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Common and Rare Alleles in Apolipoprotein B Contribute to Plasma Levels of Low-Density Lipoprotein Cholesterol in the General Population

Department of Clinical Biochemistry (M.B., M.C.A.S., A.T.-H.), Rigshospitalet, Copenhagen University Hospital; Department of Clinical Biochemistry (B.G.N.), Herlev University Hospital, The Copenhagen City Heart Study (B.G.N., G.B.J., A.T.-H.), Bispebjerg University Hospital, and Department of Medicine B (R.S.), Hillerød Hospital, all Faculty of Health Sciences, University of Copenhagen, DK-2100 Copenhagen, Denmark

Address all correspondence and requests for reprints to: Anne Tybjærg-Hansen, M.D., D.M.Sc., Chief Physician, Associate Professor, Department of Clinical Biochemistry KB3011, Section for Molecular Genetics, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen Ø, Denmark. E-mail: at-h{at}rh.regionh.dk.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Context: We have previously shown that rare mutations in the apolipoprotein B gene (APOB) may result in not only severe hypercholesterolemia and ischemic heart disease but also hypocholesterolemia. Despite this, common single-nucleotide polymorphisms (SNPs) in APOB have not convincingly been demonstrated to affect low-density lipoprotein (LDL) cholesterol levels.

Objective: We tested the hypothesis that nonsynonymous SNPs in three important functional domains of APOB and APOB tag SNPs predict levels of LDL cholesterol and apolipoprotein B and risk of ischemic heart disease.

Design: This was a prospective study with 25 yr 100% follow up, The Copenhagen City Heart Study.

Setting: The study was conducted in the Danish general population.

Participants: Participants included 9185 women and men aged 20–80+ yr.

Main Outcome Measures: Levels of LDL cholesterol and apolipoprotein B and risk of ischemic heart disease and myocardial infarction were measured. The hypothesis was formulated before genotyping.

Results: We genotyped 9185 individuals for APOB T71I (minor allele frequency: 0.33), Ivs4+171c>a (0.14), A591V (0.47), Ivs18+379a>c (0.30), Ivs18+1708g>t (0.45), T2488Tc>t (0.48), P2712L (0.21), R3611Q (0.09), E4154K (0.17), and N4311S (0.21). SNPs were associated with increases (T71I, Ivs181708g>t, T2488Tc>t, R3611) or decreases (Ivs4+171c>a, A591V, Ivs18+379a>c, P2712L, E4154, N4311S) in LDL cholesterol from –4.7 to +8.2% (–0.28 to 0.30 mmol/liter; P 0.002), and corresponding effects on cholesterol and apolipoprotein B levels. However, as predicted from the magnitude of the observed LDL cholesterol effects, none of these SNPs predicted risk of ischemic heart disease prospectively in the general population, in a case-control study, or as haplotypes.

Conclusions: Multiple common and rare alleles in APOB contribute to plasma levels of LDL cholesterol in the general population, although the effects of common alleles and haplotypes are modest.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Twin studies suggest that about 50–60% of the variation in plasma levels of apolipoprotein B is genetically determined (1). Apolipoprotein B is crucial in the initial steps of chylomicron and very low-density lipoprotein (VLDL) formation, as well as in the binding and clearance of low-density lipoprotein (LDL) by the LDL receptor. Rare missense mutations in the apolipoprotein B gene (APOB) may result in not only severe hypercholesterolemia and increased risk of ischemic heart disease but also hypocholesterolemia (2, 3, 4). In contrast, previous studies examining the association of common nonsynonymous single-nucleotide polymorphisms (SNPs) in APOB with lipid and lipoprotein levels and with risk of ischemic heart disease have been conflicting (5, 6).

For this reason, we selected six nonsynonymous SNPs in APOB, located in important functional domains crucial for lipidation of the nascent apolipoprotein B (T71I, A591V) (7, 8), involved in structural changes of apolipoprotein B during the conversion of VLDL to LDL (P2712L) (9) or known or suspected of regulating binding to the LDL receptor (R3611Q, E4154K, N4311S) (10, 11). In addition, we selected four other SNPs [Ivs4 + 171c>a, Ivs18 + 379a>c, Ivs18 + 1708 g>t, and T2488Tc>t (12)] because they together with T71I, A591V, and E4154K are predicted by HapMap to tag the genetic variation in the entire coding and intronic regions of APOB, comprising approximately 43 kb of genomic DNA.

We genotyped 9185 individuals from the Danish general population followed up prospectively for 25 yr in the Copenhagen City Heart Study and tested the following hypotheses: T71I, Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, T2488Tc>t, P2712L, R3611Q, E4154K, and N4311S in APOB predict levels of LDL cholesterol and apolipoprotein B and risk of ischemic heart disease. Results for risk of ischemic heart disease were verified in an independent case-control study comprising 944 cases and 7664 controls.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Subjects

General population sample The Copenhagen City Heart Study is a prospective cardiovascular study of the Danish general population initiated in 1976–1978 with follow-up examinations in 1981–1983, 1991–1994, and 2001–2003 (13, 14). Individuals were selected based on the national Central Population Register code to reflect the adult Danish population aged 20–80+ yr. Blood samples for DNA extraction were available on 9259 participants; of these 9185 were genotyped for all ten SNPs in APOB (T71I, Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, T2488Tc>t, P2712L, R3611Q, E4154K, and N4311S).

Information on diagnosis of ischemic heart disease (World Health Organization; International Classification of Diseases, 8th edition: codes 410–414; 10th edition: I20-I25) was collected and verified until the beginning of 2004 by reviewing all hospital admissions and diagnoses entered in the national Danish Patient Registry and all causes of death entered in the national Danish Causes of Death Registry. Ischemic heart disease was myocardial infarction (codes 410 and I21) or characteristic symptoms of angina pectoris (codes 411 and I20) (15). A diagnosis of myocardial infarction required the presence of at least two of the following criteria: characteristic chest pain, elevated cardiac enzymes, and electrocardiographic changes indicative of myocardial infarction.

Patients with ischemic heart disease A second cohort comprised 944 patients from the greater Copenhagen area referred for coronary angiography to Copenhagen University Hospital during the period 1991 through 1994. These patients had documented ischemic heart disease based on characteristic symptoms of stable angina pectoris (15), plus at least one of the following: severe stenosis on coronary angiography, a previous myocardial infarction, or a positive exercise electrocardiography test. The diagnosis of myocardial infarction was established with the same criteria as in the general population sample.

Study designs

Studies were approved by institutional review boards and Danish ethical committees [no. (KF)V.100.2039/91, Copenhagen and Frederiksberg committee, and no. KA93125, Copenhagen County committee] and conducted according to the Declaration of Helsinki. Informed consent was obtained from participants. More than 99% were white and of Danish descent.

Prospective study of risk of ischemic heart disease We included 9185 participants from The Copenhagen City Heart Study. All end points were recorded in the follow-up period 1976–2004. The median follow-up time was 25 yr (186,985 person-years). Individuals diagnosed with ischemic heart disease before entry were excluded (n = 61). We observed the following incident events: ischemic heart disease 1460, and myocardial infarction 729 (Table 1).

Laboratory analyses

SNP genotyping Genotyping was by TaqMan chemistry using an ABI Prism 7900HT sequence detection system (Applied Biosystems Inc., Foster City, CA) for T71I (rs1367117), Ivs4 + 171c>a (rs531819), A591V (rs679899), Ivs18 + 379a>c (rs10199768), and Ivs18 + 1708 g>t (rs3791980) and by PCR followed by digestion with XbaI (T2488Tc>t; rs693), BfaI (P2712L; rs676210), MspI (R3611Q; rs1801701), EcoRI (E4154K; rs1042031), or Eco57I (N4311S; rs1042034), respectively. Primers, TaqMan probes, and PCR conditions are available from the authors.

Biochemical analyses Colorimetric and turbidimetric assays were used to measure plasma levels of total cholesterol, apolipoprotein B, HDL cholesterol, and triglycerides. LDL cholesterol was calculated using the Friedewald equation (16), and non-HDL cholesterol was total cholesterol-HDL cholesterol.

Other covariates

The risk factors, diabetes mellitus, smoking, and hypertension were dichotomized and defined as ever-diabetics (self-reported disease, use of antidiabetic medication and/or a nonfasting plasma glucose > 11.0 mmol/liter), ever-smokers (ex-smoker or current smoker), ever-hypertensives (systolic blood pressure 140 mm Hg or diastolic blood pressure 90 mm Hg and/or use of antihypertensive medication). Body mass index was weight (kilograms) divided by height squared (square meters).

Statistical analysis

Data were analyzed using Stata/SE 9.2 (Stata Corp., College Station, TX). Two-sided probability values less than 0.05 were considered significant. Pairwise linkage disequilibrium was estimated using Haploview (http://www.broad.mit.edu/mpg/haploview/download/php). Mann-Whitney U test and Pearson’s ² test were used in two-group comparisons. The effect of SNP genotype on levels of cholesterol, LDL cholesterol, apolipoprotein B, and non-HDL cholesterol was determined by ANOVA and Student’s t test.

In the prospective study, with the use of left truncation (delayed entry), Cox proportional hazards regression models with age as time scale estimated hazard ratios. Multifactorial adjustment was for age, gender, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, body mass index, hypertension, diabetes, smoking, and menopausal status and use of hormonal replacement therapy for women. Bivariate tests of interaction between the covariates mentioned above and SNP genotypes on lipid, lipoprotein, and apolipoprotein levels and risk of ischemic heart disease and myocardial infarction were all nonsignificant. In the case-control study, logistic regression analysis was used to estimate odds ratios.

Estimated haplotypes containing the seven SNPs that according to HapMap tag the genetic variation in the coding and intronic regions of APOB (T71I, Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, T2488Tc>t, and E4154K) were inferred using the freely available WHAP software (17), as were levels of total cholesterol, LDL cholesterol, and apolipoprotein B and risk of ischemic heart disease and myocardial infarctions as a function of haplotypes.

Evolutionary conservation of nonsynonymous sequence variations in APOB

To compare evolutionary conservation with functional effects of the six nonsynonymous SNPs, we aligned the human APOB amino acid sequence with the orthologous sequences from other mammals, birds, fish, and sea urchin. For comparison, we included three APOB mutations (R3480P, R3500Q, R3531C) with known functional effects on LDL metabolism (2, 4). Next we examined the ability of three computer-based algorithms, PolyPhen (18), SIFT (19), and PANTHER (20), to predict the functional effects of the nonsynonymous SNPs and mutations in APOB. All three programs use sequence similarity to predict whether an amino acid substitution affects protein function, and PolyPhen in addition uses structural information.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Location of the 10 SNPs relative to the amino acid sequence and structural and functional domains of apolipoprotein B are shown in Fig. 1. Minor allele frequencies were T71I: 0.33, Ivs4 + 171c>a: 0.14, A591V: 0.47, Ivs18 + 379a>c: 0.30, Ivs18 + 1708 g>t: 0.45, T2488Tc>t: 0.48, P2712L: 0.21, R3611Q: 0.09, E4154K: 0.17, and N4311S: 0.21 (Fig. 2). All genotype distributions were in Hardy-Weinberg equilibrium.

View larger version (30K): [in this window] [in a new window]   FIG. 1. Location of the 10 SNPs relative to the amino acid sequence and the structural and functional domains of apolipoprotein B. T71V (rs1367117) and A591V(rs679899) are located in domains crucial for lipidation of the nascent apolipoprotein B (7 8 ); P2712(rs676210) is in a domain involved in structural changes of apolipoprotein B during the conversion of VLDL to LDL (9 ); and R3611Q (rs1801701), E4154K (rs1042031), and N4311S (rs1042034) are in domains known to or suspected of regulating binding to the LDL receptor (11 ). The seven SNPs predicted by HapMap (http://www.hapmap.org/index.html.en) to tag for the genetic variation in the entire APOB gene (coding regions and introns) are marked in red. MTP, Microsomal triglyceride transfer protein.

View larger version (30K): [in this window] [in a new window]   FIG. 2. Pairwise linkage disequilibrium between the 10 SNPs examined in the present study. The seven SNPs predicted by HapMap (http://www.hapmap.org/index.html.en) to tag for the genetic variation in the entire APOB gene (coding regions and introns) are marked in red. Disequilibrium statistics reported as exact values of D', ranging from –1 to +1, below the diagonal, and of r2 above the diagonal. All D' values were positive, indicating that the rare alleles at each locus segregate together. The color code also indicates the degree of linkage disequilibrium between SNPs. MAF, Minor allele frequency.

Linkage disequilibrium as r² and D' is shown for all 10 SNPs in Fig. 2. Generally, a high degree of linkage disequilibrium was present throughout the gene, especially between the five most C-terminal SNPs, indicating that these SNPs are on the same haplotypes. However, only the minor alleles of P2712L and N4311S were also highly correlated (r² = 1.0, all other r²s < 0.70) and could therefore tag or serve as proxy for the other SNP.

Nevertheless, according to HapMap, T71I, Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, T2488Tc>t, and E4154K are seven tag SNPs covering the entire APOB gene of approximately 43 kb (http://www.hapmap.org/index.html.en): T71I and Ivs4 + 171c>a form a haploblock covering the N-terminal part of the gene (12,986 nucleotides) and Ivs18 + 1708 g>t, T2488Tc>t, E4154K another block covering the most C-terminal end of the gene (18,719 nucleotides), whereas A591V and Ivs18 + 379a>c cover two haploblocks of, respectively, 5,585 and 1,329 nucleotides in between. It follows that Ivs18 + 1708 g>t, T2488Tc>t, and E4154K according to HapMap should tag P2712L, R3611Q, and N4311S because they are in the same haploblock. In this study, although these six SNPs are often on the same haplotypes (all D'>0.90), none are highly correlated, with the exception of P2712L with N4311S (Fig. 2; r² = 1.0 for P2712L with N4311S; r² = 0.30 for T2488Tc>t with P2712L/N4311S, all other r²s < 0.11). This indicates that Ivs18 + 1708 g>t, T2488Tc>t, and E4154K cannot tag or serve as a proxy for P2712L, R3611Q, or N4311S.

Lipids, lipoproteins, and apolipoprotein B levels

Overall, all 10 SNPs were associated with either increases (T71I, Ivs18 + 1708 g>t, T2488Tc>t, R3611Q) or decreases (Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, P2712L, E4154K, N4311S) in total cholesterol, LDL cholesterol, apolipoprotein B, and non-HDL cholesterol (P = 0.03 to P < 0.001 by ANOVA) (Fig. 3). T71I, Ivs18 + 1708 g>t, T2488Tc>t, and R3611Q were associated with increases in LDL cholesterol of 3.8, 2.8, 2.8, and 2.7% (0.14, 0.10, 0.10, and 0.11 mmol/liter) in heterozygotes vs. noncarriers and T71I, Ivs18 + 1708 g>t, and T2488Tc>t also with an increase in LDL cholesterol of 8.2, 6.6, and 6.9% (0.30, 0.24, and 0.25 mmol/liter) in homozygotes vs. noncarriers. Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, P2712L, E4154K, and N4311S were associated with decreases in LDL cholesterol of 4.0, 3.4, 2.1, 3.6, 1.9, and 3.6% (0.15, 0.12, 0.08, 0.14, 0.07, and 0.14 mmol/liter) in heterozygotes vs. noncarriers, and Ivs4 + 171c>a, A591V, and E4154K were also associated with decreases in LDL cholesterol of 7.4, 4.7, and 4.9% (0.28, 0.18, and 0.18 mmol/liter) in homozygotes vs. noncarriers. In absolute values, the maximum increase in LDL cholesterol as a function of SNP genotype was 0.30 mmol/liter for T71I homozygotes vs. noncarriers, whereas the maximum decrease in LDL cholesterol was 0.28 mmol/liter for Ivs4 + 171c>a homozygotes vs. noncarriers. None of the 10 SNPs were associated with increases or decreases in plasma levels of triglycerides, VLDL cholesterol, HDL cholesterol, or apolipoprotein AI (data not shown).

View larger version (33K): [in this window] [in a new window]   FIG. 3. Plasma levels of total cholesterol, LDL cholesterol, apolipoprotein B, and non-HDL cholesterol as a function of SNP genotypes in the general population, The Copenhagen City Heart Study. Values are means ± SE. Number of individuals within each genotype is given below the bars. P values above bars by ANOVA. Post hoc tests by Student’s t test: *, P < 0.05; , P < 0.01; , P < 0.001. Bonferroni corrected significance level, P < 0.008. Dashed lines are population mean values.

Risk of ischemic heart disease and myocardial infarction

Characteristics of individuals in the general population by outcome are shown in Table 1. Despite the effects on plasma levels of total cholesterol, LDL cholesterol, and apolipoprotein B (Fig. 3 and supplemental Table 1), neither the 10 SNPs alone nor the estimated nine most common haplotypes containing the seven APOB tag SNPs from HapMap predicted risk of ischemic heart disease or myocardial infarction in the general population (Fig. 4 and supplemental Table 2). Furthermore, results on risk of ischemic heart disease were verified for all 10 SNPs in a case-control study including 944 cases with ischemic heart disease and 7664 controls (supplemental Table 3).

View larger version (16K): [in this window] [in a new window]   FIG. 4. Risk of ischemic heart disease and myocardial infarction by APOB T71I, Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, T2488Tc>t, P2712L, R3611Q, E4154K, and N4311S genotypes in the general population, The Copenhagen City Heart Study. CI, Confidence interval.

Evolutionary conservation of nonsynonymous sequence variations in APOB

Of the three APOB mutations (R3480P, R3500Q, R3531C) with known functional effects on LDL metabolism (2, 4), only two were highly conserved from humans to chicken (R3500Q, R3531C) and zebra fish (R3500Q) (Fig. 5). Of the six nonsynonymous SNPs in the present study, two (A591V, P2712L) were at amino acid residues conserved from humans to zebra fish and sea urchin, and one (T71I) was conserved in mammals. Two substituted amino acids conserved in primates and some mammals (E4154K, N4311S), whereas the last SNP (R3611Q) changed an amino acid conserved in primates only.

View larger version (35K): [in this window] [in a new window]   FIG. 5. Evolutionary sequence conservation and predicted functional effects of common nonsynonymous SNPs and rare mutations (*) in APOB. Top, Cladrogram depicting the relationship between the various apolipoprotein B protein sequences aligned. Bottom, Variants associated with decreased LDL cholesterol levels in the general population (green), variants without effect on LDL cholesterol in the general population (yellow), and variants associated with increased LDL cholesterol levels in the general population (red) (2 4 12 ). Shaded boxes indicate evolutionary sequence conservation between aligned sequences. The rare mutations R3480P and R3500Q are associated with, respectively, a substantial reduction of 29% and a substantial increase of 80% in plasma levels of LDL cholesterol in the general population. The R3531C mutation is not associated with effects on plasma LDL cholesterol levels in the general population but with a slight reduction in the fractional catabolic rate of LDL cholesterol of 12% (2 4 12 ). The sequences are shown for: Homo sapiens (human), Pan troglodytes (chimpanzee), Macaca mulatta (rhesus monkey), Oryctolagus cuniculus (rabbit), Bos taurus (cow), Canis familiaris (dog), Echinops telfairi (hedgehog), Loxodonta Africana (African elephant), Mus musculus (mouse), Rattus norvegicus (rat), Dasypus novemcinctus (nine banded armadillo), Gallus gallus (chicken), Danio rerio (zebra fish), and Strongylocentrotus purpur (sea urchin). The predicted effect of each amino acid variant on protein function is shown to the right. SIFT version 1(19): –, tolerated; + deleterious (low confidence prediction); 2+, deleterious. PANTHER version 6(20): –, unlikely functional effect; +, possible deleterious functional effect; 2+, high probability of deleterious functional effect. PolyPhen (18 ): –, benign; +, possibly damaging; 2+, probably damaging. NA, Not modeled by the algorithm.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The principal finding of this study was that six nonsynonymous SNPs in important functional domains of apolipoprotein B, a synonymous SNP, and three noncoding SNPs contribute to plasma levels of LDL cholesterol and apolipoprotein B in the general population. Four of the six nonsynonymous SNPs were associated with lower plasma levels of LDL cholesterol. These sequence variants most likely lower LDL cholesterol levels by either interfering with lipidation of nascent apolipoprotein B (A591V) by reducing the production of LDL from VLDL as we have previously reported for R3480P (4) or accelerating LDL clearance by the LDL receptor (P2712L/N4311S, E4154K). Two SNPs (T71I, R3611K) were associated with increases in LDL cholesterol and are likely to do so by mechanisms that are the opposite of those discussed above. Two SNPs in introns were associated with lower plasma levels of LDL cholesterol (Ivs4 + 171c>a and Ivs18 + 379a>c) and one intron SNP and a synonymous SNP (Ivs18 + 1708 g>t and T2488Tc>t) with an increase in LDL cholesterol. These SNPs are not predicted to be functional (in potential regulatory regions or splice site variants), although little is in fact known about the intronic regions of APOB. Alternatively, these SNPs could be in linkage disequilibrium with other functional SNPs. Using HapMap, we identified six SNPs in strong linkage disequilibrium and highly correlated with five (Ivs4 + 171c>a, A591V, Ivs18 + 379a>c, Ivs18 + 1708 g>t, and E4154K) of the seven tag SNPs in APOB. However, all six were SNPs in introns, and none were predicted to be functional.

If we include three previously described mutations in apolipoprotein B (R3480P, R3500Q, R3531C) (2, 3, 4), the spectrum of apolipoprotein B alleles associated with variation in LDL cholesterol spans a wide range of allele frequencies (from 0.0004 for R3480P to 0.48 for T2488Tc>t) and a magnitude of phenotypic effects (from 29% LDL cholesterol reduction for R3480P to 80% increase for R3500Q). Taken together, our results together with those from previous studies of mutations in APOB suggest that multiple common and rare alleles in APOB contribute to plasma levels of LDL cholesterol in the general population, although the effects of the common alleles and haplotypes are modest (2, 3, 4, 12).

This is the first prospective study to report associations between these 10 SNPs in APOB and levels of total cholesterol, LDL cholesterol, apolipoprotein B, and non-HDL cholesterol as well as the ability of these SNPs to predict risk of ischemic heart disease and myocardial infarction with 25 yr follow-up in a large general population cohort. Several case-control studies have reported conflicting associations between APOB SNPs and lipid and lipoprotein levels, but some studies reported increased levels of cholesterol and/or apolipoprotein B for T71I and reduced levels of cholesterol and apolipoprotein B for P2712L/N4311S as in the present study (21, 22, 23). Only one study previously reported on R3611Q and only three studies on E4154K, but all failed to find an association with variation in lipid and lipoprotein levels (24). However, the power of previous studies to convincingly show an effect on lipid or lipoprotein levels has generally been very limited due to the size of the studies.

The effects of these SNPs on risk of ischemic heart disease have been even more contradictory, as exemplified by two recent metaanalyses on risk of ischemic heart disease conferred by E4154K: one of these reported an increased risk of ischemic heart disease and an overall odds ratio of 1.32 (1.14–1.54; n = 3870) (5), whereas the other reported no increase in risk and an overall odds ratio of 1.15 (0.78–1.70; n = 2014) (6). Both of these metaanalyses were considerably smaller than the present study alone. In this study, we had 80% power to exclude a hazard ratio at or above 1.10 for E4154K heterozygotes. E4154K heterozygosity (EK) and homozygosity (KK) was associated with, respectively, a 0.07 and 0.18 mmol/liter decrease in LDL cholesterol levels and did not predict risk of ischemic heart disease.

In The Copenhagen City Heart Study, a 0.5 mmol/liter increase in LDL cholesterol predicts a hazard ratio of 1.06 (95% confidence interval 1.03–1.09) for ischemic heart disease and a 0.5 mmol/liter decrease in LDL cholesterol predicts a hazard ratio of 0.94 (0.92–0.97). Thus, the effect on risk of ischemic heart disease predicted by the largest observed effects on LDL cholesterol for the SNPs and haplotypes studied (0.30 mmol/liter increase for T71I) would correspond to a hazard ratio close to 1, in agreement with the lack of effect of both SNPs and haplotpes on risk of ischemic heart disease found in this study.

The extent of evolutionary sequence conservation did not reliably predict the impact of either SNPs or mutations on protein function. Only one computer-based prediction algorithm predicted one of the six SNPs associated with plasma LDL cholesterol level to have a deleterious effect with high probability. Moreover, one of the three functional mutations (R3500Q) was predicted to be benign by one algorithm, and this was the mutation with by far the largest functional effect and the largest effect on phenotype. In contrast, the mutation with the smallest functional effect (R3531C) was predicted by the two algorithms available to have a deleterious effect with high probability. Thus, in silico prediction methods were poor predictors of functional variation in apolipoprotein B. This suggests that there are limitations to the usefulness of these methods, as demonstrated previously for genetic variation in PCSK9 (25). Taken together, this suggests that neither evolutionary sequence variation nor computer-based prediction of functional effects can reliably predict effects of nonsynonymous mutations or SNPs in APOB on plasma levels of lipids, lipoproteins, or apolipoprotein B. For the nonsynonymous SNPs, this assumes that no unknown nonsynonymous or regulatory SNPs in linkage disequilibrium with these six SNPs can account for the lipid phenotypes. We cannot exclude that such SNPs might exist, although at present none have been described in HapMap or in other SNP databases.

Our data support a role for common variants in APOB in determining plasma levels of LDL cholesterol. Not surprisingly, the effects of these common variants were much smaller than those of the previously described rare mutations in APOB. The associations with plasma LDL cholesterol levels for all six nonsynonymous SNPs would not have been revealed using the current tag SNPs available in HapMap because the linkage analysis showed that the correlations (r²s) between some of these tag SNPs and the nonsynonymous SNPs in the proposed haploblock were modest. This suggests that much denser SNP analysis of APOB and other genes is required for HapMap to be useful in genetic association studies.

In conclusion, the present results together with those from previous studies of mutations in APOB suggest that multiple common and rare alleles in APOB contribute significantly to plasma levels of LDL cholesterol in the general population, although the effects of the common alleles and haplotypes are modest.

	Acknowledgments

 
The authors thank Mette Refstrup and Hanne Damm for expert technical assistance. We are indebted to the staff and participants of The Copenhagen City Heart Study for their important contributions.

	Footnotes

 
This work was supported by grants from The Danish Heart Foundation, The Danish Medical Research Council, the Research Fund at Rigshospitalet, Copenhagen University Hospital, Chief Physician Johan Boserup and Lise Boserup’s Fund, Ingeborg and Leo Dannin’s Grant, and Henry Hansen and Wife’s Grant.

Disclosure Statement: The authors have nothing to disclose.

First Published Online December 26, 2007

Abbreviations: APOB, Apolipoprotein B gene; LDL, low-density lipoprotein; SNP, single-nucleotide polymorphism; VLDL, very low-density lipoprotein.

Received June 19, 2007.

Accepted December 17, 2007.

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