i2b2: Informatics for Integrating Biology & the Bedside - A National Center for Biomedical Computing
About Us Hypertension

Genetic Determinants Involved in The Pathogenesis of Human Hypertension

DBP Investigators

Principal Investigator:  Gordon H. Williams, M.D
Co-Investigators:  Lucila Ohno-Machado, M.D., Ph.D. and Robert Greenes, M. D., Ph.D.

Current Status:  Completed 2010

1. What questions did we ask in this DBP?

Can a complex “disease” like hypertension be classified into intermediate phenotypes – traits that are found to be present in some, but not all, hypertensive subjects? Are there unique haplotypes associated with these intermediate phenotypes? If so, then can genotyping be used to predict response to therapy in a population-based study and, ultimately, to target existing or develop new therapies specific for the individual intermediate phenotypes?

2. How did i2b2 help us answer these questions?

i2b2 will provide our team with a specialized data mart drawn from the Partners Research Patient Data Repository (RPDR) for comparison with the “gold standard” records on these same patients during intensive study under the controlled conditions of a GCRC. I2b2’s statisticians will analyze the phenotypic data for descriptive and predictive modeling and will bring its informatics expertise to the analysis of the genotyping and association with the extensive phenotyping.

3. What tools were developed from our work that will be of value to others?

Novel methods for viewing and exploring large collections of clinical data will be created by Core 2; novel tools for applying NLP methods to large clinical data resources will be created by experts from Core 1. All of these tools will be created specifically in response to our research needs, but they will all be generalized into the i2b2 CRC where they will be available to other researchers.

4. What new clinical discoveries arose from this work?

Identification of association or linkage with any of the genes studies would provide a major step toward unraveling the pathogenesis of this common disorder and potentially could provide a tool to identify subsets of the hypertensive population for specific therapeutic or preventative measures.


Knowledge that a large fraction of the populations' variation in blood pressure is genetically determined suggests the possibility of identifying the mutations which directly contribute to the pathogenesis of hypertension. Subdividing hypertensive patients by intermediate phenotypes may increase substantially the power of such genetic approaches. For eight years, with support from an NIH SCOR in Genetics of Hypertension, we have focused on the identification or definition of several traits to determine if they were likely intermediate phenotypes. Ten show the most promise. There are five unique features to our proposal. First, the routine use of intermediate phenotype; second state-of-the-art clinical research facilities -- General Clinical Research Centers; third, more extensive reliance on association analysis by comparing levels or changes in intermediate phenotypes among genotypes of our candidate genes; fourth documentation of genetic epistasis in our population when sub-grouped by intermediate phenotype. Finally, we have studied a large number of subjects. We have DNA, clinical and demographic data and some biochemical data from nearly 3000 individuals belonging to over 1700 pedigrees. Over 1100 of these underwent an extensive phenotyping protocol from which we obtained between 320 and 400 phenotypic data points on each subject. With funds from the SCOR, we have used principally a single polymorphism in our candidate genes to establish our genotype/phenotype relationship. To expand the number of genes and genotypes in our cohort, to analyze data and to extrapolate our results to the general hypertensive population, we will draw heavily on Cores 1 and 2 of this grant. With our data set, the continued support from the SCOR and the support of I2B2, we will be able to achieve the three-fold objectives of this project: 1)determine how intermediate phenotypes are related; 2)identify the gene(s) associated with these; and 3)determine the likelihood of genotype predicting phenotype for increased specificity for prevention and/or therapy.

Specific Aims:

Specific Aim 1. To evaluate biochemical and physiologic data to determine which factors cluster into intermediate phenotypes.

(1.1) Clinical research management system to bring all data together, including genotype data related to Specific Aim 2 below.
(1.2) Unsupervised and supervised learning models built from the data integrated in 1.1.

Specific Aim 2. To perform association and/or linkage analyses using defined intermediate phenotypes and candidate genes to determine if mutations in selected candidate gene loci contribute to the development of hypertension and/or intermediate phenotypes.

(2.1) Tool to select best SNPs and haplotype tags.
(2.2) Tool to document/disprove linkage/association between specific SNPs/haplotypes, and intermediate phenotypes; investigate epistasis.
(2.3) Tool to search literature to determine if any known phenotype/genotype associations.


· After drawing extensively on the resources of Cores 1 and 2 to “clean” the data and to analyze it using a number of statistical approaches, we have been successful in developing data on three intermediate subphenotypies: salt sensitive, non-modulation, and low renin hypertension. In each case, the goal was to determine if clinically obtained data would be useful to sub characterize hypertensives into heritable, and therefore more homogeneous, groups where we could then use genotype to predict therapeutic response. This work suggests that using clinical data will only be partially successful in identifying genetic markers for salt-sensitive hypertension. Analyses are still underway on low renin and non-modulation hypertension.

· Analysis is currently underway on 35 genes comprising 786 SNPs. Targeting was informed by prior work, haplotype association with known physiological pathways, and advice from Dr. Inna Dubchak using the enhanced VISTA system to identify evolutionarily conserved non-coding regions of interest.

New Awards Deriving from this project:

R01 HL094452: Aldosterone, HIstone Demethylase and Cardiovascular Disease.  PI Gordon Williams, MD.

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