Segregation/Linkage Analysis for Hypertension

This study has been completed.
Information provided by:
National Heart, Lung, and Blood Institute (NHLBI) Identifier:
First received: May 25, 2000
Last updated: June 23, 2005
Last verified: June 2000

To determine the genetic components of hypertension using a series of simulation experiments designed to determine the power and validity of the then recently developed methods of segregation and linkage analysis.

Cardiovascular Diseases
Heart Diseases

Study Type: Observational

Resource links provided by NLM:

Further study details as provided by National Heart, Lung, and Blood Institute (NHLBI):

Study Start Date: July 1982
Estimated Study Completion Date: June 1991
Detailed Description:


There are two general hypotheses about the nature of the genetic component of hypertension. A single gene hypothesis visualizes hypertension as a specific disease entity determined by an autosomal dominant or incompletely dominant allele with little environmental effect. A polygenic hypothesis views hypertension as determined by a large number of genetic and environmental factors operating independently with roughly equal contributions. The evidence supporting the single gene hypothesis is based primarily on bimodal and trimodal distributions of blood pressure in the population. It has been suggested that the bimodal or trimodal distributions are the result of ascertainment bias. The evidence supporting the polygenic model is based on several studies where the distribution of blood pressure is unimodal and often skewed toward higher values in both the population and in first degree relatives of hypertensive individuals. These skewed distributions can be approximately normalized using log transformations.

In this study, a particular effort was made to detect major genes. A major gene is said to exist in a particular sample if an appreciable amount of the variability of a trait in that sample is due to segregation of alleles at a single locus. The presence of a major gene does not preclude the existence of other genetic or environmental effects. In the last decade three general models have been proposed to detect the presence of a major gene. The transmission probability model is a general model for the genetic analysis of pedigree data which tests for Mendelian segregation ratios and is a generalization of the traditional methods of segregation analysis. This model has little power to differentiate between single gene and polygenic inheritance although it may be able to detect some kinds of non-single gene transmission. This method has been extended to allow analysis of multivariate traits, testing of a wide variety of hypotheses concerning modes of transmission and various ascertainment corrections. Major genes identified with this model include hypercholesterolemia, dopamine-beta-hydroxylase, and catechol-o-methytransferase.

The mixed model includes both a single locus and a multi-locus component and is designed to distinguish between the two. The model assumes that all transmission from one generation to the next that cannot be accounted for by classical polygenic inheritance is due to segregation of alleles at a single locus. It is ideal for detecting a major gene in the presence of polygenic inheritance provided that no other type of transmission is occurring. This model has been extended to include an environmental correlation among sibs. Major loci identified with this model include PTC, IgE and congenital glaucoma. The unified model is a mixed model with the single locus component parameterized in terms of transmission probabilities, and is a combination of the two previous models. Several research groups have developed methodologies to overcome the computational difficulties presented by this combined model.


The study was divided into two parts, the analysis of the methodologies and the application of the methodologies in the genetic analysis of hypertension. In the first part of the study, the power, robustness, and validity of three genetic models of segregation and linkage analysis were considered: the transmission probability model; the mixed model; and the unified model which was also a mixed model with the single locus component parameterized in terms of transmission probabilities. The methods of segregation and linkage analysis found to be most satisfactory were then applied to the analysis of data on five large pedigrees in collaboration with Wright State University and to the analysis of ten large pedigrees ascertained as part of the Bogalusa Heart Study. A determination was made of the effects of partitioning large families into nuclear families and performing segregation and linkage on these nuclear families.


Genders Eligible for Study:   Male
Accepts Healthy Volunteers:   No

No eligibility criteria

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  More Information

Publications: Identifier: NCT00005158     History of Changes
Other Study ID Numbers: 1030
Study First Received: May 25, 2000
Last Updated: June 23, 2005
Health Authority: United States: Federal Government

Additional relevant MeSH terms:
Cardiovascular Diseases
Heart Diseases
Vascular Diseases processed this record on April 14, 2014