Frequencies of Four ATP-Binding Cassette Transporter G8 Polymorphisms in Patients with Ischemic Vascular Diseases

Abstract

ATP-binding cassette transporter G8 (ABCG8) was found to participate in plant sterol and cholesterol (CHOL) transport; however, the potential associations of ABCG8 genetic variants and ischemic vascular diseases are largely unknown. Determinations of allele frequencies of four common ABCG8 polymorphisms (D19H, Y54C, T400K, and A632V) were carried out in 241 unrelated patients with ischemic stroke, 148 patients with coronary heart disease, and 191 blood donors (controls). Allele frequencies of the investigated polymorphisms in patient groups showed no significant differences compared with controls. There was a tendency toward reduced 54YY-genotype frequency among male patients with stroke. On stratification by age at disease onset, male patients with stroke under the age of 50 (n = 62) showed significantly reduced 54YY-frequency compared with male controls (n = 92; 24.2% vs. 41.3%; odds ratio: 0.45 [95% confidence intervals: 0.22-0.93]; p = 0.038). No such associations were found among women. In healthy controls, CHOL levels of individuals with the 54YY genotype (n = 71; median: 4.51 mM, 25th-75th percentiles: 4.19-5.43) were significantly reduced compared with 54YC and 54CC individuals combined (n = 120; median: 4.95 mM, 25th-75th percentiles: 4.42-5.88, p = 0.009). Further, we identified a new ABCG8-variant, T401S, in a control subject. In conclusion, ABCG8 54YY-genotype may be a potential protecting factor against ischemic stroke in young men and may influence plasma CHOL levels.

Introduction

ATP-binding cassette transporter G5 and G8 (ABCG5 and G8) are half-transporters, which together form a functional heterodimer (Graf et al., 2002, 2003). They are localized at the apical membrane of the enterocytes and at the canalicular membrane in the liver and mediate the transport of plant sterols and cholesterol (CHOL) into the intestinal lumen and bile (Klett et al., 2004). Mutations in either ABCG5 or G8 lead to elevated plasma concentration of plant sterols and cause sitosterolemia, a rare autosomal recessive disorder described by Bhattacharyya and Connor (1974), which can lead to premature atherosclerosis (Salen et al., 1985). Beside these disease-associated mutations, several single nucleotide polymorphisms (SNPs) have also been identified (Berge et al., 2002; Iida et al., 2002). A number of these SNPs have been selected for human studies to reveal any possible phenotypic associations. In several Caucasian populations, five common SNPs (Q604E in exon 13 of ABCG5; D19H, Y54C, T400K, and A632V in exons 1, 2, 8, and 13 in ABCG8, respectively) have been under intensive investigation and have been reported to influence the metabolism of plant sterols or CHOL (Weggemans et al., 2002; Hubácek et al., 2004; Kajinami et al., 2004; Grünhage et al., 2007; for review see, Rudkowska and Jones, 2008).

Several studies mention the increased risk of coronary heart disease (CHD) as a potential consequence of elevated plasma sterol levels believed to be affected by ABCG5/G8 SNPs, and one published study performed classical association in large patient cohorts with common ischemic vascular diseases (Koeijvoets et al., 2009).

The aim of our study was to investigate the frequencies and potential association of the four most common SNPs of ABCG8 (D19H, Y54C, T400K, and A632V) in patients with stroke and CHD in comparison to healthy blood donors as controls.

Materials and Methods

Subjects

Our study involved two cohorts of patients and one cohort of controls. In each cohort, subjects were recruited from the central part of Hungary and all subjects belonged to the Caucasian race.

In the first patient cohort, 241 unrelated patients (164 men and 77 women) with ischemic stroke were investigated. The mean age at disease onset was 53.4 ± 14.5 years (range: 18-86 years). Ischemic stroke was characterized by computed tomography, and the etiology was examined by carotis duplex scan (CDS). The severity of stroke varied from transient ischemic attack (TIA, 77 patients) and persistent reversible ischemic neurological deficit (121 patients) to irreversible neurological defect (43 patients). Concomitant risk factors (such as hypertension, diabetes, and smoking) were recorded. The prevalence values of risk factors were the following: hypertension, 49.0% (118/241); diabetes, 11.6% (28/241); and smoking, 53.5% (121/226).

In the second patient cohort, 148 patients (107 men and 41 women) with documented CHD were investigated. The mean age at onset was 61.4 ± 9.3 years (range: 32-86 years). Patients with CHD suffered from angina pectoris (n = 99) or acute myocardial infarction (n = 51). Coronary angiography was performed in all CHD cases.

The control group consisted of 191 repeated voluntary blood donors (2-5 previous blood donations, 92 men, and 99 women) with a mean age of 35.3 ± 11.8 years (range: 19-63 years). Blood donors were interviewed by a physician employee of the blood bank on each occasion to exclude major diseases in their previous history such as malignant disorders, infections, CHD, or stroke.

In a previous study, the same subjects were investigated for ABCA1 SNPs R219K and V771M, which were found to be protective factors against CHD and stroke (Andrikovics et al., 2006). Our study was approved by the Institutional Ethics Committee.

DNA isolation and detection of ABCG8 D19H, Y54C, T400K, and A632V alleles with LightCycler hybridization probe technique

DNA isolation was performed from anticoagulated peripheral blood with the standard “salting-out” procedure. The following ABCG8 sequence variants were studied: D19H (rs11887534, exon 1, c.52G>C); Y54C (rs4148211, exon 2, c.161A>G), T400K (rs4148217, exon 8, c.1199C>A), and A632V (rs6544718, exon 13, c.1895C>T). Genotype analyses of the four genetic variants were performed using the LightCycler technology (Roche Diagnostics).

The amplification primers, the fluorescence labeled detection, and anchor probes were designed by the LightCycler Probe Design software (Roche Diagnostics), and all oligonucleotides were synthesized by Integrated DNA Technologies (Coralville). The sequences and conditions of optimized reactions are available on request.

Genotyping was repeatedly carried out in cases of all variant genotypes, and results were evaluated by two independent investigators.

Sequencing

Polymerase chain reaction (PCR) amplification of 50 ng whole genomic DNA was carried out in 30 cycles (94°C for 45 s; 60°C for 45 s; 72°C for 45 s) with 10 pmol of each primer and 2 × PCR Master Mix (Promega). PCR products were purified with the Montage PCR Kit (Millipore). The sequencing reaction of the PCR products was performed using the BigDye Terminator v3.0 Cycle Sequencing Kit (Applied Biosystems) according to the manufacturer's instructions. For the second purification, Multiscreen-HV plates (Millipore) filled with Sephadex G-50 Superfine beads (Amersham Biosciences) were used. Automated capillary electrophoresis was performed on an ABI PRISM 310 Genetic Analyzer (Applied Biosystems).

Determinations of lipid parameters

Serum total CHOL, high density lipoprotein (HDL), and triglyceride (TG) levels were measured by standard colorimetric techniques. Low density lipoprotein (LDL) was calculated using the Friedewald formula if total CHOL, TG, and HDL CHOL values were all available. Serum samples of blood donors were separated by centrifugation and stored at −70°C before the determination of lipid parameters. Serum TG levels and LDL CHOL were not determined or calculated in the blood donor group, as fasting serum samples were not available.

Statistical analyses

Allele frequencies (AFs, %) are presented with 95% confidence intervals (95% CI). Fisher's exact or χ² tests (univariate analyses) were used to compare the frequencies of ABCG8 genotypes between the blood donor and patient groups as preliminary analyses. Crude odds ratio and 95% CI were estimated for each ABCG8 SNP. Lipid parameters are presented as medians (25th-75th percentiles). The Mann-Whitney or Kruskal-Wallis tests were used to compare lipid values observed in groups of individuals with different genotypes (all lipid variables were abnormally distributed as tested by the Kolmogorov-Smirnov test). Control, stroke, and CHD groups were separately analyzed as lipid values were measured in different centers. Analyses were conducted with the SPSS (version 13.0) software package. Testing for the presence of Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium studies were performed by the SNPstats web tool (http://bioinfo.iconcologia.net/SNPstats; Solé et al., 2006). According to the general consensus, p < 0.05 was considered significant.

Results

Genotyping of four common allelic variants of ABCG8

Using genomic DNA samples, simultaneous genotyping was carried out in the stroke- and CHD-affected patient groups as well as in the healthy control blood donor group by PCR and fluorescent allelic discrimination techniques. The results of genotyping are shown in Table 1. Numbers of cases with different genotypes, AF and CI values are given for the three investigated groups (stroke, CHD, and control) separately and as a combined group for each of the four SNPs. AFs of all four investigated ABCG8 SNPs in all investigated groups were in the range of previously published data on Caucasian populations (Gylling et al., 2004; Hubácek et al., 2004; Kajinami et al., 2004; Plat et al., 2005). There were no significant differences in AF values between the patient groups and controls.

Table 1.

Genotyping Results for ATP-Binding Cassette Transporter G8 Single Nucleotide Polymorphisms (D19H, Y54C, T400K, and A632V) in the Control and Patient Groups

Subjects	Controls n = 191	Stroke patients n = 241	CHD-patients n = 148	Total n = 580
D19H
DD	173 (90.6)	220 (91.3)	132 (89.2)	525 (90.5)
DH	18 (9.4)	20 (8.3)	15 (10.1)	53 (9.1)
HH	0	1 (0.4)	1 (0.7)	2 (0.3)
AF (%) ± 95% CI	4.7 ± 2.2	4.6 ± 1.9	5.7 ± 2.7	4.9 ± 1.3
Y54C
YY	71 (37.2)	80 (33.2)	58 (39.2)	209 (36.0)
YC	84 (44.0)	123 (51.0)	62 (41.9)	269 (46.4)
CC	36 (18.8)	38 (15.8)	28 (18.9)	102 (17.6)
AF (%) ± 95% CI	40.8 ± 5.0	41.3 ± 4.5	39.9 ± 5.7	40.8 ± 2.9
T400K
TT	124 (64.9)	164 (68.0)	94 (63.5)	382 (65.9)
TK	62 (32.5)	67 (27.8)	51 (34.5)	180 (31.0)
KK	5 (2.6)	10 (4.1)	3 (2.0)	18 (3.1)
AF (%) ± 95% CI	18.8 ± 4.0	18.0 ± 3.5	19.3 ± 4.6	18.6 ± 2.3
A632V
AA	119 (62.3)	156 (64.7)	94 (63.5)	369 (63.6)
AV	63 (33.0)	70 (29.0)	52 (35.1)	185 (31.9)
VV	9 (4.7)	15 (6.2)	2 (1.4)	26 (4.5)
AF (%) ± 95% CI	21.2 ± 4.2	20.7 ± 3.7	18.9 ± 4.6	20.4 ± 2.4

Values shown are number of cases and relative frequencies (%) in parentheses.

Allele frequencies (AF) are shown in percentages, with calculated ± 95% confidence intervals (CI).

CHD, coronary heart disease.

Analyses of HWE and linkage disequilibrium between ABCG8 genetic variants

Genotype distributions were examined for the fulfillment of the HWE in all groups for the four SNPs and no deviation was observed. Linkage disequilibrium was tested by SNPstats. Genetic association was revealed between the respective neighboring loci of the ABCG8 gene and between D19H and A632V (Table 2). Estimated haplotype frequencies were calculated for the control and the 2 patient groups separately and for the combined group (n = 580). These frequency values were very similar in all three groups, so only data for the combined group are shown in Table 3.

Table 2.

Linkage Disequilibrium for Four Loci of ATP-Binding Cassette Transporter G8

	Y54C	T400K	A632V
D19H	<0.0001 (0.035)	0.0510 (0.003)	0.0122 (0.005)
Y54C		<0.0001 (0.157)	0.6064 (<0.001)
T400K			<0.0001 (0.028)

Linkage disequilibrium was tested for four ABCG8 loci (D19H, Y54C, T400K, and A632V) by the SNPstats web tool. Values represent exact p-values for pairs of loci (and r² values in parentheses). Significant linkage disequilibrium (p < 0.05) was observed between neighboring loci and between D19H and A632V. Calculations were performed using the controls and the two patient groups combined as a single cohort (n = 580).

ABCG8, ATP-binding cassette transporter G8.

Table 3.

Estimated Haplotype Frequencies for ATP-Binding Cassette Transporter G8 Single Nucleotide Polymorphisms

Haplotype number	D19H	Y54C	T400K	A632V	Frequency
1	D	C	T	A	0.318
2	D	Y	T	A	0.267
3	D	Y	K	A	0.165
4	D	Y	T	V	0.100
5	D	C	T	V	0.090
6	H	Y	T	A	0.036
7	D	Y	K	V	0.012
8	H	Y	K	A	0.010
9	H	Y	T	V	0.003

Estimated haplotype frequencies for ABCG8 were calculated by SNPstats web tool. Nine haplotypes were determined and they are presented in decreasing order based on their relative frequencies. Letters represent single-letter amino acid codes for the four investigated genetic variants D19H, Y54C, T400K, and A632V (the less frequent [minor] alleles are indicated with boldface characters). Estimated haplotype frequency values are shown for the control and patient groups combined as a single cohort (n = 580), as comparisons between separate groups (control, stroke, and CHD) did not reveal significant differences (data not shown).

Subgroup analyses

No significant differences were found in AF values after stratification for sex in the patient and control groups. However, stratification based on age of disease onset revealed interesting differences regarding the Y54C SNP. In the group of male patients with stroke, a tendency was observed, in which the frequencies of the 54YY genotype were lower in patients diagnosed in younger ages compared with male controls. As shown in Figure 1, among patients diagnosed under the age of 50 (n = 62), the frequency of the 54YY genotype was significantly reduced compared with the male control group (n = 92) with 24.2% versus 41.3%; odds ratio: 0.45 (95% CI: 0.22-0.93); p = 0.038. No significant differences were observed between intermediate age groups of patients with stroke and the control group. A similar tendency, for example, decreases of YY genotype frequency was not observed either among subgroups of female patients with stroke according to age at diagnosis or among patients with CHD (data not shown). Significant differences were found only when comparing the frequencies of 54YY genotype, whereas comparing AFs of the other three investigated SNPs in subsets of patients based on age of diagnosis did not reveal differences.

FIG. 1.

Comparison of frequencies of 54YY genotype in the subgroups of male controls and male patients with stroke according to age at disease onset. Frequencies (%) of the 54YY genotypes and 95% confidence intervals (bars) are presented. There was a tendency toward decreased frequency of YY genotype among male patients with stroke with younger ages at diagnoses. The frequency of the YY genotype among patients with stroke diagnosed at age under 50 (n = 62) compared with male controls (n = 92) was significantly different (p = 0.038) as marked with an asterisk.

In the case of patients with stroke, several further stratifications were made based on the presence or absence of some disease characteristics, such as the presence or absence of TIA and coexisting ischemic heart disease. In addition, patients with stroke were divided into three groups according to carotis duplex scan results (1: negative, 2: up to 85%, or 3:>85% reduction of carotis artery-diameter) as well as three arbitrary defined risk groups based on the number of known risk factors (hypertension, diabetes mellitus, and smoking). None of the four ABCG8 variants showed altered AFs according to any of the subgroups just mentioned.

Serum lipid determinations

To test important genotype-phenotype associations, plasma lipid profile values were compared with genotypes. In the control group (n = 191), CHOL and HDL, whereas in subsets of patient groups (stroke: n = 111; CHD: n = 95), CHOL, LDL, HDL, and TG levels were compared with different genotypes of ABCG8 SNPs. The comparison of plasma lipid parameters and genotypic data using the Kruskal-Wallis test revealed significant differences (p = 0.018) between Y54C genotypes and blood CHOL levels in the control group. Analyzing the three genotypes separately, cases with the 54YY genotype had the lowest CHOL levels, whereas those with the 54CC genotype had the highest CHOL levels, with the heterozygous individuals having intermediate values (Table 4). On comparison of the 54YY homozygous cases (n = 71; median: 4.51 mM, 25th-75th percentiles: 4.19-5.43) with the combined group of the other two genotypes (YC and CC; n = 120; median 4.95 [25th-75th percentiles 4.42-5.88] mM) by using Mann-Whitney test, a significant difference was observed (p = 0.009). Multinomial logistic regression analyses revealed significant differences in CHOL levels between patients carrying the 54YY genotype compared with 54YC or 54CC genotype after adjustment by age and sex (p = 0.043 and p = 0.006, respectively), indicating the importance of YY homozygosity for the effect. Control individuals with the second and third most frequent haplotypes (both with 54Y allele) had significantly lower CHOL levels compared with the most frequent haplotype (containing 54C). After adjustment with age and sex, reduced CHOL levels were also detected, but this association was not significant. Surprisingly, similar differences were not found in either patient group (data not shown). Moreover, no differences were found on comparison of LDL and HDL cholesterol levels between the above groups and subgroups (not shown).

Table 4.

Cholesterol Levels of the Control Blood Donors According to Y54C Genotypes

		Cholesterol level (mM)
Y54C genotype	Number of cases	25th percentile	Median	75th percentile
YY	71	4.19	4.51	5.43
YC	84	4.32	4.95	5.82
CC	36	4.53	4.98	6.31

The comparison of plasma cholesterol levels between subgroups of controls based on Y54C genotypes using the Kruskal-Wallis test revealed significant differences (p = 0.018). Blood donors with the YY54 genotype had the lowest cholesterol levels, whereas those with the 54CC genotype had the highest cholesterol levels, with the heterozygous individuals having intermediate values.

New ABCG8 variant

The allele discrimination technique based on the melting curve analysis of fluorescent labeled probes and the amplified DNA allows the detection of additional genetic variants affecting the flanking regions of the SNP under study, if they are located within the recognition sequence of the sensor probe. During our serial analyses for the T400K variant, we repeatedly observed an unusual melting curve for one particular DNA sample. Sequencing revealed a new, nonsynonymous genetic variant: T401S (c.1201A>T), in exon 8 of ABCG8. This case was excluded from our study population.

Discussion

Several studies investigated the associations between ABCG8 SNPs and different parameters of lipid metabolism or clinical disorders. Studies investigating populations different in ethnic background, sex, or health status revealed association with different SNPs (see review of Rudkowska and Jones, 2008), suggesting that there is no single SNP or haplotype which could contribute to alterations of the transporter activity in itself. Besides these SNP-association studies, two recent genome-wide association studies supported the importance of ABCG5 and ABCG8 loci in lipid metabolism, revealing associations of lipid levels and CHD risk with ABCG5 (Aulchenko et al., 2009) and contribution of ABCG8 to polygenic dyslipidemia (Kathiresan et al., 2009).

We aimed at investigating the AFs of the four most investigated base substitutions of ABCG8 (D19H, Y54C, T400K, and A632V) in groups of subjects with stroke or CHD in comparison to healthy controls. There were no significant differences between patient (stroke and CHD) and control groups, according to AF values. In subsequent subgroup analyses, we failed to reveal any association between AFs and subgroups based on sex (in stroke, CHD, or control group), existence of TIA, coexisting ischemic heart disease, computed tomography positivity, CDS results, or arbitrary defined risk groups (in the stroke group). The above results suggest that disease severity is not affected by the investigated ABCG8 SNPs.

However, a tendency of decreasing frequencies of 54YY genotype was noted among male patients in whom stroke was diagnosed in younger ages (see Fig. 1). Comparing the male patients in whom stroke was diagnosed under the age of 50 with the male control group, the frequency of the 54YY genotype was significantly reduced (see Fig. 1), thus suggesting a protective effect against stroke. Comparing AFs instead of YY genotype frequency did not show significant differences, suggesting that the YY genotype in homozygous form is necessary for protection against stroke in young men.

In the control group (women and men together), CHOL level of individuals showed increases in the order of genotype 54YY, 54YC, and 54CC (p = 0.018). However, we did not find such an association among either patient group, which can be explained by the potential effects of other factors or medications influencing serum CHOL levels.

Koeijvoets et al. (2009), performed similar SNP-disease association studies on a large cohort of subjects with familial hypercholesterolemia (n = 2012) containing 648 subjects with cardiovascular events (553 subjects with CHD, 58 subjects with peripheral artery disease, and 37 subjects with cerebral artery disease). They investigated two of the four SNPs investigated in our study, namely D19H and T400K. There was no association of SNPs within the total cardiovascular disease group (n = 648). The D19H SNP was associated with increased risk of CHD, but only after adjustment for year of birth, sex, smoking, diabetes, HDL-C, and TG levels in multiple Cox regression analyses. Our study could not confirm this association, which can be due to a lower case number in our CHD group (n = 148 vs. 648). However, Y54C was not investigated in the above publication. The first study, which revealed association between Y54C and lipid metabolism, investigated alteration in plasma lipid levels after an 8-year period; whereas dietary habits changed (Hubacek et al., 2001). Female subjects with 54YY genotype had a marked decrease in CHOL and LDL levels, whereas heterozygotes had intermediate decrease in such lipid levels. These subjects were considered to be “high responder” to dietary changes (Hubacek et al., 2001). Another publication revealed association between Y54C and changes in CHOL metabolism after weight loss in female cases (men were not investigated) (Santosa et al., 2007).

A more recent study revealed associations between ABCG8 SNPs and lipid levels, in which lower HDL concentrations were observed in subjects with 54CC or 54YC compared with subjects with the 54YY genotype (Junyent et al., 2009). A higher level of HDL has a protecting effect against ischemic stroke (Emerging Risk Factors Collaboration, et al. 2009). In our study, we were unable to confirm the direct association between 54YY genotype and elevated HDL level (potentially due to the low case number), but we observed a protective effect of the 54YY genotype against stroke for which one potential mechanism may be the elevation of the HDL level in 54YY individuals. Our results are in agreement with a recently revealed Y54C-lipid association; that is, 54CC homozygous cases showed elevated CHOL and LDL levels in healthy individuals (Abellán et al., 2010).

Since the 54Y allele seemed to be protective against stroke in young men and was associated with lower CHOL levels in controls, we suggest that the ABCG8 transporter containing the 54Y variant might have a higher transport activity than the protein with the C allele.

Interestingly, the protecting effect of 54YY allele could be detected only in men, but not in female cases, which can be due to the lower case number in our female stroke group compared with the male stroke group (n = 77 vs. 164). However, observation of a sex-specific effect of ABCG8 SNPs is not a unique phenomenon. In a Czech population study, association between Y54C genotypes and lipid levels were described in female cases only, whereas T400K genotypes were associated with lipid levels only in men (Hubacek et al., 2001). In another study, carriers of the K variant at the T400K locus had elevated risk for gallstone disease, lower TG, and biliary phospholipid levels only in men but not in women (Wang et al., 2007).

Linkage analysis revealed genetic linkage between the investigated loci of ABCG8, which is in concordance with published data, as different studies revealed linkage between different loci of ABCG5 and G8 (Berge et al., 2002; Gylling et al., 2004; Kajinami et al., 2004; Plat et al., 2005). On calculating estimated haplotype frequencies, we observed very similar results to those published elsewhere (Berge et al., 2002; Gylling et al., 2004), that is, the three most frequent haplotypes together accounted for 75% of all haplotypes. We could not identify any haplotype that would be over- or underrepresented in any of the patient groups compared with the control group.

Finally, we identified a novel G8 variant, T401S. This variant seemed to be a unique variant, as only 1 out of 581 samples carried this genotype. Putting together the results of melting curve analyses and sequencing, we conclude that this subject is a compound heterozygote for the T400K and T401S variants. This healthy female blood donor had normal lipid parameters (CHOL, 4.23 mM; HDL, 1.1 mM).

In conclusion, our study provides data of the frequencies and distributions of ABCG8 variants in patients with ischemic vascular disease. ABCG8 54Y allele was associated with lower CHOL level in a healthy Hungarian population, whereas the same allele in homozygous form seemed to be a protecting factor against stroke in young men. Further studies are needed to confirm our findings in other populations.

Footnotes

Acknowledgments

We thank Horvath Csongorne and Pfundt Julia for technical assistance. H.A. and A.T. were supported by OTKA (K69102), the Ministry of Health (ETT 05-401/2009), KMOP 1.1.2-07/1-2008-0003, and “Vérsejt Alapítvány.”

Disclosure Statement

No competing financial interests exist.

References

Abellán

, Mansego

, Martínez-Hervás

et al. 2010. Association of selected ABC gene family single nucleotide polymorphisms with postprandial lipoproteins: results from the population-based Hortega study. Atherosclerosis, 211:203-209.

Andrikovics

, Pongrácz

, Kalina

et al. 2006. Decreased frequencies of ABCA1 polymorphisms R219K and V771M in Hungarian patients with cerebrovascular and cardiovascular diseases. Cerebrovasc Dis, 21:254-259.

Aulchenko

, Ripatti

, Lindqvist

et al. 2009. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet, 41:47-55.

Berge

, von Bergmann

, Lutjohann

et al. 2002. Heritability of plasma noncholesterol sterols and relationship to DNA sequence polymorphism in ABCG5 and ABCG8. J Lipid Res, 43:486-494.

Bhattacharyya

, Connor

. 1974. Beta-sitosterolemia and xanthomatosis. A newly described lipid storage disease in two sisters. J Clin Invest, 53:1033-1043.

Emerging Risk Factors Collaboration. Di Angelantonio

, Sarwar

et al. 2009. Major lipids, apolipoproteins, and risk of vascular disease. JAMA, 302:1993-2000.

Graf

, Li

, Gerard

et al. 2002. Coexpression of ATP-binding cassette proteins ABCG5 and ABCG8 permits their transport to the apical surface. J Clin Invest, 110:659-669.

Graf

, Yu

, Li

et al. 2003. ABCG5 and ABCG8 are obligate heterodimers for protein trafficking and biliary cholesterol excretion. J Biol Chem, 278:48275-48282.

Grünhage

, Acalovschi

, Tirziu

et al. 2007. Increased gallstone risk in humans conferred by common variant of hepatic ATP-binding cassette transporter for cholesterol. Hepatology, 46:793-801.

10.

Gylling

, Hallikainen

, Pihlajamäki

et al. 2004. Polymorphisms in the ABCG5 and ABCG8 genes associate with cholesterol absorption and insulin sensitivity. J Lipid Res, 45:1660-1665.

11.

Hubacek

, Berge

, Cohen

et al. 2001. Mutations in ATP-cassette binding proteins G5 (ABCG5) and G8 (ABCG8) causing sitosterolemia. Hum Mutat, 18:359-360.

12.

Hubácek

, Berge

, Stefková

et al. 2004. Polymorphisms in ABCG5 and ABCG8 transporters and plasma cholesterol levels. Physiol Res, 53:395-401.

13.

Iida

, Saito

, Sekine

et al. 2002. Catalog of 605 single-nucleotide polymorphisms (SNPs) among 13 genes encoding human ATP-binding cassette transporters: ABCA4, ABCA7, ABCA8, ABCD1, ABCD3, ABCD4, ABCE1, ABCF1, ABCG1, ABCG2, ABCG4, ABCG5, and ABCG8. J Hum Genet, 47:285-310.

14.

Junyent

, Tucker

, Smith

et al. 2009. The effects of ABCG5/G8 polymorphisms on plasma HDL cholesterol concentrations depend on smoking habit in the Boston Puerto Rican Health Study. J Lipid Res, 50:565-573.

15.

Kajinami

, Brousseau

, Nartsupha

et al. 2004. ATP binding cassette transporter G5 and G8 genotypes and plasma lipoprotein levels before and after treatment with atorvastatin. J Lipid Res, 45:653-656.

16.

Kathiresan

, Willer

, Peloso

et al. 2009. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet, 41:56-65.

17.

Klett

, Lee

, Adams

et al. 2004. Localization of ABCG5 and ABCG8 proteins in human liver, gall bladder and intestine. BMC Gastroenterol, 4:21.

18.

Koeijvoets

, van der Net

, Dallinga-Thie

et al. 2009. ABCG8 gene polymorphisms, plasma cholesterol concentrations, and risk of cardiovascular disease in familial hypercholesterolemia. Atherosclerosis, 204:453-458.

19.

Plat

, Bragt

, Mensink

. 2005. Common sequence variations in ABCG8 are related to plant sterol metabolism in healthy volunteers. J Lipid Res, 46:68-75.

20.

Rudkowska

, Jones

. 2008. Polymorphisms in ABCG5/G8 transporters linked to hypercholesterolemia and gallstone disease. Nutr Rev, 66:343-348.

21.

Salen

, Horak

, Rothkopf

et al. 1985. Lethal atherosclerosis associated with abnormal plasma and tissue sterol composition in sitosterolemia with xanthomatosis. J Lipid Res, 26:1126-1133.

22.

Santosa

, Demonty

, Lichtenstein

et al. 2007. Single nucleotide polymorphisms in ABCG5 and ABCG8 are associated with changes in cholesterol metabolism during weight loss. J Lipid Res, 48:2607-2613.

23.

Solé

, Guinó

, Valls

et al. 2006. SNPStats: a web tool for the analysis of association studies. Bioinformatics, 22:1928-1929.

24.

Wang

, Jiang

, Fei

et al. 2007. ATP binding cassette G8 T400K polymorphism may affect the risk of gallstone disease among Chinese males. Clin Chim Acta, 384:80-85.

25.

Weggemans

, Zock

, Tai

et al. 2002. ATP binding cassette G5 C1950G polymorphism may affect blood cholesterol concentrations in humans. Clin Genet, 62:226-229.