Evidence for a gene influencing blood pressure on chromosome 17. Genome scan linkage results for longitudinal blood pressure phenotypes in subjects from the framingham heart study

Interaction of gender and body mass index (BMI) reveals evidence of linkage for hypertension in the Framingham Heart Study

Background

Genetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies have reported regions of interest, but lack consistency across studies. Incorporation of covariates, in particular the interaction between two independent risk factors (gender and BMI) greatly improved our ability to detect linkage.

Results

We report a highly significant signal for linkage to chromosome 2p, a region that has been implicated in previous linkage studies, along with several suggestive linkage regions.

Conclusion

We demonstrate the importance of including covariates in the linkage analysis when the phenotype is complex.

Multivariate variance-components analysis of longitudinal blood pressure measurements from the Framingham Heart Study

Multivariate variance-components analysis provides several advantages over univariate analysis when studying correlated traits. It can test for pleiotropy or (in the longitudinal context) gene × age interaction. It can also have more power than univariate analyses to detect a quantitative trait locus influencing several traits. We apply multivariate variance components to longitudinal systolic blood pressure data from the Framingham Heart Study. We find evidence for a polygenic influence on blood pressure (heritabilities at different ages range from 27% to 38%). Tests based on a factor-analytic parameterization of the polygenic variance find significant (p < 2 × 10^-3) evidence that different genes affect blood pressure at different ages. Still, estimates for the proportion of polygenic variance due to shared genes ran as high as 85% for some trait pairs. Univariate and multivariate linkage analyses replicate previous linkage results on chromosome 17 (maximum LOD scores of 2.2 and 2.4, respectively). In this study, multivariate analysis provides no increase in power; this is likely due to the strong positive correlation in systolic blood pressure measured at different ages.

Analysis of gene x environment interactions in sibships using mixed models

BACKGROUND

Gene x environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to assess gene x environment interactions with respect to systolic blood pressure on sibships adjusting for repeated measures and hierarchical nesting structures. A data set containing 410 sibships from the Framingham Heart Study offspring cohort (part of the Genetic Analysis Workshop 13 data) was used for all analyses. Three mixed gene x environment models, all adjusting for repeated measurement and varying levels of nesting, were compared for precision of estimates: 1) all sibships with adjustment for two levels of nesting (sibs within sibships and sibs within pedigrees), 2) all sibships with adjustment for one level of nesting (sibs within sibships), and 3) 100 data sets containing random draws of one sibship per extended pedigree adjusting for one level of nesting.

RESULTS

The main effects were: gender, baseline age, body mass index (BMI), hypertensive treatment, cigarettes per day, grams of alcohol per day, and marker GATA48G07A. The interaction fixed effects were: baseline age by gender, baseline age by cigarettes per day, baseline age by hypertensive treatment, baseline age by BMI, hypertensive treatment by BMI, and baseline age by marker GATA48G07A. The estimates for all three nesting techniques were not widely discrepant, but precision of estimates and determination of significant effects did change with the change in adjustment for nesting.

CONCLUSION

Our results show the importance of the adjustment for all levels of hierarchical nesting of sibs in the presence of repeated measures.

Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study

The relationship between elevated blood pressure and cardiovascular and cerebrovascular disease risk is well accepted. Both systolic and diastolic hypertension are associated with this risk increase, but systolic blood pressure appears to be a more important determinant of cardiovascular risk than diastolic blood pressure. Subjects for this study are derived from the Framingham Heart Study data set. Each subject had five records of clinical data of which systolic blood pressure, age, height, gender, weight, and hypertension treatment were selected to characterize the phenotype in this analysis.

We modeled systolic blood pressure as a function of age using a mixed modeling methodology that enabled us to characterize the phenotype for each individual as the individual's deviation from the population average rate of change in systolic blood pressure for each year of age while controlling for gender, body mass index, and hypertension treatment. Significant (p = 0.00002) evidence for linkage was found between this normalized phenotype and a region on chromosome 1. Similar linkage results were obtained when we estimated the phenotype while excluding values obtained during hypertension treatment. The use of linear mixed models to define phenotypes is a methodology that allows for the adjustment of the main factor by covariates. Future work should be done in the area of combining this phenotype estimation directly with the linkage analysis so that the error in estimating the phenotype can be properly incorporated into the genetic analysis, which, at present, assumes that the phenotype is measured (or estimated) without error.

Genome-wide linkage analysis of systolic blood pressure: a comparison of two approaches to phenotype definition

Problem 1 of the Genetic Analysis Workshop 13(GAW13) contains longitudinal data of cardiovascular measurements from 330 pedigrees. The longitudinal data complicates the phenotype definition because multiple measurements are taken on each individual. To address this complication, we propose an approach that uses generalized estimating equations to obtain residuals for each time point for each person. The mean residual is then taken as the new phenotype with which to use in a variance components linkage analysis. We compare our phenotype definition approach to an approach that first reduces the multiple measurements to a single measurement and then models these summary statistics as regression terms in a variance components analysis. For each approach, multipoint linkage analysis was performed using the residuals and the SOLAR computer program. Our results show little difference between the methods based on the LOD scores.

Comparison of longitudinal variance components and regression-based approaches for linkage detection on chromosome 17 for systolic blood pressure

We compare two methods to detect genetic linkage by using serial observations of systolic blood pressure in pedigree data from the Framingham Heart Study focusing on chromosome 17. The first method is a variance components (VC) approach that incorporates longitudinal pedigree data, and the second method is a regression-based approach that summarizes all longitudinal measures in one single measure. No evidence of linkage was found either using the VC longitudinal approach or the regression-based approach, except when all time points were used from Cohorts 1 and 2 and only subjects aged 25 and 75 years were included.

Transmission ratio distortion in families from the Framingham Heart Study

Background

One implicit assumption in most linkage analysis is that live-born siblings unselected for a phenotype do not share alleles greater than the Mendelian expectation at any particular locus. However, since most families are recruited for genetic studies because of the presence of disease, there is little data available to confirm that this is the case. We hypothesized that loci that behave in a non-Mendelian fashion could be identified using genotype data from the Framingham Heart Study families. We tested the hypothesis that live-born sibs, either stratified by or irrespective of gender, demonstrate excess sharing of alleles on the autosomes, i.e., transmission ratio distortion. Multipoint linkage analysis of siblings either according to gender or not was performed using an allele-sharing method. Such observations may have implications for the mapping of loci for complex disease and quantitative traits in human pedigrees.

Results

No results that reached genome-wide significance were observed. However, four regions demonstrated excess sharing of alleles at p < 0.002 when sibships were stratified by gender-three of which were present in males. Of note, a female-specific locus co-localized with region that is linked to mean systolic blood pressure in the same families. In addition, three other regions demonstrated excess sharing of alleles in sibships irrespective of gender, including a region on chromosome 10p14-p15 (p = 7.5 × 10^-4).

Conclusion

Although no loci meeting genome-wide significance were detected to demonstrate transmission ratio distortion, loci with suggestive evidence for linkage were detected. These may have implications for the mapping of susceptibility loci for complex disease in human pedigrees.

Screening the genome to detect an association with hypertension

We report tree-based association analysis as applied to the two Framingham cohorts and to the first replication of the simulated data obtained from the Genetic Analysis Workshop 13. For this analysis, familial association is ignored. The two endpoints examined are hypertension status at initial visit and time-to-hypertension, using a censored data approach. Although linkage association has previously been reported with hypertension, we found no association using the tree-based methodology.

Genetic Analysis Workshop 13: simulated longitudinal data on families for a system of oligogenic traits

The Genetic Analysis Workshop 13 simulated data aimed to mimic the major features of the real Framingham Heart Study data that formed Problem 1, but under a known inheritance model and with 100 replicates, so as to allow evaluation of the statistical properties of various methods. The pedigrees used were the 330 real pedigree structures (comprising 4692 individuals) with some minor changes to protect confidentiality. Fifty trait genes and 399 microsatellite markers were simulated by gene dropping on 22 autosomal chromosomes. Assuming random ascertainment of families, a system of eight longitudinal quantitative traits (designed to be similar to those in the real data) was generated with a wide range of heritabilities, including some pleiotropic and interactive effects. Genes could affect either the baseline level or the rate of change of the phenotype. Hypertension diagnosis and treatment were simulated with treatment availability, compliance, and efficacy depending on calendar year. Nongenetic traits of smoking and alcohol were generated as covariates for other traits. Death was simulated as a hazard rate depending upon age, sex, smoking, cholesterol, and systolic blood pressure. After the complete data were simulated, missing data indicators were generated based on logistic models fitted to the real data, involving the subject's history of previous missing values, together with that of their spouses, parents, siblings, and offspring, as well as marital status, only-child indicators, current value at certain simulated traits, and the data collection pattern on the cohort into which each subject was ascertained.

Comparison of Haseman-Elston regression analyses using single, summary, and longitudinal measures of systolic blood pressure

To compare different strategies for linkage analyses of longitudinal quantitative trait measures, we applied the "revisited" Haseman-Elston (RHE) regression model (the cross product of centered sib-pair trait values is regressed on expected identical-by-descent allele sharing) to cross-sectional, summary, and repeated measurements of systolic blood pressure (SBP) values in replicate 34, randomly selected from the Genetic Analysis Workshop 13 simulated data. RHE linkage scans were performed without knowledge of the generating model using the following phenotypes derived from untreated SBP measurements: the first, the last, the mean, the ratio of the change between the first and last over time, and the estimated linear regression slope coefficient. Estimates of allele sharing in sibling pairs were obtained from the complete genotype data of Cohorts 1 and 2, but linkage analyses were restricted to the five visits of Cohort 2 siblings. Evidence for linkage was suggestive (p < 0.001) at markers neighboring SBP genes Gb35, Gs10, and Gs12, but weaker signals (p < 0.01) were obtained at markers mapping close to Gb34 and Gs11. Linkage to baseline genes Gb34 and Gb35 was best detected using the first SBP measurement, whereas linkage to slope genes Gs10-12 was best detected using the last or mean SBP value. At markers on chromosomes 13 and 21 displaying strongest linkage signals, marginal RHE-type models including repeated SBP measures were fit to test for overall and time-dependent genetic effects. These analyses assumed independent sib pairs and employed generalized estimating equations (GEE) with a first-order autoregressive working correlation structure to adjust for serial correlation present among repeated observations from the same sibling pair.

Risk factors for coronary artery disease and the use of neural networks to predict the presence or absence of high blood pressure

BACKGROUND

The Framingham Heart Study was initiated in 1948 as a long-term longitudinal study to identify risk factors associated with cardiovascular disease (CVD). Over the years the scope of the study has expanded to include offspring and other family members of the original cohort, marker data useful for gene mapping and information on other diseases. As a result, it is a rich resource for many areas of research going beyond the original goals. As part of the Genetic Analysis Workshop 13, we used data from the study to evaluate the ability of neural networks to use CVD risk factors as training data for predictions of normal and high blood pressure.

RESULTS

Applying two different strategies to the coding of CVD risk data as risk factors (one longitudinal and one independent of time), we found that neural networks could not be trained to clearly separate individuals into normal and high blood pressure groups. When training was successful, validation was not, suggesting over-fitting of the model. When the number of parameters was reduced, training was not as good. An analysis of the input data showed that the neural networks were, in fact, finding consistent patterns, but that these patterns were not correlated with the presence or absence of high blood pressure.

CONCLUSION

Neural network analysis, applied to risk factors for CVD in the Framingham data, did not lead to a clear classification of individuals into groups with normal and high blood pressure. Thus, although high blood pressure may itself be a risk factor for CVD, it does not appear to be clearly predictable using observations from a set of other CVD risk factors.

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Background

For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time.

Results

Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted.

Conclusion

The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.

A QTL genome scan of the metabolic syndrome and its component traits

BACKGROUND

Because high blood pressure, altered lipid levels, obesity, and diabetes so frequently occur together, they are sometimes collectively referred to as the metabolic syndrome. While there have been many studies of each metabolic syndrome trait separately, few studies have attempted to analyze them combined, i.e., as one composite variable, in quantitative trait linkage or association analysis. We used genotype and phenotype data from the Framingham Heart Study to perform a full-genome scan for quantitative trait loci underlying the metabolic syndrome.

RESULTS

Heritability estimates for all of the covariate-adjusted and age- and gender-standardized individual traits, and the composite metabolic syndrome trait, were all fairly high (0.39-0.62), and the composite trait was among the highest at 0.61. The composite trait yielded no regions with suggestive linkage by Lander and Kruglyak's criteria, although there were several noteworthy regions for individual traits, some of which were also observed for the composite variable.

CONCLUSION

Despite its high heritability, the composite metabolic syndrome trait variable did not increase the power to detect or localize linkage peaks in this sample. However, this strategy and related methods of combining correlated individual traits deserve further investigation, particularly in settings with complex causal pathways.

Nonparametric longitudinal allele-sharing model

Basically no methods are available for the analysis of quantitative traits in longitudinal genetic epidemiological studies. We introduce a nonparametric factorial design for longitudinal data on independent sib pairs, modelling the phenotypic quadratic differences as the dependent variable. Factors are the number of alleles shared identically by descent (IBD) and the age categories at which the dependent variable is measured, allowing for dependence due to age. To identify a linked marker a rank statistic tests the influence of IBD group on phenotypic quadratic differences. No assumptions are made on normality or variances of the dependent variable. We apply our method to 71 sib pairs from the Framingham Heart Study data provided at the Genetic Analysis Workshop 13. For all 15 available markers on chromosome 17 we analyzed the influence on systolic blood pressure. In addition, different selection strategies to sample from the whole data are discussed.

Multivariate sib-pair linkage analysis of longitudinal phenotypes by three step-wise analysis approaches

Background

Current statistical methods for sib-pair linkage analysis of complex diseases include linear models, generalized linear models, and novel data mining techniques. The purpose of this study was to further investigate the utility and properties of a novel pattern recognition technique (step-wise discriminant analysis) using the chromosome 10 linkage data from the Framingham Heart Study and by comparing it with step-wise logistic regression and linear regression.

Results

The three step-wise approaches were compared in terms of statistical significance and gene localization. Step-wise discriminant linkage analysis approach performed best; next was step-wise logistic regression; and step-wise linear regression was the least efficient because it ignored the categorical nature of disease phenotypes. Nevertheless, all three methods successfully identified the previously reported chromosomal region linked to human hypertension, marker GATA64A09. We also explored the possibility of using the discriminant analysis to detect gene × gene and gene × environment interactions. There was evidence to suggest the existence of gene × environment interactions between markers GATA64A09 or GATA115E01 and hypertension treatment and gene × gene interactions between markers GATA64A09 and GATA115E01. Finally, we answered the theoretical question "Is a trichotomous phenotype more efficient than a binary?" Unlike logistic regression, discriminant sib-pair linkage analysis might have more power to detect linkage to a binary phenotype than a trichotomous one.

Conclusion

We confirmed our previous speculation that step-wise discriminant analysis is useful for genetic mapping of complex diseases. This analysis also supported the possibility of the pattern recognition technique for investigating gene × gene or gene × environment interactions.

Using an age-at-onset phenotype with interval censoring to compare methods of segregation and linkage analysis in a candidate region for elevated systolic blood pressure

BACKGROUND

Genetic studies of complex disorders such as hypertension often utilize families selected for this outcome, usually with information obtained at a single time point. Since age-at-onset for diagnosed hypertension can vary substantially between individuals, a phenotype based on long-term follow up in unselected families can yield valuable insights into this disorder for the general population.

METHODS

Genetic analyses were conducted using 2884 individuals from the largest 330 families of the Framingham Heart Study. A longitudinal phenotype was constructed using the age at an examination when systolic blood pressure (SBP) first exceeds 139 mm Hg. An interval for age-at-onset was created, since the exact time of onset was unknown. Time-fixed (sex, study cohort) and time-varying (body mass index, daily cigarette and alcohol consumption) explanatory variables were included.

RESULTS

Segregation analysis for a major gene effect demonstrated that the major gene effect parameter was sensitive to the choice for age-at-onset. Linkage analyses for age-at-onset were conducted using 1537 individuals in 52 families. Evidence for putative genes identified on chromosome 17 in a previous linkage study using a quantitative SBP phenotype for these data was not confirmed.

CONCLUSIONS

Interval censoring for age-at-onset should not be ignored. Further research is needed to explain the inconsistent segregation results between the different age-at-onset models (regressive threshold and proportional hazards) as well as the inconsistent linkage results between the longitudinal phenotypes (age-at-onset and quantitative).

Susceptibility scoring in family-based association testing

BACKGROUND

Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a susceptibility residual method of adjustment for covariates.

RESULTS

Through simulation, we show that environmental adjustments that down-weight persons who are "destined" to be affected decrease the power to detect genetic association. We used the residual adjusted method on the Framingham Heart Study offspring data, provided for Genetic Analysis Workshop 13, and got mixed results.

CONCLUSION

When the genetic effect and environmental effects are independent, a susceptibility residual method of adjustment for environmental covariates reduces the power of the association test. Further study is necessary to determine if residual adjustment is appropriate in more complex disease models.

Use of tree-based models to identify subgroups and increase power to detect linkage to cardiovascular disease traits

BACKGROUND

Our goal was to identify subgroups of sib pairs from the Framingham Heart Study data set that provided higher evidence of linkage to particular candidate regions for cardiovascular disease traits. The focus of this method is not to claim identification of significant linkage to a particular locus but to show that tree models can be used to identify subgroups for use in selected sib-pair sampling schemes.

RESULTS

We report results using a novel recursive partitioning procedure to identify subgroups of sib pairs with increased evidence of linkage to systolic blood pressure and other cardiovascular disease-related quantitative traits, using the Framingham Heart Study data set provided by the Genetic Analysis Workshop 13. This procedure uses a splitting rule based on Haseman-Elston regression that recursively partitions sib-pair data into homogeneous subgroups.

CONCLUSIONS

Using this procedure, we identified a subgroup definition for use as a selected sib-pair sampling scheme. Using the characteristics that define the subgroup with higher evidence for linkage, we have identified an area of focus for further study.

Hereditary disorders of potassium homeostasis

There has been a dramatic recent increase in the understanding of the renal epithelial transport systems with the identification, cloning and characterization of a large number of membrane transport proteins. The aim of this chapter is to integrate this body of knowledge with the understanding of the clinical disorders that accompany gain, loss or dysregulation of function of these transport systems. The specific focus is on the best-defined human clinical syndromes in which there are derangements in potassium (K(+)) homeostasis. The focus is on inherited syndromes, rather than on acquired syndromes due to tubular transport defects, and the therapeutic approaches address chronic derangements of K(+) homeostasis rather than acute interventions directed at life-threatening hyperkalaemia.

Summary of Group 8: Development and extension of linkage methods

The diverse contributions to Group 8 focus on the development and extension of linkage methods, and share themes that are organized around approaches to analysis. The themes discussed include issues of the accuracy of estimates of marker identity-by-descent (IBD) information, the influence of such IBD information on linkage detection, and methods for dealing with genetic heterogeneity and multiple testing. In addition, challenges were identified and solutions were offered for coping with some of the common problems of complex trait analysis, including trait model selection and computational compromises. Analytic approaches based on Bayesian and Monte Carlo methods were prominent, and provided optimistic results.

Association of EDNRA , but not WNK4 or FKBP1B , polymorphisms with essential hypertension

In a study of the genetic basis of essential hypertension (HT), we tested four variants in three candidate genes not previously investigated in HT. These encoded the endothelin receptor type A (EDNRA), which transduces most of the vasoconstrictive properties of endothelin-1, protein kinase lysine deficient 4 (WNK4) whose gene resides in a HT linkage region on chromosome 17, and FK506-binding protein 1B (FKBP1B), which can reduce blood pressure by increasing nitric oxide. The variants were: for EDNRA, a G-->A in the 5'-UTR and C-->T in exon 8; for WNK4, a tetranucleotide repeat in intron 10; and for FKBP1B, a T-->C in exon 4. Subjects were Anglo-Celtic white Australians and included 155 HTs with two HT parents and 245 normotensives (NTs) whose parents were both NT. For EDNRA, we found a weak association of the exon 8 variant with HT (p = 0.019) and association of the 5'-UTR variant with elevation in systolic and diastolic blood pressure (BP) (p = 0.038 and 0.0031, respectively). The WNK4 intron 10 variant and the FKP1B exon 4 variant showed no association with HT, but tracking with BP was seen for the latter (p = 0.015 and 0.0011 for systolic and diastolic BP, respectively). Our study thus suggests possible involvement of EDNRA in essential HT.

A major health hazard: the metabolic syndrome

The clustering of several metabolic and cardiovascular disease risk factors has been termed the metabolic syndrome. The metabolic syndrome seems to result from a collision between susceptible "thrifty genes" and a society characterized by an increased prevalence of obesity and a sedentary lifestyle. The typical patient is characterized by abdominal obesity, a varying degree of glucose intolerance, dyslipidemia and often hypertension. The components of the metabolic syndrome are associated with insulin resistance, disturbances of coagulation and fibrinolysis, endothelial dysfunction and elevated markers of sub-clinical inflammation. The current review focuses mainly on the new definitions of the syndrome, the results of recent epidemiological studies and the consequences of the metabolic syndrome as an important risk factor for cardiovascular disease, premature death and diabetes. The metabolic syndrome constitutes a major challenge for public health professionals in the field of preventive medicine since more than 40 million U.S. adults seem to be affected by the syndrome. Lifestyle changes could have a profound influence on the syndrome and its development.

Association of the angiotensin-converting enzyme (ACE) gene G2350A dimorphism with essential hypertension

Although the angiotensin converting enzyme (ACE) is a strong candidate gene for hypertension, the extensively studied insertion-deletion dimorphism in intron 16 was not found to be associated with it. Several new polymorphisms in the ACE gene were identified, among which a dimorphism in exon 17, ACE G2350A, has a significant effect on plasma ACE concentrations. To assess the value of genotyping the ACE G2350A dimorphism in a genetically homogeneous population, we carried out a retrospective, case-control study of dimorphism G2350A for a putative association with essential hypertension (EH) in a Gulf population (Emirati)--an ethnic group characterized by no alcohol intake and no cigarette smoking. We investigated a sample population of 254 Emirati, comprising 136 normotensive controls, and 118 patients with clinical diagnoses of EH. ACE G2350A alleles were visualized by assays based on polymerase chain reaction and restriction endonuclease analysis. The ACE G2350A dimorphism showed an association with EH (chi2=6.71, 2 df, P=0.05). Further analysis revealed that the ACE G/G 2350 genotype was positively associated (OR=1.06-3.07, P=0.02) with EH. This is the first association study of the ACE G2350A dimorphism with EH, and the positive result might indicate that ACE could be a QTL for EH as originally thought.

Genetic approaches to stature, pubertal timing, and other complex traits

The factors that regulate the timing of puberty remain largely elusive, as do the factors that modulate childhood growth and adult height. However, it is clear that these developmental processes are highly heritable--much of the natural variation in growth and timing of puberty is due to genetic variation within the population. In this review, we discuss how recent genetic and genomic advances can be exploited to help understand the genetic regulation of these processes. In particular, we describe how genome-wide linkage scans and association studies, in conjunction with haplotype-based approaches, are potentially useful tools to increase our understanding of these two complex traits. Discovery of the genetic variants that regulate these two traits would expand our understanding of human neuroendocrinology, postnatal development, and the general architecture of complex genetic traits.

Genome-wide linkage disequilibrium mapping of hypertension in Japan

Hypertension is a common, complex phenotype resulting from the interaction between genetic and environmental factors. To select candidate regions potentially responsible for hypertension, we are conducting a genome-wide linkage disequilibrium (LD) mapping of hypertension using dinucleotide repeat markers in 146 hypertensive and 136 normotensive subjects. Although the LD mapping is still underway, 19 alleles of 15 markers have already shown a nominally significant association (p<0.05), with odds ratios ranging from 0.08 to 5.12, suggesting the presence of many hypertension-related loci with weak effects in the human genome. These markers should be further assessed, adjusting for confounding factors and considering gene-gene and gene-environmental interactions in additional samples. In this report, we discuss our ongoing LD mapping project and describe the 15 markers thus far discovered. Among the 15 markers, D10S537 had a highly significant association with hypertension (p=5.3x10(-5); OR=3.80; 95% CI=1.98-7.27; where OR indicates the odds ratio and 95% CI indicates the 95% confidence interval). Further analysis in a large Japanese population showed that D10S537 was significantly associated with hypertension (p=0.044; OR=1.27; 95% CI=1.01-1.59). D10S537 was more significantly associated with hypertension in subjects with normotriglyceridemia in our population (p=0.007; OR=1.47; 95% CI=1.11-1.95).

Essential hypertension: genes and dreams

Herein we review all of the data from linkage by genome scanning and from association studies in essential hypertension. Genome scans have yielded loci linked to hypertension on almost every chromosome. We tabulate all of these loci to highlight the striking inconsistency. Similarly, association studies have implicated > 66 genes to date, which we also list, but virtually all have failed to show consistent replication in other settings. Nevertheless, we believe that molecular genetics should eventually find all of the major gene variants for essential hypertension. This will be a great scientific achievement and lead to new treatments. The dream, however, of using this information in clinical genetic testing could turn out to be a nightmare. Thus at present the hype surrounding genes for complex polygenic diseases like hypertension far exceeds the reality.

Variation near the region of the lipoprotein lipase gene and hypertension or blood pressure levels in Chinese

Essential hypertension (EH) is a common late-onset disease that exhibits complex genetic heterogeneity. Human lipoprotein lipase (LPL) is a rate-limiting enzyme that regulates the catabolism of triglycerides (TG) and chylomicrons (CM). Since dyslipidemia is a common finding in hypertensive patients, the LPL gene is a logical candidate gene that could contribute to the development of hypertension. Using linkage analysis in 148 Chinese hypertensive families, we identified a region of linkage with systolic blood pressure (SBP) and diastolic blood pressure (DBP) that consisted of a 10.6-cM interval defined by markers D8S1145, D8S261, and D8S282 on chromosome 8, which maps between 31 to 41.6 cM from the 8p-telomere contained LPL gene, with statistically significant p values for the marker D8S261 (p = 0.0021 for SBP, and p = 0.0395 for DBP). In the qualitative-trait linkage analysis, evidence for linkage between the marker D8S1145 and EH was found (p = 0.0286). The transmission/disequilibrium test (TDT/S-TDT) also supported a significant linkage-disequilibrium of the allele 3 of D8S261 with EH (chi2 = 8.643, p < 0.01). Furthermore, the marker neurofilament light polypeptide (NEFL) (11 cM centromeric to the LPL gene) appeared to be in linkage with SBP and DBP (p = 0.0329 for SBP; p = 0.0319 for DBP). Additionally, two flanking markers for LPL, D8S511 (9.5 cM telomeric to the LPL gene) and D8S560 (3.2 cM centromeric to the LPL gene), also showed significant linkage with EH (p = 0.0036 for D8S511; p = 0.0115 for D8S560). Previous knowledge about the physiological involvement of LPL in blood pressure regulation and the present findings of variation near the LPL gene support the proposition that a region near the LPL gene or the LPL gene itself might contribute to the individual blood pressure variation in Chinese.

Quantitative trait linkage studies of diabetes-related traits

Genetic linkage methods for diseases with complex inheritance are based on assessment of allele sharing between affected relative pairs, but such methods have low power to detect genes with moderate effects. This may explain the difficulty in replication for many of the putative loci for type 2 diabetes. To enhance power to detect diabetes-susceptibility genes, some investigators have performed quantitative-trait linkage studies for diabetes-related traits, including measures of glycemia, insulin sensitivity, insulin secretion, obesity, lipidemia, and blood pressure. These linkage studies have not provided stronger or more consistent evidence for linkage than studies of diabetes affection status, but have identified several loci that may play an important role in the physiologic processes related to the development of type 2 diabetes.

WNK kinases regulate thiazide-sensitive Na-Cl cotransport

Pseudohypoaldosteronism type II (PHAII) is an autosomal dominant disorder of hyperkalemia and hypertension. Mutations in two members of the WNK kinase family, WNK1 and WNK4, cause the disease. WNK1 mutations are believed to increase WNK1 expression; the effect of WNK4 mutations remains unknown. The clinical phenotype of PHAII is opposite to Gitelman syndrome, a disease caused by dysfunction of the thiazide-sensitive Na-Cl cotransporter. We tested the hypothesis that WNK kinases regulate the mammalian thiazide-sensitive Na-Cl cotransporter (NCC). Mouse WNK4 was cloned and expressed in Xenopus oocytes with or without NCC. Coexpression with WNK4 suppressed NCC activity by more than 85%. This effect did not result from defects in NCC synthesis or processing, but was associated with an 85% reduction in NCC abundance at the plasma membrane. Unlike WNK4, WNK1 did not affect NCC activity directly. WNK1, however, completely prevented WNK4 inhibition of NCC. Some WNK4 mutations that cause PHAII retained NCC-inhibiting activity, but the Q562E WNK4 demonstrated diminished activity, suggesting that some PHAII mutations lead to loss of NCC inhibition. Gain-of-function WNK1 mutations would be expected to inhibit WNK4 activity, thereby activating NCC, contributing to the PHAII phenotype. Together, these results identify WNK kinases as a previously unrecognized sodium regulatory pathway of the distal nephron. This pathway likely contributes to normal and pathological blood pressure homeostasis.

Fine mapping of autistic disorder to chromosome 15q11-q13 by use of phenotypic subtypes

Autistic disorder (AutD) is a complex genetic disease. Available evidence suggests that several genes contribute to the underlying genetic risk for the development of AutD. However, both etiologic heterogeneity and genetic heterogeneity confound the discovery of AutD-susceptibility genes. Chromosome 15q11-q13 has been identified as a strong candidate region on the basis of both the frequent occurrence of chromosomal abnormalities in that region and numerous suggestive linkage and association findings. Ordered-subset analysis (OSA) is a novel statistical method to identify a homogeneous subset of families that contribute to overall linkage at a given chromosomal location and thus to potentially help in the fine mapping and localization of the susceptibility gene within a chromosomal area. For the present analysis, a factor that represents insistence on sameness (IS)--derived from a principal-component factor analysis using data on 221 patients with AutD from the repetitive behaviors/stereotyped patterns domain in the Autism Diagnostic Interview-Revised--was used as a covariate in OSA. Analysis of families sharing high scores on the IS factor increased linkage evidence for the 15q11-q13 region, at the GABRB3 locus, from a LOD score of 1.45 to a LOD score of 4.71. These results narrow our region of interest on chromosome 15 to an area surrounding the gamma-aminobutyric acid-receptor subunit genes, in AutD, and support the hypothesis that the analysis of phenotypic homogeneous subtypes may be a powerful tool for the mapping of disease-susceptibility genes in complex traits.

Human chromosome 17 in essential hypertension

Hypertension affects up to 30% of the adult population in Western societies and is a major risk factor for kidney disease, stroke and coronary heart disease. It is a complex trait thought to be influenced by a number of genes and environmental factors, although the precise aetiology remains unknown at this time. A number of methods have been successfully used to identify mutations that cause Mendelian traits and these are now being applied to the investigation of complex diseases. This review summarises the data gathered, using such approaches, that suggest there is a gene or genes on chromosome 17 causing human essential hypertension. Studies in rodent models are discussed first, followed by studies of human hypertension that include the investigation of pseudohypoaldosteronism type II, a monogenic trait that manifests with hypertension alongside other phenotypic variables. In addition, candidate gene studies, genome screens and linkage studies based on comparative mapping are outlined. To date no gene has been identified on human chromosome 17 that influences blood pressure and causes human essential hypertension. However, results of ongoing fine mapping and candidate gene studies in both rodents and man are eagerly awaited.

Genetics of blood pressure, hypertensive complications, and antihypertensive drug responses

Hypertension is the most prevalent, treatable risk factor for diseases of the heart, brain and kidneys. In this review, we discuss advances in understanding of the genetics of blood pressure regulation, the development of hypertensive complications and the pharmacodynamics of antihypertensive drug responses. Discovery of single gene mutations that cause hypertension or hypotension in humans suggests that the common final pathway for regulation of blood pressure level is via alterations in renal sodium handling. Based on a working hypothesis that common genetic variations contributing to blood pressure variation in the population may also act on this same pathway, we summarize supporting evidence emerging from linkage and selected association studies of candidate genes--including those encoding components of the renin-angiotensin-aldosterone system, the epithelial sodium channel, adrenoceptors, G protein subunits, and other cellular signaling mediators and modifiers. We proceed to distinguish ischemic target organ complications due to arteriolosclerotic changes of the microvasculature from those due to atherosclerosis involving larger conduit and capacitance arteries. Using the example of subcortical white matter ischemia of the brain, we propose that interindividual variation in the arteriolosclerotic complications is more likely than atherosclerotic complications to be related to the same genetic (and environmental) mechanisms that contribute to hypertension. We conclude by summarizing the state-of-the-art of antihypertensive pharmacogenetics, which has succeeded in rejecting the null hypothesis that genetic variation does not influence blood pressure or protective target organ responses to drug therapy. In each of the three areas covered in this review, we indicate the many remaining obstacles to the routine clinical use of genetic measurements in the diagnosis, evaluation and treatment of hypertension.

Genome scan linkage results for heart rate variability (the Framingham Heart Study)

There is a substantial heritable component to the beat-to-beat variation in heart rate. However, the molecular mechanisms underlying the control of heart rate variability (HRV) remain unknown. The present study sought to identify chromosomal regions linked to HRV phenotypes. The first 2 hours of ambulatory electrocardiographic recordings obtained from Framingham Heart Study subjects attending a routine examination were processed for HRV. HRV variables analyzed included very-low-frequency power, low-frequency power, and high-frequency power. Gender-specific residuals were used for log-transformed HRV data after adjustment for age, HR, systolic and diastolic blood pressures, and coffee and alcohol consumption. In conjunction with a 10-cM genome-wide scan, HRV data were available for 725 subjects in 230 extended families, including 390 sibling pairs. Variance component log-of-the-odds (LOD) scores were obtained. The highest multipoint LOD scores were obtained for log very-low frequency on chromosome 15 at 62 cM (LOD 1.84) and for log low frequency on chromosome 2 at 153 cM (LOD 1.81). These data suggest there may be influential genetic regions contributing to HRV. Further studies are warranted to identify genes in these regions that may influence autonomic tone. Recognition of the genetic determinants of HRV may provide additional insights into the pathophysiology of the autonomic nervous system and offer clues to its modulation.

Genetics of essential hypertension: from families to genes

Family studies demonstrated the contribution of genetic factors to the development of primary hypertension. However, the transition from this phenomenologic-biometric approach to the molecular-genetic one is more difficult. This last approach is mainly based on the Mendel paradigm; that is, the dissection of the poligenic complexity of hypertension is brought about on the assumption that the individual genetic variants underlying the development of hypertension must be more frequent in hypertensive patients than in controls and must cosegregate with hypertension in families. The validity of these assumptions was clearly demonstrated in the so-called monogenic form of hypertension. However, because of the network of the feedback mechanisms regulating BP, it is possible that that the same gene variant may have an opposite effect on BP according to the genetic and environmental backgrounds. Independent groups of observations (acute BP response to saline infusion, incidence of hypertension in a population follow-up of 9 yr, age-related changes on BP) discussed in this review suggest a positive answer to this question. Therefore the impact of a given genetic variant on BP level must be evaluated within the context of the appropriate genetic epistatic interactions. A negative finding or a minor genetic effect in a general population may become a major gene effect in a subset of people with the appropriate genetic and environmental backgrounds.

A new essential hypertension susceptibility locus on chromosome 2p24-p25, detected by genomewide search

Essential hypertension (EH) is a complex disorder that results from the interaction of a number of susceptibility genes and environmental factors. We studied an isolated Sardinian village (Talana) in which the prevalence of hypertension is comparable to that in most Western populations. Talana exhibits features, such as slow demographic growth, high inbreeding, a low number of founders, stable lifestyle and culture, and accurate genealogical records, that make it suitable for the study of complex disorders. Clinical assessment of the entire adult population (N= approximately 1,000) identified approximately 100 hypertensive subjects. For our study, we selected the individuals with the most-severe EH (i.e., diastolic blood pressure >100 mm Hg), belonging to a single deep-rooted pedigree (12 generations), whose common ancestors lived in the 17th century. We performed a three-stage genomewide search using 36 affected individuals, by means of parametric linkage and allele-sharing approaches. LOD scores >1 were observed on chromosomes 1, 2, 13, 15, 17, and 19 (stage I). The most striking result was found in a 7.57-cM region on chromosome 2p24-p25. All five nonparametric linkage statistics estimated by the SimWalk2 program lie above the significance threshold of P<.008 for the whole region. Similar significance was obtained for 2p24-25 when parametric linkage (LOD score 1.99) and linkage disequilibrium mapping (P=.00006) were used, suggesting that a hypertension-susceptibility locus is located between D2S2278 and D2S168. This finding is strengthened by a recent report of linkage with marker D2S168 in a hypertensive sib-pair sample from China.

Genetics of leukoaraiosis

Computed tomography and magnetic resonance imaging of the brains of elderly individuals frequently show areas of altered signal intensity in the periventricular and subcortical white matter, referred to as leukoaraiosis. Although mildly affected individuals appear asymptomatic, larger burdens of leukoaraiosis are associated with deficits of cognition and gait. Histopathologically, areas of leukoaraiosis invariably show sclerosis, luminal narrowing, and tortuosity of small arteries and arterioles, accompanied by variable degrees of gliosis, demyelination, and axonal loss resulting from ischemia. Genetic variation plays a substantial role in interindividual differences in the volume of leukoaraiosis and its associated adverse clinical outcomes. Characterizing genetic factors contributing to interindividual differences in leukoaraiosis has the potential to enhance understanding of molecular determinants of ischemic brain injury and lead to new approaches to the diagnosis, evaluation, treatment, and prevention of this common form of vascular dementia.

Renal genetic disorders related to K+ and Mg2+

The recent knowledge of the renal epithelial transport systems has exploded with the identification, cloning, and characterization of a large number of membrane transport proteins. The fundamental aspects of these transporters are beginning to emerge at the molecular level and are summarized in the accompanying contributions in this volume of the Annual Review of Physiology. The aim of my review is to integrate this body of knowledge with the understanding of the clinical disorders of human mineral homeostasis that accompany gain, loss, or dysregulation of function of these transport systems. The specific focus is on the best defined human clinical syndromes in which there are derangements in K(+) and Mg(2+) homeostasis.

Extension of variance components approach to incorporate temporal trends and longitudinal pedigree data analysis

Here we present a method that permits one to evaluate genetic effects and to detect genetic linkages by using serial observations of quantitative traits in pedigrees. We developed a statistical method that incorporates longitudinal family data and genetic marker information into an estimating equations framework. With this approach, we can study changes in components over time that measure polygenic and major genetic variances as well as shared and individual-specific environmental effects. Our method provides a measure of heritability from analysis of longitudinal data. Results using longitudinal family data from the Center for Preventive Medicine (Nancy, France) are presented. The results of our analysis show that the apolipoprotein E locus has no effect on interindividual variability in systolic blood pressure. We found that the longitudinal measure of heritability of systolic blood pressure is 0.32.

Blood pressure QTLs identified by genome-wide linkage analysis and dependence on associated phenotypes

Understanding genetic factors that contribute to population-wide variation in blood pressure is likely to benefit prevention and treatment of cardiovascular disease. The aim of the Victorian Family Heart Study is to identify genes for cardiovascular risk in 783 volunteer adult families recruited from the general population. In this preliminary study we sought to identify quantitative trait loci (QTLs) using a genome-wide linkage analysis in 274 adult sibling pairs of average age 24 yr selected without respect to blood pressure. We compared multipoint linkage results for carefully measured systolic (SBP) and diastolic (DBP) pressures before and after statistical adjustment for covariation with sex, oral contraception, age, height, and weight. The average BP was 123/67 (SD: 12/11) mmHg in males (n = 283) and 114/64 (SD: 10/9) mmHg in females (n = 265). Nonparametric Z-scores from multipoint GeneHunter II analysis were "suggestive" (3.1 or more) at four QTLs for SBP (chromosomes 1, 4, 16, and X) but at no QTLs for DBP. Most Z-scores were affected little by adjustment for covariates. However, the SBP QTL on chromosome 16 was obvious only for unadjusted pressures. This population-based quantitative trait analysis has identified more QTLs than any of the eight previous genome-wide scans for blood pressure. Considerable discrepancies between different studies may reflect the presence of false-positive results or real biological differences between populations.

Serum potassium is not associated with blood pressure tracking in the Framingham Heart Study

BACKGROUND

Abnormal potassium homeostasis accompanies many secondary forms of hypertension as well as uncommon inherited, monogenic forms of hypertension. We hypothesized that serum potassium may be associated with longitudinal tracking of blood pressure (BP) and development of hypertension.

METHODS

A total of 2358 participants (1292 women, 1066 men) in the Framingham Heart Study who were free of hypertension, were not taking drugs affecting potassium homeostasis, and had serum potassium measured in 1979 to 1983 were followed for longitudinal tracking of BP and development of hypertension at examination 4 years later. Progression of BP stage was defined as an increment of one or more BP category, as defined by the sixth report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-VI), between baseline and follow-up examinations.

RESULTS

At baseline, there were no differences in systolic or diastolic BP across serum potassium quartiles. Over 4 years of follow up, 37% (457 women, 412 men) of subjects progressed by one or more JNC-VI BP category. In a logistic regression model adjusting for multiple confounders, serum potassium quartile was not associated with risk of BP progression. During follow-up, 14% (162 women, 175 men) of subjects progressed to hypertension. After adjustment for multiple confounders, there was no significant association between serum potassium quartile and risk for progression to hypertension.

CONCLUSIONS

In our community-based study sample, serum potassium was not associated with current BP, longitudinal BP tracking, or progression to hypertension.

Accelerated congenics for mapping two blood pressure quantitative trait loci on chromosome 10 of Dahl rats

OBJECTIVE

To localize quantitative trait loci (QTL) in an animal model that is potentially relevant to human hypertension.

DESIGN AND METHODS

Four congenic strains have been constructed by replacing various segments of the Dahl salt-sensitive (S) rat by those of the Lewis (LEW) rat. A marker-assisted approach was employed to facilitate this process. When these congenic strains were established, their blood pressures (BPs) were measured by telemetry and compared with that of the S rat. Moreover, a search was conducted to find possible intermediate phenotypes linking the BP effects of the QTL and other physiological traits.

RESULTS

Two BP QTL, designated as QTL1 and QTL2, have been mapped to the regions of 4.2 centiMorgans (cM) and less than 12.1 cM respectively on rat chromosome 10. The effects of both QTL correlate with cardiac, left ventricular and aortic hypertrophy. The effect of QTL1 is also associated with renal hypertrophy.

CONCLUSION

The current study proved that multiple QTL exist in the region of Dahl rat chromosome 10. The identification of these QTL may help unravel the mechanisms underlying the pathogenesis of certain QTL in humans.

Phenotypic and genetic heterogeneity of familial hyperkalaemic hypertension (Gordon syndrome)

1. Familial hyperkalaemic hypertension (FHH), also called pseudohypoaldosteronism type II (PHA2) or Gordon syndrome, is a rare Mendelian-form of low-renin hypertension. The first cases of FHH were reported approximately 30 years ago and they described the peculiar biochemical abnormalities (i.e. hyperkalaemia and hyperchloraemic acidosis despite a normal glomerular filtration rate). 2. Since then, more than 90 single cases and families have been reported in the literature. These various reports show marked differences in phenotype. 3. Our group has now collected 14 unrelated pedigrees originating from different parts of France and Europe. We confirm the large variations in the age of discovery and in the severity of the biochemical abnormalities from one individual to another and from one family to another one. 4. Blood pressure levels have no significant relationship with hyperkalaemia or hyperchloraemia, but there is a positive relationship with age, as in the normal population. 5. Analyses of clinical features and Mendelian segregation in our families demonstrate autosomal-dominant inheritance, as expected from the literature. 6. Efforts have been made in the past years to unravel the gene responsible for the disease. Until now, a primary responsibility of the gene encoding the thiazide-sensitive Na-Cl cotransporter (SLC12A3) has been excluded in PHA2 families. Three loci have been identified on chromosomes 1 (PHA2A), 17 (PHA2B) and 12 (PHA2C). 7. More recently, analysis of three additional pedigrees, including 10 affected subjects, with over 25 members allowed us to demonstrate further genetic heterogeneity and the existence of at least a fourth locus. 8. The genetic heterogeneity of this syndrome, and thus the variety of molecular defects, suggests the role of either several new components of the same pathway, multiple aldosterone- regulated effectors or direct or indirect partners of the Na-Cl cotransporter.

Genetic heterogeneity of familial hyperkalaemic hypertension

BACKGROUND

Familial hyperkalaemic hypertension (FHH) is a Mendelian form of low-renin hypertension characterized by hyperkalaemia and hyperchloraemic acidosis despite a normal glomerular filtration rate. To date, three different loci have been identified, on chromosomes 1, 17 and 12.

OBJECTIVE

To test for genetic linkage between the three FHH loci and three new affected kindreds.

DESIGN AND METHODS

Clinical, biological and genetic analyses were made of three kindreds, including 11 affected individuals among 25 members. Genotyping was performed using four series of microsatellite markers spanning the chromosomes 1, 17 and 12 loci, and the thiazide-sensitive Na-Cl cotransporter (SLC12A3) gene.

RESULTS

Segregation of the trait in each kindred was compatible with an autosomal transmission, the affected individuals displaying reasonably consistent biochemical abnormalities and the expected variability in arterial hypertension. Multipoint linkage analysis excluded linkage with the four candidate loci in kindreds 1 and 2, but not with the chromosome 1 locus in kindred 3.

CONCLUSION

These results demonstrate further genetic heterogeneity and that a fourth gene is responsible for FHH in at least two unrelated kindreds. They suggest a variety of molecular defects leading to FHH.

Human hypertension caused by mutations in WNK kinases

Hypertension is a major public health problem of largely unknown cause. Here, we identify two genes causing pseudohypoaldosteronism type II, a Mendelian trait featuring hypertension, increased renal salt reabsorption, and impaired K+ and H+ excretion. Both genes encode members of the WNK family of serine-threonine kinases. Disease-causing mutations in WNK1 are large intronic deletions that increase WNK1 expression. The mutations in WNK4 are missense, which cluster in a short, highly conserved segment of the encoded protein. Both proteins localize to the distal nephron, a kidney segment involved in salt, K+, and pH homeostasis. WNK1 is cytoplasmic, whereas WNK4 localizes to tight junctions. The WNK kinases and their associated signaling pathway(s) may offer new targets for the development of antihypertensive drugs.

From symptomatic treatments to causative therapy?

The search for genes that predispose individuals to develop common chronic diseases such as asthma, diabetes and Alzheimer's promises to give insights into their molecular pathogenesis. This will lead to the development of therapies that modulate the pathology, rather than the physiology of these diseases. As academia and the pharmaceutical industry increasingly focus on this challenge, the genetic dissection of Alzheimer's is spearheading attempts to shift the therapeutic paradigm away from symptomatic to curative treatments.

Linkage and association analysis of angiotensin I-converting enzyme (ACE)-gene polymorphisms with ACE concentration and blood pressure

Considerable effort has been expended to determine whether the gene for angiotensin I-converting enzyme (ACE) confers susceptibility to cardiovascular disease. In this study, we genotyped 13 polymorphisms in the ACE gene in 1,343 Nigerians from 332 families. To localize the genetic effect, we first performed linkage and association analysis of all the markers with ACE concentration. In multipoint variance-component analysis, this region was strongly linked to ACE concentration (maximum LOD score 7.5). Likewise, most of the polymorphisms in the ACE gene were significantly associated with ACE (P<.0013). The two most highly associated polymorphisms, ACE4 and ACE8, accounted for 6% and 19% of the variance in ACE, respectively. A two-locus additive model with an additive x additive interaction of these polymorphisms explained most of the ACE variation associated with this region. We next analyzed the relationship between these two polymorphisms (ACE4 and ACE8) and blood pressure (BP). Although no evidence of linkage was detected, significant association was found for both systolic and diastolic BP when a two-locus additive model developed for ACE concentration was used. Further analyses demonstrated that an epistasis model provided the best fit to the BP variation. In conclusion, we found that the two polymorphisms explaining the greatest variation in ACE concentration are significantly associated with BP, through interaction, in this African population sample. Our study also demonstrates that greater statistical power can be anticipated with association analysis versus linkage, when markers in strong linkage disequilibrium with a trait locus have been identified. Furthermore, allelic interaction may play an important role in the dissection of complex traits such as BP.