ABCA1 gene promoter DNA methylation is associated

research paper

Research paper

Epigenetics 7:5, 1-9; May 2012; © 2012 Landes Bioscience

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ABCA1 gene promoter DNA methylation is associated with HDL particle profile and coronary artery disease in familial hypercholesterolemia Simon-Pierre Guay,1,2 Diane Brisson,2 Johannie Munger,1,2 Benoit Lamarche,3 Daniel Gaudet2,4 and Luigi Bouchard1,2,* 3

1 Department of Biochemistry; Université de Sherbrooke; Sherbrooke, QC Canada; 2ECOGENE-21 and Lipid Clinic; Chicoutimi Hospital; Saguenay, QC Canada; Institute of Nutraceuticals and Functional Foods; Université Laval; Québec, QC Canada; 4Department of Medicine; Université de Montréal; Montréal; QC, Canada

Key words: HDL-cholesterol, ABCA1, DNA methylation, familial hypercholesterolemia, coronary artery disease Abbreviations: ABCA1, ATP-binding cassette A1; apo, apolipoproprotein; ARH, LDLR adaptor protein-1; BMI, body mass index; CAD, coronary artery disease; CVD, cardiovascular disease; GAPDH, glyceraldehydes-3-phosphate dehydrogenase; FH, familial hypercholesterolemia; FHA, familial hypoalphalipoproteinemia; HDL, high-density lipoprotein; LDL, low-density lipoprotein; LDLR, low-density lipoprotein receptor; PCR, polymerase chain reaction; PCSK9, proprotein convertase subtilisin/kexin type 9; PL, phospholipids; RCT, reverse cholesterol transport; RIN, RNA integrity number; SLSJ, saguenay-lac-saint-jean; STAT, signal transducers and activators of transcription; T2D, type 2 diabetes; TGD, tangier disease; VLDL, very low-density lipoprotein

© 2012 Landes Bioscience. High-density lipoprotein cholesterol (HDL-C) concentration, a strong coronary artery disease (CAD) clinical biomarker, shows significant interindividual variability. However, the molecular mechanisms involved remain mostly unknown. ATPbinding cassette A1 (ABCA1) catalyzes the cholesterol transfer from peripheral cells to nascent HDL particles. Recently, a differentially methylation region was identified in ABCA1 gene promoter locus, near the first exon. Therefore, we hypothesized that DNA methylation changes at ABCA1 gene locus is one of the molecular mechanisms involved in HDL-C interindividual variability. The study was conducted in familial hypercholesterolemia (FH), a monogenic disorder associated with a high risk of CAD. Ninety-seven FH patients (all p.W66G for the LDLR gene mutation and not under lipid-lowering treatment) were recruited and finely phenotyped for DNA methylation analyses at ABCA1 gene locus. ABCA1 DNA methylation levels were found negatively correlated with circulating HDL-C (r = -0.20; p = 0.05), HDL2-phospholipid levels (r = -0.43; p = 0.04), and with a trend for association with HDL peak particle size (r = -0.38; p = 0.08). ABCA1 DNA methylation levels were also found associated with prior history of CAD (CAD = 40.2% vs. without CAD = 34.3%; p = 0.003). These results suggest that epigenetic changes within the ABCA1 gene promoter contribute to the interindividual variability in plasma HDL-C concentrations and are associated with CAD expression. These findings could change our understanding of the molecular mechanisms involved in the pathophysiological processes leading to CAD.

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Plasma high-density lipoprotein cholesterol (HDL-C) concentration has been repeatedly identified as a strong, independent and inverse predictor of atherosclerotic cardiovascular disease risk (CVD), especially of coronary artery disease (CAD).1-3 This association relates on the HDL particles’ antioxidant, anti-inflammatory and antithrombotic properties, as well as their ability to remove excess peripheral cholesterol and transport it back to the liver for excretion or re-utilization; this pathway is called reverse cholesterol transport (RCT).4 Most of the variation in circulating HDL-C levels observed is the result of complex interactions between genetic and environmental factors. Heritability estimates for HDL-C levels are very high (up to 60%), and a number of genes have already been associated with its plasma concentration variation, including ATP-binding membrane cassette transporter

A1 (ABCA1).5-7 However, the genes and molecular mechanisms influencing HDL-C variability remain mostly to be identified.8 ABCA1 is an important modulator of HDL-C concentrations. It catalyzes the transfer of lipids from various tissues and cells to apolipoprotein A-I (apo A-I), the rate-limiting step in the biogenesis of HDL particles.9 Mutations in the ABCA1 gene (chromosome 9q31) are responsible for Tangier disease (TGD, OMIM 205400), a rare autosomal recessive genetic disorder, as well as for familial hypoalphalipoproteinemia (FHA, OMIM 604091) a more common form of HDL deficiency. TGD is characterized by markedly reduced plasma HDL-C and HDL-phospholipid (PL) levels and is associated with a high CVD risk.10,11 In order to better document the role of the epigenome in complex diseases, epigenetic changes at the ABCA1 gene locus were recently investigated.12,13 Epigenetics refers to the heritable and reversible regulation of gene transcription by molecular

*Correspondence to: Luigi Bouchard; Email: [email protected] Submitted: 11/29/11; Revised: 01/19/12; Accepted: 02/06/12 http://dx.doi.org/10.4161/epi.7.5.19633 www.landesbioscience.com Epigenetics

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Table 1. Characteristics of subjects from the HDL particle fine phenotyping subgroup (n = 25) Characteristics

Mean ± s.e.

Range

Age (years)

51.5 ± 2.7

[24.0–73.0]

Gender (H/F)

25/0

-

Waist circumference

99.0 ± 2.3

[79.0–131.0]

BMI (kg/m2)

28.2 ± 1.0

[21.7–41.9]

HDL-cholesterol (mmol/L)

1.04 ± 0.05

[0.64–1.49]

HDL2-phospholipid (mmol/L)

0.40 ± 0.03

[0.18–0.74]

HDL3-phospholipid (mmol/L)

0.98 ± 0.03

[0.71–1.36]

HDL peak particle size (Å)

90.2 ± 2.0

[80.3–111.3]

HDL-triglycerides (mmol/L)

0.25 ± 0.01

[0.12–0.39]

Apolipoprotein AI (g/L)

1.40 ± 0.04

[1.00–1.80]

Total cholesterol (mmol/L)

6.26 ± 0.38

[3.73–11.85]

LDL-cholesterol (mmol/L)

4.51 ± 0.30

[2.38–8.26]

Apolipoprotein B (g/L)

1.29 ± 0.07

[0.81–2.23]

Total triglycerides (mmol/L)

1.72 ± 1.29

[0.57–7.86]

have reported that maternal transmission of FH influences offspring lipid metabolism, suggesting that epigenetics programming during pregnancy could be implicated in the regulation of blood lipid concentrations in FH.26 Therefore, recent findings suggest that epigenetics and the resulting transcriptomic adaptations may account for the FH phenotype variability. The aims of this study were thus to assess whether the ABCA1 promoter DNA methylation shows variability and to which extent these changes can explain blood lipid profile variation as well as CAD expression differences in a cohort of 97 individuals at high CAD risk, originating from the same French-Canadian founder population and carrying the same FH-causing LDLR mutation. Results Tables 1 and 2 show the characteristics of subjects. On average, men from the HDL particle fine phenotyping subgroup were overweight, and showed a wide range of HDL-C levels and particle size (Table 1). Overall, men had higher waist circumference and lower HDL-C levels compared with women (Table 2). DNA methylation analyses and genomic context. A total of 26 CpGs located within five ABCA1 CpG island loci were epigenotyped in leukocyte DNA samples. These loci and the results presented below are illustrated in Figure 1. The 18 CpGs tested in ABCA1-B to ABCA1-E loci demonstrated very low levels of DNA methylation (all 0.70; p < 0.001). They were therefore analyzed together, resulting in a mean DNA methylation level of 35.9 ± 8.8% at this locus. Potential binding sites for transcription factors, such as AP-2, AP-4, ETS1, SRY and STAT, were found closed to or within the epigenotyped ABCA1-A locus (Fig. S1). Correlations between HDL particles’ phenotype, ABCA1 DNA methylation and RNA expression levels. We first showed that lower mean DNA methylation levels at the ABCA1-A CpG island locus were associated with a higher concentration of circulating HDL-C after controlling for age, gender, waist circumference and fasting triglyceridemia (Fig. 2A). Very similar associations were observed after stratification for gender (data not shown). Although the eight CpGs analyzed were well correlated with each other, correlation between DNA methylation and HDL-C concentration seems to be stronger for CpG2 and CpG7 (r = -0.22, p = 0.04 and r = -0.23, p = 0.02 respectively). We also found that ABCA1-A locus DNA methylation levels were correlated with HDL2-PL levels (Fig. 2B), when controlling for age, waist circumference and fasting triglyceridemia. Moreover, a trend for correlation with HDL peak particle size was observed when controlling for the same potential confounding variables (Fig. 2C). ABCA1 expression was also assessed in circulating blood leukocytes, but it wasn’t found significantly correlated with ABCA1 DNA methylation levels, HDL-C and HDL2-PL levels and HDL particle size (data not shown). Plasma samples and RNA, respectively for HDL particle size

© 2012 Landes Bioscience. CAD (%)

28.0

-

Mean wash-out (days)

6.7 ± 1.5

[1.0–29.0]

Mean ABCA1 DNA methylation (%)

39.2 ± 1.8

[23.2–59.9]

Mean ABCA1 expression (AU)

0.99 ± 0.03

[0.75–1.32]

ABCA1, ATP-binding cassette A1; AU, arbitrary unit; BMI, body mass index; CAD, coronary artery disease; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

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mechanisms independent of the DNA sequence.14 DNA methylation is the best-understood and stable epigenetic mark. It occurs at position 5' of the cytosine pyrimidine ring and is generally associated with gene expression repression.15-18 Toby et al. first showed that ABCA1 promoter region DNA methylation levels are higher in adults who had experienced prenatal exposure to famine decades ago.12 The same group then confirmed the interindividual DNA methylation variability at the ABCA1 promoter gene locus.13 However, it has never been shown whether ABCA1 DNA methylation changes are associated with circulating lipid profile alteration and/or CAD risk. To verify this hypothesis, we studied the ABCA1 DNA methylation in familial hypercholesterolemia (FH). FH is a frequent monogenic disorder characterized by high low-density lipoprotein cholesterol (LDL-C) concentrations, early atherosclerosis and premature occurrence of CAD ( 1.006 g/ml), whereas VLDL were found at the top (d < 1.006 g/ml). Then, the bottom fraction was used to isolated HDL particles with a precipitation of LDL with heparin and MnCl2. Triglyceride

and apo A-I contents were determined in this HDL particle fraction. HDL2 particles were then precipitated from the HDL fraction with a 4% solution of low-molecular-mass dextran sulfate, to obtain HDL3 particles in the supernatant. Phospholipids in HDL and HDL3 fractions were measured by choline-oxidase—DAOS method with the Wako Phospholipids C kit (Wako Chemicals; #433-36201) with an Olympus analyzer (Diagnostic Systems Group) as described by the manufacturer. The HDL2 phospholipid concentration was subsequently obtained after subtraction of the HDL3 phospholipid concentration from the total HDL phospholipids. Apo B and apo A-I levels were measured using nephelometry, as previously described in reference 46. HDL particle size was determined from 10 μL of whole plasma using non-denaturing 4–30% PAGGE, as previously described in reference 47. ABCA1 DNA methylation and mRNA level measurements. DNA was purified from whole blood samples with Gentra Puregen Blood Kit (Qiagen, #158389). Isolation and purification of intracellular RNA from whole blood stabilized in PAXgene Blood RNA Tubes (Qiagen, #762165) was completed with PAXgene Blood RNA Kit (Qiagen, #762164). RNA quality was assessed with Agilent 2100 Bioanalyser RNA Nano Chips (Agilent Technologies, #5067-1511). On average, the RNA showed good to very good quality (mean RNA integrity number (RIN) = 8.3 ± 0.6). The ABCA1 proximal gene promoter and first exon comprise a 2,000 bp strict CpG island, according to these criteria: (1) 500 bp minimum length; (2) 50% or higher GC content; and (3) 0.60 or higher observed dinucleotides CpG/expected dinucleotides CpG. We used gold standard Pyrosequencing technology, an accurate and quantitative sequencing assay, to determine basespecific cytosine methylation levels at five different loci within the ABCA1 CpG island (Fig. 1). Pyrosequencing assays combine sodium bisulfite DNA conversion chemistry (EpiTech Bisulfite Kits; Qiagen; #59104), polymerase chain reaction (PCR) amplification (Pyromark PCR Kit; Qiagen; #978703) and sequencing by synthesis assay (Pyromark Gold Q24 Reagents; Qiagen; #978802) of the target sequence. Sodium bisulfite preferentially deaminates unmethylated cytosine residues to thymines (after PCR amplification), whereas methyl-cytosines remain unmodified. PCR primers were selected using PyroMark Assay Design software v2.0.1.15. The PCR and pyrosequencing primers for ABCA1 gene CpG island loci amplification are described in Supplemental Table 1. Overall, 26 CpG dinucleotides were analyzed. cDNA was generated from total RNA using a random primer hexamer provided with the High Capacity cDNA Archive Kit (Applied Biosystems, #4368814). Equal amounts of cDNA were run in duplicate and amplified in a 20 μL reaction containing 10 μL of 2x Universal PCR Master Mix (Applied Biosystem, #4366072). Primers and TaqMan probes were obtained from Applied Biosystems (ABCA1: Hs01059118_m1). Each sample was calibrated to the GAPDH housekeeping genes (endogenous controls; GAPDH: Hs99999905_m1).48 Relative quantification estimations were performed using a 7500 Real-Time PCR System as recommended by the manufacturer. ABCA1/GAPDH Ct ratio (1/x) values were used in the analyses.

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Identification of potential binding motifs in ABCA1 proximal promoter regions. A literature review in reference 28–30, as well as the Genomatix software31 were used to identify the potential binding motifs for transcription factors in the ABCA1 proximal promoter region, especially at the five epigenotyped loci (ABCA1-A to ABCA1-E). This step was useful to determine specific regions where DNA methylation may interfere with transcription factor binding, and therefore influence gene expression. Statistical analyses. Statistical analyses were performed to investigate the association between ABCA1 DNA methylation, metabolic profile and previous history of CAD. In order to better understand the potential clinical impact of the ABCA1 epivariants, we analyzed its association with HDL particle fine phenotyping variables (triglyceride, phospholipid and apo AI contents of HDL particles) and ABCA1 gene leukocyte expression among a subsample of 25 FH men for which these phenotypes were available. Categorical variables were compared using a Pearson χ2-statistic, whereas mean group differences for continuous variables were compared with a Student t-test. Partial Pearson correlation controlling for known and significant confounding factors (age, gender, waist circumference and fasting triglyceridemia) was used to determine the association between the ABCA1 DNA methylation and expression profile with different lipid and metabolic characteristics. Results were considered statistically significant when p-value < 0.05 (two-sided). All statistical analyses were performed with the SPSS package (release 11.5.0, SPSS).

manuscript. Diane Brisson conceived the study design, participated to the data analysis/interpretation process and revised the manuscript. Johannie Munger and Benoît Lamarche participated to the data collection and revised the manuscript. Daniel Gaudet contributed to the study design, supplied the patients’ genotype and clinical evaluation, research infrastructure and revised the manuscript. Luigi Bouchard conceived the study design, participated to the data analysis/interpretation process and revised the manuscript. Acknowledgments

Authors are thankful to all participants and the staff of the ECOGENE-21 Laboratory and Clinical Research Center. Particularly, we warmly acknowledge the contribution of Sébastien Claveau (M.Sc.,), Nadia Mior, Jeannine Landry (R.N.) and Chantale Aubut (R.N.) for their dedicated work in this study. We also express our gratitude to Céline Bélanger and Julie St. Pierre for their thoughtful revision of the manuscript. During this research, Simon-Pierre Guay was recipient of a doctoral research award from the Canadian Institutes for Health and Research (CIHR), and a master’s award from the Fonds de la recherche en santé du Québec (FRSQ). Dr. Daniel Gaudet holds the Canada Research Chair in preventive genetics and community genomics (www.chairs.qc.ca). Luigi Bouchard is a junior research scholar from the FRSQ. This project was supported by ECOGENE-21, the CIHR team in community genetics (grant #CTP-82941), the Fondation des maladies du coeur du Québec, the FRSQ and the Banting Research Foundation.


Disclosure of Potential Conflicts of Interest

Note

The authors have no conflict of interest to disclose.

Supplemental material may be downloaded here: www.landesbioscience.com/journals/epigenetics/article/19633/

Author’s Contributions

Simon-Pierre Guay contributed to the study design, performed the data collection, the data analysis/interpretation and wrote the References 1.

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