Etiologic Heterogeneity of Hyperapobetalipoproteinemia (HyperapoB)
Results From Segregation Analysis in Families With Premature Coronary Artery Disease
Abstract Hyperapobetalipoproteinemia (hyperapoB) is a common familial lipoprotein disorder associated with premature coronary artery disease (CAD). HyperapoB is characterized by an increased number of small, dense LDL particles. Patients with hyperapoB may be normotriglyceridemic (normoTG) or hypertriglyceridemic (hyperTG). We tested the hypothesis that a major locus controls the hyperapoB phenotype by using data from 1035 participants in 145 families enriched for premature CAD. Segregation analysis was conducted, and results suggest etiologic heterogeneity in these families. Families (n=55) with one or more hyperTG hyperapoB individuals strongly supported mendelian recessive inheritance of hyperapoB. Under this mendelian model, individuals with the high-risk genotype had a baseline risk of 0.78, but parental and spouse’s hyperapoB phenotypes did influence the probability of displaying hyperapoB. Low-risk genotypes had virtually no risk of displaying hyperapoB. The other subgroup of families (n=72), in which all hyperapoB individuals were normoTG, did not show any clear pattern of inheritance. Eighteen families did not have any hyperapoB individual. In the 55 families with hyperTG hyperapoB, diabetes was more prevalent in hyperapoB individuals (18.3% of hyperTG hyperapoB individuals, 9.6% of normoTG hyperapoB individuals) than in normal individuals (4.9%). Both hyperTG hyperapoB and normoTG hyperapoB phenotypes were significant predictors for blood pressure in the 55 families, but not in the total population. These associations further suggest a link between hyperapoB and the small, dense LDL syndromes. This study successfully demonstrated mendelian inheritance of the hyperapoB phenotype and also suggested etiologic heterogeneity of hyperapoB.
- apolipoprotein B
- familial combined hyperlipidemia
- coronary artery disease
- segregation analysis
- etiologic heterogeneity
Reprints requests to Suh-Hang Hank Juo, MD, PhD, Laboratory of Statistical Genetics, The Rockefeller University, 1230 York Ave, Box 192, New York, NY 10021.
- Received December 30, 1996.
- Accepted May 20, 1997.
Hyperapobetalipoproteinemia was first described by Sniderman et al1 from a study of 100 consecutive patients undergoing elective coronary arteriography. HyperapoB is characterized by an increased number of small, dense LDL particles and an elevated LDL-B level with normal or borderline high LDL-C levels. Patients with hyperapoB may be normoTG or hyperTG. We have found that hyperapoB was the most common phenotype (34%) associated with premature CAD2 ; hyperTG hyperapoB was even more strongly associated with CAD (odds ratio 17.5) than normoTG hyperapoB (odds ratio 2.5). Sniderman and colleagues3 found one third of the offspring of hyperapoB survivors of premature myocardial infarction also had hyperapoB. One cohort study, the Montreal Heart Study,4 found an increase in LDL-B levels was the strongest indicator of progression of coronary atherosclerosis during a 10-year follow-up after an aortocoronary artery bypass surgery.
In one report, familial dyslipidemias were found in more than 50% of premature CAD patients.5 More than 20 years ago, Goldstein et al6 initially described familial combined hyperlipidemia. Subsequently, several other dyslipidemic phenotypes: hyperapoB,1 7 LDL subclass pattern B,8 9 familial dyslipidemic hypertension,10 11 and syndrome X12 have also been described. These dyslipidemic syndromes appear related to each other through the presence of small, dense LDL. There is a great deal of interest in understanding the genetic mechanisms and molecular basis of these dyslipidemic small, dense LDL phenotypes, because they are common and strong risk factors for CAD.
There are two metabolic defects in hyperapoB patients.13 First, there is an increased production of apoB in the liver, resulting in the overproduction of VLDL particles and subsequently the overproduction of LDL particles. It has been postulated that there is an increased transfer of core TG from VLDL particles for cholesteryl ester in LDL particles, with subsequent hydrolysis of TG in the cholesteryl ester–depleted LDL particles, resulting in the production of small, dense LDL particles. Second, there appears to be a delayed clearance of postprandial TG-rich lipoproteins (chylomicrons and chylomicron remnants) in patients with hyperapoB.
A number of candidate genes have been proposed to explain the small, dense LDL syndromes, including the APOB gene, the lipoprotein lipase gene, the APO AI/CIII/AIV gene complex, the ATHS gene on chromosome 19, and the LDL receptor gene.14 More recently, evidence has been reported that the genes for manganese superoxide dismutase and cholesteryl ester transfer protein are also linked to LDL particle size.15
Previous work from this laboratory in this cohort of families from the JH-CAD Family Study provided evidence for a single gene effect on the plasma levels of apoB16 and also indicated that such levels were not linked to the APOB gene.17 Here we have extended our genetic studies of apoB to include the discrete phenotype hyperapoB and to examine in more detail the hypothesis that a major locus controls hyperapoB.
The JH-CAD Study ascertained 203 white probands (99 males and 104 females) undergoing elective diagnostic coronary angiography at the Johns Hopkins Hospital from 1985 to 1988. The probands in this study were selected using the following criteria: (1) men aged 50 or less, and women aged 60 or less, (2) not taking lipid-lowering medication, and (3) had not suffered a myocardial infarction in the last 12 weeks. In the subsequent family study (ie, JH-CAD Family Study), the probands’ spouses, first-degree relatives, and any second-degree relative willing to participate were recruited. A total of 145 families participated the JH-CAD Family Study. There were 145 probands and 892 family members (408 males and 484 females) in the JH-CAD Family Study. Among the 892 family members, 397 were first-degree relatives of the probands. Family size ranged from 3 to 28 members. Nineteen families had four generations, 122 families had three generations, and 4 families had two generations.
Definition of HyperapoB and Other Lipoprotein Phenotypes
A diagnostic algorithm has been developed2 that distinguishes hyperapoB as a distinct lipoprotein phenotype. In this algorithm, hyperapoB is defined as an elevated LDL-B level (defined as greater than 130 mg/dL in d>1.006 g/mL infranatant), an LDL-C level below the 90th percentile (age and sex specific),18 and the absence of chylomicrons and type III hyperlipoproteinemia (dysbetalipoproteinemia). Patients with hyperapoB are characterized further as hyperTG hyperapoB (TG≥90th percentile, age and sex specific)18 or normoTG hyperapoB (TG<90th percentile, age and sex specific). Other lipoprotein patterns that are determined by this algorithm include type III, type IIa, type IIb, type IV, hypoalpha, isolated high LP(a), and normal.
Assignment of Families to Three Different Types
Since etiologic heterogeneity is likely for most hyperlipidemias, we separated the total families into three types based on the presence of the hyperTG hyperapoB phenotype in a family. Families were classified as hyperTG if any individual was hyperTG hyperapoB. Therefore, a hyperTG family may have both normoTG and hyperTG hyperapoB individuals, but it must have at least one hyperTG hyperapoB individual. If all hyperapoB individuals in a family were normoTG, the family was assigned to normoTG. Fifty-five families were classified as hyperTG, 72 families as normoTG, and 18 families without any hyperapoB individual were denoted normal. To minimize the impact of ascertainment bias in the subset analysis, 18 normal families that did not segregate hyperapoB were added to both normoTG and hyperTG families, respectively, as representative of a background population. Segregation analysis was then repeated on two subgroups: the 18 normal families plus 55 hyperTG families(I); and the 18 normal families plus 72 normoTG families (II).
Segregation analysis of the hyperapoB phenotype (we lumped hyperTG hyperapoB and normoTG hyperapoB into the same outcome phenotype in segregation analysis) was carried out using the REGD program of SAGE.19 This program implements the logistic regressive model for segregation analysis of a discrete phenotype,20 and here single major locus and nontransmitted major factor (ie, environmental factor) models were considered. This regressive logistic approach models the log of the odds of having the hyperapoB phenotype as a function of a single unobserved locus and additional familial factors. This unobserved single locus has two possible factors or alleles, A and B, forming three classes of essential “ousiotypes,”21 denoted AA, AB, or BB, and the baseline risk for each ousiotype is to be estimated. The frequencies of factor A and B are denoted PA and (1−PA), respectively. The probabilities of transmitting an A factor from a parent of a given ousiotype to the offspring are denoted by the transmission parameters τAA, τAB, and τBB, respectively. In classic Mendelian models, τAA, τAB, and τBB will be 1.0, 0.5, and 0. Residual familial aggregation not explained by this major locus is modeled by an effect of having a hyperapoB spouse and/or parent on the log-odds of observing the phenotype. This regressive model is formulated as where P(Y=1) is the risk of having the hyperapoB phenotype, βi (i=AA, AB, or BB) is the estimated baseline parameter for each ousiotype, δSP is the overall effect of having a hyperapoB spouse, and δMO and δPO represent the residual effect of having a hyperapoB mother and a hyperapoB father, respectively. The risk of having the hyperapoB phenotype for each ousiotype is calculated by where baseline risk for each ousiotype can be calculated if δSP, δMO, and δFO are set to zero. For this analysis, we constrained each individual β coefficient to be between −10 and +10, because risk is essentially zero or one at these values or beyond.
Three different types of mendelian inheritance (ie, dominant, recessive, and codominant) are fit, along with environmental models in which multiple ousiotypes are considered but all transmission parameters are constant. Sporadic models with a single baseline risk with familial effects are included in the series of models considered here.
The LRT is used to compare hierarchical models. Twice the difference in log-likelihoods (−2lnL) between a restricted and an unrestricted model can be treated as a χ2 statistic with degrees of freedom equal to the difference in the number of parameters fit under the two models. The best-fitting model is the one requiring the fewest estimated parameters while giving a log-likelihood not significantly smaller than the most general model.
A heterogeneity χ2 statistic computed as which has k(I-1) degrees of freedom for a model with k parameters was used to confirm etiologic heterogeneity of hyperapoB among this study population.
One-way ANOVA and linear regression models were conducted by using the SAS statistical package (SAS Institute, Cary, NC), to test for significant differences in quantitative covariates among different types of hyperapoB (normoTG hyperapoB and hyperTG hyperapoB), and the predictive effects of hyperapoB on other atherogenic traits. χ2 tests were used to test for association with discrete covariates.
Among the 145 probands, 84 (44 males and 40 females) were found to have angiographically defined premature CAD. There were 101 multiplex families in which two or more individuals had the hyperapoB phenotype, 26 simplex families in which only one individual had hyperapoB, and 18 families without any hyperapoB individual. The distributions of gender and the hyperapoB phenotype in these families are described in Table 1⇓. The hyperapoB phenotype in two probands could not be classified. Prevalence of hyperapoB among probands was 24% (34/143), and about one third of hyperapoB probands were also hyperTG. A higher prevalence (37%, 334/892) of hyperapoB was seen among the family members, but hyperTG hyperapoB was less common (18%, 60/334) among family members with hyperapoB than among probands with hyperapoB. The prevalence of hyperapoB (regardless of TG levels) in probands and family members was significantly different (χ21=10.04, P<.05). Although males had more hyperapoB individuals than females, there was no statistical significance (χ21=1.97, P>.05). The higher prevalence of hyperapoB in family members than probands could result from: (1) overrepresentation of the affected family members, or (2) undersampling of probands with hyperapoB under our eligibility criteria.
Segregation Analysis in the Total Sample
Table 2⇓ shows estimated parameters for six models of inheritance fit to these data from all 145 families. When all restricted models were compared with the most general model (model 6), all models were strongly rejected (P<.005) on the basis of the LRT. However, the most general model is not biologically meaningful. Overall, results of this segregation analysis are inconclusive.
Characteristics of Families in Three Different Types
The characteristics of the three types of families are summarized in Table 3⇓. There was a higher proportion of multiplex families among hyperTG families than among normoTG families. The average number of children from each parent was similar in both hyperTG and normoTG families, but normal families had fewer children from each parent.
The characteristics of participants are shown in Table 4⇓, stratified by the types of family and then by types of hyperapoB. Generally speaking, there were significant differences of diabetes prevalence, glucose levels, age at interview, body mass index, and systolic and diastolic BP among hyperTG hyperapoB, normoTG hyperapoB, and normal individuals (all P values <0.05), while gender distribution was not significantly different among these three types of individuals (P>.05). Using linear regression models, the hyperTG hyperapoB phenotype was a strong predictor (ie, regression coefficient [β] of hyperTG hyperapoB=30.19±5.64) for blood glucose levels in the 55 hyperTG families. However, this predictive effect disappeared when the total population was used. Similarly, the hyperTG hyperapoB and normoTG hyperapoB phenotypes were significant predictors for BP in the 55 hyperTG families (ie, hyperTG hyperapoB β=9.49±2.95 for systolic BP and β=3.89±1.77 for diastolic BP; normoTG hyperapoB β=6.67±2.48 for systolic BP but was not significant for diastolic BP), but neither was a significant predictor when the total population was used. It also needs to be noted that these linear regressions did not take familial relationship into account; namely, they treated each individual as an independent one. Therefore, interpretation of the significance levels of regression coefficients needs to be more conservative. Several other lipids were significantly different between the two types of hyperapoB (beyond TG levels, by definition had to differ) (Figure⇓). HyperTG hyperapoB patients were reported to have a higher CAD risk in the total group of probands,2 and here we found that even normoTG hyperapoB probands from the 55 hyperTG families had a higher risk of CAD than those from the 72 normoTG families; however, the sample size was too small to conduct a meaningful statistical test (4 of 6 in hyperTG families versus 10 of 17 in normoTG families).
Segregation Analyses in Subgroups of Families
Table 5⇓ shows estimated parameters for six different models of inheritance fit to data from families in the subgroup I (55 hyperTG families plus 18 normal families). Overall, results from this subgroup were consistent with Mendelian inheritance of a recessive allele leading to a high risk of having hyperapoB. Comparison of all the restricted models with the most general model (model 6) showed that both recessive model 3 and codominant model 4 could not be rejected (χ24=4.75, P>.1; χ23=4.75, P>.1, respectively), while dominant model 2 was rejected. The sporadic model with familial effects and the environmental model were strongly rejected (P<.001) in this subgroup. Comparing models 3 and 4 using the LRT showed the recessive model 3 was the most parsimonious model for this subgroup of families (we also compared the results without constraining baseline parameter for each ousiotype in segregation analysis and the most parsimonious model is still the recessive model; data not shown).
Model 3 in Table 5⇑ suggested that 49% of this population had the high-risk genotype (AA), which had baseline risk of 0.78. If any individual with this high-risk AA genotype had either a hyperapoB mother, father, or spouse, the risk could be reduced to 0.58, 0.30, or 0.70, respectively. These negative effects of parents were not significant when the major gene effect was not incorporated into the models (see model 1 in Table 5⇑), but these negative effects became larger and significant after hypothesizing a major gene effect. The possible explanations for this paradoxical reduction of risk will be discussed. Since hyperTG families supported a mendelian fashion of inheritance, these families will be referred to as “genetic families” in the following sections.
Segregation analysis in the subgroup II (72 normoTG families plus 18 normal families) produced no clear pattern of inheritance (Table 6⇓). Comparing every mendelian model (models 2 through 4) to the most general model 6, all the Mendelian models were rejected (all P<.025). Both environmental model 5 and sporadic model 1 were rejected (both P<.025) also. For this subgroup of families, the best-fitting model was the most general model 6, which itself is difficult to interpret because the allele frequency maximized at its upper bound. Overall, non-Mendelian inheritance was favored in this subgroup, and the 72 normoTG families will be called “nongenetic families” in the following sections.
We performed heterogeneity χ2 statistic using model 3 from Table 5⇑ on both the total families and the three individual subtypes (we treated hyperTG [n=55], normoTG [n=72], and normal [n=18] families as three separated subgroups to have 145 families. Thus, the sum of families in subgroups was equal to the total data set) and maximized all parameters. This test gave strong evidence of etiologic heterogeneity (χ2 12=75, P<.001).
The purpose of this study was to test for the possible genetic control of the hyperapoB phenotype. Complex segregation analysis under class A logistic regressive models was used to determine whether the observed familial clustering of hyperapoB was consistent with genetic control. Segregation analysis of the total group of 145 families produced no clear picture; however, after stratifying the families into subgroups based on the presence of any hyperTG hyperapoB individual in the family, stronger evidence of mendelian control emerged. The hyperTG families supported a recessive mendelian model, but normoTG families failed to identify any single mechanism (genetic or nongenetic) as best. Such different findings suggest etiologic heterogeneity. Furthermore, the heterogeneity χ2 statistic also confirms this idea.
These findings are consistent with the previous hypothesis of etiologic heterogeneity of the hyperapoB phenotype. Our findings offer a basis to conduct linkage studies in hyperapoB families showing evidence of mendelian control.
The negative residual parent-offspring coefficients in the best-fitting model (model 3 in Table 5⇑) are difficult to interpret, although other studies using these regressive logistic models also reported negative residual familial effects in analysis of unrelated diseases.22 23 To investigate possible sources of these negative residual parental effects, we checked hyperapoB status in all father-offspring and mother-offspring pairs (Table 7⇓). HyperapoB fathers had fewer hyperapoB than non-hyperapoB offspring, and a similar pattern was also found in the mother-offspring pair. These discordant patterns suggest parental hyperapoB phenotype is not the major determinant for the child’s hyperapoB status. We also wondered whether non-hyperapoB parents who had other related dyslipidemias (ie, type IIa, IIb, IV, and hypoalpha) could increase the risk of having hyperapoB in their offspring and ignoring these related dyslipidemias could lead to negative residual parental effects. We found only three parent-offspring trios that comprised a hyperapoB child, a related dyslipidemic father, and normal mother in 55 hyperTG families. Therefore, it seems unlikely that another related dyslipidemia in parents could account for these negative coefficients.
However, there are several possible explanations for negative residual parental effects: (1) simultaneously considering effects of a single major locus and residual familial correlation may have overparameterized this model; (2) some hyperapoB individuals could be phenocopies, and their children would not have hyperapoB most of the time; (3) residual familial correlations could reflect unmeasured environmental (or genetic) effects that may interact with the major gene, or (4) hyperapoB may be under oligogenic control, and therefore, the one-locus segregation analysis would be simplistic, forcing coefficients for the residual parental effects to behave unexpectedly. While we cannot readily explain these negative parental coefficients, they do suggest that the pattern of inheritance of hyperapoB is even more complicated than previously thought.
There are two alternative explanations for not finding evidence of major gene effects among the 72 normoTG families (ie, nongenetic families): (1) one or more unknown nongenetic risk factors determine the hyperapoB phenotype in these families, and if so, these families may offer a unique opportunity to identify these nongenetic factors; (2) some normoTG families may be misspecified, and thus there is a mixture of genetic and nongenetic mechanisms in this subgroup of families.
We tested for other different characteristics between normoTG hyperapoB and hyperTG hyperapoB individuals who were only from the genetic families (n=55), and we also investigated whether there were different characteristics between normoTG hyperapoB individuals who were in the genetic and in the nongenetic (n=72) families to give more insight into the biological consequences of hyperapoB. HyperTG hyperapoB individuals had quite different lipid profiles from normoTG hyperapoB individuals, beyond the obvious difference in TG levels (Figure⇑). NormoTG hyperapoB individuals from either the genetic or nongenetic families had similar lipid profiles, except for VLDL-C levels. In the genetic families, hyperTG hyperapoB individuals had higher total plasma apoB (including apoB in VLDL, IDL, and LDL particles) but similar LDL-B compared with the normoTG hyperapoB individuals. These observations suggest defects in the overproduction of apoB or VLDL is milder in normoTG hyperapoB than in hyperTG hyperapoB individuals. Moreover, hyperTG hyperapoB individuals had higher VLDL-C but lower LDL-C levels than normoTG hyperapoB individuals, which might suggest even more transfer of TG from VLDL to LDL for cholesteryl ester in LDL among hyperTG hyperapoB individuals, and this subsequently leads to smaller LDL particles. We have previously measured LDL size and density in these probands, and LDL size was significantly inversely correlated with LDL TG and with LDL-B, and LDL size was significantly positively correlated with LDL-C and with LDL-C-to-LDL-B ratio.24 Because of similar mean of age at interview (49.7 years in hyperTG versus 50.8 years in normoTG) in these two forms of hyperapoB, it seems unlikely that normoTG hyperapoB will progress to hyperTG hyperapoB.
Diabetes was more common in hyperTG hyperapoB individuals (18.3%), followed by normoTG hyperapoB individuals (9.6% in hyperTG families and 8.2% in normoTG families), and then by normal individuals (4.9% in hyperTG families; 3.6% in normoTG families, and 6.7% in normal families) (Table 4⇑). HyperTG hyperapoB individuals had a higher mean fasting blood glucose level than the other groups. Furthermore, hyperTG hyperapoB individuals tended to have higher BP, lower HDL-C levels, and smaller, denser LDL particles (Figure⇑), which provides further evidence for a phenotypic overlap between hyperapoB, familial dyslipidemic hypertension, LDL subclass pattern B, and syndrome X. The hyperTG hyperapoB phenotype can predict BP and blood glucose levels in the hyperTG families, but not in the total families, which may indicate a mutant gene is one of the common genetic mechanisms of hypertension and diabetes in the hyperTG families but may not be a common cause of hypertension or diabetes in the general population. The genetic relationship between these disorders displays some interesting points and needs further investigation.
ApoB is a direct gene product and primarily found in LDL particles. Eight studies using segregation analyses in quantitative levels of plasma apoB have been reported.16 25 26 27 28 29 30 31 These studies suggested a major gene influencing apoB levels in their respective populations. Since apoB overproduction is one of the metabolic hallmarks of hyperapoB, one important question to ask is whether a common allele leading to an upward shift in apoB levels also causes hyperapoB. Coresh et al16 used a subset (116 families) of the present study (145 families), and found evidence for etiologic heterogeneity in the regulation of apoB levels. They found 57 families supported a Mendelian major gene model for apoB levels, while the other 59 families did not have any clear-cut pattern of genetic inheritance. Since our study also showed etiologic heterogeneity of hyperapoB, we analyzed the concordance rate of classification of families in both studies, and it showed only 55% of families (ie, 64/116 families had consistent classification, either genetic or nongenetic). These results suggested the major locus for apoB levels is different from that for hyperapoB. Another study31 also investigated this question in a sample enriched for familial combined hyperlipidemia, and found 85% of hyperapoB individuals did not carry a copy of this hypothetical “elevated apoB” allele. The above evidence seems to suggest apoB levels per se and hyperapoB may be controlled by different genes.
There are some limitations in our study. Since hyperapoB may be caused by either genetic or nongenetic factors, there is an unknown proportion of “phenocopies” of hyperapoB even in the genetic families. The prevalence of hyperapoB in the general population is unknown; nevertheless, apoB levels above 95th percentile in adult Americans were greater than 130 mg/dL (unpublished data from NHANES III, P.S. Bachorik, 1996). Although phenocopies will influence the estimated parameters from segregation analysis, the apparent difference in estimated risks among three genotypes in the best-fitting model in Table 5⇑ cannot be attributed to phenocopies alone. The ascertainment scheme in our subgroup analyses was complicated, which makes precise ascertainment correction very unlikely. Although we used 18 normal families as a background population in each subgroup analysis to minimize the impact of ascertainment bias, there is likely to be some residual impact on the results, eg, the allele frequency may be inflated. However, the general inference for families enriched for premature CAD should still be valid.
Among familial dyslipidemias associated with premature CAD, familial hypercholesterolemia is best characterized, but it accounts for only a small proportion (about 5%) of premature CAD.32 This study is the first step in exploring genetic components of hyperapoB, which is associated with more than 30% of premature CAD,2 and our results offer a basis to deal with etiologic heterogeneity that should be expected in most complex disorders.
Selected Abbreviations and Acronyms
|CAD||=||coronary artery disease|
|HDL-C, LDL-C, VLDL-C||=||HDL, LDL, and VLDL cholesterol|
|JH-CAD||=||Johns Hopkins Coronary Artery Disease|
|LDL-B||=||LDL apolipoprotein B|
|LRT||=||likelihood ratio test|
Part of this work was supported by grants from the National Institutes of Health Specialized Center of Research in Arteriosclerosis (1-P50-HL47212-05, NHLBI 31497-08, and HD 32193-02). The results of this paper were obtained by using the program package SAGE, which is supported by a US Public Health Service resource grant (1 P41 RR03655) from the Division of Research Resource. The authors thank Hazel Smith for patient recruitment and Jeff Jenkins for his assistance in data management. We would like to thank Drs David Duffy, Joe Coresh, Joan Bailey-Wilson, and Christopher Amos for their invaluable suggestions on this analysis.
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