPs) have identified genetic markers associated with obesity. However, a large proportion of the heritability of obesity remains unexplained. Copy number variation (CNV) has been cited as a possible source of missing heritability in common diseases such as obesity. We conducted a CNV genome-wide association study of BMI in two African-American cohorts from Genetic Epidemiology Network of Arteriopathy (GENOA) and Hypertension Genetic Epidemiology Network (HyperGEN). We performed independent and identical association analyses in each study, then combined the results in a meta-analysis. We identified three CNVs associated with BMI, obesity, and other obesity-related traits after adjusting for multiple testing. These CNVs overlap the PARK2, GYPA, and SGCZ genes. Our results suggest that CNV may play a role in the etiology of obesity in AAs.

Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans

Leukocyte telomere length (LTL) is associated with a number of common age-related diseases and is a heritable trait. Previous genome-wide association studies (GWASs) identified two loci on chromosomes 3q26.2 (TERC) and 10q24.33 (OBFC1) that are associated with the inter-individual LTL variation. We performed a meta-analysis of 9190 individuals from six independent GWAS and validated our findings in 2226 individuals from four additional studies. We confirmed previously reported associations with OBFC1 (rs9419958 P = 9.1 × 10⁻¹¹) and with the telomerase RNA component TERC (rs1317082, P = 1.1 × 10⁻⁸). We also identified two novel genomic regions associated with LTL variation that map near a conserved telomere maintenance complex component 1 (CTC1; rs3027234, P = 3.6 × 10⁻⁸) on chromosome17p13.1 and zinc finger protein 676 (ZNF676; rs412658, P = 3.3 × 10⁻⁸) on 19p12. The minor allele of rs3027234 was associated with both shorter LTL and lower expression of CTC1. Our findings are consistent with the recent observations that point mutations in CTC1 cause short telomeres in both Arabidopsis and humans affected by a rare Mendelian syndrome. Overall, our results provide novel insights into the genetic architecture of inter-individual LTL variation in the general population.

Genotype imputation for African Americans using data from HapMap phase II versus 1000 genomes projects

Genotype imputation provides imputation of untyped single nucleotide polymorphisms (SNPs) that are present on a reference panel such as those from the HapMap Project. It is popular for increasing statistical power and comparing results across studies using different platforms. Imputation for African American populations is challenging because their linkage disequilibrium blocks are shorter and also because no ideal reference panel is available due to admixture. In this paper, we evaluated three imputation strategies for African Americans. The intersection strategy used a combined panel consisting of SNPs polymorphic in both CEU and YRI. The union strategy used a panel consisting of SNPs polymorphic in either CEU or YRI. The merge strategy merged results from two separate imputations, one using CEU and the other using YRI. Because recent investigators are increasingly using the data from the 1000 Genomes (1KG) Project for genotype imputation, we evaluated both 1KG-based imputations and HapMap-based imputations. We used 23,707 SNPs from chromosomes 21 and 22 on Affymetrix SNP Array 6.0 genotyped for 1,075 HyperGEN African Americans. We found that 1KG-based imputations provided a substantially larger number of variants than HapMap-based imputations, about three times as many common variants and eight times as many rare and low-frequency variants. This higher yield is expected because the 1KG panel includes more SNPs. Accuracy rates using 1KG data were slightly lower than those using HapMap data before filtering, but slightly higher after filtering. The union strategy provided the highest imputation yield with next highest accuracy. The intersection strategy provided the lowest imputation yield but the highest accuracy. The merge strategy provided the lowest imputation accuracy. We observed that SNPs polymorphic only in CEU had much lower accuracy, reducing the accuracy of the union strategy. Our findings suggest that 1KG-based imputations can facilitate discovery of significant associations for SNPs across the whole MAF spectrum. Because the 1KG Project is still under way, we expect that later versions will provide better imputation performance.

Three ontologies to define phenotype measurement data

BACKGROUND

There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol.

RESULTS

Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository.

CONCLUSION

An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.

Whole-exome sequencing and an iPSC-derived cardiomyocyte model provides a powerful platform for gene discovery in left ventricular hypertrophy

Rationale: Left ventricular hypertrophy (LVH) is a heritable predictor of cardiovascular disease, particularly in blacks. Objective: Determine the feasibility of combining evidence from two distinct but complementary experimental approaches to identify novel genetic predictors of increased LV mass. Methods: Whole-exome sequencing (WES) was conducted in seven African-American sibling trios ascertained on high average familial LV mass indexed to height (LVMHT) using Illumina HiSeq technology. Identified missense or nonsense (MS/NS) mutations were examined for association with LVMHT using linear mixed models adjusted for age, sex, body weight, and familial relationship. To functionally assess WES findings, human induced pluripotent stem cell-derived cardiomyocytes (induced pluripotent stem cell-CM) were stimulated to induce hypertrophy; mRNA sequencing (RNA-seq) was used to determine gene expression differences associated with hypertrophy onset. Statistically significant findings under both experimental approaches identified LVH candidate genes. Candidate genes were further prioritized by seven supportive criteria that included additional association tests (two criteria), regional linkage evidence in the larger HyperGEN cohort (one criterion), and publically available gene and variant based annotations (four criteria). Results: WES reads covered 91% of the target capture region (of size 37.2 MB) with an average coverage of 65×. WES identified 31,426 MS/NS mutations among the 21 individuals. A total of 295 MS/NS variants in 265 genes were associated with LVMHT with q-value <0.25. Of the 265 WES genes, 44 were differentially expressed (P < 0.05) in hypertrophied cells. Among the 44 candidate genes identified, 5, including HLA-B, HTT, MTSS1, SLC5A12, and THBS1, met 3 of 7 supporting criteria. THBS1 encodes an adhesive glycoprotein that promotes matrix preservation in pressure-overload LVH. THBS1 gene expression was 34% higher in hypertrophied cells (P = 0.0003) and a predicted conserved and damaging NS variant in exon 13 (A2099G) was significantly associated with LVHMT (P = 4 × 10⁻⁶). Conclusion: Combining evidence from cutting-edge genetic and cellular experiments can enable identification of novel LVH risk loci.

A variant upstream of the CDH13 adiponectin receptor gene and metabolic syndrome in Swedes

Metabolic syndrome (MetS) constitutes a worldwide epidemic burst accounting for billions of cardiovascular disease events and deaths. The genetic basis of MetS is largely unknown. The rs11646213 T → A polymorphism maps at 16q23.3 upstream of the CDH13 gene codifying for cadherin-13 (also known as T-cadherin or H-cadherin), which is considered a vascular adiponectin receptor. This and other single-nucleotide polymorphisms have been associated with hypertension and adiponectin level in separate studies. The aim of the present study was to evaluate the effect of the CDH13 rs11646213 T → A polymorphism on individual components of MetS and on MetS. The polymorphism was genotyped in the cardiovascular cohort of the Malmö Diet and Cancer Study (n = 4,942) and successively in the Malmö Preventive Project (n = 17,675) cohort at baseline and after an average of 23 years of follow-up (reinvestigation). Four different definitions of MetS were applied to these cohorts. In the cardiovascular arm, CDH13 rs11646213 AA homozygotic women showed a trend toward higher triglycerides and lower high-density lipoprotein cholesterol and presented a higher MetS score (composite sum of MetS phenotypes). MetS (Adult Treatment Panel III definition) was more prevalent in AA homozygotic women compared to T-carriers, a result confirmed in the Malmö Preventive Project cohort at baseline and at reinvestigation with an increased risk from 19% to 45% in AA homozygotic women. In conclusion, the CDH13 rs11646213 T > A polymorphism was consistently associated with MetS in Swedish women recruited in 2 large cohorts. In light of the role of cadherin-13 as a vascular receptor for adiponectin, our study supports the genetic basis for the role of adiponectin in MetS pathogenesis.

Variants on chromosome 6p22.3 associated with blood pressure in the HyperGEN study: follow-up of FBPP quantitative trait loci

BACKGROUND

A recent meta-analysis of genome-wide linkage scans of blood pressure (BP) in the large (N = 13,044) Family Blood Pressure Program (FBPP) identified five quantitative trait loci (QTLs) on chromosomes 6, 8, 20, and 21. We conducted follow-up fine mapping studies in 1,251 African (AA) and 1,254 European American (EA) participants of the Hypertension Genetic Epidemiology Network (HyperGEN).

METHODS

Ethnic-specific linear mixed effects models were used to test associations of BP with genotyped and imputed single nucleotide polymorphisms (SNPs) contained in the logarithm of odds (LOD) score ≥2 interval under each of the QTL peaks. We used multipoint variance components models to perform linkage analysis conditional on each significant SNP in the QTL region to see if the SNP explained the QTL.

RESULTS

Three intergenic SNPs (rs898164, rs2876587, rs6935795) on chromosome 6p22.3 were significantly associated with pulse pressure (using appropriate Bonferroni correction). Conditioning on the significant SNPs reduced the chromosome 6 QTL linkage evidence by 14-30%. Both AAs and EAs exhibited suggestive associations between BP and intronic SNPs on chromosomes 8q24.12 (genes: OPG in AAs, SAMD12 in EAs), 20q13.12 (genes: SLC13A3 in AAs, SLC12A5 in EAs), and 21q21.1 (genes: C21orf34 in AAs, BC039377 in EAs).

CONCLUSIONS

Significant associations with common SNPs explained less than 1/3 of the QTL evidence. Our results cannot refute the hypothesis that rare variants account for most of the statistical evidence for the FBPP linkage peaks. Whole genome resequencing can identify the variants driving the linkage peaks and genome-wide association study (GWAS) hits thereby spurring investigations to deepen our understanding of hypertension pathophysiology.