Effects of Rare and Common Blood Pressure Gene Variants on Essential HypertensionNovelty and Significance
Results From the Family Blood Pressure Program, CLUE, and Atherosclerosis Risk in Communities Studies
Rationale: Hypertension affects ≈30% of adults in industrialized countries and is the major risk factor for cardiovascular disease.
Objective: We sought to study the genetic effect of coding and conserved noncoding variants in syndromic hypertension genes on systolic blood pressure (BP) and diastolic BP to assess their overall impact on essential hypertension.
Methods and Results: We resequenced 11 genes (AGT, CYP11B1, CYP17A1, HSD11B2, NR3C1, NR3C2, SCNN1A, SCNN1B, SCNN1G, WNK1, and WNK4) in 560 European American (EA) and African American ancestry GenNet participants with extreme systolic BP. We investigated genetic associations of 2535 variants with BP in 19997 EAs and in 6069 African Americans in 3 types of analyses. First, we studied the combined effects of all variants in GenNet. Second, we studied 1000 Genomes imputed polymorphic variants in 9747 EA and 3207 African American Atherosclerosis Risk in Communities subjects. Finally, we genotyped 37 missense and common noncoding variants in 6591 EAs and in 6521 individuals (3659 EA/2862 African American) from the CLUE and Family Blood Pressure Program studies, respectively. None of the variants individually reached significant false-discovery rates ≤0.05 for systolic BP and diastolic BP. However, on pooling all coding and noncoding variants, we identified at least 5 loci (AGT, CYP11B1, NR3C2, SCNN1G, and WNK1) with higher association at evolutionary conserved sites.
Conclusions: Both rare and common variants at these genes affect BP in the general population with modest effects sizes (<0.05 standard deviation units), and much larger sample sizes are required to assess the impact of individual genes. Collectively, conserved noncoding variants affect BP to a greater extent than missense mutations.
Essential hypertension (EH), or hypertension (HTN) not ascribable to secondary causes, affects ≈30% of adults in industrialized countries and is largely of unknown molecular pathogenesis.1 Although measured blood pressure (BP) is moderately heritable (heritability ≈40%–60%),2 it also varies with age, body mass index, diet, stress level, and sympathetic tone. The major physiological hypothesis for BP variation is the Guyton hypothesis, which indicates that variation in kidney fluid regulation, depending on salt clearance,3 leads to BP differences. The identification of numerous Mendelian syndromic hypotension and HTN genes is proof of the Guyton hypothesis since the encoded proteins regulate renal salt–water balance.4
Recently, there has been increasing effort to systematically study common polymorphisms in interindividual variation in HTN risk. Two large genome-wide association studies, from the Cohorts for Heart and Aging Research in Genetic Epidemiology5 and Global Blood Pressure Genetics6 consortia, and a recent meta-analysis from the International Consortium for Blood Pressure (ICBP) genome-wide association study,7 have made progress in this direction with the identification of 29 loci explaining 1% to 2% of systolic BP (SBP) and diastolic BP (DBP) in >200,000 subjects of European American (EA) ancestry. The identified variants in ICBP also showed effects in individuals of East Asian (N=29719), South Asian (N=23977), and African ancestries (N=19775). Other analogous studies of individuals of Asian (22900 subjects) and African (9608 subjects) ancestries have additionally identified 5 SBP and 3 DBP loci.8–12 Nevertheless, the precise genes at each mapped locus, their functions in BP regulation, and how functional variants in them lead to physiological variation in BP all remain unknown and are major challenges. We undertook the alternative approach of trying to assess how sequence variants in known Mendelian syndromic hypertension genes affect BP variation in multiple large cohorts.
For the detection of gene variants, we chose as exemplars angiotensinogen (AGT), with a known effect on EH and renal tubular dysgenesis, and 10 additional genes (CYP11B1, CYP17A1, HSD11B2, NR3C1, NR3C2, SCNN1A, SCNN1B, SCNN1G, WNK1, WNK4; Online Table I) known to harbor loss-of-function or gain-of-function or dominant-negative mutations leading to a variety of autosomal dominant or recessive HTN syndromes (Online Table II). The disease-associated variants and mutations at these genes are all rare, except for those at AGT. Thus, we enquired whether any sequence variants within these genes in the general population were associated with EH, ie, did these genes play a larger role in elevating BP in the general population and lead to EH?
We first determined the DNA sequences of these genes to identify genetic variants at coding sequences, intron–exon junctions, and all highly conserved noncoding elements in the vicinity of each gene. Our sequenced sample included 560 individuals from the GenNet network of the Family Blood Pressure Program (FBPP),13 equally divided into 8 strata comprising EA and African American ancestry, males and females, and the highest (top) and lowest (bottom) 70 individuals for each stratum, corresponding to ≈15% sex-adjusted, age-adjusted, and body mass index–adjusted SBP thresholds. The 2535 identified variants were studied in 3 ways. We first examined the effect of all identified variants, missense, and noncoding variants, pooled as a class, in 280 EA and 280 African American of our original GenNet samples by weighting them according to their evolutionary conservation or predicted deleterious effect. We then studied all polymorphisms (minor allele frequency [MAF] ≥1%) and, finally, a selected group of coding variants predicted to be deleterious based on protein sequence conservation and the nature of the chemical substitution. These 2 classes of variants were studied for genetic association with SBP and DBP by imputation in the population-based cohort Atherosclerosis Risk in Communities (ARIC) (9747 EAs and 3207 African Americans) using first visit measurements and by direct genotyping in the population-based CLUE (6591 EA subjects) cohort and the family-based FBPP (3659 EA and 2862 African American subjects) study. Our general conclusion is that despite not finding statistical significance at individual variants, these genes, in aggregate, do show statistically significant effects on BP. In addition, we conclude that rare coding variants have genetic effects of the same magnitude as that of common noncoding polymorphisms and that the contribution of noncoding variants is not negligible. Finally, assessing the contribution of individual genes will require much larger sample sizes.
An expanded Methods section is available in the Online Data Supplement.
Cohorts and Samples Studied
Family Blood Pressure Program
We chose 560 independent samples, equally divided between males and females and EA and African American ancestry, from the total of 705 EA and 521 African American unrelated GenNet subjects of FBPP.13 We selected 70 individuals with the most extreme SBP residuals (top/bottom levels). Specifically, we selected 560 GenNet subjects, whose SBP residuals lay below the ≈15th %tile (corresponding to residuals of −50.02 to −5.29 mmHg) or above the ≈85th percentile (corresponding to residuals of 2.47–85.65 mmHg) (Figure 1).
Atherosclerosis Risk in Communities
For the polymorphic variant study, we used genome-wide association study data from the ARIC14 samples to study their association with BP at visit 1 for 9747 EAs and 3207 African Americans (Online Table III).
For the rare putatively deleterious variants association studies, we had access to and genotyped DNA samples from 7065 Odyssey subjects in the CLUE study.15
DNA Sequencing and Genotyping Methods
For each gene, we considered all exons ±50 nt flanking sequence, 2 kb upstream or downstream of the gene, and mammalian-conserved noncoding elements within 5 kb of the gene (>70% sequence identity across >100 bp in human–mouse and human–rat alignments or logarithm of odds >50 from the 17-species alignment from the University of California at Santa Cruz Genome Browser) for Sanger resequencing (Online Methods). We designed primers for the Sequenom pooled assay of 15 nonsynonymous deleterious variants from Resequencing and Genotyping Services (RS&G; this study) and 26 replicated common variants from ICBP7 using the MassArray Assay Design Software; we could develop successful assays for 11 and 26 variants, respectively, and a 27th variant was genotyped using Taqman. We followed the standard genotyping protocols for Sequenom16 and Taqman.17
For our analyses, we adjusted the BP measurements for potential medication effects by adding 15/10 mmHg to SBP/DBP in individuals who were using antihypertensive drugs at the time of ascertainment.18 The residuals of SBP/DBP were adjusted for age, age-squared, sex, and body mass index, separately, for the EAs and African Americans.
The significance level was set as false-discovery rates ≤0.05. We analyzed the overall effects of our 2535 variants by collapsing (pooling) them in 2 ways: weighting all variants by their conservation (phyloP) score and weighting only missense variants by their predicted deleterious effect (PolyPhen2 scores) for each gene in EAs and African Americans separately, followed by pooling across all 11 genes using the Madsen and Browning allele frequency weighted sum method in combination with conservation or deleterious effects as described by Price et al.19
We used BEAGLE20 (version 3.3) to impute RS&G and 1000 Genomes polymorphic variants (MAF ≥1%) within 10-kb boundaries of the 11 gene regions in ARIC using 1000 Genomes European (EUR)/African (AFR) reference panels for EAs and African Americans. Variants with imputation score r2≤0.3 were removed before association analysis with PLINK21 for SBP and DBP at visit 1. For genetic association analysis of individual rare putatively deleterious variants, we used MERLIN22 (-assoc) in CLUE and FBPP.
We assumed independent sampling, additive genetic model, and that BP continuous trait increased from a 2-component normal mixture distribution in which 1 component corresponded to the variant allele whose genetic effect was shifted by s standard deviation units with respect to the other component corresponding to the reference allele. Their variances are assumed to be the same and equal to 1, and their mixing proportions reflect the allele frequencies q and p (=1–q), respectively. The power to detect the difference in the means of the 2 components is as follows:
where Φ is the standard normal cumulative distribution function of sample size n, is the quantile of the standard normal distribution at α significance level. The second summand is very small and can be ignored.
DNA Sequencing and Variant Detection
For each individual, we obtained, on average, 150448 bp of DNA sequence, of which 47091 bp (31%) was coding and 103357 bp (69%) was conserved noncoding. Across all 560 individuals, this led to a dataset comprising ≈85 Mb with a variant distribution as shown in Table 1. A variable pattern of genetic variation is observed across the 11 genes. The data suggest modest variation in the numbers of single nucleotide variants across the 11 genes in comparison with the expectation based on the length of sequence scanned (P=0.044 in EAs; P=1.7×10−4 in African Americans), but this is highly significant for the total number of coding and conserved noncoding variants (P=3.15×10−62 in EAs; P=7.22×10−57 in African Americans). Some of this difference in statistical significance is likely attributable to the absolute smaller numbers of coding than total variants. Nevertheless, these results suggest significant variation in the evolutionary constraint on conserved noncoding and intronic sequences as well. Notable outliers among these genes are CYP11B1 and NR3C1 with significant excess and deficiency of coding variants, respectively. Among all variants, 7 genes are outliers, with NR3C2, SCNN1B, SCNN1G, and WNK1 supporting a significant increase and CYP17A1, NR3C1, and WNK4 supporting a significant decrease in variation as compared with the length of the sequence scanned. A similar overall trend is observed with insertions and deletions in which the total number of variants is nonrandom across genes with respect to the length scanned (P=1.78×10−6 in EAs; P=1.99×10−8 in African Americans). These data on variation suggest the great variability in the observed numbers and types of variants across genes and coding vs noncoding segments of each gene, regardless of the guanine-cytosine content of the genes. This implies that because the individuals sequenced harbor a mixture of functionally relevant and neutral variants and, consequently, phenotypically relevant and irrelevant variants, the detection of genetic effects at a specific gene is dependent on factors beyond sample size. In other words, despite our extensive sequencing, we might not have sampled functional variants equally across each gene.
Global Tests of BP Effects
We first examined the distribution of variants by their allele frequency class and their residual SBP phenotype, as affected by their membership in only the top BP class or only the bottom class vs those present in both classes. This analysis constitutes a global test of association between SBP and the entire set of genetic variants we identified (Table 2). Overall, there is no enrichment of variants at either the higher or the lower SBP threshold (265 vs 291, P=0.27 for EAs; 432 vs 378, P=0.06 for African Americans). Interestingly, only a borderline significance was observed at the protein sequence level where nonsynonymous variants were slightly enriched at the extremes (P=0.049 for EAs; P=0.021 for African Americans). When this pattern was tested across the 11 genes, the results were highly significant across the 3 BP classes (P=5.0×10−8 for EAs; P=6.4×10−3 for African Americans) but not for the bottom vs top comparisons (P=0.25 for EAs; P=0.07 for African Americans), suggesting that either the effect is weak or the trend is attributable to the differences in numbers of variants across genes, as demonstrated previously. These results are not unexpected because the majority of variants we detected, even at bona fide BP genes, are not related to the BP phenotype. If there is an effect, then it must be relegated to only a few variants; the small over representation for nonsynonymous sites may arise from a larger fraction of these variants affecting BP.
To test this last hypothesis, we performed an alternate analysis of the association effect of all variants on BP by weighting each variant by its presumed functional effect. Because we sequenced both coding and conserved noncoding elements, our first analysis of all variants used conservation (phyloP) score as weights; our second analysis focused on nonsynonymous variants only, which are generally more conserved, and used PolyPhen2 scores, an index of deleterious effect, as weights. All analyses were performed using the Madsen-Browning weighted sum method from the pooling test by Price et al19 (Table 3). Interestingly, the class of all variants (1205 in EAs and 1842 in African Americans) was significantly associated with SBP in both populations (P=0.008 in EAs; P=0.004 in African Americans) but not with DBP in either (P=0.073 in EAs; P=0.189 in African Americans). When the analyses were restricted to missense alleles, none of the associations was significant because they were based on only 39 and 70 variants in EAs and African Americans, respectively. Individual genes showed considerable variation but, being based on few variants, few of these tests were significant. However, for the test of all variants in individual genes, 5 of the 11 genes were statistically significant (false-discovery rates ≤0.05) for SBP: AGT (P=0.009), CYP11B1 (P=0.005), NR3C2 (P=4×10−5), and SCNN1G (P=3.5×10−4) in EAs, and WNK1 (P=0.004) in African Americans. When we studied noncoding variants separately and also weighted them by conservation phyloP scores, the effect in individual gene locus was even more significant with 2 additional loci: CYP17A1 (P=0.026) and HSD11B2 (P=0.010), with false-discovery rates ≤0.05 (Online Table IV).
Association Studies of Common Variants
To further elaborate the effects of individual common variants, we tested genetic association in EA and African American subjects in 2 general population samples (ARIC: N=12954; CLUE: N=6591); Online Table III provides summaries of demographic and BP-related phenotypic data for these samples. Our sequencing screen identified 564 of 1277 variants in EAs and 872 of 1972 variants in African Americans that were polymorphic (MAF ≥1%). Although these variants could be directly tested for association, statistical power would be greater if we could additionally use imputed variants. We used data from the 1000 Genomes Project,23 together with our RS&G data and ARIC Affymetrix 6.0 marker data,5 to perform imputation at the 11 loci (Online Table I) using the computer program BEAGLE,20 for 9747 EAs and 3207 African Americans in ARIC. As a check of the utility of sequencing in study samples vs imputation from reference panels, we compared, for the sequenced targets only, the numbers of variants in RS&G only, in 1000 Genomes only, and those shared by both for each locus and in aggregate (Online Figure I). Despite locus-specific variation, the overall pattern is clear: there were more variants identified by RS&G and 1000 Genomes (1605 variants found in RS&G only, 567 variants in 1000 Genomes only, and 858 in both). Although there are numerous systematic technical differences between RS&G (Sanger technology, comprehensive coverage, alignment to sequenced portion only) and 1000 Genomes (next-generation sequencing, low coverage, alignment to whole genome), and because the combined sample size is larger, we believe that the use of BP-enriched samples in RS&G (280 EAs and 280 African Americans), as compared with the random samples in 1000 Genomes (379 EUR and 246 AFR), is a reason that there was a larger number of variants.
Two of the 11 genes, namely HSD11B2 and WNK4, have unusual MAF distributions in 1000 Genomes, with many variants <10%, few >40%, and none at intermediate frequencies. This suggests that the variation patterns in these 2 regions may result in improper imputation; therefore, they were not included in our association analyses. There was a remainder of 1821 EUR variants and 2534 AFR variants in the combined panel of RS&G and 1000 Genomes to be imputed into ARIC. After imputation, we excluded variants with imputation score r2<0.3, leaving 731 variants in EUR and 827 in AFR. We performed genetic association studies in ARIC for visit 1 SBP and DBP using 727 EA and 807 African American variants in 9 gene regions. Only 6 highly correlated variants in CYP17A1 reached statistical significance (false-discovery rates ≤0.05) in EAs (N=9747) and none in African Americans (N=3207; Online Table V). All 6 positive variants have been previously identified in EA genome-wide association study5,6 and were not unique to RS&G. Thus, despite the CYP17A1 association, common RS&G variants did not contribute to this finding.
These results could be attributable to an absence of common causal coding variation in the 9 genes studied or low statistical power. To test this aspect directly, we performed a positive control experiment and genotyped 27 replicated common variants known to be associated with BP5–7 in available samples from highly selected families that are expected to be enriched for BP variants (GenNet and HyperGEN networks of FBPP: N=6521; CLUE: N=6591; see Methods and Online Table III). The results, taken together (Online Table VI), show significant associations at only ATP2B1 and FES in the EAs only. This clearly demonstrates, using true positive single nucleotide variants, the low statistical power (empirically, 2/27 or 7%) of these noncoding variants in ≈6500 EA subjects in CLUE and even lower power in the ≈3000 EA/African American subjects in FBPP. Admittedly, the average allelic effects of these 27 variants in the ICBP study are ≈0.6 mmHg and ≈0.4 mmHg for SBP and DBP, respectively.7 Given that the population phenotypic variances for SBP and DBP are ≈16 mmHg and ≈10 mmHg, respectively, these average effect sizes are ≈0.04 σ for both SBP and DBP, where the effect is measured in units of the phenotypic standard deviation (σ). Comparing these results with power calculations (Online Table VIII) at the CLUE and FBPP sample sizes and allele frequencies and various assumed effect sizes suggests that these noncoding polymorphisms have statistical power <33 and <10 in CLUE and FBPP subjects, respectively (Online Table VII).
Association Studies of Rare Variants
As demonstrated, the totality of all variants identified by sequencing, of which the majority were rare (Table 2), showed significant association with SBP in both EAs and African Americans (Table 3), but effects at individual genes were not well-resolved. Consequently, for rare variant analysis, we first attempted to assess their functional impact because they engender low statistical power by virtue of their rarity; in other words, a higher probability of causality would decrease false-positives. Assessing function is straightforward for coding nonsynonymous variants in which predictions of likely effect are based on protein conservation and the nature of specific substitutions; however, this is tenuous for noncoding variants whose functions are poorly understood. We gauge their impact using evolutionary conservation, although recent advances in the Encyclopedia of DNA Elements project24 may lead to future improvements. Consequently, we restricted attention to 54 EA and 94 African American nonsynonymous variants, of which 26 and 46 variants were singletons and the remaining 29 and 48 variants were present in multiple copies, respectively (Figure 2). It is not surprising that the fraction of novel variants (not in single nucleotide polymorphism database 129) are higher for singleton (88% or 63/72) compared with multiplex variants (34% or 20/58). We predicted whether the nonsynonymous variants were deleterious using the computer programs Sorting Intolerant from Tolerant25 and PolyPhen.26 The fraction of these functional candidate variants, defined as those predicted to be deleterious by both algorithms, was 26% (34 of 130) overall, but it was higher for the singleton (31% or 22/72) than for the multiplex (21% or 12/58) variants because of natural selection. From the total of 15 EA predicted deleterious nonsynonymous variants, we were able to genotype 11 in larger cohorts (Table 4). We genotyped these 11 variants in a sample of 6591 unrelated EA subjects from CLUE and 6521 related individuals (3659 EAs and 2862 African Americans) from FBPP. The characteristics of the genotyped individuals are provided in Online Table III and summary genetic association results in Table 4, with detailed results in Online Table VII. None of the variants shows statistical significance. Of these 11 variants, 7 are rare (MAF 0.01%–0.6%) in both EAs and African Americans; the remaining 4 variants are polymorphic (MAF ≥1%) in either EAs or African Americans. In other words, the infrequency of these variants suggests that they do not appear in phenotypically validated EH subjects and therefore cannot be a major determinant of risk.
The outcome of our analyses is the result of either an absence of a true effect or a small effect at individual single nucleotide variants that we do not have the power to detect. This distinction is important because the expectation is that rare variants (MAF ≤5%) should have much larger effect sizes than common variants and, moreover, we have already demonstrated a cumulative effect of all single nucleotide variants in GenNet (Table 3). We suggest instead that the majority of the effect of rare variants, or any variant for that matter, is small. Thus, the power to detect associations is low unless the variant frequency is >5% or unless the allelic effect is >0.25 σ (Online Table VIII). For polymorphic variants at 1% frequency, the calculated statistical powers are 19% and 55% at sample sizes of 3000 and 7000, respectively, and an allelic effect is >0.25 σ. The paucity of positive results from this study suggests that the true effect size is considerably smaller and probably of the same order of magnitude as those for noncoding polymorphisms (0.05 σ). Published data show that the allelic effect of the positive control rs2681472 in ATP2B1 is ≈0.06 to 0.07σ,5,6 which at an allele frequency of between 15% and 20% and a sample size between 3000 and 7000 has a power between 13% and 40% but in 10000 samples has power >60%. Consequently, rs2681472 is highly significant in ARIC but much less so in CLUE and FBPP.
By studying the role of syndromic HTN genes in BP regulation and EH in nonsyndromic subjects from the general population at the extremes of the corrected SBP residual distribution, we found meager, but not an absence of, evidence of effects at individual rare or common variants at known HTN genes. However, on pooling all variants, we obtained statistically significant association of these same genes with SBP; the much smaller collection of missense variants was nonsignificant. The statistical significance of all elements (coding and conserved noncoding) suggests the low statistical power of testing effects of coding alleles with the sample sizes here and strongly implicates the importance of conserved noncoding variants to interindividual BP variation.
Genetic association studies are important but remain difficult because of the lack of statistical power to definitively identify associations. Statistical power of such studies depend on both the sample size and the population variance explained, with the latter being a function of allelic effect size and its frequency. Thus, low power can stem from the use of inadequate sample sizes given the numerous variants tested, and from the small genetic effects of these variants. In this study, we started with genes that are known to impact BP physiology, and we examined both common and predicted deleterious rare variants within these genes to focus the analyses on variants that are expected to have higher impact on BP. Moreover, enrichment of variants by sequencing BP extremes should have also enriched for causal variants. Additionally, we used a large sample size given the few genes we examined: 19997 EAs (3659 in FBPP, 6591 in CLUE, and 9747 in ARIC), along with 6069 African Americans (2862 in FBPP and 3207 in ARIC). Nevertheless, we did not detect pervasive associations that survived multiple testing correction, although common and rare variants were studied in 2 different populations.
The fundamental question in BP genetics is, what is the expected genetic effect of any functional or causal allele? To understand our results, consider the average allelic effect from other BP studies. We estimated these effects by calculating the median allelic BP effect of each genetic variant identified from 5 groups of alleles: (1) 91 disease-causing mutations in 111 syndromic patients across the 11 genes from the Human Gene Mutation Database (HGMD) with BP values as cited in the published literature; (2) 12 disease-causing mutations from HGMD in 69 GenNet individuals (in 7 of 11 genes; Online Table IX); (3) 2379 single nucleotide variants in all 560 GenNet individuals (in all 11 genes); (4) 11 predicted deleterious mutations we studied in ≈13000 CLUE and FBPP subjects; and (5) 27 validated ICBP variants we studied in ≈13000 CLUE and FBPP subjects (Online Table X). This classification attempts to produce an allelic series from an expected largest-to-smallest effect: we estimated the median effects to be 3.57, 0.73, 0.55, 0.11, and 0.01, respectively, with corresponding standard errors of 0.34, 0.42, 0.02, 0.15, and 0.003. This suggests that although the genes we selected for study do have rare mutations of very large effect (class a, 3.57 σ), these mutations are not observed in the GenNet individuals we sequenced. However, of the previously identified HGMD mutations, we did detect in GenNet (class b) their effect size is considerably (5×) smaller, at 0.73 σ. These mutations are enriched because the background effect of all variants (class c) we identified in GenNet, individuals already selected for SBP extremes, was smaller still, at 0.55 σ. Despite predictions of deleterious effects at the 11 variants (class d) we genotyped in a much larger sample of ≈13000 subjects in FBPP and CLUE, these variants have a smaller effect yet, at 0.11 σ. As a comparator, the replicated genome-wide association study variants (class e) in ≈13000 subjects in FBPP and CLUE had an effect size of 0.01 σ, which is smaller than that of the original ICBP study and likely demonstrates the winner's curse. Many variants in these 5 classes are not present in Exome Variant Server database. For those that are found in Exome Variant Server, the average population frequencies (from Exome Variant Server) are much lower than 5%.27 These results make it clear that for a homeostatically controlled trait like BP, allelic effects in the general population are unlikely to be >0.11 σ even at recognized BP genes. Even more broadly, if all BP allelic effects are <0.25 σ, then for alleles at 1%, 5%, and 10%, statistical power is never >80% unless the numbers of individuals studied are >110000, >22000, and >11000, respectively; the detection is even more difficult for DBP.
Although analyses of individual rare and common variants did not yield significant associations with SBP or DBP, we identified 5 loci that are significantly associated with SBP by pooling all variants in each gene and across all genes. Additionally, 12 variants in 7 genes, from the total of 2535 originally identified, also were present in HGMD as disease-causing mutations (Table 3). Three of these 7 genes (AGT, CYP11B1, and SCNN1G) also are statistically associated with SBP by pooling of all variants. Two additional genes (CYP17A1 and HSD11B2) were found to be statistically associated with SBP by pooling only noncoding elements (Online Table IV). Furthermore, 2 additional loci (NR3C2 and WNK1), not noted in HGMD, were significantly associated with SBP in the pooled variant test. Hence, our results show that at least 5 of the 11 syndromic HTN loci also contribute to BP and EH in the general population, and that conservation (phyloP score) provided greater statistical significance than classifying missense variants by their deleterious effect (PolyPhen2 score). This implies that conservation analysis, based on numerous genome sequences, may be more informative than restricting to only missense variants and their prediction of deleterious effect, at least for complex traits like BP. The underlying reasons for this are that our ability to predict the deleterious effect may be poor for the numerous missense mutations we identified except for the severest alleles, and that variation at noncoding elements is a significant contributor to complex diseases. The recent study by Yang et al,28 who demonstrated the existence of numerous variants at both coding and noncoding elements proximal to genes, is consistent with this view. Consequently, studies of both the exome and the conserved genomic segments in the human genome need to be comprehensively examined in large samples to fully elaborate the contributions to BP physiology and EH.
The authors appreciate the work of and technical help from Dr Mark Rieder (University of Washington, Department of Genome Sciences, Seattle, WA) and Dr Samuel Levy (J. Craig Venter Institute, Rockville, MD) for DNA sequencing in the Resequencing and Genotyping Services. The authors thank the personnel of the CLUE and Family Blood Pressure Program studies for sample selection, and gratefully acknowledge the efforts of Gina Hilton and Joan Ritho for genotyping in the CLUE cohort. The authors thank the staff and participants of the Atherosclerosis Risk in Communities study for their important contributions. The authors used the Human Gene Mutation Database under a license to the Aravinda Chakravarti laboratory at the Johns Hopkins University School of Medicine.
Sources of Funding
This work was supported by grant HL086694 from the National Heart, Lung, and Blood Institute (NHLBI) to A.Chakravarti, and by The Resequencing and Genotyping Service, funded by the NHLBI, who performed sequencing at the University of Washington, Department of Genome Sciences, Seattle, WA, and the J. Craig Venter Institute, Rockville, MD (N01-HV-48194 and N01-HV-48196 to A.Chakravarti). The Atherosclerosis Risk in Communities Study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health (NIH) contract HHSN268200625226C. Infrastructure was partly supported by grant UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research.
In October 2012, the average time from submission to first decision for all original research papers submitted to Circulation Research was 12.5 days.
The online-only Data Supplement is available with this article at http://circres.ahajournals.org/lookup/suppl/doi:10.1161/CIRCRESAHA.112.276725/-/DC1.
Non-standard Abbreviations and Acronyms
- Atherosclerosis Risk in Communities
- blood pressure
- diastolic blood pressure
- European American
- essential hypertension
- Family Blood Pressure Program
- Human Gene Mutation Database
- minor allele frequency
- Resequencing and Genotyping Services
- systolic blood pressure
- single nucleotide variant
- Received June 29, 2012.
- Revision received November 3, 2012.
- Accepted November 12, 2012.
- © 2013 American Heart Association, Inc.
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Novelty and Significance
What Is Known?
Essential hypertension affects ≈30% of adults in industrialized countries but its molecular pathogenesis is largely unknown.
Blood pressure (BP) is a heritable trait with a heritability estimate of ≈40% to 60%. It also is influenced by age, body mass index, diet, stress level, and sympathetic tone.
Mendelian forms of hypotension and hypertension are caused by rare DNA variants that have large impacts on BP.
In addition, a number of common DNA variants have been discovered to impact BP, explaining 1% to 2% of systolic BP and diastolic BP variations in the general population.
What New Information Does This Article Contribute?
Rare variants in genes known to be involved in hypotension or hypertension do not have large effects in the general population.
Conserved noncoding sequences, at these same genes, although lacking precise functional information, contribute significantly to BP variation.
If all genetic effects are small, then large studies (with a minimum of 50000 subjects) are required to obtain meaningful results.
We resequenced the coding and conserved noncoding regions of 11 genes known to be involved in hypertension by focusing on individuals at the extremes of systolic BP. Analyses of common and rare variants at these 11 genes, individually, did not yield significant association with systolic BP or diastolic BP. However, by pooling coding and conserved noncoding elements, and by weighting their genetic contribution by allele frequency and nucleotide conservation, we detected a strong association with BP in at least 5 loci. This analysis suggests that both common and rare variants have small effects (≈0.05 standard deviation unit) on BP. The findings of this study reveal a significant contribution of conserved noncoding elements in genes known to be involved in hypotension or hypertension to BP traits in the general population. Consequently, both the exome and the conserved genomic segments in the human genome need to be comprehensively examined in large samples to allow full elucidation of the genetic contributions to BP.