1 INSERM U525, Paris, France.
2 INSERM U525, Nancy, France.
Correspondence: Laurence Tiret, INSERM U525, Faculté de Médecine, 91 Bd de lHôpital, 75634 Paris Cedex 13, France. E-mail: laurence.tiret{at}chups.jussieu.fr
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Methods This study investigated whether lipids and blood pressure (BP) levels shared a common familial component with height. The sample included 865 nuclear families from the French STANISLAS cohort volunteering for a free health examination between 1993 and 1994. Within-individual correlations and familial intra-trait and cross-trait correlations were estimated using the Estimating Equation technique extended to a bivariate phenotype.
Results Height negatively correlated to total and low density lipoprotein cholesterol (LDL-C) and triglycerides in both parents and offspring, and positively correlated to high density lipoprotein cholesterol (HDL-C) in parents only. In offspring, the correlation between height and HDL-C markedly increased with sexual maturation to reach after puberty the same value as in parents. The correlation of height with systolic BP was negative in fathers and positive in sons, whereas it was non-significant in mothers and daughters. The pattern of cross-trait familial correlations between height and LDL-C was compatible with the existence of a weak transmissible component explaining the relationship between these two traits. By contrast, the pattern observed for HDL-C and triglycerides was rather compatible with the influence of shared environmental factors. No familial clustering between height and BP levels was detected.
Conclusions The association between short stature and increased LDL-C might be partly of familial origin.
Accepted 3 February 2003
A number of case-control and cohort studies have demonstrated that short stature is a risk factor for coronary heart disease (CHD).19 This association persists even after adjusting for other risk factors such as smoking, blood pressure (BP), serum cholesterol, body mass index (BMI), and lung function, or for factors which clearly influence attained height such as childhood socioeconomic circumstances.1,10
The mechanisms linking short stature to increased CHD risk remain unknown. It has been suggested that the inverse relationship between height and CHD risk could be attributable to fetal origins. The fetal-origins hypothesis, first proposed by Barker,11 postulates that short stature and complications of later life are both the consequences of impaired fetal growth. However, while Barker referred to fetal undernutrition as the main cause of intrauterine growth retardation, it is likely that genetic factors also influence fetal growth restriction and participate in the reduction of attained height and the early programmingof CHD.
The hypothesis of a genetic contribution to the relationship between height and CHD is supported by the results of the European Atherosclerosis Research Study (EARS) which showed that young adults whose father had had a premature myocardial infarction were shorter in height than age- and sex-matched controls, this difference being independent of fathers educational attainment.12 In the EARS study, the most discriminant factors between subjects with and without a paternal history of CHD were low density lipoprotein cholesterol (LDL-C), apolipoprotein (apo) B, and triglycerides levels,13 and these factors negatively correlated with height more strongly in cases than in control subjects.12 These findings suggested that common transmissible factors jointly influencing height and lipids might be involved in the familial predisposition to CHD.
A genetic contribution to the relationship between height and cardiovascular risk factors would imply a clustering of these traits within families. Height14,15 and cardiovascular risk factors such as lipid and BP levels1619 are known to be highly heritable, but little is known about their possible familial clustering. The present study was aimed at investigating whether cardiovascular risk factors shared a common familial determinism with height. For this purpose, a series of bivariate familial correlation analyses between height and each of the risk factors was performed, in order to test the hypothesis of a co-variation of the traits within families. Significant cross-trait correlations between biological relatives (e.g. correlation between the height of a sib and the cholesterol level of the other sib), but not between spouses, would suggest that common transmissible factors are involved in the aetiology of both traits. Conversely, cross-trait correlations of similar magnitude among all family members would rather suggest the influence of shared lifestyle factors.20,21 This study was performed in the STANISLAS cohort composed of 865 healthy nuclear families.
![]() |
Methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Weight (to the nearest 100 g) and height (to the nearest 0.1 cm) were measured in subjects not wearing shoes or clothes. Two trained nurses measured BP with subjects in the supine position, after a 10-minute rest, on the right arm with a mercury sphygmomanometer and appropriately sized cuff, using the first and the fifth phases of the Korotkoff sounds. The average of two BP measurements (5-minute intervals) was used. In children, Tanner stage of sexual development was recorded by a physician based on a scale ranging from 2 to 10, as hairiness and external genitals scales were added, where stage 2 is pre-pubertal and stage 10 post-pubertal status.
Fasting blood samples were drawn after at least an 8-hour overnight fast. Serum levels of total cholesterol (total-C), high density lipoprotein cholesterol (HDL-C), and triglycerides were determined by routine clinical chemistry procedures. Values of LDL-C were calculated using the Friedewalds formula:23 LDL-C = [(total-C x 0.387) (HDL-C x 0.387) (triglycerides x 0.875/5)]/0.387, all units being in mmol/l.
Familial correlation analyses were performed by use of the Estimating Equations (EE) technique extended to a bivariate phenotype as previously described.21 Three kinds of correlations are estimated by this method: familial intra-trait correlations (e.g. correlations of height between family members), within-individual cross-trait correlations (e.g. correlations between height and total-C in any class of relatives), and familial cross-trait correlations (e.g. correlations between height of an individual and total-C of his/her relative). Within-individual intra-trait correlations were estimated in the four classes of relatives (fathers, mothers, sons, and daughters) and familial intra-trait and cross-trait correlations were estimated in the four types of pairs of relatives (spouses, father-offspring, mother-offspring, and sib-sib). A Gaussian working correlation matrix was used in all analyses. Hypothesis testing was performed by use of the generalized Wald test statistics.21 For example, testing the equality between three correlations (father-offspring, mother-offspring, and sib-sib) was achieved by using a Wald statistic which follows, under the null hypothesis, a 2-distribution with 2 d.f. Familial cross-trait correlations were estimated assuming a symmetric model which specified, for example, that the correlation between fathers height and offsprings total-C was identical to the correlation between fathers total-C and offsprings height. The validity of this hypothesis had been first tested for each pair of traits by comparing a general model with a restricted model assuming symmetry (
2 with 4 d.f.) and was never rejected. The strategy for testing the hypothesis of a common transmissible component influencing the association between height and any cardiovascular trait was (1) to test the homogeneity of the father-offspring, mother-offspring, and sib-sib cross-trait correlations (
2 with 2 d.f.), and (2) to compare the spouse correlation to the common correlation between biological relatives (assuming equality between the three aforementioned correlations).
In all analyses, height, lipids, and BP levels were first adjusted for age in all subjects, and Tanner stage in offspring. In a second step, lipids and BP levels were additionally adjusted for weight, oral contraception, and fathers occupational level (lower versus others). All adjustments were performed within the EE regression model, separately in each class of relatives, hence implicitly controlling for gender effects. Parents taking lipid-lowering (n = 71) or anti-hypertensive (n = 39) medications were excluded from analyses on lipid or BP variables, respectively. The triglyceride distribution was log-transformed to remove positive skewness.
A P-value < 0.05 was considered as significant.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
|
|
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
The pattern of familial cross-trait correlations for LDL-C, with significant correlations between biological relatives and no correlation between spouses, suggested that transmissible factors might partly explain the negative association of this trait with height. A very similar pattern of cross-trait correlations was observed for apoB levels in the same cohort (data not shown). Even though statistically significant, the magnitude of the cross-trait correlation between biological relatives was weak, as might have been anticipated from the moderate within-individual correlation between height and LDL-C in this population of healthy subjects. Populations at high risk of CHD might be more appropriate for detecting a familial clustering between height and risk factors of CHD, as suggested by the EARS study where correlations between LDL-C (or apoB) levels and height were stronger in individuals having a paternal history of CHD than in control subjects.12
By contrast with LDL-C, the pattern of familial cross-trait correlations between height and HDL-Cwith the correlation between biological relatives of similar magnitude to the spouse correlationsuggested that the clustering of these two traits was rather influenced by shared environmental factors. For triglycerides, the pattern was intermediate between LDL-C and HDL-C, with higher cross-trait correlations between biological relatives than between spouses, although the difference did not reach statistical significance. Actually, HDL-C and triglyceride levels are part of the cluster of risk factors defining the insulin resistance syndrome, or syndrome X, which is suspected to have a genetic basis but is also influenced by familial shared lifestyle factors.21,28
The relationship between height and BP levels appeared more complex, with an inversion of the correlation between childhood and adulthood, which was mainly observed in males, and no significant familial cross-trait correlation. It is widely admitted that the rise in BP during childhood closely relates to growth and sexual maturation. However, a meta-analysis of the systolic BP changes during childhood and adolescence showed that the positive correlation with age during childhood fell to 0 in boys and even reversed in girls at the end of puberty.29 We found a similar reduction of the correlation between systolic BP and height between the pre-pubertal and the post-pubertal periods. A plausible interpretation for these findings might be that, as for lipids, a short stature would be associated with an adverse BP profile, as suggested in adults, but in children, this negative relationship would be masked by the massive effect of growth on BP levels.
The biological mechanisms underlying the association between height and CHD risk are unclear. It is beyond dispute that environmental factors, probably related to early nutrition, account for a substantial proportion of the variability of height in the population, as suggested in particular by the trends in height over the last decades.30 While attained height is generally regarded as a reflection of early life experience,31 the relationship between height and CHD is often assumed to arise from the same period.11 That socioeconomic confounding is not the only explanation for such finding is attested by the association observed between height and cardiovascular disease in the socioeconomically homogeneous US population of male physicians.5 The role of genetic factors in the height/CHD relationship has not yet been properly examined, even in twin studies which are often advocated for testing a genetic influence32,33 (see ref. 12 for a critical discussion). The hypothesis of a genetic contribution was, however, suggested by the results of the EARS study showing that height was an independent transmissible risk factor for CHD.12 In accordance with the EARS findings, our results would be compatible with the hypothesis of a transmissible component in the relationship linking height to LDL-C.
Some limitations of the present study have to be discussed. First, the sample of families is probably not representative of the whole population of the region, depending on the bias that is associated with the participation in a free health check-up. It is likely that this sample is in healthier condition than the general population, and this is a second limitation of our study since, as mentioned above, a clustering of CHD risk factors would probably be easier to detect in high-risk populations. To which extent our findings would apply to older cohortswith different birthweight and height distributions as well as larger family sizesis also unknown. Finally, since several phenotypes were examined, we cannot exclude the fact that multiple testing resulted in some false positive results.
In conclusion, the present study suggests that transmissible factors might, at least partly, explain the relationship linking short stature to increased LDL-C levels. The hypothesis of a genetic contribution will have to be more formally tested by examining candidate gene polymorphisms. Genes belonging to the system of insulin-like growth factors (IGF) appear as strong candidates given their role in pre- and postnatal growth34 as well as susceptibility to cardiovascular disease.3537
KEY MESSAGES
|
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
2 Palmer JR, Rosenberg L, Shapiro S. Stature and the risk of myocardial infarction in women. Am J Epidemiol 1990;132:2732.[Abstract]
3 Davey Smith G, Shipley MJ, Rose G. Magnitude and causes of socioeconomic differentials in mortality: further evidence from the Whitehall Study. J Epidemiol Community Health 1990;44:26570.[Abstract]
4 Yarnell JW, Limb ES, Layzell JM, Baker IA. Height: a risk marker for ischaemic heart disease: prospective results from the Caerphilly and Speedwell Heart Disease Studies. Eur Heart J 1992;13:160205.[Abstract]
5 Hebert PR, Rich-Edwards JW, Manson JE et al. Height and incidence of cardiovascular disease in male physicians. Circulation 1993;88:143743.[Abstract]
6 Krahn AD, Manfreda J, Tate RB, Mathewson FA, Cuddy TE. Evidence that height is an independent risk factor for coronary artery disease (the Manitoba Follow-Up Study). Am J Cardiol 1994;74:39899.[CrossRef][ISI][Medline]
7 Kannam J, Levy D, Larson M, Wilson P. Short stature and risk for mortality and cardiovascular disease events. The Famingham Heart Study. Circulation 1994;90:224147.[Abstract]
8 Parker DR, Lapane KL, Lasater TM, Carleton RA. Short stature and cardiovascular disease among men and women from two southeastern New England communities. Int J Epidemiol 1998;27:97075.[Abstract]
9 Wamala SP, Mittleman MA, Horsten M, Schenck-Gustafsson K, Orth-Gomer K. Short stature and prognosis of coronary heart disease in women. J Intern Med 1999;245:55763.[CrossRef][ISI][Medline]
10 Notkola V, Punsar S, Karvonen MJ, Haapakoski J. Socio-economic conditions in childhood and mortality and morbidity caused by coronary heart disease in adulthood in rural Finland. Soc Sci Med 1985;21:51723.[CrossRef][ISI][Medline]
11 Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 1993;36:6267.[ISI][Medline]
12 Kee F, Nicaud V, Tiret L, Evans A, OReilly D, De Backer G. Short stature and heart disease: nature or nurture? The EARS Group. Int J Epidemiol 1997;26:74856.[Abstract]
13 Rosseneu M, Fruchart JC, Bard JM et al. on behalf of the EARS Group. Plasma apolipoprotein concentrations in young adults with a parental history of premature coronary heart disease and in control subjectsThe EARS Study. Circulation 1994;89:196773.[Abstract]
14 Silventoinen K, Kaprio J, Lahelma E, Koskenvuo M. Relative effect of genetic and environmental factors on body height: differences across birth cohorts among Finnish men and women. Am J Public Health 2000;90:62730.
15 Hirschhorn JN, Lindgren CM, Daly MJ et al. Genomewide linkage analysis of stature in multiple populations reveals several regions with evidence of linkage to adult height. Am J Hum Genet 2001; 69:10616.[CrossRef][ISI][Medline]
16 Friedlander Y, Kark JD, Stein Y. Biological and environmental sources of variation in plasma lipids and lipoproteins: the Jerusalem Lipid Research Clinic. Hum Hered 1986;36:14353.[ISI][Medline]
17 Clarke WR, Schrott HG, Burns TL, Sing CF, Lauer RM. Aggregation of blood pressure in the families of children with labile high systolic blood pressure. The Muscatine Study. Am J Epidemiol 1986;123:6780.[Abstract]
18 Knuiman MW, Divitini ML, Welborn TA, Bartholomew HC. Familial correlations, cohabitation effects, and heritability for cardiovascular risk factors. Ann Epidemiol 1996;6:18894.[CrossRef][ISI][Medline]
19 Mitchell BD, Kammerer CM, Blangero J et al. Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans. The San Antonio Family Heart Study. Circulation 1996;94:215970.
20 Rice T, Nadeau A, Perusse L, Bouchard C, Rao DC. Familial correlations in the Quebec family study: cross-trait familial resemblance for body fat with plasma glucose and insulin. Diabetologia 1996;39:135764.[CrossRef][ISI][Medline]
21 Tregouet DA, Herbeth B, Juhan-Vague I, Siest G, Ducimetiere P, Tiret L. Bivariate familial correlation analysis of quantitative traits by use of estimating equations: application to a familial analysis of the insulin resistance syndrome. Genet Epidemiol 1999;16:6983.[CrossRef][ISI][Medline]
22 Siest G, Visvikis S, Herbeth B et al. Objectives, design and recruitment of a familial and longitudinal cohort for studying gene-environment interactions in the field of cardiovascular risk: the Stanislas cohort. Clin Chem Lab Med 1998;36:3542.[ISI][Medline]
23 Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499502.
24 Webber LS, Srinivasan SR, Wattigney WA, Berenson GS. Tracking of serum lipids and lipoproteins from childhood to adulthood. The Bogalusa Heart Study. Am J Epidemiol 1991;133:88499.[Abstract]
25 Bergstrom E, Hernell O, Persson LA, Vessby B. Serum lipid values in adolescents are related to family history, infant feeding, and physical growth. Atherosclerosis 1995;117:113.[CrossRef][ISI][Medline]
26 Uiterwaal CS, Witteman JC, de Bruijn AM, Hofman A, Grobbee DE. Families and natural history of lipids in childhood: an 18-year follow-up study. Am J Epidemiol 1997;145:77785.[Abstract]
27 van Lenthe FJ, van Mechelen W, Kemper HC, Twisk JW. Association of a central pattern of body fat with blood pressure and lipoproteins from adolescence into adulthood. The Amsterdam Growth and Health Study. Am J Epidemiol 1998;147:68693.[Abstract]
28 Hong Y, Pedersen NL, Brismar K, de Faire U. Genetic and environmental architecture of the features of the insulin-resistance syndrome. Am J Hum Genet 1997;60:14352.[ISI][Medline]
29 Brotons C, Singh P, Nishio T, Labarthe DR. Blood pressure by age in childhood and adolescence: a review of 129 surveys worldwide. Int J Epidemiol 1989;18:82429.[Abstract]
30 Acheson D. Nutritional monitoring of the health of the Nation. J Soc Health 1987;6:20914.
31 Power C, Manor O, Fox J. Health and Class: The Early Years. London: Chapman and Hall, 1991.
32 Vagero D, Leon D. Ischaemic heart disease and low birth weight: a test of the fetal-origins hypothesis from the Swedish Twin Registry. Lancet 1994;343:26063.[CrossRef][ISI][Medline]
33 Allison DB, Paultre F, Heymsfield SB, Pi-Sunyer FX. Is the intra-uterine period really a critical period for the development of adiposity? Int J Obes Relat Metab Disord 1995;19:397402.[Medline]
34 Fant ME, Weisoly D. Insulin and insulin-like growth factors in human development: implications for the perinatal period. Semin Perinatol 2001;25:42635.[ISI][Medline]
35 Jiang X, Srinivasan SR, Dalferes ER Jr, Berenson GS. Plasma insulin-like growth factor 1 distribution and its relation to blood pressure in adolescents: the Bogalusa Heart Study. Am J Hypertens 1997;10:71419.[CrossRef][ISI][Medline]
36 Verdecchia P, Reboldi G, Schillaci G et al. Circulating insulin and insulin growth factor-1 are independent determinants of left ventricular mass and geometry in essential hypertension. Circulation 1999;100:180207.
37 Bayes-Genis A, Conover CA, Schwartz RS. The insulin-like growth factor axis: A review of atherosclerosis and restenosis. Circ Res 2000; 86:12530.