- Research article
- Open Access
- Open Peer Review
Heritability and major gene effects on left ventricular mass in the Chinese population: a family study
© Chien et al; licensee BioMed Central Ltd. 2006
- Received: 27 October 2005
- Accepted: 31 August 2006
- Published: 31 August 2006
Genetic components controlling for echocardiographically determined left ventricular (LV) mass are still unclear in the Chinese population.
We conducted a family study from the Chin-San community, Taiwan, and a total of 368 families, 1145 subjects, were recruited to undergo echocardiography to measure LV mass. Commingling analysis, familial correlation, and complex segregation analysis were applied to detect component distributions and the mode of inheritance.
The two-component distribution model was the best-fitting model to describe the distribution of LV mass. The highest familial correlation coefficients were mother-son (0.379, P < .0001) and father-son (0.356, P < .0001). Genetic heritability (h2) of LV mass was estimated as 0.268 ± 0.061 (P < .0001); it decreased to 0.153 ± 0.052 (P = .0009) after systolic blood pressure adjustment. Major gene effects with polygenic components were the best-fitting model to explain the inheritance mode of LV mass. The estimated allele frequency of the gene was 0.089.
There were significant familial correlations, heritability and a major gene effect on LV mass in the population-based families.
- Left Ventricular Hypertrophy
- Left Ventricular Mass
- Segregation Analysis
- Genetic Heritability
- Sibling Correlation
Left ventricular (LV) hypertrophy profoundly affects morbidity and mortality from cardiovascular diseases, including myocardial infarction, congestive heart failure, and stroke [1, 2]. Therefore, it is important to measure LV mass and manage LV hypertrophy among the hypertensive population in clinical practice . The noninvasive imaging methods of echocardiography have greatly expanded our capability in evaluating increased LV mass, and have thus enhanced our understanding of the natural history of LV hypertrophy [4–6]. Blood pressure and volume overload are recognized as a strong determinant of LV hypertrophy ; however, interindividual variations in LV mass can be explained, only to a limited extent, by hemodynamic load . Moreover, LV hypertrophy may occur in the absence of hypertension . Genetic components have been considered as important factors for LV mass, and twin studies have shown that heritability accounts for up to 20–70% [10–13].
The family member study design is a useful tool for investigating genetic and environmental components of complex traits . Significant heritability and evidence of strong familial aggregation in LV mass have been reported in different populations, such as in Caucasian [10, 13, 15–18], African Americans [17, 19], American Indians  and Caribbean Hispanic families . But data based on Chinese are not available. Furthermore, investigation on the mode of inheritance by segregation analysis among families can provide parametric estimates for linkage analyses . Even though some major susceptibility genes have already been identified, segregation analysis can provide further evidence for major gene effects in the trait . Previous segregation study showed the mode of inheritance of LV mass was compatible to polygenic model , but the study did not prove major gene effects controlling LV mass. Segregation analysis can investigate if the major gene effects exist, besides the polygenic background effects, and help to facilitate the further genomic study.
The study of young families from one community could provide a feasible way to investigate genetic components among the general population, because hypertension complications are comparatively rare and the environmental factors are more homogeneous than hospital-based subjects. The researchers in the Tecumseh Offspring Study showed that among the young population (mean 17 years old), parental LV mass explained a meaningful small percentage for adolescent offspring LV mass variance. The community-based family study was to investigate the mode of inheritance of LV mass in the Taiwanese population.
This family study was part of the Chin-Shan Community Cardiovascular Cohort Study, a prospective cohort study beginning in 1990 [24, 25]. The family study arm started in 1997 and was designed to recruit adolescent probands from students in the only junior high school in the community. The proposal was approved by the Institutional Review Board of National Taiwan University Hospital and oral informed consent was obtained in each participant.
At first, a total of 1063 students (with a response rate of 94.6%) agreed to participate in a general health check-up after informed consent was obtained. They underwent examinations for anthropometric measures, blood pressure, lipid profiles and echocardiographic measures. The selected youths were stratified into two groups on the basis of seven measures, including total cholesterol, triglyceride, low density lipoprotein (LDL) cholesterol, body mass index, systolic pressure, diastolic pressure, and high density lipoprotein (HDL) cholesterol. There were 368 students selected for this study. All the students with values below the 10th percentile for HDL cholesterol and above the 90th percentile (for all students in this study) for any of the other six measures, were ascertained as high-risk probands (n = 171). The control young probands (n = 197) were randomly sampling from other young students. After obtaining informed consent from probands' family members, the same measures were performed for each family member.
Because the original stratification was not based exclusively on LV mass and the results of segregation analysis for the families were similar, the results of all families together with correction for ascertainment on proband's status were reported in this study. The ascertainment strategy is to select probands in upper 90th percentiles of the risk factor distribution, and this strategy can substantially increase the power over random sampling. We used the proband high risk status as a surrogate strategy, which could identify individuals in high extreme LV mass distribution in the regressive model.
Echocardiographic measures have been described in detail previously . Four cardiologists performed and read the measurements. All subjects were asked to lie in the left lateral decubitus position to assure standardized measurement. We recorded the real-time image in video tapes simultaneously and calculated the measures in consecutive beats. We checked the agreement and reliability among these 4 cardiologists as follows. A sub-sample of 15 participants was selected to receive echocardiography by all four physicians to estimate the inter-observer variability of measurement parameters. The intraclass correlation reliability was calculated by a simple replication one-way analysis of variance test . The values of interrater correlation coefficient reliability of LV mass were 0.80, indicating good agreement.
LV mass and related characteristics of the study participants were specified by proband, sibling and parent status. Mean, standard deviation, skewness and kurtosis were presented to show the distribution of related traits. The residual LV mass from the multiple linear regression model, after adjusting for age, gender, body mass index, smoking, and alcohol drinking status, plus sample mean, were used for further genetic analysis.
We used commingling analysis on LV mass values to test whether the data were best described by one, two, or three more Normal distributions by ADMIX program . The parameters for each component's mean, variance and proportion were estimated by the maximum likelihood method. The best-fitted commingling distribution model was defined by comparing the likelihood ratio test statistics among different nested models.
The intra-familial correlation coefficients of LV mass trait were measured in different pairs, including spouse, parent-offspring, and siblings, by FCOR program in S.A.G.E. . We tested if the correlation coefficients of parent-offspring pairs were statistically different from zero by the Fisher's z test . Heritability estimate of LV mass in the families was estimated by the variance component model, which was implemented in the SOLAR software .
Complex segregation analysis
Segregation analysis of adjusted LV mass was conducted using regressive models as implemented in the REGC program in S.A.G.E. . These models assume that the variation of LV mass among family members is the result of a major gene effect, with residual variation reflecting both familial correlations and individual variation. The presence of a major gene is assessed by allowing two factors or alleles (A and B) at a single locus, resulting in three 'ousiotypes' (AA, AB, BB) in individuals. The means of LV mass for each ousiotype is denoted μAA, μAB, μBB, with one common variance of σ2. The frequencies of allele A and B are denoted qA and (1- qA), respectively. The distribution of types in the population is assumed to be in Hardy-Weinberg equilibrium. Individuals of each type are assumed to transmit allele A to their offspring with transmission probabilities τAA, τAB and τBB, respectively. Residual familial resemblance unable to be explained by this major locus is modeled by familial correlations. The correlation between spouses, parents and offspring, mother and offspring, father and offspring, and between siblings are denoted ρMF, ρPO, ρMO, ρFO, and ρSS, respectively. For this study, we adopted class D regressive models, in which residual sib-sib correlations are equal among all sibs of common parentage and can be due to any cause. If ρPO is held equal to ρSS, these models have been shown to be mathematically and numerically equivalent to the conventional mixed model of inheritance in nuclear families .
The analyses started with fitting a general model, in which all parameters were allowed to be estimated. Then we compared the general model with various submodels, in which certain parameters were restricted to specific values. Under a Mendelian model, the transmission probabilities, i.e., τAA, τAB and τBB, were held equal to Mendelian expectations of 1, 0.5, and 0. A nontransmitted environmental effect model predicted that the probability of an individual having one ousiotype or another was independent of both the person's generation and the ousiotypes of his/her parents. For the environmental model in this study, each of the transmission probabilities was taken to be equal to the factor frequency, i.e., τAA = τAB = τBB = qA. Both the Mendelian and environmental models can allow for residual familial correlations. A pure polygenic model assumed no major gene effect, so gene frequency and transmission probabilities were all fixed to one. The fit of hierarchical models was compared with the likelihood ratio test, calculated as -2 of the difference between the ln likelihood of the models being compared. The likelihood ratio value follows a chi-square distribution, with degrees of freedom equal to the difference between the models in the number of parameters estimated. Among nonhierarchical models, the most parsimonious model is that with the lowest values of Akaike's information criterion (AIC = -2 ln likelihood +2 [number of estimated parameters]) .
We used the adjusted LV mass values without a logarithm transformation for the segregation analysis since a normalizing transformation of a skewed trait would decrease the power to detect a major gene effect when one exists . We fitted the environmental model to detect possible environmental effects. If such a model was rejected, the major gene effects were not caused by the skewness of the LV mass levels .
Description of study participants
Basic characteristics of participants in the study, specified by generations (n = 1,145)
Probands (N = 368)
Siblings (N = 333)
Parents (N = 444)
LV mass (gm)
LV mass index (gm/m2.7)
Commingling analysis results
Familial correlation and genetic heritability estimates
Familial correlation coefficients and significant levels for testing the null hypothesis among the various familial pairs in the studied family members.
Complex segregation analysis result
Parameter estimates from segregation analysis of residual LV mass values: Class D regressive models, conditional on proband phenotypes
Pure familial correlation, i.e. polygenic
Pure major gene (Mendel)
Mendel + familial correlation (mixed codominant)
A Dominant, μAB = μAA
A Recessive, i.e. B Dominant, μAB = μBB
Significant heritability and familial correlations of LV mass were proven in this study, based on a large number of adolescent proband families. We also demonstrated that the inheritance mode of LV mass was compatible with major genes effects among the Chinese population. This study had two scientific contributions. First, there is considerable homogeneity in this study population. Most of the subjects live in the same community; hence their social and living environments tended to be more similar than those in different communities. Also, the characteristics of study subjects can avoid the potential bias of recruitment from a hospital setting. Second, the results are particularly relevant for a population at low risk for atherosclerosis, since the probands were systematically selected from young adolescents in the community, in which the complication of hypertension and LV hypertrophy were not prevalent in the study population.
Summary of heritability estimates of left ventricular mass trait
Study population origins
Numbers of families/subjects
Heritability estimate (h2)
Post et al. 1997 15
Caucasians, Framingham families, no systemic diseases
Age, height, weight, systolic blood pressure
Limit in subjects without systemic diseases nor medication history
Garner et al. 2000 13
White, European families
Kotchen et al. 2000 19
African American, hypertensive, hyperlipidemia
FCOR and ASSOC in SAGE program to perform the analysis
Arnett et al. 2001 16
African Americans & white hypertensive
Age, gender, systolic blood pressure, obesity
Sibling correlations 0.29–0.44 in African American, 0.04–0.12 in white
High sibling correlation in African Americans
Palatini et al. 2001 23
Tecumseh Offspring Study
251 offspring and 290 parents
Age, gender, body height systolic blood pressure, insulin, urinary sodium excretion,
No estimate of h2, parental LV mass explained 7.6% of total variance of offspring LV mass
Multiple linear regression models Young offspring (mean 17 years old)
Mayosi et al. 2002 17
British Caucasians, hypertensive probands from hospital or clinics
Age, systolic blood pressure, weight, height, WHR, diabetes
Ascertainment correction: yes
Swan et al. 2003 18
55 pairs MZ vs. 55 pairs DZ
Age, gender, blood pressure, weight
Bella et al. 2004 12
Relative pairs, mostly sibpairs
American Indian families, different geographic location
455/1373, 1305 relative pairs, 1077 sibpairs
Age, gender, centers, weight, height, systolic blood pressure, heart rate, medication, diabetes
0.17(multiple adjusted) -0.27 (first three variates adjusted)
No significant heritability in Arizona Indians
Juo et al. 2005 20
Age, gender, weight
Adding systolic blood pressure, diabetes, medication did not affect the estimate
Ethnic Chinese, young probands, community-based
Age, gender, body mass index, blood pressure
0.15 (multiple adjusted) -0.27 (first 3 variates adjusted)
The heritability decreased after adjusting for blood pressure. It implied possible pleiotrophic effects of genes on controlling blood pressure and LV mass. Hemodynamic load, such as stroke volume, has an influence on LV mass among young adults and adolescents, and this impact is more important than body size. However, high proportions of LV mass variations still remain unexplained . Genetic components played important role in residual LV mass variations. We ascertained young proband families, where hypertension complications are comparatively rare, and from one community population, where environmental factors are rather homogeneous for genetic studies. Our study subjects were rather young, and our results showed results similar to the Tecumseh offspring study .
We found the highest correlations were in parent-son pairs, which indicated male offspring had influential effects from parents. Our estimate of sibling correlation was as the same as Framingham sibling pairs (0.16), while the estimates of parent-offspring and spouse correlations (0.29 and 0.25, respectively) were much higher than those in Framingham pairs (0.15 in parent-offspring, 0.05 in spouse) . For intra-familial resemblance, greater father-offspring correlations were observed among the British Caucasian population, much higher than mother-child correlations . Our study also showed sex-specific patterns of familial correlations; the highest was the parent-son pairs (0.36–0.38) and the lowest was the father-daughter (0.08). Different parent-of-origin effects on offspring LV mass was reported in European families . The mother-offspring correlation coefficient was significantly higher than father-offspring correlation among the European population. The discrepancy implies the importance of ethnic difference on parental factors on offspring traits. Also, high spouse correlation implies that the common household effects were important for controlling LV mass. Lifestyle habits, such as salt intake and physical activity, might be also familial aggregation and may thus explain the high correlation between spouse pairs.
There were several studies on genomic profiles for LV mass. For example, a cross-breeding hypertensive rat model demonstrated two loci with high LOD scores [38, 39]. There were many reports on candidate genes such as G-protein beta-3, aldosterone synthase, and beta-1 adrenoceptor genes associated with LV mass [18, 40]. Our study results can provide further genomic research on LV mass.
The limitations of our study were as follows. Firstly, only mathematical modeling methods such as commingling and segregation analyses were investigated and no candidate gene markers were investigated. Although we postulated one major gene with allele frequency around 0.1 controlling LV mass and 2-component commingling patterns, we did not shed light on which genes most likely involved. Secondly, epistasis among genes or gene-environmental interaction cannot be explored in this study. Incorporation with environmental factors can elucidate the possible roles of risk factors and interaction effects.
We showed that there were significant parent-son correlation coefficients, genetic heritability and major gene effects controlling LV mass among ethnic Chinese in Taiwan. Candidate gene markers could be used to investigate the association and linkage with LV mass.
Owing to the kind participation of the people of Chin-Shan County, Taiwan, this study is ongoing. The authors wish to thank the staff of the Department of Cardiology, National Taiwan University Hospital, Taiwan, for their contributions and cooperation. This study was partly funded by grants from the National Science Council of Taiwan (NSC93-2314-B-002-218, NSC92-2314-B-002-197) and National Taiwan University Hospital (NTUH.92S025).
- Levy D: Left ventricular hypertrophy epidemiological insights from the Framingham heart study. Drugs. 1988, 35 (Suppl 5): 1-5.View ArticlePubMedGoogle Scholar
- Kannel WB: Fifty years of Framingham Study contributions to understanding hypertension. J Hum Hypertens. 2000, 14: 83-90. 10.1038/sj.jhh.1000949.View ArticlePubMedGoogle Scholar
- Okin PM, Devereux RB, Jern S, Kjeldsen SE, Julius S, Nieminen MS, Snapinn S, Harris KE, Aurup P, Edelman JM, Wedel H, Lindholm LH, Dahlof B, LIFE Study Investigators: Regression of electrocardiographic left ventricular hypertrophy during antihypertensive treatment and the prediction of major cardiovascular events. JAMA. 2004, 292: 2343-2349. 10.1001/jama.292.19.2343.View ArticlePubMedGoogle Scholar
- Chien KL, Sung FC, Hsu HC, Su TC, Lee YT: Left Ventricular mass and correlated atherosclerotic risk factors in young adolescents: report from Chin-Shan community cardiovascular study in Taiwan. Atherosclerosis. 2001, 155: 431-437. 10.1016/S0021-9150(00)00579-7.View ArticlePubMedGoogle Scholar
- Devereux RB, Roman MJ, de Simone G, O'Grady MJ, Paranicas M, Yeh JL, Fabsitz RR, Howard BV: Relations of left ventricular mass to demographic and hemodynamic variables in American Indians: the Strong Heart Study. Circulation. 1997, 96: 1416-1423.View ArticlePubMedGoogle Scholar
- Goble MM, Mosteller M, Moskowitz WB, Schieken RM: Sex differences in the determinants of left ventricular mass in childhood. The Medical College of Virginia twin study. Circulation. 1992, 85: 1661-1665.View ArticlePubMedGoogle Scholar
- Ganau A, Devereux RB, Pickering TG, Roman MJ, Schnall PL, Santucci S, Spitzer MC, Laragh JH: Relation of left ventricular hemodynamic load and contractile performance to left ventricular mass in hypertension. Circulation. 1990, 81: 25-36.View ArticlePubMedGoogle Scholar
- de Simone G, Devereux RB, Kimball TR, Mureddu GF, Roman MJ, Contaldo F, Daniels SR: Interaction between body size and cardiac workload: influence on left ventricular mass during body growth and adulthood. Hypertension. 1998, 31: 1077-1082.View ArticlePubMedGoogle Scholar
- Chen CH, Ting CT, Lin SJ, Hsu TL, Ho SJ, Chou P, Chang MS, O'Connor F, Spurgeon H, Lakatta E, Yin FC: Which arterial and cardiac parameters best predict left ventricular mass?. Circulation. 1998, 98: 422-428.View ArticlePubMedGoogle Scholar
- Bielen E, Fagard R, Amery A: The inheritance of left ventricular structure and function assessed by imaging and Doppler echocardiography. Am Heart J. 1991, 121: 1743-1749. 10.1016/0002-8703(91)90021-9.View ArticlePubMedGoogle Scholar
- Busjahn A, Knoblauch H, Knoblauch M, Bohlender J, Menz M, Faulhaber HD, Becker A, Schuster H, Luft FC: Angiotensin-converting enzyme and angiotensinogen gene polymorphisms, plasma levels, cardiac dimensions. A twin study. Hypertension. 1997, 29: 165-170.View ArticlePubMedGoogle Scholar
- Bella JN, MacCluer JW, Roman MJ, Almasy L, North KE, Best LG, Lee ET, Fabsitz RR, Howard BV, Devereux RB: Heritability of left ventricular dimensions and mass in American Indians: The Strong Heart Study. J Hypertens. 2004, 22: 281-286. 10.1097/00004872-200402000-00011.View ArticlePubMedGoogle Scholar
- Garner C, Lecomte E, Visvikis S, Abergel E, Lathrop M, Soubrier F: Genetic and environmental influences on left ventricular mass. A family study. Hypertension. 2000, 36: 740-746.View ArticlePubMedGoogle Scholar
- Khoury MJ, Beaty TH, Cohen BH: Fundamentals of Genetic Epidemiology. 1993, New York: Oxford University PressGoogle Scholar
- Post WS, Larson MG, Myers RH, Galderisi M, Levy D: Heritability of left ventricular mass: the Framingham heart study. Hypertension. 1997, 30: 1025-1028.View ArticlePubMedGoogle Scholar
- Arnett DK, Hong Y, Bella JN, Oberman A, Kitzman DW, Hopkins PN, Rao DC, Devereux RB: Sibling correlation of left ventricular mass and geometry in hypertensive African Americans and whites: the HyperGEN study. Hypertension Genetic Epidemiology Network. Am J Hypertens. 2001, 14: 1226-1230. 10.1016/S0895-7061(01)02200-2.View ArticlePubMedGoogle Scholar
- Mayosi BM, Keavney B, Kardos A, Davies CH, Ratcliffe PJ, Farrall M, Watkins H: Electrocardiographic measures of left ventricular hypertrophy show greater heritability than echocardiographic left ventricular mass. Eur Heart J. 2002, 23: 1963-1971. 10.1053/euhj.2002.3288.View ArticlePubMedGoogle Scholar
- Swan L, Birnie DH, Padmanabhan S, Inglis G, Connell JM, Hillis WS: The genetic determination of left ventricular mass in healthy adults. Eur Heart J. 2003, 24: 577-582. 10.1016/S0195-668X(02)00524-9.View ArticlePubMedGoogle Scholar
- Kotchen TA, Kotchen JM, Grim CE, George V, Kaldunski ML, Cowley AW, Hamet P, Chelius TH: Genetic determinants of hypertension: identification of candidate phenotypes. Hypertension. 2000, 36: 7-13.View ArticlePubMedGoogle Scholar
- Juo SH, Di Tullio MR, Lin HF, Rundek T, Boden-Albala B, Homma S, Sacco RL: Heritability of left ventricular mass and other morphologic variables in Caribbean Hispanic subjects: the Northern Manhattan Family Study. J Am Coll Cardiol. 2005, 46: 735-737. 10.1016/j.jacc.2005.05.025.View ArticlePubMedPubMed CentralGoogle Scholar
- Jarvik GP: Complex segregation analyses: uses and limitations. Am J Hum Genet. 1998, 63: 942-946. 10.1086/302075.View ArticlePubMedPubMed CentralGoogle Scholar
- Cui J, Antoniou AC, Dite GS, Southey MC, Venter DJ, Easton DF, Giles GG, McCredie MR, Hopper JL: After BRCA1 and BRCA2-what is next? multifactorial segregation analyses of three-generation, population-based Australian families affected by female breast cancer. Am J Hum Genet. 2001, 68: 420-431. 10.1086/318187.View ArticlePubMedGoogle Scholar
- Palatini P, Krause L, Amerena J, Nesbitt S, Majahalme S, Tikhonoff V, Valentini M, Julius S: Genetic contribution to the variance in left ventricular mass: the Tecumseh Offspring Study. J Hypertens. 2001, 19: 1217-1222. 10.1097/00004872-200107000-00006.View ArticlePubMedGoogle Scholar
- Chien KL, Hsu HC, Su TC, Lee YT: Consistency in genetic inheritance mode and heritability patterns of triglyceride vs. high density lipoprotein cholesterol ratio in two Taiwanese family samples. BMC Genet. 2003, 4: 7-16. 10.1186/1471-2156-4-7.View ArticlePubMedPubMed CentralGoogle Scholar
- Chien KL, Chen WJ, Hsu HC, Su TC, Chen MF, Lee YT: Major gene effects on apolipoprotein B concentrations in families of adolescents-results from a community-based study in Taiwan. Clin Chim Acta. 2005, 365: 194-199. 10.1016/j.cca.2005.08.025.View ArticlePubMedGoogle Scholar
- Fleiss JL: The Design and Analysis of Clinical Experiments. 1986, New York: John Wiley & Sons, 1-432.Google Scholar
- Devereux RB, Reichek N: Echocardiographic determination of left ventricular mass in man anatomic validation of the method. Circulation. 1977, 55: 613-618.View ArticlePubMedGoogle Scholar
- de Simone G, Daniels SR, Devereux RB, Meyer RA, Roman MJ, de Divitiis O, Alderman MH: Left ventricular mass and body size in normotensive children and adults: assessment of allometric relations and impact of overweight. JACC. 1992, 20: 1251-1260.View ArticlePubMedGoogle Scholar
- Cloninger CR, von Knorring L, Oreland L: Pentametric distribution of platelet monoamine oxidase activity. Psychiatry Research. 1985, 15: 133-143. 10.1016/0165-1781(85)90049-6.View ArticlePubMedGoogle Scholar
- S.A.G.E. 5.2, Statistical Analysis for Genetic Epidemiology. 2006, [http://darwin.cwru.edu/sage/]
- Snedecor GW, Cochran WG: Statistical methods. 1980, Ames, Iowa, USA: The Iowa State University Press, 7Google Scholar
- Almasy L, Blangero J: Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998, 62: 1198-1211. 10.1086/301844.View ArticlePubMedPubMed CentralGoogle Scholar
- Demenais FM, Bonney GE: Equivalence of the mixed and regressive models for genetic analysis. I Continuous traits Genetic Epidemiol. 1989, 6: 597-617. 10.1002/gepi.1370060505.View ArticleGoogle Scholar
- Akaike H: A new look at the statistical model identification. IEEE Transactions on Automatic Control. 1974, AC-19: 716-723. 10.1109/TAC.1974.1100705.View ArticleGoogle Scholar
- Prenger VL, Beaty TH, Kwiterovich PO: Genetic determination of high-density lipoprotein-cholesterol and apolipoprotein A-1 plasma levels in a family study of cardiac catheterization patients. Am J Hum Genet. 1992, 51: 1047-1057.PubMedPubMed CentralGoogle Scholar
- Demenais F, Lathrop M, Lalouel JM: Robustness and power of the unified model in the analysis of quantitative measurements. Am J Hum Genet. 1986, 38: 228-234.PubMedPubMed CentralGoogle Scholar
- Kuznetsova T, Staessen JA, Olszanecka A, Ryabikov A, Stolarz K, Malyutina S, Fagard R, Kawecka-Jaszcz K, Nikitin Y, European Project On Genes in Hypertension (EPOGH) Investigators: Maternal and paternal influences on left ventricular mass of offspring. Hypertension. 2003, 41: 69-74. 10.1161/01.HYP.0000042429.62541.A9.View ArticlePubMedGoogle Scholar
- Innes BA, McLaughlin MG, Kapuscinski MK, Jacob HJ, Harrap SB: Independent genetic susceptibility to cardiac hypertrophy in inherited hypertension. Hypertension. 1998, 31: 741-746.View ArticlePubMedGoogle Scholar
- Tsujita Y, Iwai N, Tamaki S, Nakamura Y, Nishimura M, Kinoshita M: Genetic mapping of quantitative trait loci influencing left ventricular mass in rats. Am J Physiol Heart Circ Physiol. 2000, 279: H2062-2067.PubMedGoogle Scholar
- Patel DA, Li S, Chen W, Srinivasan SR, Boerwinkle E, Berenson GS: G-6A polymorphism of the angiotensinogen gene and its association with left ventricular mass in asymptomatic young adults from a biethnic community: the Bogalusa Heart Study. Am J Hypertens. 2005, 18: 1437-1441. 10.1016/j.amjhyper.2005.05.031.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2261/6/37/prepub
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