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Arteriosclerosis, Thrombosis, and Vascular Biology. 2002;22:1720-1725
Published online before print August 1, 2002, doi: 10.1161/01.ATV.0000032133.12377.4D
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(Arteriosclerosis, Thrombosis, and Vascular Biology. 2002;22:1720.)
© 2002 American Heart Association, Inc.

Lipoproteins

Locus Controlling LDL Cholesterol Response to Dietary Cholesterol Is on Baboon Homologue of Human Chromosome 6

Candace M. Kammerer; David L. Rainwater; Laura A. Cox; Jennifer L. Schneider; Michael C. Mahaney; Jeffrey Rogers; John L. VandeBerg

From the Department of Human Genetics (C.M.K.), University of Pittsburgh, Pittsburgh, Pa; the Southwest Foundation for Biomedical Research (C.M.K., D.L.R., L.A.C., J.L.S., M.C.M., J.R., J.L.V.), San Antonio, Tex; and the Southwest National Primate Research Center (J.R., J.L.V.), San Antonio, Tex.

Correspondence to Candace M. Kammerer, Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, 130 De Soto St, Pittsburgh, PA 15261. E-mail ckammerer{at}hgen.pitt.edu

Abstract

Objective— Cholesterolemic responses to dietary lipids are known to be heritable, but the genes that may affect this response have yet to be identified. Using segregation analysis, we previously detected a potential quantitative trait locus (QTL) in baboons that influenced low density lipoprotein cholesterol response to dietary cholesterol. We performed linkage analyses to locate this QTL by using data on the baboon genetic linkage map.

Methods and Results— We obtained evidence for linkage of this potential QTL to the same locus (D6S311) on the baboon homologue of human chromosome 6 by using variance components and parametric linkage analysis methods (2-point lod scores 4.17 [genomic probability value 0.008] and 2.81 [genomic P=0.10], respectively). Linkage analyses of serum levels of apolipoprotein B dietary response, a correlated trait, also gave weak suggestive evidence of linkage to this chromosomal region (maximum 2-point lod score 1.91). Although the LPA locus is nearby, we found no evidence of linkage with LPA.

Conclusions— This report is the first to localize, in any primate species, a potential QTL that influences low density lipoprotein cholesterol response to dietary cholesterol.


Key Words: LDL • diet • linkage • baboons

An increased plasma level of LDL cholesterol (LDLC) is a well-known risk factor for the development of cardiovascular disease (CVD). Epidemiological studies have also shown that dietary factors increase the risk of CVD; however, there is considerable interindividual variability in cholesterolemic response to dietary lipid,1 and a proportion of this variation in response is genetic.2–4 Polymorphisms in some genes involved in lipid metabolism have been associated with cholesterolemic response to dietary change in humans, although these effects generally are small.5 One of the current challenges in cardiovascular research is to identify genes that interact with environmental factors, such as diet, to affect the risk of developing CVD.

Using segregation analysis on data from a large population of pedigreed baboons, we previously detected a major gene that affects LDLC response to increased dietary cholesterol (LDLCRC).6 In this case, LDLC refers to all apoB-containing lipoproteins that are predominantly particles in the LDL size interval in baboons.7 This major gene (or quantitative trait locus [QTL]) accounted for much of the genetic variation in LDLCRC and also affected some of the variation in LDLC on the basal diet. To locate this potential QTL, we performed linkage analyses based on the recently developed genetic linkage map for baboons.8

Methods

Animals
Data were analyzed on a total of 760 pedigreed baboons (Papio hamadryas) consisting of 10 pedigrees ranging in size from 42 to 107 animals. These 2- and 3-generation pedigrees consisted of 218 founders (33 sires and 185 dams) and their 542 offspring. Serum lipid and lipoprotein, as well as genotypic, data were available on 632 of the pedigreed baboons. These families provided a large number of pairwise relationships for genetic analyses, including 1210 first-degree, 6546 second-degree, 1495 third-degree, and 62 fourth-degree relative pairs with data. The 216 males and 416 females with data had a mean±SD age of 9.6±6.9 years (range 2.2 to 22.5 years) and a mean±SD weight of 16.8±8.5 kg (range 5.2 to 45.2 kg) at the outset of the experiment.

All animals were maintained at the Southwest Foundation for Biomedical Research, a facility certified by the Association for Assessment and Accreditation of Laboratory Animal Care International. The experimental protocol was approved by the Institutional Animal Care and Use Committee.

Diet Protocol
All baboons were subjected to the same 4-step dietary challenge as previously described.6 Briefly, these steps were as follows: (1) Animals were fed a baseline monkey diet (Wayne Teklad), low in fat ({approx}4% of calories) and cholesterol (0.03 mg/kcal), for at least 2 months before the baseline blood sample. (2) Animals were fed a diet high in saturated fat (40% of calories from fat by the addition of lard) and cholesterol (1.7 mg/kcal) for 7 weeks before the high-cholesterol high-fat (HCHF) diet blood sample. (3) Animals were fed the baseline diet for a 7-week washout period. (4) Animals were fed a high-fat-only diet (40% of calories from lard, 0.03 mg/kcal of cholesterol) for 7 weeks before the low-cholesterol high-fat (LCHF) diet blood sample.

After an overnight fast, baboons were immobilized with ketamine (10 mg/kg), and blood samples were drawn from the femoral vein. The blood was allowed to clot, and the serum was obtained by low-speed centrifugation. Serum samples were either refrigerated and used for cholesterol assays within the week, or they were frozen at -80°C in small aliquots9 for assays of apoB, Lp(a), and lipoprotein size. At the time of blood drawing, body weight (in kilograms) was recorded.

Measurement of Lipids and Lipoproteins
Cholesterol concentrations (millimolar) were measured enzymatically10 with a reagent supplied by Boehringer-Mannheim Diagnostics and a Ciba-Corning Express Plus clinical chemistry analyzer. Cholesterol in HDL was determined in the supernatant after precipitation of apoB-containing lipoproteins by use of heparin-Mn2+,11 and LDLC was calculated as the difference between total and HDL cholesterol. Cholesterol in apoB-containing lipoproteins resides primarily in LDL particles; other relatively minor contributors of cholesterol to this LDLC value include VLDL, IDL, and Lp(a). Average coefficients of variation for control products in these assays were 2.2% and 4.6% for total cholesterol and HDL cholesterol, respectively.

We used composite gradient gels made in the laboratory12 to separate baboon lipoproteins on the basis of size. Lipoprotein cholesterol was stained with Sudan black B and was quantified by use of an LKB UltroScan XL laser densitometer with in-house-developed software.12 Gels were calibrated with carboxylated polystyrene microspheres (38-nm diameter), a lyophilized plasma standard containing 2 LDL bands (27.5 and 26.6 nm),13 and thyroglobulin (17 nm), which were used to identify the interval of 24 to 30 nm containing baboon LDLs. LDL median diameters (LDLdiams) were determined as the diameter (in nanometers) for which half the LDL absorbance was on larger and half was on small particles. The coefficient of variation for LDLdiam in a lyophilized baboon serum standard run on each gel was 0.7% (n=306 gels).

Serum concentrations of apoB (in milligrams per deciliter) were measured by an immunoturbidometric assay using a Ciba-Corning Express Plus clinical chemistry analyzer and the protocol recommended by the reagent manufacturer (Diasoran). The calibration curve was generated from a set of 5 fractionated pooled normal human serum samples provided by Diasoran. Intra-assay and interassay coefficients of variation for control products in these assays were 3% and 7%, respectively.

Serum Lp(a) concentrations (in milligrams per deciliter) were measured by using a commercial kit [Apo-Tek Lp(a), Sigma Diagnostics], which is specific for Lp(a) particles by virtue of requiring sequential binding by antibodies directed against both apo(a) and apoB.14 Samples were assayed as suggested by the supplier, and control products supplied with the kit gave coefficient of variation estimates of 8.3% at 7.7 mg/dL and 6.4% at 25.7 mg/dL. Assay repeatability for baboon samples was 98.0%.

As previously described,6 LDLCRC was calculated as the difference in LDLC between the HCHF and LCHF diets (LDLCHCHF-LDLCLCHF). After detecting evidence for linkage for the potential QTL for LDLCRC, we subsequently analyzed data on 3 phenotypes that are components of LDLC: Lp(a) and apo(B) concentrations and LDLdiam. For these phenotypes, we analyzed data on the basal diet (subscript basal) as well as response to dietary cholesterol (subscript RC). LpaRC, apoBRC, and LDLdiamRC were calculated as the difference between trait values on the HCHF and LCHF diets. Before analysis, LDLCRC, Lpabasal, and LpaRC were transformed by natural logarithms to reduce skewness and kurtosis. Also, all values >±4 SD from the mean were removed before analysis (a maximum of 2 values for any phenotype).

Genotypes
Published human primers were used to amplify 279 homologous microsatellite loci from baboon genomic DNA samples. Approximately two thirds of the genotypes and 236 of these highly polymorphic markers were generated by researchers at Axys Pharmaceuticals, Inc, as part of another project and were used in the previously described baboon genomic map.9 Genotypes of the baboons were determined through gel electrophoresis of the fluorescently labeled polymerase chain reaction products in ABI 373 or ABI 377 automated sequencers with Perkin-Elmer Gene Scan software and analysis with Perkin-Elmer Genotyper software.

Genotypes at the LPA locus were inferred on the basis of the apo(a) size polymorphism.15 Briefly, serum samples were treated with SDS under reducing conditions, and apo(a) isoform phenotypes were resolved by electrophoresis in acrylamide gradient gels and detected by using a system16 that identifies 12 isoform sizes in baboons.

Statistical Analyses
We used univariate quantitative genetic analysis to assess the residual heritability of the lipid traits while simultaneously incorporating the effects of covariates such as sex, sex-specific linear and quadratic age, and weight.17 All parameters were estimated by using maximum likelihood methods. Significance of the residual heritability and the covariate effects were assessed by comparing the likelihood of a submodel, in which the specific parameter to be tested was fixed at zero, with that of a model in which all parameters were estimated, with the use of the likelihood ratio test, as described in detail elsewhere.15 This statistic is asymptotically distributed as a {chi}2 with 1 df.

Multivariate quantitative genetic methods18 were used to calculate genetic correlations ({rho}G) between LDLCRC and the component lipid phenotypes and to estimate the magnitude of pleiotropic effects of the underlying genes. Large genetic correlations between traits imply that the same gene or genes influence both traits. Total phenotypic correlations ({rho}P) were calculated as follows: {rho}P={surd}h12 · {surd}h22{rho}G+{surd}(1-h12) · {surd}(1-h22) · {rho}E, where h12 and h22 are the heritabilities of the 2 traits and {rho}E is the nongenetic correlation.

Two-point and multipoint genomic scans were performed on data from the baboon pedigrees by using a variance components method that has been extended for use on full pedigrees as implemented in SOLAR.19 Briefly, we estimated the genetic variance attributable to the region around a specific genetic marker ({varsigma}2m) by specifying the expected genetic covariances between arbitrary relatives as a function of the identity-by-descent relationships at a given marker locus assumed to be tightly linked to a locus influencing the quantitative trait. We compared the likelihood of the restricted model, in which {varsigma}2m=0 (no linkage), with that of a model in which the variance due to the marker is estimated. Because underlying nonnormality of a trait can inflate lod scores, we performed 10 000 simulations with an unlinked marker and then used regression analyses to estimate a lod score adjustment factor for LDLCRC, as described previously.20 After detection of linkage to a QTL for LDLCRC, we subsequently estimated adjustment factors for the component phenotypes. All 2-point and multipoint lod scores given in the text are empirically adjusted lod scores. Following the suggestion of Lander and Kruglyak21, and using data on baboons (ie, 20 autosomes with total length of 23.75 morgans),8 we calculated genomic probability values for linkage to the phenotype of interest, LDLCRC.

Demonstration of linkage between the previously detected major locus for LDLCRC and the same baboon chromosome 4 markers linked to the LDLCRC QTL located via variance component linkage analysis would indicate that these loci are identical. We performed parametric lod-score linkage analyses between the major locus for LDLCRC and genotypes at the microsatellite markers by using Pedigree Analysis Package,18 as described in detail elsewhere.22 In these analyses, the parameters describing the inheritance of the LDLCRC major gene were fixed at their maximum likelihood estimates; these parameters include the frequency of the major locus (fA), the means of each major locus genotype (µAA, µAa, and µaa), the overall standard deviation ({varsigma}), the effects (ß) of significant covariates, and the residual heritability. The logarithmic odds of linkage versus no linkage were calculated at recombination frequencies ({theta}) equal to 0.01, 0.05, 0.10, 0.15, and 0.20. In the text, we report lod scores at {theta}=0.05. 0.10, and 0.15 only, but lod scores for other {theta} values were consistent with these results.

Results

Previously, we had detected a QTL for LDLCRC6 by using segregation analysis methods on 575 baboons. We currently have data on an additional {approx}50 baboons; therefore, we reestimated the residual heritability and effects of covariates and, as expected, obtained nearly identical results, eg, h2=0.59±0.08 (n=575)6 versus h2=0.54±0.08 (n=628, Table 1). We reestimated the parameters describing the major gene by using data for 628 individuals and obtained values that are essentially identical to those reported previously6; ie, fA=0.74, µAA=1.72, µAa=1.80, µaa=2.12, {varsigma}=0.11, ß weight=-0.003, and h2=0.14.


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  		Table 1. Means, Covariate Effects, and Heritabilities of Lipid Traits in Baboons

We performed a genome screen by using variance components linkage analysis methods to search for QTLs affecting LDLCRC. The maximum 2-point lod score across all chromosomes (Table 2) was 4.17 (genomic P=0.008) at locus D6S311 on baboon chromosome 4q, which is homologous to human chromosome 6q.8 The chromosome with the next highest 2-point lod score was baboon chromosome 3 (lod score 1.68). The structural locus for apo(a), LPA, also maps to human chromosome 6q.23 Apo(a) is the unique component of Lp(a) particles, a CVD risk factor, and variation at LPA accounts for {approx}90% of variation in Lp(a) concentrations in humans and baboons15,24 (Table 1). Thus, we genotyped the animals in the study for LPA and mapped this locus onto baboon 4q, but we found no evidence for linkage (lod <1.0) of the potential QTL for LDLCRC to LPA (Table 3).


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  		Table 2. Highest Two-Point lod Scores for LDLCRC for Each Baboon (PHA) Chromosome (and the Human [HSA] Homologue)


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  		Table 3. Two-Point lod Scores for LDLCRC Concentrations With Baboon Chromosome 4 Loci Using Variance Components Linkage Analyses and Parametric Linkage Analyses at Three Recombination Frequencies ({theta}) Using the Major Gene Model

To determine the relationship between this potential QTL and the previously reported major locus for LDLCRC, we performed parametric 2-point linkage analyses by using the LDLCRC major locus model obtained from segregation analysis. Overall, the results of the 2-point parametric linkage analyses correspond well with the results of the variance components analyses (Table 3). For example, linkage of the LDLCRC major gene to loci on 4p (D6S276 through D6S1048) was strongly excluded (lod score <-2.0 at {theta}=0.05). In addition, the 2 loci that gave the highest lod scores with the use of variance components linkage analyses also gave the highest parametric lod scores (for D6S501, lod score 2.89 at {theta}=0.10, genomic P=0.08; for D6S311, lod score 2.81 at {theta}=0.15, genomic P=0.10). The observation that the highest parametric lod scores are obtained at a {theta} value of 0.10 to 0.15, rather than a {theta} value of <0.05, is not unexpected because the major locus model is likely to be incorrectly specified. Two-point parametric linkage analyses are fairly robust to incorrect specification of the model; however, the estimate of the recombination fraction is inflated.25 Both methods also gave no evidence for linkage with D6S1028, a locus with high heterozygosity (0.78) that is located between the 2 loci with the highest lod scores. Such an anomalous result may imply that a marker locus is incorrectly ordered, and although compared with human 6q, this region of baboon 4q is substantially rearranged, the logarithmic odds for placement of D6S1028 in this position are >19.0. At this time, we have no a priori reason to remove D6S1028; thus, we have included it in the subsequent multipoint linkage analyses. Overall, both methods of linkage analysis strongly indicate that a potential QTL for LDLC response to dietary cholesterol is located on baboon 4q.

Variation in LDLC response to dietary cholesterol could be due to changes in the numbers or sizes of LDL particles, or both, and may also be correlated with changes in Lp(a) concentrations. Because there is only 1 apoB molecule per ß-lipoprotein particle, apoB concentrations are directly related to numbers of LDL particles, and LDLdiam is a measure of LDL particle size (as stained for cholesterol by using Sudan black B). To gain additional insight into the nature of this potential QTL for LDLCRC, we performed quantita- tive genetic and linkage analyses on the following variables: (1) apoBbasal, apoB concentrations measured on the basal diet; (2) apoBRC, apoB response to dietary cholesterol; (3) LDLdiambasal, a variable representing the median diameter of the LDLC particles on the basal diet; (4) LDLdiamRC, a variable representing the change in median diameter of the LDLC particles in response to dietary cholesterol; (5) Lpabasal, Lp(a) concentrations measured on the basal diet; and (6) LpaRC, a variable representing Lp(a) response to dietary cholesterol. As expected from previous analyses,15 Lpabasal and LpaRC were highly and moderately heritable (h2=0.92±0.05 and 0.32±0.07, respectively). Both apoB traits were moderately heritable, but the LDLdiam phenotypes had low heritabilities (Table 1). In addition, apoBRC and LDLdiamRC were strongly correlated with LDLCRC; both phenotypic and genetic correlations were >0.6 for both traits (Table 4). In contrast, the total phenotypic and genetic correlations of LDLCRC with apoB concentration and LDLdiam on the basal diet and Lp(a) concentrations on both diets were substantially lower. Although the genetic correlation between LDLCRC and LDLdiamRC is high, the very low heritability of LDLdiamRC indicates that linkage analyses are likely to be uninformative because the environmental noise will mask any genetic signals.


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  		Table 4. Total Phenotypic ({rho}P), Genetic ({rho}G), and Nongenetic ({rho}E) Correlations Between LDLCRC and Other Lipoprotein Phenotypes

Because the quantitative genetic analyses indicated that variation in LDLCRC is genetically correlated with some of the component phenotypes, we next performed multipoint variance components linkage analyses with use of the sex-averaged map. As expected, for LDLCRC we obtained a maximum multipoint lod score near D6S311 (lod score 3.86, genomic P=0.011; Figure). Furthermore, the 1-lod support interval for the LDLCRC QTL ranges from D6S1028 to D6S1040 and does not encompass the LPA locus. We also performed multipoint linkage analyses of LDLCRC by using the female and male map distances and again obtained maximum multipoint lod scores near D6S311 (lod score 4.11 and 3.35, respectively), and the respective 1-lod support intervals did not encompass the LPA locus (results not presented). As further support for our hypothesis that the LDLCRC QTL is not LPA, multipoint variance components linkage analyses of Lpabasal gives a maximum multipoint lod score (21.96) at the LPA locus, and the 1-lod support interval does not encompass the location of the LDLCRC QTL (Figure).



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  		Multipoint adjusted lod-score profile of LDLCRC (solid line), apoBRC (dashed line), and Lp(a)basal (dot-dashed line) for baboon chromosome 4. Vertical lines represent 1-lod support units.

Results of multipoint linkage analyses of baboon chromosome 4 revealed no evidence of a QTL affecting LDL diameter for either diet, for LpaRC, or for apoBbasal concentrations (maximum multipoint lod score <1.4 for all traits, data not shown). These linkage results are not surprising given either the low heritabilities or the low genetic correlation with LDLCRC of these traits. However, we obtained weak suggestive evidence (maximum multipoint lod score 1.90) that a QTL may affect apoBRC concentrations (Figure).

Discussion

Many epidemiological studies, as well as dietary studies, have shown that dietary cholesterol has an adverse effect on lipid profile,26 although lipemic response varies among individuals.1 This interindividual variability in response confounds the usefulness of general dietary recommendations27; however, the fact that genes control some of the interindividual variation in lipemic response2–4 suggests that dietary intervention may be efficacious in specific individuals. Therefore, identification of the genes responsible for this genotype by diet effect would facilitate the targeting and evaluation of treatment protocols for susceptible individuals.

To date, most studies in humans have investigated whether lipemic response to diet differs among adults26,28 and children29 with different genotypes at a known candidate locus for lipoprotein metabolism.5 Although the differential effects of polymorphisms at some candidate genes, such as APOA4, on dietary response have been well documented,26 differential effects among genotypes at other candidate loci are more controversial.26,30 Furthermore, these variants account for relatively little of the total variation in lipemic response, suggesting that additional, as-yet-unidentified, genes are involved.

LDLC and apoB concentrations are well-known risk factors for development of CVD, and several investigators have used segregation analysis on family data to detect evidence of major genes affecting these phenotypes.31,32 In addition, investigators using linkage analysis methods have reported numerous QTLs affecting LDL-related phenotypes,33–36 2 of which map to chromosome 6.36,37 However, with the exception of candidate gene polymorphisms, there have been no reports of QTLs affecting LDLC or apoB dietary response in humans.

We previously detected a major gene for serum LDLC response to dietary cholesterol6 in baboons, a primate model used in atherosclerosis research.1 Multipoint linkage analyses using variance components methods indicate that a QTL for LDLCRC resides on the baboon chromosome 4q (maximum lod score 3.86 near D6S311, genomic P=0.011). When we performed parametric linkage analyses using parameters describing the previously detected LDLCRC major gene,6 we also obtained our highest 2-point linkage signal (lod score 2.89, genomic P=0.08) in this region. The results of these 2 linkage analyses support our hypothesis that a QTL for LDLC response to dietary cholesterol in baboons is located on baboon chromosome 4q, which is homologous to human chromosome 6q. Because baboons are phylogenetically closely related to humans and exhibit similarities in lipoprotein metabolism, especially in response to an atherogenic diet,38 variants at this potential QTL for LDLCRC may also play a role in human lipoprotein metabolism.

Because our measure of LDLC includes Lp(a) cholesterol concentration, it was possible that the potential QTL for LDLCRC might actually be the LPA locus, which maps to human chromosome 6q. We performed linkage analyses using data on Lp(a) concentrations to test this hypothesis. As can be seen in the Figure, the 1-lod support interval of the QTL for LDLCRC does not encompass LPA, nor does the 1-lod support interval (around LPA) for Lp(a) concentration encompass the QTL for LDLCRC. Thus, the QTL for LDLCRC is not LPA.

To gain insight into the possible mode of action of this potential QTL for LDLCRC, we performed quantitative trait linkage analyses on data involving apoB concentrations and LDLdiam on the basal diet and on data involving the response to dietary cholesterol. We obtained no evidence for possible QTLs on baboon chromosome 4 for apoBbasal, LDLdiambasal, or LDLdiamRC (maximum multipoint lod score <1.4). However, we obtained weak suggestive evidence that a QTL for apoBRC concentrations might be present (lod score 1.90, Figure). If it is assumed that a QTL for apoBRC does exist, one explanation for the low lod score may be that {approx}20% fewer individuals were phenotyped for this trait than for LDLCRC (Table 1), thus reducing the power of the linkage analyses. Therefore, we speculate that this potential QTL for LDLCRC may be associated with increased numbers of LDL particles rather than increased particle size.

We have not, as yet, identified any candidate genes for this QTL. With the exception of the LPA locus, which we have excluded, no obvious candidate genes exist in this region. Furthermore, the rearrangements between human chromosome 6 and baboon chromosome 4 structure8 preclude us from accurately evaluating relevant candidate genes with the use of the human genome map at this time. Fine mapping of the region will be necessary for an informative evaluation of possible candidate genes for this potential QTL for LDLC response to dietary cholesterol.

Acknowledgments

This work was supported in part by grants from the National Institutes of Health (HL-28972 and RR-08781). The authors are grateful to the following individuals for help with various aspects of the study: Catherine Jett, Shifra Birnbaum, Perry H. Moore, Jr, Wendy R. Shelledy, and Jane F. VandeBerg for technical assistance; Drs K.D. Carey and Karen S. Rice for managing the breeding colony and conducting the dietary challenge; and Drs Phillip Morin and Geoff Joslyn of Axys Pharmaceuticals for generating much of the genotype data.

Received April 25, 2002; accepted July 22, 2002.

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