AJP - Heart Calcium Transients and Cell-Sarcomere
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Am J Physiol Heart Circ Physiol 293: H3366-H3371, 2007. First published October 5, 2007; doi:10.1152/ajpheart.00042.2007
0363-6135/07 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental Tables
Right arrow All Versions of this Article:
293/6/H3366    most recent
00042.2007v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Spielmann, N.
Right arrow Articles by Bouchard, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Spielmann, N.
Right arrow Articles by Bouchard, C.

Genome-wide linkage scan for submaximal exercise heart rate in the HERITAGE family study

Nadine Spielmann,1 Arthur S. Leon,2 D. C. Rao,3,4 Treva Rice,3 James S. Skinner,5 Tuomo Rankinen,1 and Claude Bouchard1

1Pennington Biomedical Research Center, Human Genomics Laboratory, Louisiana State University System, Baton Rouge, Louisiana; 2School of Kinesiology, University of Minnesota, Minneapolis, Minnesota; 3Division of Biostatistics and 4Departments of Genetics and Psychiatry, Washington University School of Medicine, St. Louis, Missouri; and 5Department of Kinesiology, Indiana University, Bloomington, Indiana

Submitted 10 January 2007 ; accepted in final form 3 October 2007


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
The purpose of this study was to identify regions of the human genome linked to submaximal exercise heart rates in the sedentary state and in response to a standardized 20-wk endurance training program in blacks and whites of the HERITAGE Family Study. A total of 701 polymorphic markers covering the 22 autosomes were used in the genome-wide linkage scan, with 328 sibling pairs from 99 white nuclear families and 102 pairs from 115 black family units. Steady-state heart rates were measured at the relative intensity of 60% maximal oxygen uptake (HR60) and at the absolute intensity of 50 W (HR50). Baseline phenotypes were adjusted for age, sex, and baseline body mass index (BMI) and training responses (posttraining minus baseline, {Delta}) were adjusted for age, sex, baseline BMI, and baseline value of the phenotype. Two analytic strategies were used, a multipoint variance components and a regression-based multipoint linkage analysis. In whites, promising linkages (LOD > 1.75) were identified on 18q21-q22 for baseline HR50 (LOD = 2.64; P = 0.0002) and {Delta}HR60 (LOD = 2.10; P = 0.0009) and on chromosome 2q33.3 for {Delta}HR50 (LOD = 2.13; P = 0.0009). In blacks, evidence of promising linkage for baseline HR50 was detected with several markers within the chromosomal region 10q24-q25.3 (peak LOD = 2.43, P = 0.0004 with D10S597). The most promising regions for fine mapping in the HERITAGE Family Study were found on 2q33 for HR50 training response in whites, on 10q25-26 for baseline HR60 in blacks, and on 18q21–22 for both baseline HR50 and {Delta}HR60 in whites.

exercise training; linkage; quantitative trait loci; genotype

IN RECENT YEARS, a large body of evidence has clearly established sedentarism as a risk factor for a number of diseases that become more prevalent with age in both sexes. In contrast, physical activity regularly performed in a variety of settings is considered beneficial because of favorable metabolic and cardiovascular outcomes (9, 17, 30, 31, 37, 49). Previous studies have shown associations between elevated heart rate (HR) at rest and increased risk of both all-cause and cardiovascular mortality (7, 18, 21, 22, 25, 26, 33). Although HR during submaximal exercise is known to decrease in response to regular endurance training (16, 51), its recovery after maximal and submaximal exercise is considered a powerful predictor of mortality (14, 15). However, interindividual differences in training-induced changes in HR are considerable.

In the Health, Risk Factors, Exercise Training and Genetics (HERITAGE) Family Study, the steady-state HR at the absolute intensity of 50 W (HR50) and relative intensity of 60% (HR60) of maximal oxygen uptake (VO2max) were significantly reduced after 20 wk of endurance training (51). The maximal heritability estimates for baseline HR50 and HR60 reached 59 and 46%, respectively. The maximal heritabilities were 34 and 29% for {Delta}HR50 and {Delta}HR60, respectively, for the changes in response to a 20-wk endurance training program ({Delta}, posttraining minus baseline) (5). Furthermore, complex segregation analysis supported the hypothesis of a major recessive gene effect on baseline HR50 and a major dominant gene effect on {Delta}HR50 in the same families (4).

The identification of the genes and mutations affecting exercise HR would lead to a better understanding of the biology of adaptation to exercise. The objective of this study was to perform a genome-wide linkage scan for HR50 and HR60 measured in the sedentary state and in response to a 20-wk endurance training program in the HERITAGE Family Study.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Subjects. The HERITAGE Family Study design, inclusion criteria, and protocol have been described previously (8). A total of 503 white subjects (245 men and 258 women) from 99 nuclear families and 276 black subjects (91 men and 185 women) from 115 family units were included. Complete training response data were available for 472 whites (229 men and 243 women) and 254 blacks (88 men and 166 women). The maximum number of sibling pairs available was 328 and 102 in whites and blacks, respectively. All subjects were healthy and sedentary at baseline. Sedentary was defined as no regular physical activity over the previous 6 mo. The study protocol was approved by the Institutional Review Boards at each of the five participating centers of the HERITAGE Family Study consortium. Written informed consent was obtained from each participant.

Exercise training program. Subjects completed a 20-wk endurance training program (3 days per week for a total of 60 exercise sessions) under supervision using Universal Aerobicycles (Cedar Rapids, IA), which were monitored electronically by the Fit Net system to maintain the participants' HR at levels associated with fixed percentages of their VO2max. The training program started at 55% of VO2max for 30 min per session and gradually increased to 75% of VO2max for 50 min per session during the last 6 wk of training. All training sessions were supervised on site, and adherence to the protocol was strictly monitored.

Submaximal exercise test. Before and after the 20-wk training program, each subject completed two submaximal exercise tests on separate days. Submaximal exercise tests at 50 W and at 60% of VO2max were conducted on a cycle ergometer. Subjects exercised 8–12 min at an absolute work load of 50 W and at a relative power output equivalent to 60% of VO2max, with a 4-min period of seated rest between the exercise periods. HR was monitored throughout the test with an electrocardiogram, and two HR values were recorded once steady state had been achieved. The HR values presented in this article represent the mean of two submaximal tests (i.e., 4 individual measurements), both before and after training. A detailed description of the exercise test methodology has been reported previously (46). The reproducibility of the submaximal exercise HR measurements was very high, with coefficients of variation and intraclass correlations ranging from 4.4 to 5.1% and 0.88 to 0.89, respectively (52).

Data adjustment. Baseline HR50 and HR60 measurements were adjusted for the effects of sex, age, and body mass index (BMI) using stepwise multiple regressions (42). Training response phenotypes were additionally adjusted for baseline value of the phenotype. In summary, HR50 and HR60 phenotypes were regressed on up to a third-degree polynomial in age and on BMI (separately within race-by-gender-by-generation subgroups). Only significant terms (5% level) were retained (i.e., the model did not need to be saturated). The residuals from this regression were then standardized to zero mean and unit variance and constituted the analysis variables.

Molecular studies. A total of 701 markers covering the 22 autosomes with a mean spacing of 4.1 Mb on the physical map were used. PCR conditions and genotyping methods have been reported previously (12). DNA sequencers from LI-COR were used to detect the PCR products, and genotypes were scored semiautomatically using the software SAGA. Incompatibilities of Mendelian inheritance were checked, and markers showing incompatibilities were regenotyped (<10% were retyped). Microsatellite markers were selected mainly from the Marshfield panel version 8a. In addition to this panel of markers, some restriction fragment length polymorphism (RFLP) markers were integrated in the scan. These RFLPs included candidate genes relevant for HERITAGE phenotypes such as submaximal HR. Map locations of the markers were taken from the Build 35 of the National Center for Biotechnology Information (NCBI) physical map.

A quantitative trait loci (QTL) of interest on chromosome 10q25 included two potential candidate genes, the adrenergic receptors {alpha}2A (ADRA2A) and β1 (ADRB1), which were further investigated by genotyping 16 linkage disequilibrium bin tagging single-nucleotide-polymorphisms (tagSNP) from the SeattleSNP database (http://pga.mbt.washington.edu/; see Supplemental Tables 1 and 2 for details). (Supplemental data for this article is available at the American Journal of Physiology-Heart and Circulatory Physiology website.) SNP genotyping was performed using a primer extension method with fluorescence polarization detection (FP-TDI). Changes in fluorescence polarization after excitation of the samples by plane-polarized light were measured using a Victor2 plate reader (PerkinElmer Life Sciences). The allele calling was done using the SNPscorer genotyping software (PerkinElmer Life Sciences).


View this table:
[in this window]
[in a new window]

  		Table 1. Descriptive characteristics of white and black subjects of the HERITAGE Family Study

 

View this table:
[in this window]
[in a new window]

  		Table 2. Promising linkages with submaximal HR at baseline and in response to training in whites

 
Statistical analyses. Linkage analysis was performed using multipoint variance components and regression-based models as implemented in MERLIN (2). Under the variance components model, a phenotype is influenced by the additive effects of a trait locus (g), a residual familial background modeled as a pseudopolygenic component (GR), and a residual nonfamilial component (r). The effects of the trait locus and the pseudopolygenic component on the phenotype represent the locus-specific (h2g) and residual genetic (h2r) heritabilities. The linkage hypothesis is tested by restricting the trait locus heritability to zero. A likelihood ratio test contrasts the null hypothesis (h2g = 0) with the alternative (h2g estimated). The difference in –2 ln L (minus twice the log likelihood) between the null and alternate hypotheses is asymptotically distributed as a 50:50 mixture of a {chi}12 and a point mass at zero, and the P value is one-half of that associated with the {chi}2 value with 1 df (difference in the number of parameters estimated) (2). All analyses were conducted separately in blacks and whites. Promising linkage was defined as logarithm of the odds (LOD) >1.75 (P < 0.0023) as recommended by Rao and Province (41).

As a follow-up of the linkage signal observed on chromosome 10q25 in blacks, association studies were performed using 6 and 10 tagSNPs on ADRA2A and ADRB1 loci, respectively. Associations were explored using two complementary methods: a variance components and likelihood ratio test-based procedure in the QTDT software package and a MIXED model-based procedure in the SAS software package. The total association model of the QTDT software utilizes a variance-components framework to combine a phenotypic means model and the estimates of additive genetic, residual genetic, and residual environmental variances from a variance-covariance matrix into a single-likelihood model (1). The evidence of association is evaluated by maximizing the likelihoods under two conditions: the null hypothesis (L0) restricts the additive genetic effect of the marker locus to zero (βa = 0), whereas the alternative hypothesis does not impose any restrictions to βa. The quantity of twice the difference of the log likelihoods between the null and the alternative hypotheses, 2[ln(L1) – ln(L0)], is distributed as {chi}2 with 1 df. A dominance effect can be tested in a similar manner, but the alternative hypothesis model includes estimates for both additive (βa) and dominant (βa x βa) genetic effects, and the likelihood ratio test is based on {chi}2 distribution with 2 df (1). In the MIXED model, nonindependence among family members was adjusted for by using a sandwich estimator, which asymptotically yields the same parameter estimates as ordinary least squares or regression methods, but the SEs and, consequently, hypothesis tests are adjusted for the within-family dependencies. The method is general, assuming the same degree of dependency among all members within a family. The pairwise linkage disequilibrium (LD) between the SNPs was assessed using the ldmax program available in the GOLD software package (1).


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
The descriptive characteristics of 503 white and 276 black subjects are presented in Table 1. Pre- and posttraining data for HR50 and HR60 in the HERITAGE Family Study have been described and discussed elsewhere (51).

In whites, the strongest evidence of linkage for baseline HR50 was detected on chromosome 18q21.33 (LOD = 2.64, P = 0.0002) (Fig. 1). In addition, promising linkage for {Delta}HR50 was detected on chromosome 2q33.3 (LOD = 2.13, P = 0.0009) and for {Delta}HR60 on chromosome 18q21.1 (LOD = 2.10, P = 0.0009) (Table 2). In blacks, five markers within the chromosomal region 10q24–q25.3 showed evidence of linkage for baseline HR60 with peak linkage detected with marker D10S597 (LOD = 2.43, P = 0.0004). Further evidence of linkage with baseline HR50 was found on chromosomes 3q11.1–12.3 (LOD = 1.88, P = 0.002), 9q32–33.1 (LOD = 1.93, P = 0.001), and 10q25.1 (LOD = 1.84, P = 0.002) (Table 3).


Figure 1
View larger version (26K):
[in this window]
[in a new window]

  		Fig. 1. Linkage (LOD) results on chromosome 18 for baseline heart rate at 50 W (B_HR50) in black and white subjects and heart rate at 60% of maximal oxygen uptake (VO2max) training response (D_HR60) in white subjects. LOD, logarithm of the odds.

 

View this table:
[in this window]
[in a new window]

  		Table 3. Linkages for baseline submaximal HR phenotypes in blacks

 
The QTLs for baseline HR50 and HR60 on chromosome 10q25 detected in blacks (Fig. 2) harbor two excellent candidate genes for exercise HR: adrenergic receptors β1 (ADRB1) and {alpha}2A (ADRA2A). We performed association tests using 6 ADRA2A and 10 ADRB1 SNPs in black subjects. The Arg389Gly (rs1801253) variant in the ADRB1 locus was associated with baseline HR50 in siblings (P = 0.02 MIXED model; P = 0.03 QTDT dominance model) and in the whole cohort (P = 0.04 MIXED model). No significant association was found between the Arg389Gly (rs1801253) and baseline HR60.


Figure 2
View larger version (26K):
[in this window]
[in a new window]

  		Fig. 2. Linkage results for baseline heart rate at 50 W (HR50) and 60% VO2max (HR60) on chromosome 10 in black subjects. VC, multipoint variance-components linkage analysis; Reg, regression-based multipoint linkage analysis.

 
The linkage model of the QTDT captured the same linkage signal with the ADRA2A and ADRB1 tagSNPs for baseline HR50 as did the original genome-wide linkage scan. When the association parameter was added to the model, the signal at the ADRA2A locus remained virtually unchanged. However, at the ADRB1 locus, the signal weakened from LOD = 2.07 to LOD = 0.62 at Arg389Gly (rs1801253), suggesting that the SNP may explain a substantial portion of the QTL variance (Fig. 3).


Figure 3
View larger version (13K):
[in this window]
[in a new window]

  		Fig. 3. Results of the QTDT software linkage model with and without an association term for baseline HR50. Evidence of linkage with Arg389Gly in the ADRB1 (adrenergic receptor β1) gene considerably weakened when the association term is included in the model, suggesting that Arg389Gly partially explains the linkage with baseline HR50. ADRA2, adrenergic receptor {alpha}2A.

 

   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
A genome-wide search for QTLs influencing submaximal exercise HR50 and HR60 before and in response to a 20-wk endurance training program was undertaken in the HERITAGE Family Study. This is the first study attempting to localize genomic regions affecting submaximal exercise HR. Identifying QTLs and resolving them in terms of genes and mutations would benefit our understanding of basic human exercise physiology.

We identified QTLs on chromosome 18q21–22 for baseline HR50 and HR60 training responses and on chromosome 2q33 for training-induced changes in HR50 in whites. Furthermore, we detected promising linkage signals within the chromosomal region 10q24–q25.1 for baseline HR50 and HR60 in the black HERITAGE Family Study cohort. So far, no other genome-wide linkage scans are available for submaximal exercise HR phenotypes that could be used to compare our results. However, the HyperGen Study reported a QTL for resting HR on chromosome 10q24–q25 near the QTL for sedentary state submaximal exercise HR found in black HERITAGE families (50).

The regulation of the cardiovascular system is under tight control to establish and maintain homeostasis. G protein-coupled receptor signaling is an important component of this regulation. Adrenergic receptors (ARs) are a member of the superfamily G protein-coupled receptors, which bind epinephrine and norepinephrine, thereby mediating their intracellular effects (20). The activation of {alpha}2A-ARs in the brain stem leads to a reduction in sympathetic tone, with a resultant decrease in HR and blood pressure (3, 27). {alpha}2A-ARs are the principle regulators of catecholamine release, and their absence results in altered sympathetic regulation due to loss of {alpha}2A-mediated inhibition of 1) sympathetic tone in the brain stem and 2) catecholamine release from the sympathetic nerve terminus (3). β1-ARs are key mediators of the sympathetic inotropic and chronotropic effects in the heart response to catecholamines (10, 36). Furthermore, β1-ARs play a dominant role in adrenergic-mediated increases in HR by regulating contractility, and their absence results in a decrease in the average HR (19). A nonsynonymous polymorphism, Arg389Gly, has been detected in the coding region of the β1-AR gene (48). In vitro, the wild-type Arg389 form produces increased high-affinity agonist binding and enhanced adenylyl cyclase activities compared with the 389Gly form (32, 34, 47). In addition, the Arg389 variant has been reported to have greater inotropic and cAMP responses to norepinephrine than the 389Gly variant (44), but others have not confirmed these genotype-dependent differences (35, 45). Although higher resting HR has been reported in siblings homozygous for the Arg389 allele (6, 24), HR response to acute exercise has not been associated with the Arg389Gly genotype (11, 29, 36, 38, 53). In the present study, we found a modest association between the Arg389Gly variant and baseline HR50 in blacks but not in whites. Subjects homozygous for the 389Gly allele showed higher baseline HR50 values compared with the other genotypes. As much as 2.3% of the variance in baseline HR50 was explained by Arg389Gly in black subjects. The implications of the ADRB1 gene SNPs for the HR response to exercise need to be further investigated. It also should be noted that the 1-LOD linkage region on chromosome 10q25 spans almost 20 Mb and contains 118 genes (Supplemental Table 3). The possibility that other genes in the region (in addition to ADRB1) also may affect submaximal exercise HR phenotypes remains to be explored in fine mapping studies.

In addition, we found evidence of linkage on chromosome 18 for several submaximal HR phenotypes in blacks and whites. These results suggest that the general region of chromosome 18q21–q22 may harbor genes that affect submaximal exercise HR in both blacks and whites. The HR50 and {Delta}HR60 QTL on 18q21.1 coincides with previously reported QTLs for changes in fat mass and percent body fat with training (13) and for submaximal exercise diastolic blood pressure at 50 W in blacks (40).

We also found evidence of promising linkage on chromosome 2q33 for {Delta}HR50 in whites. This QTL is localized in the vicinity of the HERITAGE QTLs for submaximal exercise cardiac output and stroke volume training responses (2q32.1) (39) and for baseline abdominal visceral fat level (2q36) (43). Furthermore, a gene causing familial primary pulmonary hypertension (BMPR2) is located on this area (28), and our {Delta}HR50 QTL overlaps with QTLs for resting systolic and diastolic blood pressures reported in Old Order Amish (23).

Our analyses dealt with two HR phenotypes measured during submaximal exercise. Although the phenotypes are correlated, the relationship is not as strong as one might expect. The correlations between adjusted baseline HR50 and HR60 were r = 0.66 in whites and r = 0.57 in blacks, whereas the correlations between training responses were r = 0.54 in whites and r = 0.49 in blacks. As these correlations already indicate, HR50 and HR60 are also physiologically different phenotypes. HR50 is defined using the same absolute workload (50 W) for all subjects both before and after training, whereas HR60 is based on workload relative to each individual maximal exercise capacity (60% of VO2max). Therefore, HR50 reflects cardiac response to a standard low-intensity physical exertion, and the change in HR50 with endurance training is a measure of improvement in cardiac function. On the other hand, HR60 provides information about cardiac performance relative to one's maximal capacity. Against this background, it would not be surprising if these two traits were affected by both common as well as trait-specific sets of genes.

It is a common feature in genetic studies that QTLs affecting a given trait may vary across ethnicities, and there are several potential reasons for this observation. First, a true ethnicity-specific mutation, DNA sequence variant, or haplotype may affect the trait variance in only one ethnic group. Second, an ethnicity-specific gene-environment interaction effect, i.e., an environmental factor that promotes or inhibits the expression of a specific DNA sequence variant effect on a trait of interest may be present in one ethnic group but not in another. Third, differences in phenotype means and distributions between ethnic groups may reflect differences in the physiological pathways and, consequently, set of genes that regulate and/or modify the trait values. For example, mean baseline HR50 was higher in blacks than in whites, whereas mean baseline HR60 tended to be higher in whites than in blacks. Finally, differences in sample sizes, family structures, and other study design-related features could contribute to differences in observed QTLs.

In summary, we have reported the first genome-wide scan for HR50 and HR60 at baseline and in response to 20-wk of endurance training. The strongest evidence of linkage was detected with baseline HR50 on chromosome 18q in white subjects. In addition, evidence of linkage for {Delta}HR50 was identified on chromosome 2q33 and for {Delta}HR60 on chromosome 18q. We also identified a QTL on chromosome 10q25 for baseline HR50 and HR60 in black subjects. An exploration of two candidate genes of this QTL yielded an association between an ADRB1 SNP, Arg389Gly, and baseline HR50 in blacks. These genomic regions should be further explored to identify the genes and mutations that contribute to the regulation of exercise heart rate.


   GRANTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
The HERITAGE Family Study is supported by National Heart, Lung, and Blood Institute Grant HL-45670. A. S. Leon is partially supported by the Henry L. Taylor Endowed Professorship in Exercise Science and Health Enhancement, and C. Bouchard is partially supported by the George A. Bray Chair in Nutrition.


   FOOTNOTES
 

Address for reprint requests and other correspondence: C. Bouchard, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808-4124 (e-mail: bouchac{at}pbrc.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

  1. Abecasis GR, Cardon LR, Cookson WO. A general test of association for quantitative traits in nuclear families. Am J Hum Genet 66: 279–292, 2000.[CrossRef][Web of Science][Medline]
  2. Abecasis GR, Cherny SS, Cookson WO, Cardon LR. Merlin–rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 30: 97–101, 2002.[CrossRef][Web of Science][Medline]
  3. Altman JD, Trendelenburg AU, MacMillan L, Bernstein D, Limbird L, Starke K, Kobilka BK, Hein L. Abnormal regulation of the sympathetic nervous system in alpha2A-adrenergic receptor knockout mice. Mol Pharmacol 56: 154–161, 1999.[Abstract/Free Full Text]
  4. An P, Borecki IB, Rankinen T, Perusse L, Leon AS, Skinner JS, Wilmore JH, Bouchard C, Rao DC. Evidence of major genes for exercise heart rate and blood pressure at baseline and in response to 20 weeks of endurance training: the HERITAGE family study. Int J Sports Med 24: 492–498, 2003.[CrossRef][Web of Science][Medline]
  5. An P, Perusse L, Rankinen T, Borecki IB, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Bouchard C, Rao DC. Familial aggregation of exercise heart rate and blood pressure in response to 20 weeks of endurance training: the HERITAGE family study. Int J Sports Med 24: 57–62, 2003.[CrossRef][Web of Science][Medline]
  6. Bengtsson K, Melander O, Orho-Melander M, Lindblad U, Ranstam J, Rastam L, Groop L. Polymorphism in the beta(1)-adrenergic receptor gene and hypertension. Circulation 104: 187–190, 2001.[Abstract/Free Full Text]
  7. Blair SN, Kohl HW 3rd, Paffenbarger RS Jr, Clark DG, Cooper KH, Gibbons LW. Physical fitness and all-cause mortality. A prospective study of healthy men and women. JAMA 262: 2395–2401, 1989.[Abstract/Free Full Text]
  8. Bouchard C, Leon AS, Rao DC, Skinner JS, Wilmore JH, Gagnon J. The HERITAGE family study. Aims, design, and measurement protocol. Med Sci Sports Exerc 27: 721–729, 1995.
  9. Bouchard CS, Shephard RJ, Stephens T. (editors). Physical Activity, Fitness and Health: International Proceedings and Consensus Statement. Champaign, IL: Human Kinetics, 1994.
  10. Brodde OE. Beta 1- and beta 2-adrenoceptors in the human heart: properties, function, and alterations in chronic heart failure. Pharmacol Rev 43: 203–242, 1991.[Web of Science][Medline]
  11. Buscher R, Belger H, Eilmes KJ, Tellkamp R, Radke J, Dhein S, Hoyer PF, Michel MC, Insel PA, Brodde OE. In-vivo studies do not support a major functional role for the Gly389Arg beta 1-adrenoceptor polymorphism in humans. Pharmacogenetics 11: 199–205, 2001.[CrossRef][Web of Science][Medline]
  12. Chagnon YC, Borecki IB, Perusse L, Roy S, Lacaille M, Chagnon M, Ho-Kim MA, Rice T, Province MA, Rao DC, Bouchard C. Genome-wide search for genes related to the fat-free body mass in the Quebec family study. Metabolism 49: 203–207, 2000.[CrossRef][Web of Science][Medline]
  13. Chagnon YC, Rice T, Perusse L, Borecki IB, Ho-Kim MA, Lacaille M, Pare C, Bouchard L, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Rao DC, Bouchard C. Genomic scan for genes affecting body composition before and after training in Caucasians from HERITAGE. J Appl Physiol 90: 1777–1787, 2001.[Abstract/Free Full Text]
  14. Cole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-rate recovery immediately after exercise as a predictor of mortality. N Engl J Med 341: 1351–1357, 1999.[Abstract/Free Full Text]
  15. Cole CR, Foody JM, Blackstone EH, Lauer MS. Heart rate recovery after submaximal exercise testing as a predictor of mortality in a cardiovascularly healthy cohort. Ann Intern Med 132: 552–555, 2000.[Abstract/Free Full Text]
  16. Cotes JE, Berry G, Burkinshaw L, Davies CT, Hall AM, Jones PR, Knibbs AV. Cardiac frequency during submaximal exercise in young adults; relation to lean body mass, total body potassium and amount of leg muscle. Q J Exp Physiol Cogn Med Sci 58: 239–250, 1973.[Abstract/Free Full Text]
  17. Durstine JL, Haskell WL. Effects of exercise training on plasma lipids and lipoproteins. Exerc Sport Sci Rev 22: 477–521, 1994.[Medline]
  18. Dyer AR, Persky V, Stamler J, Paul O, Shekelle RB, Berkson DM, Lepper M, Schoenberger JA, Lindberg HA. Heart rate as a prognostic factor for coronary heart disease and mortality: findings in three Chicago epidemiologic studies. Am J Epidemiol 112: 736–749, 1980.[Abstract/Free Full Text]
  19. Ecker PM, Lin CC, Powers J, Kobilka BK, Dubin AM, Bernstein D. Effect of targeted deletions of β1- and β2-adrenergic-receptor subtypes on heart rate variability. Am J Physiol Heart Circ Physiol 290: H192–H199, 2006.[Abstract/Free Full Text]
  20. Eckhart AD, Koch WJ. Transgenic studies of cardiac adrenergic receptor regulation. J Pharmacol Exp Ther 299: 1–5, 2001.[Abstract/Free Full Text]
  21. Gillman MW, Kannel WB, Belanger A, D'Agostino RB. Influence of heart rate on mortality among persons with hypertension: the Framingham Study. Am Heart J 125: 1148–1154, 1993.[CrossRef][Web of Science][Medline]
  22. Greenland P, Daviglus ML, Dyer AR, Liu K, Huang CF, Goldberger JJ, Stamler J. Resting heart rate is a risk factor for cardiovascular and noncardiovascular mortality: the Chicago Heart Association Detection Project in Industry. Am J Epidemiol 149: 853–862, 1999.[Abstract/Free Full Text]
  23. Hsueh WC, Mitchell BD, Schneider JL, Wagner MJ, Bell CJ, Nanthakumar E, Shuldiner AR. QTL influencing blood pressure maps to the region of PPH1 on chromosome 2q31–34 in Old Order Amish. Circulation 101: 2810–2816, 2000.[Abstract/Free Full Text]
  24. Humma LM, Puckett BJ, Richardson HE, Terra SG, Andrisin TE, Lejeune BL, Wallace MR, Lewis JF, McNamara DM, Picoult-Newberg L, Pepine CJ, Johnson JA. Effects of beta1-adrenoceptor genetic polymorphisms on resting hemodynamics in patients undergoing diagnostic testing for ischemia. Am J Cardiol 88: 1034–1037, 2001.[CrossRef][Web of Science][Medline]
  25. Kannel WB, Kannel C, Paffenbarger RS Jr, Cupples LA. Heart rate and cardiovascular mortality: the Framingham Study. Am Heart J 113: 1489–1494, 1987.[CrossRef][Web of Science][Medline]
  26. Kristal-Boneh E, Silber H, Harari G, Froom P. The association of resting heart rate with cardiovascular, cancer and all-cause mortality. Eight year follow-up of 3527 male Israeli employees (the CORDIS Study). Eur Heart J 21: 116–124, 2000.[Abstract/Free Full Text]
  27. Kurnik D, Muszkat M, Li C, Sofowora GG, Solus J, Xie HG, Harris PA, Jiang L, McMunn C, Ihrie P, Dawson EP, Williams SM, Wood AJ, Stein CM. Variations in the alpha2A-adrenergic receptor gene and their functional effects. Clin Pharmacol Ther 79: 173–185, 2006.[CrossRef][Web of Science][Medline]
  28. Lane KB, Machado RD, Pauciulo MW, Thomson JR, Phillips JA 3rd, Loyd JE, Nichols WC, Trembath RC. Heterozygous germline mutations in BMPR2, encoding a TGF-beta receptor, cause familial primary pulmonary hypertension. The International PPH Consortium. Nat Genet 26: 81–84, 2000.[CrossRef][Web of Science][Medline]
  29. Leineweber K, Bruck H, Temme T, Heusch G, Philipp T, Brodde OE. The Arg389Gly beta1-adrenoceptor polymorphism does not affect cardiac effects of exercise after parasympathetic inhibition by atropine. Pharmacogenet Genomics 16: 9–13, 2006.[Web of Science][Medline]
  30. Leon A. (editor). Physical Activity and Cardiovascular Health: A National Consensus. Champaign, IL: Human Kinetics, 1997.
  31. Leon AS, Sanchez OA. Response of blood lipids to exercise training alone or combined with dietary intervention. Med Sci Sports Exerc 33: S502–S515; discussion S528–S509, 2001.
  32. Liggett SB. Polymorphisms of adrenergic receptors: variations on a theme. Assay Drug Dev Technol 1: 317–326, 2003.[CrossRef][Web of Science][Medline]
  33. Mark DB, Lauer MS. Exercise capacity: the prognostic variable that doesn't get enough respect. Circulation 108: 1534–1536, 2003.[Free Full Text]
  34. Mason DA, Moore JD, Green SA, Liggett SB. A gain-of-function polymorphism in a G-protein coupling domain of the human beta1-adrenergic receptor. J Biol Chem 274: 12670–12674, 1999.[Abstract/Free Full Text]
  35. Molenaar P, Rabnott G, Yang I, Fong KM, Savarimuthu SM, Li L, West MJ, Russell FD. Conservation of the cardiostimulant effects of (–)-norepinephrine across Ser49Gly and Gly389Arg β1-adrenergic receptor polymorphisms in human right atrium in vitro. J Am Coll Cardiol 40: 1275–1282, 2002.[Abstract/Free Full Text]
  36. Nieminen T, Lehtimaki T, Laiho J, Rontu R, Niemela K, Koobi T, Lehtinen R, Viik J, Turjanmaa V, Kahonen M. Effects of polymorphisms in β1-adrenoceptor and alpha-subunit of G protein on heart rate and blood pressure during exercise test. The Finnish Cardiovascular Study. J Appl Physiol 100: 507–511, 2006.[Abstract/Free Full Text]
  37. Powell KE, Thompson PD, Caspersen CJ, Kendrick JS. Physical activity and the incidence of coronary heart disease. Annu Rev Public Health 8: 253–287, 1987.[CrossRef][Web of Science][Medline]
  38. Ranade K, Jorgenson E, Sheu WH, Pei D, Hsiung CA, Chiang FT, Chen YD, Pratt R, Olshen RA, Curb D, Cox DR, Botstein D, Risch N. A polymorphism in the beta1 adrenergic receptor is associated with resting heart rate. Am J Hum Genet 70: 935–942, 2002.[CrossRef][Web of Science][Medline]
  39. Rankinen T, An P, Perusse L, Rice T, Chagnon YC, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Rao DC, Bouchard C. Genome-wide linkage scan for exercise stroke volume and cardiac output in the HERITAGE Family Study. Physiol Genomics 10: 57–62, 2002.[Abstract/Free Full Text]
  40. Rankinen T, An P, Rice T, Sun G, Chagnon YC, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Rao DC, Bouchard C. Genomic scan for exercise blood pressure in the Health, Risk Factors, Exercise Training and Genetics (HERITAGE) Family Study. Hypertension 38: 30–37, 2001.[Abstract/Free Full Text]
  41. Rao DC, Province MA. The future of path analysis, segregation analysis, and combined models for genetic dissection of complex traits. Hum Hered 50: 34–42, 2000.[CrossRef][Web of Science][Medline]
  42. Rice T, Borecki IB, Bouchard C, Rao DC. Commingling analysis of regional fat distribution measures: the Quebec family study. Int J Obes Relat Metab Disord 16: 831–844, 1992.[Web of Science][Medline]
  43. Rice T, Chagnon YC, Perusse L, Borecki IB, Ukkola O, Rankinen T, Gagnon J, Leon AS, Skinner JS, Wilmore JH, Bouchard C, Rao DC. A genomewide linkage scan for abdominal subcutaneous and visceral fat in black and white families: The HERITAGE Family Study. Diabetes 51: 848–855, 2002.[Abstract/Free Full Text]
  44. Sandilands AJ, O'Shaughnessy KM, Brown MJ. Greater inotropic and cyclic AMP responses evoked by noradrenaline through Arg389 beta 1-adrenoceptors versus Gly389 beta 1-adrenoceptors in isolated human atrial myocardium. Br J Pharmacol 138: 386–392, 2003.[CrossRef][Web of Science][Medline]
  45. Sarsero D, Russell FD, Lynham JA, Rabnott G, Yang I, Fong KM, Li L, Kaumann AJ, Molenaar P. (–)-CGP 12177 increases contractile force and hastens relaxation of human myocardial preparations through a propranolol-resistant state of the beta 1-adrenoceptor. Naunyn Schmiedebergs Arch Pharmacol 367: 10–21, 2003.[CrossRef][Web of Science][Medline]
  46. Skinner JS, Wilmore KM, Jaskolska A, Jaskolski A, Daw EW, Rice T, Gagnon J, Leon AS, Wilmore JH, Rao DC, Bouchard C. Reproducibility of maximal exercise test data in the HERITAGE family study. Med Sci Sports Exerc 31: 1623–1628, 1999.
  47. Small KM, McGraw DW, Liggett SB. Pharmacology and physiology of human adrenergic receptor polymorphisms. Annu Rev Pharmacol Toxicol 43: 381–411, 2003.[CrossRef][Web of Science][Medline]
  48. Tesson F, Charron P, Peuchmaurd M, Nicaud V, Cambien F, Tiret L, Poirier O, Desnos M, Jullieres Y, Amouyel P, Roizes G, Dorent R, Schwartz K, Komajda M. Characterization of a unique genetic variant in the beta1-adrenoceptor gene and evaluation of its role in idiopathic dilated cardiomyopathy. CARDIGENE Group. J Mol Cell Cardiol 31: 1025–1032, 1999.[CrossRef][Web of Science][Medline]
  49. U.S. Department of Health and Human Services. Physical Activity and Health: A Report of the Surgeon General. Washington, DC: Washington, DC: Public Health Service, 1996. (Publ. S/N 017-023-00196-5).
  50. Wilk JB, Myers RH, Zhang Y, Lewis CE, Atwood L, Hopkins PN, Ellison RC. Evidence for a gene influencing heart rate on chromosome 4 among hypertensives. Hum Genet 111: 207–213, 2002.[CrossRef][Web of Science][Medline]
  51. Wilmore JH, Stanforth PR, Gagnon J, Rice T, Mandel S, Leon AS, Rao DC, Skinner JS, Bouchard C. Heart rate and blood pressure changes with endurance training: the HERITAGE Family Study. Med Sci Sports Exerc 33: 107–116, 2001.
  52. Wilmore JH, Stanforth PR, Turley KR, Gagnon J, Daw EW, Leon AS, Rao DC, Skinner JS, Bouchard C. Reproducibility of cardiovascular, respiratory, and metabolic responses to submaximal exercise: the HERITAGE Family Study. Med Sci Sports Exerc 30: 259–265, 1998.
  53. Xie HG, Dishy V, Sofowora G, Kim RB, Landau R, Smiley RM, Zhou HH, Wood AJ, Harris P, Stein CM. Arg389Gly beta 1-adrenoceptor polymorphism varies in frequency among different ethnic groups but does not alter response in vivo. Pharmacogenetics 11: 191–197, 2001.[CrossRef][Web of Science][Medline]




This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental Tables
Right arrow All Versions of this Article:
293/6/H3366    most recent
00042.2007v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Spielmann, N.
Right arrow Articles by Bouchard, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Spielmann, N.
Right arrow Articles by Bouchard, C.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2007 by the American Physiological Society.