Consistency of genetic inheritance mode and heritability patterns of triglyceride vs. high density lipoprotein cholesterol ratio in two Taiwanese family samples.

BACKGROUND: Triglyceride/HDL cholesterol ratio (TG/HDL-C) is considered as a risk factor for cardiovascular events. Genetic components were important in controlling the variation in western countries. But the mode of inheritance and family aggregation patterns were still unknown among Asian-Pacific countries. This study, based on families recruited from community and hospital, is aimed to investigate the mode of inheritance, heritability and shared environmental factors in controlling TG/HDL-C.
RESULTS: Two populations, one from community-based families (n = 988, 894 parent-offspring and 453 sibling pairs) and the other from hospital-based families (n = 1313, 76 parent-offspring and 52 sibling pairs) were sampled. The population in hospital-based families had higher mean age values than community-based families (54.7 vs. 34.0). Logarithmic transformed TG/ HDL-C values, after adjusted by age, gender and body mass index, were for genetic analyses. Significant parent-offspring and sibling correlations were also found in both samples. The parent-offspring correlation coefficient was higher in the hospital-based families than in the community-based families. Genetic heritability was higher in community-based families (0.338 +/- 0.114, p = 0.002), but the common shared environmental factor was higher in hospital-based families (0.203 +/- 0.042, p < 0.001). Commingling analyses showed that more than one-component distribution models were the best-fit models to explain the variance in both populations. Complex segregation analysis by regressive models revealed that in both samples the best-fit model of TG/HDL-C was the model of environmental effects plus familial correlation, in which significant parent-offspring and sibling correlations were demonstrated. Models of major gene effects were rejected in both samples.
CONCLUSION: Variations of TG/HDL-C in the normal ranges were likely to be influenced by multiple factors, including environmental and genetic components. Higher genetic factors were proved in younger community-based families than in older hospital-based families.

Background

Triglyceride and high density lipoprotein (HDL) cholesterol are important components in insulin resistance syndrome and are considered as risk factors for cardiovascular diseases [1-4]. Atherogenic dyslipidemia, including hypertriglyceridemia and low HDL cholesterol levels are the targets for primary prevention by lifestyle intervention in Adult Treat Panel III guidelines [5]. The ratio of triglyceride vs. HDL cholesterol (TG/HDL-C) can be considered a single phenotype trait for cardiovascular risk [6,7]. TG/HDL-C is a simple, readily calculated measurement about atherogenic plasma lipoproteins, and related to lipoprotein particle sizes [8]. Shared gene and environmental factors were reported to influence HDL cholesterol and triglyceride levels simultaneously [9]. Also, pleiotrophic effects on low HDL cholesterol and high triglyceride were evident among families [7,9,10]. Extensive genomic scanning study on this combined trait was also reported to linkage with chromosome 7 [11].

Many factors were associated with HDL cholesterol and triglyceride levels, such as age, gender, lifestyle activities, and obesity. But the proportion of TG/HDL-C variances explained by known factors was small. Genetic factors was considered as a significant role in determining serum levels [12]. Even linkage results of TG/HDL-C were reported in Framingham families [11], there were inconsistent study results about the mode of inheritance of TG/HDL-C, especially for HDL cholesterol phenotype. The reasons of inconsistency were due to different ascertainment strategies and study population characteristics [13-21]. In brief, most studies on the mode of inheritance of HDL cholesterol demonstrated major gene effects. Amos et al. showed major gene effect existed in a multiple generation pedigree family [13]. Also, Borecki et al demonstrated that HDL cholesterol was controlled by the major gene effect [22]. The allele frequency of autonomic recessive gene in the Jerusalem families was 0.06 [23]. Coresh et al. [17] proved one autosomal dominant gene with allele frequency of 0.25. Mahaney et al. also demonstrated in Mexican American population, HDL cholesterol was controlled by a major dominant recessive gene [20]. In the other side, Cupples et al. cannot demonstrate the major gene effect in Berkeley families [18]. Moll et al. [24] and Prenger et al. [21] cannot define the major gene effect in HDL cholesterol levels among high risk probands of coronary heart disease. The controversial results about the mode of inheritance of HDL cholesterol implied that complex pathogenesis mechanisms existed. Furthermore, genetic factors controlling TG/HDL-C ratio were more complicated. Although several disorders of dyslipidemia were identified by candidate-gene studies and positional cloning experiments, there remain many problems still remain to be resolved.

Different mechanisms exist between special monogenic hyperlipidemia and general population. For example, more than 600 low density lipoprotein (LDL) receptor mutations underlie familial hypercholesterolemia type, but no single LDL receptor single nucleotide polymorphism has been associated with variation of plasma lipoproteins in the general population [12]. Also, it is still unclear whether common genetic variant can help to predict risk of CHD in general population. So we should define homogeneous and low-risk general population samples to elucidate the genetic roles in controlling TG/HDL-C. This study, based on two samples, one from rather young families in community-based population, another from older adult subjects undertaking health screening in hospital-based population, was designed to estimate the roles of genetic components and the mode of inheritance in TG/HDL-C among Taiwanese.

Results

Hospital-based family members had higher mean age values than community-based families (34.0 vs. 54.7, respectively, Table 1). Also, there were higher total cholesterol, triglyceride, HDL cholesterol, LDL cholesterol and lower TG/HDL-C values in hospital-based families than those in community based families, with smaller standard deviation values (Table 1). High values of skewness and kurtosis were found in both of triglyceride and TG/HDL-C ratio, and the logarithm transformed TG/HDL-C had near zero values of skewness and kurtosis, indicating compatible with normal distribution. We adjusted logarithm transformed TG/HDL-C in linear model by age, gender and body mass index, and residual values were for further genetic analyses. The explained variability of TG/HDL-C by gender, age, interaction of age and gender, and body mass index were 24.1% in the community-based sample and 19.4% in hospital-based one. Age had significant effects only among younger community families, but not among older hospital-based families. Body mass index had significant positive effects on TG/HDL-C in both samples (Table 2).

Table 1

Various lipid profiles in the two study population samples

	Community-based (N= 988)				Hospital-based (N= 1313)
	Mean	SD	Skewness	Kurtosis	Mean	SD	Skewness	Kurtosis
Age (years)	34.0	20.1	0.80	-0.47	54.7	11.5	-0.27	0.14
Total cholesterol (mg/dL)	182.4	39.7	0.74	2.15	194.4	36.2	0.25	1.37
Triglyceride (mg/dL)	117.5	93.3	3.61	18.23	130.4	79.3	2.26	8.05
HDL cholesterol (mg/dL)	42.9	10.5	0.53	0.34	52.8	14.6	0.81	0.88
LDL cholesterol (mg/dL)	103.0	41.6	0.53	0.41	116.2	31.2	0.55	0.55
Triglyceride vs. HDL ratio	3.15	3.53	5.45	48.53	2.86	2.37	2.55	9.30
Logarithm of triglyceride vs. HDL-C ratio	0.85	0.70	0.76	0.89	0.80	0.70	0.22	-0.19

Abbreviations: SD: standard deviation, HDL-C: high density lipoprotein cholesterol, LDL-C: low density lipoprotein cholesterol

Table 2

Estimated parameter, standard error and explained variability in the linear regression models for logarithm transformed TG/HDL ratio values in two samples.

	Community based			Hospital based
Variables	Estimated parameter	Standard error	P	Estimated parameter	Standard error	P
Intercept	-0.710	0.144	<.0001	0.071	0.403	0.860
Gender (women/men)	-0.040	0.068	0.5529	-0.876	0.173	<.0001
Age	0.022	0.005	<.0001	-0.014	0.011	0.212
Gender*Age	-0.004	0.002	0.038	0.012	0.003	<.0001
Body mass index	0.056	0.005	<.0001	0.076	0.006	<.0001
R square	24.1%			19.4%

The commingling distributions of two populations were compatible with more than one-component normal distribution (Table 3). In younger community-based families, the best-fit model of explaining TG/HDL-C variance was the 2-component model, whose component means, variances, and proportions were (-0.256, 0.754), (0.609, 1.389), and (74.7%, 25.3%), respectively. The χ2 for comparing the 2-component with 1-component distribution was 6.46 (degree of freedom [df] = 3, p = 0.091). For hospital-based families, the best-fit model was the 3-component model (χ2 = 3.27, df = 3, p = 0.353, compared with 4-component model). We found in older hospital-based families, there were wider range of mean estimates and lower proportions of high mean components than the younger community-based families.

Table 3

Commingling analysis of adjusted log TG/HDL ratio in two population samples.

I. Community-based:
	Component means				Component variances				Component proportions (%)
Components	μ1	μ2	μ3		σ21	σ22	σ23		π1	π2	π3		-2ln(l)+c	χ2	P
1	0.000				0.999				1.000				3534.99
2	-0.256	0.754			0.609	1.389			0.747	0.253			3470.74	64.25
3	-0.576	0.091	2.466		0.296	0.884	0.824		0.237	0.735	0.028		3464.28	6.46
II. Hospital-based
	Component means				Component variances				Component proportions (%)
Components	μ1	μ2	μ3	μ4	σ21	σ22	σ23	σ24	π1	π2	π3	π4	-2ln(l) + c	χ2	P
1	0				0.999				1				3725.13
2	-0.514	0.508			0.578	0.897			0.497	0.503			3708.05	17.08	0.001
3	-0.682	0.341	2.471		0.499	0.806	0.016		0.358	0.630	0.012		3697.61	10.44	0.015
4	-1.510	-0.275	1.043	2.359	0.258	0.529	0.218	0.104	0.048	0.732	0.186	0.034	3694.35	3.27	0.353

We found that all correlation coefficient values in hospital-based relative pairs were higher than those in community, and the parent-offspring coefficient in hospital was significantly higher than one in community(0.420 vs. 0.215, P = 0.046) (Table 4). The range of parent-offspring and sibling correlations were 0.22 to 0.42, highest in hospital-based families. Also, in the hospital families, the spouse correlation was 0.142, which implied possible assortive mating or common shared household factors in older hospital-based families. But in the community-based sample, the spouse correlation was only 0.044, without significant difference from zero. To explore the possible effects on examination dates, we re-arranged the dataset according to examination dates, and found all spouses in the hospital-based sample were recruited in the same day, and almost spouses (90%) in the community-based sample were recruited within two weeks. The spouse correlations in the remaining different exam date were similar as one in the same date (0.044), so the examination dates did not affect apparently spouse correlation values.

Table 4

Familial correlation coefficients in residual log TG/HDL values in the two populations, after adjusting with age and gender effects.

	Community-based		Hospital-based		P¶
	Numbers of Pair	Estimated coefficient	Numbers of Pair	Estimated coefficient
Spouse	156	0.044†	530	0.142***	0.143
Parental-Offspring	894	0.215***	76	0.420***	0.046
Sibling	453	0.225***	52	0.276*	0.367

†: P > 0.05, *: 0.01

†: P > 0.05, *: 0.01