Genetics of blood pressure and hypertension: the role of rare variation (2024)

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The role of heredity in influencing blood pressure and the risk of hypertension is well established. However, progress in identifying specific genetic variation that contributes to heritability has been very limited. This is despite the completion of the human genome sequence, the development of extraordinary amounts of information on genome sequence variation, and the study of blood pressure heritability in linkage analysis, candidate gene studies, and most recently genome-wide association studies. This article discusses the development of this research and the obstacles we encountered. This work has made it clear that the genetic architecture of blood pressure regulation in the population is unlikely to be shaped by common genetic variation in a discrete set of blood pressure influencing genes. Instead, heredity can be explained by rare variations that have their greatest impact within family trees rather than on the population as a whole. Rare variants in a wide range of genes are likely to be the focus of hypertension genetics in the coming years, and the new strategies that can be used to uncover this genetic variation and the problems we must confront are considered.

Introduction

Blood pressure is a heritable trait, with heritability estimates indicating that 30–70% of the variance in traits is due to genetic variation (1–8). The progress of genetic research to identify the genes that contain this variation and thereby influence blood pressure regulation and the risk of hypertension has reached a new plateau with the publication in the past year of several genetic studies in large populations containing very large numbers of genetic studies have examined. stable genetic markers in an attempt to link individual markers to blood pressure and hypertension (9,10). The application of such genome-wide association studies (GWAS) in populations is a major technical achievement that requires not only large and well-characterized populations, but also the ability to accurately type very large numbers (hundreds of thousands) of single-nucleotide polymorphisms. SNPs) in these individuals. This work has made some progress, but much of this progress has been to test and largely reject the hypothesis that a significant portion of blood pressure heritability is associated with a discrete number of relatively common genetic variants. New insights have been gained, but confusing issues remain. In this respect, the current situation is similar to the results of the first mapping efforts using linkage analysis in pedigrees reported several years ago (2,11–19). It is time to reflect on how research into the genetic basis of high blood pressure has reached its current point, to reflect on the unexplained role of hereditary factors that still seems to persist, and to reflect on the prospects and obstacles to further progress.

The genome sequence and its variation provide the substrate for genetic research into blood pressure

The Human Genome Project was founded in 1990, a rough draft was announced in 2000, and a completed sequence in 2004. This large-scale effort was characterized by extraordinary technical feats, driven by the great potential value that was expected to arise from knowledge of the detailed sequence of the human genome. The completed genome sequence is just one of many resources that made the genome project possible. As knowledge of genome sequence expanded, so did knowledge of sequence variation. Extensive and detailed knowledge of the variation in the human genome sequence has been an important resource for leveraging mapping efforts to identify the genetic variation that contributes to common diseases, including high blood pressure. The HapMap project recognized the value of knowledge of sequence variation and was initiated as an effort to sample the common genetic variation across different world populations (20). Remarkable advances in the efficiency of whole-genome sequencing have led to the 1000 Genomes Project, currently underway, which is collecting DNA samples from a highly diverse range of human subpopulations representing every major continent, as well as numerous mixed populations .21). This project will provide much more information about human genetic diversity and population-specific genetic variation.

The first systematic approach to investigate whether genetic markers could be found that were consistently associated with blood pressure levels or the presence of hypertension was conducted by mapping populations consisting of related individuals. These studies were driven by the excitement generated by the highly successful application of this approach to single-gene diseases. In contrast, the outcome of linkage mapping studies in complex genetic diseases has been characterized by rather modest progress (22,23). The reported studies were limited by relatively low analytical power, lack of positional resolution, identification of a limited number of linked genomic regions, poor replication of these findings within similar populations and between populations of different ethnic composition, and modest effects associated with the linked markers . . A better way to approach the mapping problem was needed, combining new technical breakthroughs that enabled the use of much larger numbers of SNP markers in mapping with a theoretical framework to account for the role of genetic variation in the population in the presence of high blood pressure. .

Common variation in common diseases

In 1996, Risch and Merikangas proposed a new approach to the problem of identifying genetic variation that contributes to complex genetic susceptibility to disease.24). This new approach was attractive not only because there was a clear need to advance the field, but also because it articulated a rationale that, by linking recent human demographic history to an evolutionary framework, offered the opportunity to make discoveries with a potential broad impact. This framework suggested that since humans are a relatively new species, having only spread across the planet for about forty millennia, and since the propensity for common diseases such as hypertension appears to exist in all human populations, the component of this propensity, explained by genetic variation, may have existed in ancestral humans before the global diaspora. For such genetic variation to be maintained so widely among different human populations, the frequency of such variation must be relatively high. As information about the extent and distribution of genetic variation began to accumulate, the task of determining which common variation might play a role in disease risk began to come within reach.

Implementation of the experimental approach to test the common disease: common variant (CD:CV) hypothesis involves population-wide genotyping of a very large number of common SNP variants to determine which variants show a significant association with blood pressure or hypertension. Such large-scale genotyping provides a way to directly identify the causal variants (or reveal them via linkage disequilibrium as likely contained in haplotype blocks in adjacent regions of the genome). This approach is not without obstacles. One is the sheer scale of the endeavor: a survey of 500,000 SNPs per For an individual in a population of 10,000 individuals, 5 billion individual genotype tests are required – a significant analytical challenge. Improvements in genotyping technology have generally enabled robust and reliable genotyping methods (25,26). It also creates a problem of multiple testing, as each SNP is tested separately for association with the desired trait(s). The problem of multiple testing is overcome by adjusting p-values, which requires very low p-values ​​(typical marker sets require approximately < 1 × 10⁻⁸) to reject the null hypothesis that a given SNP is not associated with the trait. A small risk of this approach is the assumption that all the variation needed to conduct this type of study can be sampled directly (or indirectly, because it lies in strong linkage disequilibrium near an SNP that has been sampled), so that none or only a small portion of any detectable causative variation would be missed with the large number of SNPs sampled.

The overall performance of the technical elements of such a large-scale GWAS is well supported by the results generated when this type of study was applied to several common diseases and by the ability of GWAS studies to replicate results obtained in independent samples . For example, repeated findings have been found on specific markers associated with disease risk in diseases such as prostate cancer (27–29), diabetes type 1 (30–33) en diabetes type 2 (34,35). A complete inventory of published GWAS studies is maintained by the NIH Human Genome Research Institute (http://www.genome.gov/gwastudies/). Success, as usual in complex disease genetics, is a label that must be carefully defined: although associations have been found between SNP markers and disease traits, this does not mean that the marker is the causal variant, or even that it is the causal variant. variation is in the gene that contains or is closest to the associated variant (36). Progress in uncovering such causal variants and proving their functionality is still at an early stage.

GWAS for blood pressure and hypertension are emerging, but provide limited insight

Thus, with a mature and robust analytical approach, the first attempts to apply GWAS to blood pressure and hypertension were reported in 2007. As might be expected, these initial studies were somewhat exploratory in nature and provided an important opportunity to map out the parameters (population size). ), quantitative versus dichotomous phenotypes, marker counts, control populations, statistical analysis) necessary to achieve discovery. The first published study was conducted by the Wellcome Trust Case Control Consortium (WTCCC). This ambitious project sampled a Northern European population using GWAS to investigate seven common diseases (37). The experimental design used 2000 cases for each of the diseases studied and 3000 combined controls from two separate cohorts. SNPs were typed using the Affymetrix 500K Mapping Set. Although successful for some disease markers, the WTCCC project failed to find markers with alleles that occurred at a significantly higher frequency in hypertensive subjects than in control subjects. This was a disappointing first result. However, the contrast between the affected and control populations was significantly diluted. This dilution was due to the control population not being screened to remove hypertensive subjects. Because it was a common disease, there was likely a relatively high frequency of hypertension among the controls, which reduced the strength of the contrast between the control and affected samples. The outcome of the primary hypothesis that SNPs could be identified that were significantly associated with hypertension was not supported by this initial effort, and as a result, the genetic architecture of hereditary susceptibility to hypertension remained unclear.

Efforts to clarify this picture included follow-up studies that focused on SNPs identified in the WTCCC study that came closest to statistical significance. Studies in the US-based Family Blood Pressure Program cohort examined these SNPs in populations of predominantly European, African American, and American Hispanic descent.38). The FBPP, like the WTCCC, is a consortium of different research populations, and more than 11,000 individuals participated in the study. The study design was not GWAS, but rather explicit replication testing of the 6 SNPs with the highest p-values ​​obtained in the WTCCC. The FBPP study found that only one of the six SNPs tested was associated with blood pressure levels. Notably, another distinction between the FBPP study design and the WTCCC design is that the FBPP examined the relationship between the SNPs and the continuous characteristic of blood pressure, as well as the dichotomous characteristic of hypertension, while the WTCCC could only examine the status of hypertension . . The use of continuous characteristics (systolic and diastolic blood pressure) increases study power compared to the dichotomous characteristic of hypertension examined in the WTCCC study. Furthermore, the FBPP study population included related individuals and could therefore use transmission disequilibrium tests to examine the relationship between SNP allele inheritance and traits. The results of this study are both impressive and confusing. A single SNP (rs1937506) was shown to be associated with blood pressure in European Americans, for whom the effect size of a single copy of the G allele was estimated at −25 mm Hg. This is an unexpectedly large effect. This marker does not label a gene or genomic region previously identified through alternative screening methods as variation affecting blood pressure. This is quite surprising, although possible explanations are conceivable. Remarkably, in Hispanic Americans, the same allele contributed to aincreaseat a blood pressure of +28 mmHg a very large opposite effect. Although this could be explained by different background allele frequencies in this population or by the presence of another variation in the linkage disequilibrium with rs1937596, the magnitude and opposing effect of this variant remain insufficiently explained. In African Americans, the same allele had no effect on blood pressure. Despite the large effects on blood pressure in European and Hispanic Americans, the SNP was not found to be significantly associated with affected status (hypertensive versus normotensive). To add to the confusion, the location of the SNP in a region of the genome missing nearby genes rules out any simple association between the SNP (or adjacent sequence variation) and known functional pathways that influence blood pressure regulation. A study of the same six variants from the WTCCC study in an Asian population showed mixed results (39). Two SNPs (rs6997709 and rs7961152) were associated with systolic and diastolic blood pressure, respectively, while the last SNP (rs7961152) was also found to be associated with hypertension status. Thus, surprisingly different results are observed for both SNPs and ethnicities in this attempt to replicate and confirm the WTCCC results.

Additional GWAS studies on blood pressure and hypertension have been reported. These studies have been conducted using a variety of populations, including genetically isolated European American Amish (40), African Americans (41), Europeans (42) and Asians (43).table 1summarizes the populations studied and key findings. The studies have produced interesting and potentially important positive results. However, the results obtained vary with regard to the loci and markers uncovered. This result is inconsistent with the CD:CV hypothesis. However, the results do not suggest that the high frequency of hypertension in the studied populations is due to the existence of a hypertensionlimited number ofof shared hypertension loci. This raises the possibility of extensive heterogeneity in the genetic loci that contribute to hypertension, both within and between populations. The new image also clearly indicates that the loci detected in the GWAS are associated with very small effects on blood pressure. Another novel feature is that while some blood pressure-associated SNPs are clearly located in or near genes, others are located in gene deserts. For the latter variants, this implies a difficult path forward in the expected functional validation of these variants.

GWAS turns to meta-analysis

The value of increasing the analytical power of GWAS studies by increasing the size of the study population has not been overlooked and has resulted in the simultaneous publication of two large studies in which the population size has been dramatically expanded. In both cases, this was achieved by combining samples from a range of medium to large-scale epidemiological studies. The first, known as the Global BPgen study, examined the association of SNP with blood pressure in 34,433 subjects of European descent, with follow-up studies in more than 80,000 subjects of European and South Asian descent.9). The CHARGE consortium conducted its discovery study using genotype data from nearly 30,000 North American subjects and used the global BPgen discovery population to track key associations (10). The results of these studies are summarized intable 2. Together, the two studies have reinforced the picture emerging from GWAS studies: if sufficiently powered, these studies can find reliable blood pressure associations; the blood pressure associations detected are usually also hypertension status associations; the associations may contain significant overlaps between different populations; when these associations arise from markers in or near genes, these genes are largely not located in prominent pathways known to have significant effects on blood pressure regulation targeted by mainstream antihypertensive pharmacotherapy; and the risk effects for blood pressure and hypertension associated with these findings are consistently small.

Although the results of GWAS in hypertension and blood pressure are important, a significant part of their importance is due to what they did not reveal, rather than what they did reveal. Most striking is their inability to generate observations that can explain the high estimated heritability of blood pressure. While the field of population genetics of hypertension has evolved over more than a decade, from relatively modest study designs of linkage-based mapping in populations of related individuals to very large populations of unrelated individuals, much of what emerges could have come. these studies found no gene variation contributing to significant effects on blood pressure; agreement between linkage mapping studies and GWAS was negligible; genetic information that would contribute in a clinically meaningful sense to the prediction of disease risk in individuals has not emerged; no new (or old) targets for pharmacotherapeutic development have been discovered; and no insight has been gained into how genetics can lead to the personalization of hypertension therapy (pharmacological or non-pharmacological). In a disease where adherence is low and existing therapies lack specificity for the underlying pathogenetic mechanism, perhaps contributing to a high rate of adverse events, progress in identifying rational new drug targets or connections between genes and existing drug targets would be valuable . Furthermore, no coherent picture has emerged of the functional pathways through which genetic variation may act together to increase the risk of hypertension. Only one study has attempted to infer pathogenesis pathways from GWAS findings and has done so based on GWAS hits that either did not replicate or did not replicate when tested.41).

The heredity gap

The putative role of common variation in blood pressure regulation has encouraged major investments in GWAS. The exciting sense of possibility has combined with rapid technological advances in the field of genotyping to make the conduct of these studies irresistibly attractive. Have these forces dampened research and criticism of the assumptions underlying the blood pressure GWAS? A central problem arises from well-established evidence that blood pressure and hypertension status exhibit relatively high heritability. If 30-70% of blood pressure variance can be correctly attributed to genetic variation, then GWAS studies have clearly made no more than a trivial dent in even the lowest estimates of heritability, and there is still much genetic discovery to be made. finished. The alternative is that the methods used to assess the human heritability of these traits have overestimated genetic factors and underestimated other influences (shared environment, diet, age, exercise, BMI). The estimate of heritability is limited because the other variables involved (environmental and phenotypic variations) are difficult to measure accurately. In the case of blood pressure, the phenotype is indeed a very dynamic variable with significant sampling problems. Measuring heritability among related individuals inevitably results in greater sharing of the environment, which can have important effects both in the time frame of the estimate (individuals sharing the same current environment) and even larger effects in the long term (individuals sharing a similar environment). environment ). environment, possibly from conception). However, although the heritability of blood pressure is generally overestimated, it seems unlikely that the magnitude of such overestimation can explain the entire missing heritability that remains to be explained after GWAS.

Continued progress in genetic studies of blood pressure and hypertension requires a framework to account for the inability to identify common variants affecting these traits by GWAS. One possible explanation is that GWAS has failed to uncover underlying variants because it is designed to sample common variants (typically those with allele frequencies greater than 2-5%). By exclusion, this suggests that rare variants may play a greater role in heritability than predicted by the CD:CV hypothesis. The effectiveness of GWAS in detecting trait effects arising from rare variants is limited. Individual rare variants have their phenotypic effect in families segregating these variants and are diluted in cross-sectional population analysis. Within families, rare variants may have a much larger effect size than that found for common variants and may be responsible for the greater heritability. For common traits such as hypertension, this implies that there may be many rare variants in a population that could influence the trait, a situation that poses a new set of problems for its successful detection and verification.

Rare variants appear

Pioneering work by Richard Lifton and colleagues is beginning to outline the role that rare variants may play in hypertension. Over several years, this group has made remarkable progress in mapping the genes and mutations responsible for rare Mendelian forms of hypertension and their reverse counterparts, mutations that lead to syndromes of hypotension. These findings are in harmony with, and have even further confirmed, an important theoretical construct in the systems analysis of blood pressure, namely that the only way to influence blood pressure in the long term is to alter sodium handling in the kidneys.44,45). Each of the genes reported to influence blood pressure has been shown to function in an important renal pathway that acts on or regulates sodium reabsorption. Although it is clear that the Mendelian mutations discovered by Lifton and colleagues contribute insignificantly to the risk of population hypertension, it is possible that genes whose effects on blood pressure regulation are large enough to reveal Mendelian features may also contain other variations that have the same influence. distinctive features.

There is now data available that sheds some light on this question. SLC12A1 and KCNJ1 are genes that contribute to Barrter syndrome, while mutation in SLC12A3 causes the less severe Gitelman syndrome, both rare Mendelian salt-wasting diseases associated with low blood pressure. The known disease-causing mutations in these genes occur in the hom*ozygous autosomal recessive state at frequencies of ~1 per million and per 40,000 for Barrter and Gitelman diseases, respectively. Gene sequencing of these three target genes in the Framingham Heart Study population (1,985 subjects and 1,140 family members) has identified novel variation in these genes and defined the frequency of such variation in this population (46). The gene sequencing effort identified 46 synonymous substitutions, 89 missense substitutions, one nonsense mutation and two frameshift mutations. Twenty-three subjects showed a total of ten different previously known and biochemically proven loss-of-function mutations. Mutations different from these ten known mutations were assessed as potentially damaging when they alter amino acids that are highly conserved. The final yield of potentially deleterious variation was 30 different mutations present in 49 subjects. A rather unorthodox analytical approach was then applied. The carriers of potentially harmful mutations in all three genes were treated as a group and analyzed to determine whether blood pressure levels were different in this group compared to the Framingham Heart Study cohort. Systolic blood pressure was found to be lower (by 5.7 mmHg at age 40 and by 9.0 mmHg at age 60) in the mutation-carrying group. Analysis was also performed within families, comparing siblings who carried a mutant allele with siblings who did not carry such an allele. Lower blood pressure was also observed in the mutant allele carriers. Furthermore, the prevalence of hypertension was lower in the mutation-bearing group than in the Framingham cohort.

These studies indicate that 1 in 64 members of the Framingham cohort may carry a mutant allele that affects blood pressure when the mutation is selected for an effect on a conserved amino acid and when clustered across three genes. Collectively, these mutations appear to reduce the risk of hypertension by 60% by age 60. It is unlikely that any of these variations would have emerged in a GWAS study of common variation, as the frequency of each variant is below the threshold for classification. as usual. These studies have thus begun to clarify the possibility that the risk of hypertension in at least part of the population may be strongly influenced by functional rare variation. Given the possible deleterious effects of the hom*ozygous state of such mutations on individual health, one might expect that purifying selection would eliminate them. But that may not be the case. In an interesting modeling study on the possible role of rare variants in common diseases, Pritchard has concluded that it is possible that common disease characteristics could be due to rare variants.47). This modeling suggests that loci harboring rare variants that affect common diseases may be characterized by relatively high mutation rates. This would lead to extensive allelic heterogeneity of the disease, sufficient to explain disease in the presence of weak purifying selection. These predictions and others like them by Eyre-Walker (48), seems to harmonize quite well with observations in the Framingham cohort. Thus, it is reasonable to predict that other loci that influence blood pressure in the population, including loci containing genes that influence sodium reabsorption in the kidney, will also be subject to relatively high mutation rates, and therefore have an extensive will incorporate allelic diversity of rare alleles among the populations. disease. associated alleles.

It is worth considering that the Framingham study identified 92 missense, frameshift and nonsense mutations in the three target genes. Conclusions on the effect of rare mutations on the risk of blood pressure and hypertension were limited to only the 30 mutations previously shown to cause Gitelman or Barrter syndromes (10 SNPs) or the mutations that alter highly conserved amino acids (20 SNPs) . And these conclusions were reached in a new, unorthodox way. The typical hypothesis for testing the association between sequence variation and disease tests the relationship with a single variant. In their study of gene variation in Barrter and Gitelman syndrome, the relevance to blood pressure and hypertension was revealed through a hypothesis that excluded amino acid-altering variants affecting amino acids with lower conservation rates and pooled variation, so that there was not just one variant. tested simultaneously, but variants in more than one functional gene were also tested simultaneously.

The work on rare variants in the Framingham cohort highlights two important potential challenges that must be overcome to fully elucidate the role of rare variants in influencing blood pressure and hypertension. The first problem to be addressed is that of the appropriate formulation of hypotheses for testing rare variations. The most parsimonious approach is to test individual variants for trait effects. However, this would certainly require populations much larger than the Framingham cohort, because these variants will be so rare that detection of their effects would require the power provided by a sufficient number of carriers (49). If allelic heterogeneity is a feature of most genes that contributes to rare variation, as Pritchard's modeling and the Framingham study suggest, then more often than not many variants in each gene will need to be tested separately. The alternative approach of testing multiple variants simultaneously is based on assumptions that are tested first. For example, that all non-synonymous mutations affecting amino acids that are highly conserved are detrimental to protein function. Some variants may give gain-of-function mutations and therefore may have opposite effects on trait values ​​or status. While gain-of-function mutations are undoubtedly less common, the suggestion to ignore them carries a certain danger (50). Thus, merging variants that have untested and potentially divergent trait effects may obscure the real effects associated with individual variants. Allelic heterogeneity poses a practical problem whose solution is not yet clear. Perhaps simply increasing the sample size will prove sufficient, although the upper limits of the required sample size may be very large indeed if the effect associated with the variant is small (49). In the Framingham study, there are many variants, including variants that cause non-synonymous amino acid changes, which, due to the reasoning formulated for testing the effects of variants, are not tested. Is it always reasonable to exclude such variants from an overall analysis, or is it only reasonable when newly discovered variation can be compared to a diverse set of biochemically and functionally characterized disease alleles to ensure that similar traits are shared? What effect can variants that affect the level of gene expression contribute to phenotypes? If pooling is used, is it possible to simultaneously test variants that affect both expression level and protein composition? The acid test of functional genetic variation has always been to express the variant protein and demonstrate altered functional properties consistent with the trait effect. The enormous number of potentially relevant variants makes this a difficult task. Intermediate steps that extend simple properties of amino acid changes that affect conserved or non-conserved amino acids (46), or assume that all non-synonymous variants are harmful (50) or that involve predicting altered biochemical properties of substituted amino acids on broad aspects of protein function may provide a useful alternative to testing each individual variant, but such indirect approaches are uncertain and enter uncharted territory.

Rarely a way forward

These insights begin to outline a strategy for detecting variation in blood pressure and hypertension. Such a strategy would target genes known to affect or influence renal sodium reabsorption, would examine relatively large and well-characterized populations, would utilize extensive re-sequencing of the target genes, and would characterize the resulting variation in terms of the possibility and predictability of functional effects of mutation. Because some of the functional variation may arise from sequence variation in noncoding regions that influence transcription, protein abundance, and activity, it is likely necessary to extend this strategy beyond the coding regions of genes. Compound heterozygosity must also be taken into account, as allelic heterogeneity can result in large trait effects due to heterozygosity for two different non-wild-type alleles (51). In the field of blood pressure and hypertension, the range of genes that can be targeted by such studies can be very large, reflecting the role of different regulatory systems (autonomic, endocrine, autocrine, vascular, endothelial and renal epithelium) capable of affect blood pressure. Although existing studies have emphasized the role of renal sodium transport genes and their local regulatory pathways in influencing blood pressure (52,53), it is conceivable that other genes, including genes not expressed in the kidneys, may indirectly influence sodium reabsorption in the kidneys.

The selection of such functional candidate genes, including those genes that may be subject to more frequent mutations and thus more likely to contribute to the high diversity of deleterious alleles, awaits new whole-genome sequencing studies of genetic variation in multigenerational pedigrees, which will prioritize between genes can make possible. potential candidate genes. One such study has been published and has clarified and confirmed previous estimates of the genome-wide de novo mutation rate by directly comparing the genome sequences of parents and offspring (54). These studies also support previous expectations that a higher mutation rate in the male germline contributes asymmetrically to the total mutation and confirm the expected high mutation rate affecting the CpG sequence. The recent publication of small-scale whole-genome sequencing studies suggests the imminent arrival of sufficient whole-genome sequencing data across generations to determine whether local differences in mutation rates can be identified and whether this is a useful can be a tool for refining the candidate gene. list for the identification of rare deleterious mutations by gene sequencing in large populations.

Final thoughts

The road back, as human geneticists have struggled to shed light on how hypertension risk is transmitted in populations, has been frustrating and challenging. It is undoubtedly a difficult problem. The next key findings to date are that, in stark contrast to Mendelian traits, there are no easy answers: there are no genes with alleles responsible for a large proportion of the total population variation in blood pressure and risk of hypertension. Common variants that affect blood pressure can be identified, but their contribution is much smaller than expected. Although these results are generally negative, they have an important bearing on battlefield design: either heritability estimates are dramatically wrong, or, more likely, these traits are influenced by alleles that are quite heterogeneous and unusual. The loci containing genes with alleles that influence blood pressure may also be heterogeneous if the population is considered broadly. This indeed appears to be the case: otherwise linkage analysis should have been a more productive approach to identifying such variation. The best explanation for the lack of success of linkage studies is that their power is eroded by the extensive heterogeneity of blood pressure loci in the population.

Platt and Pickering were antagonists in a controversy that consumed the hypertension research community for many years in the 20th century.^ecentury (55). The main element of their dissent was, on the one hand, the belief that the heredity of hypertension was simple and Mendelian, while on the other hand blood pressure was a persistent trait and therefore unmistakably the result of polygenic inheritance. Clarity has been hampered by the difficulty of accurately assessing this dynamic and inherently variable trait and by the lack of genetic tools that could provide definitive answers. The current era of genome-wide sequencing and variation testing is finally beginning to shed some light on the question that created this schism. Ultimately, it would not be surprising to find that both antagonists were partly right: some families may transmit blood pressure traits through single loci with major consequences, while blood pressure traits in the population as a whole arise through multiple loci, with individual pedigrees transmitting effects. of a limited number of such loci. Ultimately, there can be satisfaction for both parties. But the most important thing is to make progress in this difficult challenge so that concrete and specific information on the causes of hypertension is obtained, which can revive and improve the control of this very widespread and dangerous disease.

References