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Brief Rapid Communication
Genome-Wide Linkage Analyses of Systolic Blood Pressure
Using Highly Discordant Siblings
Julia Krushkal, PhD; Robert Ferrell, PhD; Stephen C. Mockrin, PhD; Stephen T. Turner, MD;
Charles F. Sing, PhD; Eric Boerwinkle, PhD
Downloaded from http://circ.ahajournals.org/ by guest on August 11, 2017
Background—Elevated blood pressure is a risk factor for cardiovascular, cerebrovascular, and renal diseases. Complex
mechanisms of blood pressure regulation pose a challenge to identifying genetic factors that influence interindividual
blood pressure variation in the population at large.
Methods and Results—We performed a genome-wide linkage analysis of systolic blood pressure in humans using an
efficient, highly discordant, full-sibling design. We identified 4 regions of the human genome that show statistical
significant linkage to genes that influence interindividual systolic blood pressure variation (2p22.1 to 2p21, 5q33.3 to
5q34, 6q23.1 to 6q24.1, and 15q25.1 to 15q26.1). These regions contain a number of candidate genes that are involved
in physiological mechanisms of blood pressure regulation.
Conclusions—These results provide both novel information about genome regions in humans that influence interindividual
blood pressure variation and a basis for identifying the contributing genes. Identification of the functional mutations in
these genes may uncover novel mechanisms for blood pressure regulation and suggest new therapies and prevention
strategies. (Circulation. 1999;99:1407-1410.)
Key Words: hypertension n blood pressure n genetics n genes
E
levated blood pressure of unknown origin is a common
risk factor for cardiovascular disease, stroke, end-stage
renal disease, and peripheral vascular disease.1,2 The contributors to elevated blood pressure are poorly understood, but
multiple lines of evidence have implicated both genetic and
environmental factors.3 Studies aimed at identifying the genes
that contribute to interindividual blood pressure variation
have been limited to candidate genes; the results have proven
informative but not always consistent.4 Investigations of
several rare mendelian forms of high blood pressure, such as
Liddle syndrome,5 have revealed causative mutations, but
their very low frequency diminishes their public health
impact. An alternative approach is to use genetic linkage
analyses to systematically evaluate the human genome for
segments that contain genes that influence blood pressure
levels.
Genome-wide genetic linkage studies for complex traits
pose several challenges that require careful study design
and analysis. Although these traits aggregate in families,
they do not segregate in any clear mendelian fashion as a
result of there being multiple contributing genes, each with
polymorphic allele frequencies and small to moderate
effects. In this report, we describe the results of using
modern genome-wide linkage analysis methods and an
efficient discordant sib pair design6,7 to localize genes that
affect interindividual systolic blood pressure (SBP)
variation.
Methods
These analyses were performed as part of the GENOA Network of
the Family Blood Pressure Program and were based on data
collected on 3974 members of 583 multigeneration pedigrees
from Rochester, Minn, ascertained without regard to health
status.8 SBP levels were measured for each individual 3 times $2
minutes apart with a random-zero sphygmomanometer, and the
average of these 3 readings was used for the linkage analyses
reported herein. Fifty-five pedigrees with 1 or more full siblings
above the sex- and age-specific 80th percentile and 1 or more full
siblings below the sex- and age-specific 20th percentile of the
SBP distribution were identified from the sample of 583 pedigrees. These pedigrees contained 69 discordant full-sibling pairs.
The two discordant groups of siblings were not significantly
different (P.0.05) for average age (mean, 16 years), weight
(mean, 57 kg), height (mean, 162 cm), and body mass index
(mean, 21 kg/m2) or for gender prevalence (51% male). All 427
individuals in the 55 pedigrees were genotyped for 359 highly
polymorphic marker loci located on the 22 human autosomes
Received October 19, 1998; revision received December 22, 1998; accepted January 25, 1999.
From the Institute of Molecular Medicine (J.K., E.B.) and the Human Genetics Center (E.B.), University of Texas–Houston Health Science Center,
Houston, Tex; Department of Human Genetics (R.F.), University of Pittsburgh, Pittsburgh, Pa; National Heart, Lung, and Blood Institute (S.C.M.),
Bethesda, Md; Division of Hypertension (S.T.T.), Department of Internal Medicine, Mayo Clinic, Rochester, Minn; and Department of Human Genetics
(C.F.S.), University of Michigan, Ann Arbor, Mich.
Guest Editor for this article was Joseph Loscalzo, MD, Boston University Medical Center, Boston, Mass.
Detailed results of the genome-wide linkage analyses discussed in this article can be found on the World Wide Web at http://www.circulationaha.org
Correspondence to Eric Boerwinkle, PhD, Human Genetics Center, University of Texas–Houston Health Science Center, PO Box 20334, Houston, TX
77225. E-mail [email protected]
© 1999 American Heart Association, Inc.
Circulation is available at http://www.circulationaha.org
1407
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Genome-Wide Analyses of Systolic Blood Pressure
Significant and Suggestive Genomic Regions Containing Genes
Affecting SBP Variation
Lowest P Value
of the Peak
Nearby
Markers
t
Chromosome
,0.0001
23.96
6
4 cM distal
to D6S1009
0.0033
22.80
15
3 cM distal
to D15S652
0.0076
22.49
5
At D5S1471
0.0089
22.43
2
At D2S1788
0.0160
22.19
18
At D18S843
0.0171
22.16
9
At D9S301
0.0193
22.11
2
2 cM distal
to D2S441
0.0234
22.02
21
At D21S1446
0.0240
22.01
20
3 cM proximal
to D20S478
0.0309
21.90
5
1 cM proximal
to D5S817
0.0314
21.89
16
5 cM distal
to D16S402
0.0353
21.84
2
At D2S1334
Significant P,0.01
Suggestive
0.01,P,0.05
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(Research Genetics). Genotyping was performed by standard
methods with an Applied Biosystems/Perkin Elmer 377 automatic
DNA sequencer.
Genotypes from all 427 individuals were used to calculate the
multipoint identity by descent probabilities every 1 centimorgan
(cM) by use of the hidden Markov model method.9 Marker order
and genetic distances were provided by the CHLC/Weber screening set versions 8.0 and 6.0 (Research Genetics) and the Marshfield Medical Research Foundation (Marshfield, Wis). Genetic
linkage between the marker and trait loci was assessed with the t
statistic of Risch and Zhang.7 We compared identity by descent
sharing among the 69 discordant sibling pairs with that expected
under the null hypothesis of no linkage. Significance levels
(probability values) were determined from a 1-sided Student’s t
test with 68 degrees of freedom. Probability values ,0.01 were
considered significant, and probability values between 0.01 and
0.05 were considered suggestive. The reader should be cautioned,
however, that all results, significant or not, should be confirmed
in a similar population before definite conclusions are drawn.
Detailed results for each chromosome are not provided in this
brief communication. Rather, they may be obtained on the World
Wide Web (http://www.circulationaha.org) or by writing the
communicating author (E.B.)
Results
Detailed results of the genome-wide linkage analyses are
provided at http://www.circulationaha.org. Multipoint linkage analyses of the 22 autosomes identified 4 regions that
showed significant linkage to genes that influence SBP
variation (P,0.01) and 8 regions that showed suggestive
linkage (0.01,P,0.05). The genomic location of these
regions is described in the Table. The 12 regions are located
on 9 chromosomes (chromosomes 2, 5, 6, 9, 15, 16, 18, 20,
and 21). The 4 regions of particular interest by virtue of
having probability values ,0.01 are located on chromosomes
2, 5, 6, and 15.
The region with the greatest significance level rejecting
the null hypothesis of no linkage between a marker locus
and a gene influencing SBP variation was located on
chromosome 6 (P50.00009; t523.96) between markers
D6S1009 and D6S1003 (Figure, panel A). An interval 4
cM in length between positions 143 and 146 cM on
chromosome 6 had a P value of #0.0001. A 12-cM
interval on chromosome 6 between map positions 134 and
155 cM had P values ,0.01. On chromosome 15 at map
position 97 cM from the tip of the short arm, the significance level was 0.0033 (t522.80), and the region between
map positions 84 and 101 cM had a level of significance
,0.01 (panel B). At the distal end of the long arm of
chromosome 5, the position of marker D5S1471 had a
significance level of 0.0076 (t522.49) (panel C). Each
position between 188 and 192 cM from the beginning of
the chromosome 5 linkage map had a probability value
,0.01. On chromosome 2, the position of marker D2S1788
had a P value of 0.0089 (t522.43), and the map positions
between 57 and 59 cM from the beginning of the chromosome 2 linkage map had a probability value ,0.01
(panel D).
Discussion
We report herein the results of the first genome-wide
linkage analysis for genes that influence interindividual
blood pressure variation in humans. This analysis identified several regions that are likely to contribute to genetic
differences in SBP levels. Regions 2p22.1 to 2p21, 5q33.3
to 5q34, 6q23.1 to 6q24.1, and 15q25.1 to 15q26.1 on
chromosomes 2, 5, 6, and 15, respectively, are significantly linked to genes that influence interindividual SBP
differences. These regions contain a number of known
genes, shown in the Figure, the products of which have
previously been suggested to affect blood pressure regulation at the physiological level. These genes code for
proteins involved in a variety of blood pressure– controlling systems, vascular smooth muscle tone, natriuresis,
cellular calcium homeostasis, and hormonal and neural
regulation of the renin-angiotensin system. For example,
the product of the aminopeptidase N gene on chromosome
15 regulates vasopressin release via the mechanism of the
N-terminal cleavage of angiotensin III.10 DNA sequence
variants in these known genes and in nearby anonymous
expressed sequence tags are candidates for contributing to
interindividual blood pressure variation in the population
at large by virtue of their positions within the region
identified by linked marker loci.
Our analysis also identified regions of the genome and
candidate genes that are likely not to have a major impact
on interindividual SBP variation in this population. Chromosome 8, for example, provided no evidence that it
contains a gene that affect interindividual SBP variation.
Each position on this chromosome had a P value between
0.57 and 1.0. As reported previously by other investigators
using a candidate-gene approach, the renin gene on chromosome 1 did not yield any evidence for linkage to SBP
Krushkal et al
March 23, 1999
1409
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Significant genome region identified by highly discordant sibling linkage design. Thin dotted lines indicate values of t statistic, whereas
bold lines show significance levels for deviation of observed identity by descent sharing from that expected under the null hypothesis
of no linkage (P values). Black triangles flank the regions with P,0.01. Location intervals for candidate genes are shown by bold horizontal lines on top of each panel. A, Chromosome 6 region. PLN indicates phospholamban; ESR, estrogen receptor. B, Chromosome
15 region. ANPEP indicates aminopeptidase N. C, Chromosome 5 region. ADRA1B indicates a1B-adrenergic receptor; DRD1A, dopamine receptor type 1A. D, Chromosome 2 region. CALM2 indicates calmodulin 2; NCX1, sodium-calcium exchanger 1. Candidate-gene
locations were obtained from the Genome Database (http://www.gdbwww.gdb.org) and the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov).
(P.0.13). Such negative results, however, should be
interpreted with caution in light of the low power of
genetic exclusion analyses for complex quantitative traits,
such as blood pressure.11
We considered a probability value of ,0.01 in a region
to be statistically significant. This is the same probability
value suggested by others (eg, Rao12) for identifying
regions for further investigation. We realize that this
probability value for identification of regions of interest
for positional candidate-gene analysis is greater than that
suggested by Lander and Kruglyak.13 However, as discussed by many, such extreme probability values overemphasize the statistical interpretation or evaluation of a
single study and will promote type II inferential errors (ie,
failure to detect a blood pressure– controlling gene when it
is really there). In addition, confident identification of
linked regions, regardless of probability values, should not
come from any single study but rather as the result of
confirmation of linkage among similar populations of
inference. Ultimately, however, the contributing genes
must be identified and functional mutations characterized
so that the underlying molecular and physiological mechanisms that relate gene variation to blood pressure variation can be unveiled.
The results of this genome-wide linkage analysis of SBP
provide a focus for future genetic studies. First, this study has
identified chromosomal regions now hypothesized to contain
blood pressure– controlling genes, which requires verification
and additional testing. Second, it focuses the search for and
cloning of new blood pressure–regulating genes. Finally, it
provides a list of genes for detailed DNA sequence analyses
aimed at identifying functional mutations that affect SBP
variation. Identification of genes that contribute to blood
pressure levels will provide a better understanding of the
origin of high blood pressure and establish a basis for the
development of improved prevention and treatment regimens.
The data reported herein on the genetic contributors to
interindividual SBP variation have implications not only for
our understanding of high blood pressure but also for our
understanding of the factors that contribute to its complications, such as cardiovascular, cerebrovascular, and renal
diseases.
Acknowledgments
This study was supported by NIH grants HL-39107, HL-51021,
HL-54481, HL-54457, and HL-54464 from the National Heart,
Lung, and Blood Institute.
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Genome-Wide Analyses of Systolic Blood Pressure
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Genome-Wide Linkage Analyses of Systolic Blood Pressure Using Highly Discordant
Siblings
Julia Krushkal, Robert Ferrell, Stephen C. Mockrin, Stephen T. Turner, Charles F. Sing and Eric
Boerwinkle
Downloaded from http://circ.ahajournals.org/ by guest on August 11, 2017
Circulation. 1999;99:1407-1410
doi: 10.1161/01.CIR.99.11.1407
Circulation is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231
Copyright © 1999 American Heart Association, Inc. All rights reserved.
Print ISSN: 0009-7322. Online ISSN: 1524-4539
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http://circ.ahajournals.org/content/99/11/1407
Data Supplement (unedited) at:
http://circ.ahajournals.org/content/suppl/1999/03/15/99.11.1407.DC1
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