NOS1 Methylation and Carotid Artery Intima-Media Thickness in Children Carrie V. Breton, Caron Park, Kim Siegmund, W. James Gauderman, Lora Whitfield-Maxwell, Howard N. Hodis, Ed Avol and Frank D. Gilliland Circ Cardiovasc Genet. 2014;7:116-122; originally published online March 12, 2014; doi: 10.1161/CIRCGENETICS.113.000320 Circulation: Cardiovascular Genetics is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Copyright © 2014 American Heart Association, Inc. All rights reserved. Print ISSN: 1942-325X. Online ISSN: 1942-3268
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Original Article NOS1 Methylation and Carotid Artery Intima-Media Thickness in Children Carrie V. Breton, ScD; Caron Park, MS; Kim Siegmund, PhD; W. James Gauderman, PhD; Lora Whitfield-Maxwell, RN, MA; Howard N. Hodis, MD; Ed Avol, MS; Frank D. Gilliland, MD, PhD Background—Nitric oxide (NO) plays an important role in cardiovascular health by maintaining and regulating vascular tone and blood flow. Epigenetic regulation of NO synthase (NOS), the genes responsible for NO production, may affect cardiovascular disease, including the development of atherosclerosis in children. Methods and Results—We measured percentage DNA methylation using bisulfite conversion and pyrosequencing assays on DNA from buccal cells provided by 377 participants of the Children’s Health Study on whom carotid artery intimamedia thickness (CIMT) measurements were also collected. We examined a total of 16 CpG loci located within NOS1, NOS2A, NOS3, ARG1, and ARG2 genes responsible for NO production. CIMT was measured using high-resolution B-mode carotid ultrasound. The association between percentage DNA methylation in ARG and NOS genes with CIMT was evaluated using linear regression adjusted for sex, ethnicity, body mass index, age at CIMT, town of residence, and experimental plate for pyrosequencing reactions. Differences in the association by ethnicity and ancestral group were also evaluated. For a 1% increase in average DNA methylation of NOS1, CIMT increased by 1.2 μm (P=0.02). This association was greater in Hispanic children of Native American descent (β=2.3; P=0.004) than in non-Hispanic whites (β=0.3; P=0.71) or Hispanic whites (β=1.0; P=0.35). Conclusions—DNA methylation of NOS1 has a plausible role in atherogenesis through regulation of NO production, although ancestry may alter the magnitude of this association. (Circ Cardiovasc Genet. 2014;7:116-122.) Key Words: cardiovascular diseases ◼ carotid artery intima-media thickness ◼ epigenomics ◼ nitric oxide synthase
C
ardiovascular disease (CVD) is the leading cause of morbidity and mortality in the general population.1 Atherosclerosis, a progressive process of lipid deposition in which the arterial wall thickens over time, is a well-known underlying pathology for the majority of clinical cardiovascular events. Atherosclerosis begins in childhood with fatty streak formation in the intima of arteries.2,3 Carotid artery intima-media thickness (CIMT) is a noninvasive measure of atherosclerosis and a strong indicator of CVD in adults.4,5
Clinical Perspective on p 122 Multiple biological pathways are implicated in the pathogenesis of atherosclerosis, some of which involve nitric oxide (NO).6 NO has a presumed cardioprotective role through the regulation of vascular tone and blood pressure, preventing platelet aggregation and inhibiting smooth muscle cell proliferation.7,8 NO is synthesized from l-arginine by NO synthase (NOS) enzymes of which there are 3 main isoforms, including neuronal (or NOS1), inducible (or NOS2A), and endothelial NOS (or NOS3). All 3 isoforms are expressed in the cardiovascular and respiratory systems of humans.7,9 Existing evidence from in vitro and animal studies shows that epigenetic
changes in NOS1, NOS2A, and NOS3 from DNA methylation and histone modification are associated with gene expression and that these epigenetic variations in NOS can affect NO generation and bioavailability.10–12 Arginase (ARG) competes with NOS for the common substrate l-arginine, suggesting that ARG may play a factor in regulating NO synthesis by moderating the availability of intracellular l-arginine.13,14 In mammals, there are 2 isoforms of ARG, one is the cytosolic isoform (ARG1), and the other is the mitochondrial isoform (ARG2). Both are expressed in endothelial, vascular smooth muscle, and airway epithelial cells.13,15,16 Changes in NOS and ARG expression instigated by epigenetic modifications may have the potential to influence NO synthesis and impact cardiovascular health outcomes. In a population-based cohort of children who had participated in the Southern California Children’s Health Study (CHS), we investigated the potential role for epigenetic regulation of NO, an important player in CVD.17,18 Specifically, we evaluated whether DNA methylation of NOS and ARG genes is associated with CIMT in children. Because CVD rates vary by ethnicity and because the CHS population comprised both Hispanic white and non-Hispanic white children,
Received August 12, 2013; accepted February 14, 2014. From the Department of Preventive Medicine (C.V.B., C.P., K.S., W.J.G., H.N.H., E.A., F.D.G.) and Atherosclerosis Research Unit (L.W.-M., H.N.H.), University of Southern California, Los Angeles, CA. The Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.113.000320/-/DC1. Correspondence to Carrie V. Breton, ScD, Department of Preventive Medicine, USC Keck School of Medicine, 2001 N Soto St, Los Angeles, CA 90032. E-mail [email protected] © 2014 American Heart Association, Inc. Circ Cardiovasc Genet is available at http://circgenetics.ahajournals.org
DOI: 10.1161/CIRCGENETICS.113.000320
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Breton et al NOS1 Methylation and Carotid IMT 117 and Hispanics whites are a heterogeneous population, we also evaluated the potential for the association to vary by selfreported ethnicity and genetically determined ancestral group.
Methods Study Population This study was nested in the ongoing CHS.17 We sampled children from the 5341 kindergarten and first graders who were enrolled in the study in 2002. A subset of 940 non-Hispanic white and Hispanic white children who had buccal samples collected for genetic analysis and fractional exhaled nitric oxide measurements were selected for DNA methylation analysis as described previously.19 For the purpose of this study, we selected only 377 children who had both genetic information and CIMT measurement data. This study was approved by the University of Southern California institutional review board for human studies.
CIMT Measurements A Mindray DC-7 Diagnostic System attached to a 10-MHz linear array transducer was used to obtain high-resolution B-mode ultrasound images of the carotid arteries by a single imaging specialist from the USC Atherosclerosis Research Unit Core Imaging and Reading Center. All ultrasound examinations were obtained at the children’s schools in the 2007 to 2008 school year (year 6 of CHS). Phantom test images were used to calibrate the instrument. The determined parameters were preset and used across all school sites throughout the study.20–22 To ensure that CIMT was measured at the same point in the cardiac cycle, a single-lead ECG was simultaneously recorded along with the B-mode image, and the images contained internal anatomic landmarks for probe angulation reproducibility (patents 2005, 2006, 2011).23 CIMT was measured along the far wall of the distal common carotid artery between the lumen–intima and media–adventitia along an electronically generated 1-cm length just 0.25 cm from the carotid artery bulb by automated computerized edge detection with an in-house developed software package (patents 2005, 2006, 2011).24,25 Replicate CIMT measurements were collected on 44 subjects for both left and right CIMT to evaluate reproducibility. Intraclass correlation coefficients were 0.88 and 0.84, and percent coefficient of variation was 7.9 and 7.1, respectively.
Buccal Cell Sample Collection Buccal cells were used as a readily accessible surrogate for evaluating the association between DNA methylation of NO-related genes and CIMT. Buccal cell samples were collected in school years: 2004 to 2005 (year 3 of CHS) or 2006 to 2007 (year 5 of CHS). Children were provided with 2 toothbrushes and instructed to brush their teeth with the first one. They were instructed to gently brush the buccal mucosa with the second toothbrush. The brush was then placed in a leak-proof container that was filled with an alcohol-based fixative. Children then swished liquid throughout their mouths and expelled the fluid into a container. The majority of buccal cell specimens were collected at school under the supervision of study staff. The remaining specimens were collected at home and sent to us by mail. Buccal cell suspensions were centrifuged at 2000g on the day they were received in the laboratory. The pellets were stored frozen at −80°C until used for DNA extraction, at which time they were resuspended and incubated in 600 μL of lysis solution from a PUREGENE DNA isolation kit (catalog No. D-5000; GENTRA, Minneapolis, MN) containing 100 μg/mL proteinase K overnight at 55°C. DNA extraction was performed according to manufacturer’s recommendations. The DNA samples were resuspended in the hydration solution (GENTRA) and stored at −80°C.
gene expression or location within a transcription factor binding site. Polymerase chain reaction primers targeting these loci were developed using MethPrimer software.26 Primers were designed not to overlap with any repeated elements or single-nucleotide polymorphism sites, and the specificity of the primer sequence was confirmed using in silico polymerase chain reaction (Table I in the Data Supplement).
DNA Methylation Methylation analysis has been described in detail previously.27 Briefly, laboratory personnel performing DNA methylation analyses were blinded to study subject information. Bisulfite conversion of 1 μg of genomic DNA extracted from buccal mucosal cells was performed with the EZ-96 DNA Methylation-Gold Kit (Zymo Research, Orange, CA) according to the manufacturer’s recommended protocol. Methylation analyses were performed using the HS 96 Pyrosequencing System (Biotage AB, Uppsala, Sweden) as described in previous work.28 Hct116 cell line DNA was used as inter- and intraplate control DNA for each plate run on the pyrosequencing. Percent coefficient of variation across the plates ranged from 2.1% to 5.5% for NOS2A and 1.1% for NOS3. The output from pyrosequencing is reported as a percent of DNA methylation at each CpG locus. As a quality control check to estimate the bisulfite conversion efficiency, we placed duplicate genomic DNA samples on each bisulfite conversion plate to estimate the internal plate variation of bisulfite conversion and the pyrosequencing reaction. Conversion efficiency was >95%. We also added universal polymerase chain reaction products amplified from cell line DNA on each pyrosequencing plate to check the run-to-run and plate-to-plate variation in performing pyrosequencing reactions. In addition, the pyrogram peak pattern from every sample was checked to confirm the quality of reaction.
Ancestry We computed ancestry using the program STRUCTURE from a set of ancestral informative markers that were scaled to represent the
Table 1. Descriptive Statistics of the 377 Children’s Health Study Participants Characteristics Age at CIMT scan, y 10*
129 (34.2)
11
184 (48.8)
12
64 (17.0)
Male
177 (47.0)
Ancestry Non-Hispanic white Hispanic white Hispanic Native American
We examined a total of 16 CpG loci located within NOS1, NOS2A, NOS3, ARG1, and ARG2 as described previously (Figure I in the Data Supplement).19 Loci were chosen based on likelihood for affecting
140 (37.1) 71 (19.2) 158 (42.8)
Study communities Long Beach
16 (4.2)
Mira Loma
56 (14.9)
Riverside
40 (10.6)
San Dimas
42 (11.1)
Upland
58 (15.4)
Glendora
54 (14.3)
Anaheim
38 (10.1)
Santa Barbara BMI (n=376), mean±SD, kg/m2
Selection of CpG Methylation Loci
n (%)
73 (19.4) 20.12±3.97
BMI indicates body mass index; and CIMT, carotid artery intima-media thickness. *Two 9-year-old children were grouped with the 10-year-old children because of the small sample size.
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118 Circ Cardiovasc Genet April 2014 Table 2. Distribution of CIMT (μm) by Population Study Characteristics CIMT Characteristics
n
Mean
SD
377
562.0
40.6
10†
129
555.3
46.5
11
184
564.6
36.6
12
64
567.6
37.4
Male
177
565.4
37.5
Female
200
559.0
43.0
140
567.2
41.7
71
561.5
38.6
158
558.0
40.7
CIMT Age at CIMT scan y
P Value 0.06*
Sex
0.13
Ancestry
0.15†
Non-Hispanic white Hispanic white Hispanic Native American
CIMT indicates carotid artery intima-media thickness. *Test for trend. †F test for comparison of CIMT means across 3 groups.
proportion of Native American and white ancestry.29 Ancestry was divided into 3 groups based on self-reported ethnicity and a genetic ancestry score. Children who reported they were non-Hispanic white were predominately of white ancestry based on ancestral score. Children who reported they were Hispanic white were further divided based on their ancestry score into primarily white ancestry if they were genetically more white than Native American or primarily Native American ancestry if they were genetically more Native American.
Statistical Analyses Descriptive analyses examined the distribution of DNA methylation in ARG and NOS genes, CIMT, and subject characteristics. Normality of the distribution of CIMT as well as the model residuals was assessed by the Shapiro–Wilk test. Spearman correlations were used to evaluate pairwise correlations of percentage methylation between different CpGs in the same gene. Linear regression was used to examine the association between CIMT and percentage DNA methylation of ARG and NOS genes (as continuous variables), adjusting
for potential confounders including sex, race, body mass index, age at CIMT scan, town of residence, and experimental plate for pyrosequencing reactions. We chose these variables because they were known to be predictors of CIMT or were identified as confounders that affected the variability observed in the data. We additionally assessed whether systolic and diastolic blood pressures were predictors of CIMT in our cohort and whether adjustment for blood pressure altered the association between methylation and CIMT. Neither systolic nor diastolic blood pressure was associated with CIMT directly, nor did blood pressure alter the association with DNA methylation. We also evaluated year of buccal cell collection as a potential confounder but did not find it to alter our results. Therefore, the final models did not include adjustment for blood pressure or for buccal cell collection year. For the variable age at CIMT scan, ages 9 and 10 years were combined because of the small sample size in age 9 years (n=2). Body mass index was treated as a continuous variable. Both left and right CIMT were evaluated, and similar results were observed. Thus, an average of left and right CIMT was calculated and used for all analyses presented. Additional analyses were conducted in which methylation variables for ARG and NOS genes were dichotomized into 2 categories. For loci that had ≥20% zero values of methylation (NOS2A positions 4–7 and ARG2), the dichotomized variable was categorized as either unmethylated or methylated. The remaining loci were dichotomized into low methylation or high methylation where the cutoff point was at the median. For genes that had multiple CpG loci measured, we also evaluated the average percent methylation separately for loci within and outside of CpG islands. We reported results of the linear regression models as micrometer changes in CIMT for a 1% difference in DNA methylation. For the dichotomized model, results were reported as micrometer changes in CIMT for DNA that was methylated or had high methylation. Lastly, we added statistical interaction terms to the linear regression model and used an overall likelihood ratio test to assess whether the association between DNA methylation of ARG and NOS genes varied by ancestry. All tests assumed a 2-sided alternative hypothesis with a significant level of 0.05. The data were analyzed using SAS software version 9.2.
Results The children of this study were on average aged 11 years when CIMT was measured (range, 9–12 years). A little less than half of the children were male, and 63% were of Hispanic white ethnicity (Table 1). CIMT measurements were generally normally distributed with an average of 562.0 μm
Figure. Distribution of percent methylation of CpG loci in NOS and ARG genes. Genes with multiple CpG loci in the noted region have been averaged together.
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Breton et al NOS1 Methylation and Carotid IMT 119 Table 3. Association Between Percent Methylation of NOS and ARG Genes and CIMT (μm) Effect on CIMT per 1% Increase in Methylation Gene Loci
n
Estimate
P Value†
Effect on CIMT in Subjects With High vs Low Methylation* n
Estimate
P Value†
NOS1 Position 1
363
0.73
0.05
363
10.90
0.01
Position 2
357
0.83
0.14
357
4.52
0.33
Position 3
353
0.81
0.02
353
11.73
0.01
Average
363
1.17
0.02
363
15.83
0.0004‡
359
−0.92
0.37
359
−7.70
0.11
Position 2
359
−0.39
0.68
359
−8.81
0.09
Position 3
366
0.70
0.22
366
8.05
0.08
NOS2A Position 1
Average
359
−0.94
0.43
359
−3.67
0.50
Position 4
376
−0.46
0.58
376
−2.48
0.66
Position 5
376
−0.68
0.35
376
−0.73
0.87
Position 6
376
−0.91
0.41
376
1.27
0.79
Position 7
376
−2.24
0.05
376
−3.05
0.53
CpG island average
376
−1.19
0.25
376
−13.60
0.13
367
0.04
0.91
367
−4.05
0.37
NOS3 Position 1 Position 2
367
−0.49
0.25
367
−5.85
0.18
Average
367
−0.23
0.60
367
−8.04
0.06
374
−0.66
0.20
374
−5.89
0.20
ARG1 Position 1 ARG2 Position 1
356
0.38
0.59
356
7.00
0.17
Position 2
355
−0.33
0.59
355
−2.18
0.66
Position 3
355
−0.67
0.34
355
4.64
0.57
Average
356
−0.27
0.72
356
20.37
0.07
CIMT indicates carotid artery intima-media thickness. *High methylation was defined as greater than the median value for all loci except NOS2A positions 4 to 7 and ARG2, which were categorized as completely unmethylated or methylated. †Adjusted for sex, ancestry, body mass index, plate, town, and age at IMT scan. ‡P10 untranslated first exons36 that are alternatively spliced to a common coding exon 2. In humans, many of these first exon variants contain an identical coding region and thus encode an NOS1 enzyme with conserved activity across tissues. However, alternative inclusion of weaker and stronger first exons is known to affect NOS1 translational efficiency and mRNA stability. Differential activation and repression of their associated promoters by stimuli such as hypoxia36
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120 Circ Cardiovasc Genet April 2014 Table 4. Association Between DNA Methylation of NOS1 and CIMT by Genetic Ancestry Non-Hispanic White
Hispanic White
Hispanic Native American
n
Estimate
P Value*
n
Estimate
P Value*
n
Estimate
P Value*
LRT P Value†
Position 1
135
0.1
0.83
70
1.4
0.13
150
1.5
0.02
0.33
Position 2
133
0.0
0.97
69
0.2
0.87
147
1.5
0.09
0.84
Position 3
133
0.1
0.90
67
0.8
0.30
145
1.5
0.01
0.27
Average
135
0.3
0.71
70
1.0
0.35
150
2.3
0.004
0.31
NOS1
CIMT indicates carotid artery intima-media thickness; and LRT, likelihood ratio test. *Stratum-specific P values. †P value from multi–degree of freedom LRT test for overall significance of interaction. Pairwise comparisons of each ancestry group with non-Hispanic white as the reference were not significant. The P values for a comparison of Hispanic Native American with non-Hispanic white were 0.13, 0.75, 0.11, and 0.15 for positions 1, 2, 3, and the average, respectively. The P values for a comparison of Hispanic white with non-Hispanic white were 0.82, 0.90, 0.60, and 0.79 for positions 1, 2, 3, and the average, respectively.
or epigenetic events12 is hypothesized to affect the variety, abundance, and subcellular localization of NOS1 transcripts in particular tissue types.37 Our CpG locus of interest resides near the translation initiation start site in exon 2 between 2 CTCF transcription factor binding sites, and exonic DNA methylation was recently shown to influence CTCF-promoted spliceosome assembly, rates of transcription elongation, and differential inclusion of upstream exons through methylation-dependent inhibition of CTCF binding.38 Because inclusion of different NOS1 first exons is known to impact NOS1 transcript abundance, it is conceivable that differential methylation of our CpG locus in exon 2 may similarly affect the variety and abundance of NOS1 transcripts and NO bioavailability and thus affect vascular health through heritable epigenetic mechanisms. Previous studies illustrate the importance of considering genetic ancestry when evaluating cardiovascular outcomes such as hypertension, peripheral arterial disease, and atherosclerosis,38–40 and emerging literature suggests that ancestry may influence the epigenome.41,42 Moreover, the rates of risk factors for CVD in Native American populations have increased in the last several decades.43 We evaluated whether the association between DNA methylation in NOS and ARG genes would vary by genetic ancestry and found that the association between DNA methylation in NOS1 and CIMT seemed strongest in Hispanic white children who were predominately of Native American ancestry. Currently little is known about how DNA methylation patterns may vary by ancestry.41 However, differences in diet or other exposures that affect epigenetic patterns may be differentially distributed across ancestry groups and may explain our findings. Alternatively, different genetic polymorphisms in NOS1 may exist across these groups, which may be correlated with DNA methylation in our measured locus. Nonetheless, our results provide the intriguing suggestion that epigenetic patterns associated with disease may vary by ancestry and thus warrant further consideration in epigenetic association studies. We observed no associations between CIMT and DNA methylation in ARG genes or in NOS2A and NOS3. The limitation of a small cohort may have prevented us from detecting potential significant results. The use of buccal cells to obtain DNA methylation is another limitation. Because we used a tissue source not directly related to the vasculature,
tissue-specific associations have likely been missed. Obtaining such a sample in our cohort of children was not feasible. Therefore, noninvasive buccal cell samples were used as a proxy to assess non–tissue-specific epigenetic changes at a locus thought to be related to cardiovascular health in children. Moreover, CpG methylation in NOS1 is consistent across multiple tissues derived from all 3 germ layers (Figure II in the Data Supplement; Marmal-aid R package available at http://marmal-aid.org/visualise.html) and thus could reflect a feature of CVD pathobiology at a tissue level that warrants further follow-up. This consistency of NOS1 methylation values across tissue types also raises intriguing questions about the role for environmental influences that might affect CIMT through epigenetic mechanisms and points to the early prenatal period as a potentially important window of susceptibility from such early life environmental influences. One limitation of the current study, however, is that an NO-generated decrease in vascular tone might also result as a consequence of atherosclerosis rather than a precursor. Although DNA methylation was measured 1 to 3 years before CIMT assessment in our study, the amount of time necessary for systemic changes in NO production to alter the structure of the carotid artery in children is not known. We conducted tests on multiple loci within 5 different genes; thus, consideration for multiple testing is warranted. Even with the use of a conservative Bonferroni correction, the association between high versus low average methylation in NOS1 remains significant. Last, we did not have data on flow-mediated dilation, and so a direct correlation between NOS1 methylation and changes in NO bioactivity could not be made. In this study, we provide evidence that differences in percentage DNA methylation in NOS1 are associated with subclinical atherosclerosis in children. We observed a stronger association between NOS1 and CIMT in children with Native American ancestry. These results suggest the possibility that buccal cell NOS1 methylation is biomarker of an epigenetic process for regulation of NO, a key molecule in vascular health and atherogenesis.
Sources of Funding This work was supported by the Southern California Environmental Health Sciences Center (grant No. 5P30ES007048) funded by
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Breton et al NOS1 Methylation and Carotid IMT 121 National Institute of Environmental Health Sciences and grants 5R01ES014708, 1K01ES017801, 5P01ES009581, R826708-01, and RD831861-01.
Disclosures None.
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associated with exhaled nitric oxide in children with asthma. Am J Respir Crit Care Med. 2011;184:191–197. 20. Kaplan RC, Kingsley LA, Gange SJ, Benning L, Jacobson LP, Lazar J, et al. Low CD4+ T-cell count as a major atherosclerosis risk factor in HIVinfected women and men. AIDS. 2008;22:1615–1624. 21. Kaplan RC, Sinclair E, Landay AL, Lurain N, Sharrett AR, Gange SJ, et al. T cell activation and senescence predict subclinical carotid artery disease in HIV-infected women. J Infect Dis. 2011;203:452–463. 22. Baker JV, Henry WK, Patel P, Bush TJ, Conley LJ, Mack WJ, et al; Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy Investigators. Progression of carotid intima-media thickness in a contemporary human immunodeficiency virus cohort. Clin Infect Dis. 2011;53:826–835. 23. Hodis HN, Mack WJ, LaBree L, Mahrer PR, Sevanian A, Liu CR, et al; VEAPS Research Group. Alpha-tocopherol supplementation in healthy individuals reduces low-density lipoprotein oxidation but not atherosclerosis: the Vitamin E Atherosclerosis Prevention Study (VEAPS). Circulation. 2002;106:1453–1459. 24. Selzer RH, Hodis HN, Kwong-Fu H, Mack WJ, Lee PL, Liu CR, et al. Evaluation of computerized edge tracking for quantifying intima-media thickness of the common carotid artery from B-mode ultrasound images. Atherosclerosis. 1994;111:1–11. 25. Selzer RH, Mack WJ, Lee PL, Kwong-Fu H, Hodis HN. Improved common carotid elasticity and intima-media thickness measurements from computer analysis of sequential ultrasound frames. Atherosclerosis. 2001;154:185–193. 26. Li LC, Dahiya R. MethPrimer: designing primers for methylation PCRs. Bioinformatics. 2002;18:1427–1431. 27. Breton CV, Salam MT, Wang X, Byun HM, Siegmund KD, Gilliland FD. Particulate matter, DNA methylation in nitric oxide synthase, and childhood respiratory disease. Environ Health Perspect. 2012;120:1320–1326. 28. Byun HM, Siegmund KD, Pan F, Weisenberger DJ, Kanel G, Laird PW, et al. Epigenetic profiling of somatic tissues from human autopsy specimens identifies tissue- and individual-specific DNA methylation patterns. Hum Mol Genet. 2009;18:4808–4817. 29. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155:945–959. 30. Seddon MD, Chowienczyk PJ, Brett SE, Casadei B, Shah AM. Neuronal nitric oxide synthase regulates basal microvascular tone in humans in vivo. Circulation. 2008;117:1991–1996. 31. Seddon M, Melikian N, Dworakowski R, Shabeeh H, Jiang B, Byrne J, et al. Effects of neuronal nitric oxide synthase on human coronary artery diameter and blood flow in vivo. Circulation. 2009;119:2656–2662. 32. Morishita T, Tsutsui M, Shimokawa H, Horiuchi M, Tanimoto A, Suda O, et al. Vasculoprotective roles of neuronal nitric oxide synthase. FASEB J. 2002;16:1994–1996. 33. Wilcox JN, Subramanian RR, Sundell CL, Tracey WR, Pollock JS, Harrison DG, et al. Expression of multiple isoforms of nitric oxide synthase in normal and atherosclerotic vessels. Arterioscler Thromb Vasc Biol. 1997;17:2479–2488. 34. Schleithoff C, Voelter-Mahlknecht S, Dahmke IN, Mahlknecht U. On the epigenetics of vascular regulation and disease. Clin Epigenetics. 2012;4:7. 35. Baccarelli A, Ghosh S. Environmental exposures, epigenetics and cardiovascular disease. Curr Opin Clin Nutr Metab Care. 2012;15:323–329. 36. Ward ME, Toporsian M, Scott JA, Teoh H, Govindaraju V, Quan A, et al. Hypoxia induces a functionally significant and translationally efficient neuronal NO synthase mRNA variant. J Clin Invest. 2005; 115:3128–3139. 37. Bros M, Boissel JP, Gödtel-Armbrust U, Förstermann U. Transcription of human neuronal nitric oxide synthase mRNAs derived from different first exons is partly controlled by exon 1-specific promoter sequences. Genomics. 2006;87:463–473. 38. Wassel CL, Jacobs DR Jr, Duprez DA, Bluemke DA, Sibley CT, Criqui MH, et al. Association of self-reported race/ethnicity and genetic ancestry with arterial elasticity: the Multi-Ethnic Study of Atherosclerosis (MESA). J Am Soc Hypertens. 2011;5:463–472. 39. Manichaikul A, Palmas W, Rodriguez CJ, Peralta CA, Divers J, Guo X, et al. Population structure of Hispanics in the United States: the multi- ethnic study of atherosclerosis. PLoS Genet. 2012;8:e1002640. 40. Allison MA, Peralta CA, Wassel CL, Aboyans V, Arnett DK, Cushman M, et al. Genetic ancestry and lower extremity peripheral artery disease in the Multi-Ethnic Study of Atherosclerosis. Vasc Med. 2010; 15:351–359.
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122 Circ Cardiovasc Genet April 2014 41. DeMeo DL, Rybicki BA. DNA methylation and ancestry: the smoke starts to clear. Am J Respir Crit Care Med. 2013;188:1049–1051. 42. Leng S, Liu Y, Thomas CL, Gauderman WJ, Picchi MA, Bruse SE, et al. Native American ancestry affects the risk for gene methylation in the lungs
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CLINICAL PERSPECTIVE Nitric oxide (NO) plays an important role in cardiovascular health by maintaining and regulating vascular tone and blood flow. Epigenetic regulation of NO synthase, the genes responsible for NO production, may affect cardiovascular disease. In this study, we provide evidence that differences in percentage DNA methylation in NOS1 are associated with carotid artery intima-media thickness in children. A stronger association was observed in Hispanic children with Native American ancestry as compared with Hispanic and non-Hispanic children of white ancestry. Because DNA methylation in NOS1 is consistent across multiple tissues derived from all 3 germ layers, NOS1 methylation measured in easily accessible buccal cell samples may have usefulness as a biomarker of NO regulation. Such a biomarker might help inform cardiovascular risk, particularly in the context of genetic ancestry.
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SUPPLEMENTAL MATERIAL
Figure Legend Figure 1. Schematic view of CpG loci depicting exon-intron structure and position of selected PCR amplicons. NOS1(a), NOS2 ‘non-CpG islands’(b), NOS2 ‘CpG islands shore’(c), NOS2 ‘CpG islands’(d), NOS3 (e), ARG1 (f), ARG2 (g). The chromosomal location of first CpG that we examined is marked in left side of gene map. Figure legend is shown in below.
Figure 2. Distribution of methylation patterns across multiple tissue types for NOS1 (chr12:117643947117891975) based on publicly available data using the Marmal-aid R package (available at http://marmalaid.org/visualise.html). Yellow represents unmethylated and blue represents methylated CpGs.
Figure 1. a.
b.
c.
d.
e.
f.
g.
NOS1 (nNOS) Chr12:117,769,145 (GRCH37/hg19)
Figure 2.
Supplemental Tables
Table 1. Primer sequences and reaction conditions for NOS and ARG genes Gene Primer Sequence Annealing PCR Temp size(bp ) o NOS1 PCR NOS156.7 C 223 Forward F:AGGTTGGTAATGAAGATATTTAGAGAAT AG
NOS2 A
NOS2 A
PCR Reverse
NOS1-R(biotin) : TCACCCACTCATAACTAATAACCC
PSQ sequencing PCR Forward
NOS1-SP:TTTTAGGGATA
PCR Reverse
iNOS(23151567)-R(biotin): AAACTATCTAAAACTACCCAATCCC
PSQ sequencing PCR Forward
iNOS(23151671)-SP:TTTATAATTTTGTAG
iNOS(23151743)-F: AAAAATAATTTTTTGGATGGTATGG
iNOS(23150425)-F: TTAGGGTTAGGTAAAGGTATTTTTGTTT
Location*
chr12:117,769,145
TDOWN5 3
177
chr17: 26,127,523
TDOWN5 3
212
chr17: 26,126,267
NOS2 A
NOS3
ARG1
PCR Reverse
iNOS(23150214)-R(biotin): CAATTCTATAAAACCACCTAATAATCTTAA
PSQ sequencing
iNOS(23150395)-SP: TAAAGGTATTTTTGTTTTAA
PCR Forward
iNOS(23145018)-F: GGAAGGTAGGGAAGGAGGGGTAGTT
PCR Reverse
iNOS(23144776)-R(biotin): AAAAATCCTACAAAACAACCTACACAACC
PSQ sequencing PCR Forward
iNOS(23144840)-SP: GAGGGGTTGGG NOS3-F: GGATATTTGGGTTTTTATTTA
PCR Reverse
NOS3-R(biotin): CAATAAAAAAAAACTCTCCA
PSQ sequencing PCR Forward
NOS3-SP: TGGGATAGGGG
PCR Reverse
ARG1R(biotin):TTTTTCCTTACCTATCCCTTTA
ARG1-F: GGAGTTAGTTGTTTTTATTAGA
TNCTD
243
chr17:26,120,703
TDOWN5 3
187
chr7:150,690,770
56.7oC
200
chr6: 131,894,428
ARG2
PSQ sequencing PCR Forward
ARG1-SP: TGTTAGAGTATGAG
PCR Reverse
ARG2-R(biotin): AAAAACTACCCCTTAAAAAC
PSQ sequencing
ARG2-SP: GGGGTTGGTTGGAGG
ARG2-F: GGAGAGTATAGGTTAGAGTG
56.7oC
274
chr14: 68,086,547
*The chromosomal location of the first CpG that we examined according to assembly of GRCh37/hg19
Table 2. Distribution of percent methylation of CpG loci in NOS and ARG genes Gene Loci Location N Min Q1 Median
Q3
Max
NOS1 Position 1
Non-island
364 45.5 64.1
68.5
72.4
85.7
Position 2
Non-island
358 75.0 86.9
89.9
92.3
100.0
Position 3
Non-island
353 39.3 57.9
62.0
65.8
88.7
Average
Non-island
364 57.8 70.1
73.4
76.4
85.3
Position 1
Non-island
360 79.2 90.5
92.1
93.3
97.4
Position 2
Non-island
360 84.2 95.7
98.3
100.0
100.0
Position 3
Non-island
367 35.1 49.1
51.7
54.6
63.3
Promoter Average*
Non-island
360 82.3 93.4
95.1
96.2
98.3
NOS2A
Position 4
Island
377
0
0.7
1.5
2.5
25.6
Position 5
Island
377
0
0
1.1
2.1
27.1
Position 6
Island
377
0
0
0.5
1.2
21.3
Position 7
Island
377
0
0
0.7
1.2
22.6
Island
377
0
0.6
1.0
1.6
23.8
CpG Island Average† NOS3 Position 1
Non-island
368 43.1 86.7
90.5
93.4
100.0
Position 2
Non-island
368 67.6 88.0
91.3
94.2
100.0
Average
Non-island
368 65.9 87.6
90.7
93.2
100.0
ARG1
Position 1
Non-island
375 50.8 60.8
63.9
67.2
79.8
ARG2 Position 1
Island
357
0
0
0.7
1.4
29.7
Position 2
Island
356
0
0
0.8
1.9
32.3
Position 3
Island
356
0
1.0
1.5
3.5
28.7
Average
Island
357
0
0.7
1.1
2.2
29.1
Q1: 1st quartile (25th percentile), Q3: 3rd quartile (75th percentile). *
Promoter average of position 1 and 2.
†
CpG Island average of position 4 to 7.
Table 3. Spearman pairwise correlations for NOS1 and NOS3 CpG loci. NOS1 NOS3 Position Position Position Position Position 1 2 3 1 2 Position 1.0 0.5* 0.6* 0.0 -0.1 NOS1 1 Position 2 1.0 0.5* 0.0 0.0 Position 3 1.0 -0.1 -0.1* Position 1.0 0.4* NOS3 1 Position 2 1.0 * p
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Original Article NOS1 Methylation and Carotid Artery Intima-Media Thickness in Children Carrie V. Breton, ScD; Caron Park, MS; Kim Siegmund, PhD; W. James Gauderman, PhD; Lora Whitfield-Maxwell, RN, MA; Howard N. Hodis, MD; Ed Avol, MS; Frank D. Gilliland, MD, PhD Background—Nitric oxide (NO) plays an important role in cardiovascular health by maintaining and regulating vascular tone and blood flow. Epigenetic regulation of NO synthase (NOS), the genes responsible for NO production, may affect cardiovascular disease, including the development of atherosclerosis in children. Methods and Results—We measured percentage DNA methylation using bisulfite conversion and pyrosequencing assays on DNA from buccal cells provided by 377 participants of the Children’s Health Study on whom carotid artery intimamedia thickness (CIMT) measurements were also collected. We examined a total of 16 CpG loci located within NOS1, NOS2A, NOS3, ARG1, and ARG2 genes responsible for NO production. CIMT was measured using high-resolution B-mode carotid ultrasound. The association between percentage DNA methylation in ARG and NOS genes with CIMT was evaluated using linear regression adjusted for sex, ethnicity, body mass index, age at CIMT, town of residence, and experimental plate for pyrosequencing reactions. Differences in the association by ethnicity and ancestral group were also evaluated. For a 1% increase in average DNA methylation of NOS1, CIMT increased by 1.2 μm (P=0.02). This association was greater in Hispanic children of Native American descent (β=2.3; P=0.004) than in non-Hispanic whites (β=0.3; P=0.71) or Hispanic whites (β=1.0; P=0.35). Conclusions—DNA methylation of NOS1 has a plausible role in atherogenesis through regulation of NO production, although ancestry may alter the magnitude of this association. (Circ Cardiovasc Genet. 2014;7:116-122.) Key Words: cardiovascular diseases ◼ carotid artery intima-media thickness ◼ epigenomics ◼ nitric oxide synthase
C
ardiovascular disease (CVD) is the leading cause of morbidity and mortality in the general population.1 Atherosclerosis, a progressive process of lipid deposition in which the arterial wall thickens over time, is a well-known underlying pathology for the majority of clinical cardiovascular events. Atherosclerosis begins in childhood with fatty streak formation in the intima of arteries.2,3 Carotid artery intima-media thickness (CIMT) is a noninvasive measure of atherosclerosis and a strong indicator of CVD in adults.4,5
Clinical Perspective on p 122 Multiple biological pathways are implicated in the pathogenesis of atherosclerosis, some of which involve nitric oxide (NO).6 NO has a presumed cardioprotective role through the regulation of vascular tone and blood pressure, preventing platelet aggregation and inhibiting smooth muscle cell proliferation.7,8 NO is synthesized from l-arginine by NO synthase (NOS) enzymes of which there are 3 main isoforms, including neuronal (or NOS1), inducible (or NOS2A), and endothelial NOS (or NOS3). All 3 isoforms are expressed in the cardiovascular and respiratory systems of humans.7,9 Existing evidence from in vitro and animal studies shows that epigenetic
changes in NOS1, NOS2A, and NOS3 from DNA methylation and histone modification are associated with gene expression and that these epigenetic variations in NOS can affect NO generation and bioavailability.10–12 Arginase (ARG) competes with NOS for the common substrate l-arginine, suggesting that ARG may play a factor in regulating NO synthesis by moderating the availability of intracellular l-arginine.13,14 In mammals, there are 2 isoforms of ARG, one is the cytosolic isoform (ARG1), and the other is the mitochondrial isoform (ARG2). Both are expressed in endothelial, vascular smooth muscle, and airway epithelial cells.13,15,16 Changes in NOS and ARG expression instigated by epigenetic modifications may have the potential to influence NO synthesis and impact cardiovascular health outcomes. In a population-based cohort of children who had participated in the Southern California Children’s Health Study (CHS), we investigated the potential role for epigenetic regulation of NO, an important player in CVD.17,18 Specifically, we evaluated whether DNA methylation of NOS and ARG genes is associated with CIMT in children. Because CVD rates vary by ethnicity and because the CHS population comprised both Hispanic white and non-Hispanic white children,
Received August 12, 2013; accepted February 14, 2014. From the Department of Preventive Medicine (C.V.B., C.P., K.S., W.J.G., H.N.H., E.A., F.D.G.) and Atherosclerosis Research Unit (L.W.-M., H.N.H.), University of Southern California, Los Angeles, CA. The Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.113.000320/-/DC1. Correspondence to Carrie V. Breton, ScD, Department of Preventive Medicine, USC Keck School of Medicine, 2001 N Soto St, Los Angeles, CA 90032. E-mail [email protected] © 2014 American Heart Association, Inc. Circ Cardiovasc Genet is available at http://circgenetics.ahajournals.org
DOI: 10.1161/CIRCGENETICS.113.000320
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Breton et al NOS1 Methylation and Carotid IMT 117 and Hispanics whites are a heterogeneous population, we also evaluated the potential for the association to vary by selfreported ethnicity and genetically determined ancestral group.
Methods Study Population This study was nested in the ongoing CHS.17 We sampled children from the 5341 kindergarten and first graders who were enrolled in the study in 2002. A subset of 940 non-Hispanic white and Hispanic white children who had buccal samples collected for genetic analysis and fractional exhaled nitric oxide measurements were selected for DNA methylation analysis as described previously.19 For the purpose of this study, we selected only 377 children who had both genetic information and CIMT measurement data. This study was approved by the University of Southern California institutional review board for human studies.
CIMT Measurements A Mindray DC-7 Diagnostic System attached to a 10-MHz linear array transducer was used to obtain high-resolution B-mode ultrasound images of the carotid arteries by a single imaging specialist from the USC Atherosclerosis Research Unit Core Imaging and Reading Center. All ultrasound examinations were obtained at the children’s schools in the 2007 to 2008 school year (year 6 of CHS). Phantom test images were used to calibrate the instrument. The determined parameters were preset and used across all school sites throughout the study.20–22 To ensure that CIMT was measured at the same point in the cardiac cycle, a single-lead ECG was simultaneously recorded along with the B-mode image, and the images contained internal anatomic landmarks for probe angulation reproducibility (patents 2005, 2006, 2011).23 CIMT was measured along the far wall of the distal common carotid artery between the lumen–intima and media–adventitia along an electronically generated 1-cm length just 0.25 cm from the carotid artery bulb by automated computerized edge detection with an in-house developed software package (patents 2005, 2006, 2011).24,25 Replicate CIMT measurements were collected on 44 subjects for both left and right CIMT to evaluate reproducibility. Intraclass correlation coefficients were 0.88 and 0.84, and percent coefficient of variation was 7.9 and 7.1, respectively.
Buccal Cell Sample Collection Buccal cells were used as a readily accessible surrogate for evaluating the association between DNA methylation of NO-related genes and CIMT. Buccal cell samples were collected in school years: 2004 to 2005 (year 3 of CHS) or 2006 to 2007 (year 5 of CHS). Children were provided with 2 toothbrushes and instructed to brush their teeth with the first one. They were instructed to gently brush the buccal mucosa with the second toothbrush. The brush was then placed in a leak-proof container that was filled with an alcohol-based fixative. Children then swished liquid throughout their mouths and expelled the fluid into a container. The majority of buccal cell specimens were collected at school under the supervision of study staff. The remaining specimens were collected at home and sent to us by mail. Buccal cell suspensions were centrifuged at 2000g on the day they were received in the laboratory. The pellets were stored frozen at −80°C until used for DNA extraction, at which time they were resuspended and incubated in 600 μL of lysis solution from a PUREGENE DNA isolation kit (catalog No. D-5000; GENTRA, Minneapolis, MN) containing 100 μg/mL proteinase K overnight at 55°C. DNA extraction was performed according to manufacturer’s recommendations. The DNA samples were resuspended in the hydration solution (GENTRA) and stored at −80°C.
gene expression or location within a transcription factor binding site. Polymerase chain reaction primers targeting these loci were developed using MethPrimer software.26 Primers were designed not to overlap with any repeated elements or single-nucleotide polymorphism sites, and the specificity of the primer sequence was confirmed using in silico polymerase chain reaction (Table I in the Data Supplement).
DNA Methylation Methylation analysis has been described in detail previously.27 Briefly, laboratory personnel performing DNA methylation analyses were blinded to study subject information. Bisulfite conversion of 1 μg of genomic DNA extracted from buccal mucosal cells was performed with the EZ-96 DNA Methylation-Gold Kit (Zymo Research, Orange, CA) according to the manufacturer’s recommended protocol. Methylation analyses were performed using the HS 96 Pyrosequencing System (Biotage AB, Uppsala, Sweden) as described in previous work.28 Hct116 cell line DNA was used as inter- and intraplate control DNA for each plate run on the pyrosequencing. Percent coefficient of variation across the plates ranged from 2.1% to 5.5% for NOS2A and 1.1% for NOS3. The output from pyrosequencing is reported as a percent of DNA methylation at each CpG locus. As a quality control check to estimate the bisulfite conversion efficiency, we placed duplicate genomic DNA samples on each bisulfite conversion plate to estimate the internal plate variation of bisulfite conversion and the pyrosequencing reaction. Conversion efficiency was >95%. We also added universal polymerase chain reaction products amplified from cell line DNA on each pyrosequencing plate to check the run-to-run and plate-to-plate variation in performing pyrosequencing reactions. In addition, the pyrogram peak pattern from every sample was checked to confirm the quality of reaction.
Ancestry We computed ancestry using the program STRUCTURE from a set of ancestral informative markers that were scaled to represent the
Table 1. Descriptive Statistics of the 377 Children’s Health Study Participants Characteristics Age at CIMT scan, y 10*
129 (34.2)
11
184 (48.8)
12
64 (17.0)
Male
177 (47.0)
Ancestry Non-Hispanic white Hispanic white Hispanic Native American
We examined a total of 16 CpG loci located within NOS1, NOS2A, NOS3, ARG1, and ARG2 as described previously (Figure I in the Data Supplement).19 Loci were chosen based on likelihood for affecting
140 (37.1) 71 (19.2) 158 (42.8)
Study communities Long Beach
16 (4.2)
Mira Loma
56 (14.9)
Riverside
40 (10.6)
San Dimas
42 (11.1)
Upland
58 (15.4)
Glendora
54 (14.3)
Anaheim
38 (10.1)
Santa Barbara BMI (n=376), mean±SD, kg/m2
Selection of CpG Methylation Loci
n (%)
73 (19.4) 20.12±3.97
BMI indicates body mass index; and CIMT, carotid artery intima-media thickness. *Two 9-year-old children were grouped with the 10-year-old children because of the small sample size.
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118 Circ Cardiovasc Genet April 2014 Table 2. Distribution of CIMT (μm) by Population Study Characteristics CIMT Characteristics
n
Mean
SD
377
562.0
40.6
10†
129
555.3
46.5
11
184
564.6
36.6
12
64
567.6
37.4
Male
177
565.4
37.5
Female
200
559.0
43.0
140
567.2
41.7
71
561.5
38.6
158
558.0
40.7
CIMT Age at CIMT scan y
P Value 0.06*
Sex
0.13
Ancestry
0.15†
Non-Hispanic white Hispanic white Hispanic Native American
CIMT indicates carotid artery intima-media thickness. *Test for trend. †F test for comparison of CIMT means across 3 groups.
proportion of Native American and white ancestry.29 Ancestry was divided into 3 groups based on self-reported ethnicity and a genetic ancestry score. Children who reported they were non-Hispanic white were predominately of white ancestry based on ancestral score. Children who reported they were Hispanic white were further divided based on their ancestry score into primarily white ancestry if they were genetically more white than Native American or primarily Native American ancestry if they were genetically more Native American.
Statistical Analyses Descriptive analyses examined the distribution of DNA methylation in ARG and NOS genes, CIMT, and subject characteristics. Normality of the distribution of CIMT as well as the model residuals was assessed by the Shapiro–Wilk test. Spearman correlations were used to evaluate pairwise correlations of percentage methylation between different CpGs in the same gene. Linear regression was used to examine the association between CIMT and percentage DNA methylation of ARG and NOS genes (as continuous variables), adjusting
for potential confounders including sex, race, body mass index, age at CIMT scan, town of residence, and experimental plate for pyrosequencing reactions. We chose these variables because they were known to be predictors of CIMT or were identified as confounders that affected the variability observed in the data. We additionally assessed whether systolic and diastolic blood pressures were predictors of CIMT in our cohort and whether adjustment for blood pressure altered the association between methylation and CIMT. Neither systolic nor diastolic blood pressure was associated with CIMT directly, nor did blood pressure alter the association with DNA methylation. We also evaluated year of buccal cell collection as a potential confounder but did not find it to alter our results. Therefore, the final models did not include adjustment for blood pressure or for buccal cell collection year. For the variable age at CIMT scan, ages 9 and 10 years were combined because of the small sample size in age 9 years (n=2). Body mass index was treated as a continuous variable. Both left and right CIMT were evaluated, and similar results were observed. Thus, an average of left and right CIMT was calculated and used for all analyses presented. Additional analyses were conducted in which methylation variables for ARG and NOS genes were dichotomized into 2 categories. For loci that had ≥20% zero values of methylation (NOS2A positions 4–7 and ARG2), the dichotomized variable was categorized as either unmethylated or methylated. The remaining loci were dichotomized into low methylation or high methylation where the cutoff point was at the median. For genes that had multiple CpG loci measured, we also evaluated the average percent methylation separately for loci within and outside of CpG islands. We reported results of the linear regression models as micrometer changes in CIMT for a 1% difference in DNA methylation. For the dichotomized model, results were reported as micrometer changes in CIMT for DNA that was methylated or had high methylation. Lastly, we added statistical interaction terms to the linear regression model and used an overall likelihood ratio test to assess whether the association between DNA methylation of ARG and NOS genes varied by ancestry. All tests assumed a 2-sided alternative hypothesis with a significant level of 0.05. The data were analyzed using SAS software version 9.2.
Results The children of this study were on average aged 11 years when CIMT was measured (range, 9–12 years). A little less than half of the children were male, and 63% were of Hispanic white ethnicity (Table 1). CIMT measurements were generally normally distributed with an average of 562.0 μm
Figure. Distribution of percent methylation of CpG loci in NOS and ARG genes. Genes with multiple CpG loci in the noted region have been averaged together.
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Breton et al NOS1 Methylation and Carotid IMT 119 Table 3. Association Between Percent Methylation of NOS and ARG Genes and CIMT (μm) Effect on CIMT per 1% Increase in Methylation Gene Loci
n
Estimate
P Value†
Effect on CIMT in Subjects With High vs Low Methylation* n
Estimate
P Value†
NOS1 Position 1
363
0.73
0.05
363
10.90
0.01
Position 2
357
0.83
0.14
357
4.52
0.33
Position 3
353
0.81
0.02
353
11.73
0.01
Average
363
1.17
0.02
363
15.83
0.0004‡
359
−0.92
0.37
359
−7.70
0.11
Position 2
359
−0.39
0.68
359
−8.81
0.09
Position 3
366
0.70
0.22
366
8.05
0.08
NOS2A Position 1
Average
359
−0.94
0.43
359
−3.67
0.50
Position 4
376
−0.46
0.58
376
−2.48
0.66
Position 5
376
−0.68
0.35
376
−0.73
0.87
Position 6
376
−0.91
0.41
376
1.27
0.79
Position 7
376
−2.24
0.05
376
−3.05
0.53
CpG island average
376
−1.19
0.25
376
−13.60
0.13
367
0.04
0.91
367
−4.05
0.37
NOS3 Position 1 Position 2
367
−0.49
0.25
367
−5.85
0.18
Average
367
−0.23
0.60
367
−8.04
0.06
374
−0.66
0.20
374
−5.89
0.20
ARG1 Position 1 ARG2 Position 1
356
0.38
0.59
356
7.00
0.17
Position 2
355
−0.33
0.59
355
−2.18
0.66
Position 3
355
−0.67
0.34
355
4.64
0.57
Average
356
−0.27
0.72
356
20.37
0.07
CIMT indicates carotid artery intima-media thickness. *High methylation was defined as greater than the median value for all loci except NOS2A positions 4 to 7 and ARG2, which were categorized as completely unmethylated or methylated. †Adjusted for sex, ancestry, body mass index, plate, town, and age at IMT scan. ‡P10 untranslated first exons36 that are alternatively spliced to a common coding exon 2. In humans, many of these first exon variants contain an identical coding region and thus encode an NOS1 enzyme with conserved activity across tissues. However, alternative inclusion of weaker and stronger first exons is known to affect NOS1 translational efficiency and mRNA stability. Differential activation and repression of their associated promoters by stimuli such as hypoxia36
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120 Circ Cardiovasc Genet April 2014 Table 4. Association Between DNA Methylation of NOS1 and CIMT by Genetic Ancestry Non-Hispanic White
Hispanic White
Hispanic Native American
n
Estimate
P Value*
n
Estimate
P Value*
n
Estimate
P Value*
LRT P Value†
Position 1
135
0.1
0.83
70
1.4
0.13
150
1.5
0.02
0.33
Position 2
133
0.0
0.97
69
0.2
0.87
147
1.5
0.09
0.84
Position 3
133
0.1
0.90
67
0.8
0.30
145
1.5
0.01
0.27
Average
135
0.3
0.71
70
1.0
0.35
150
2.3
0.004
0.31
NOS1
CIMT indicates carotid artery intima-media thickness; and LRT, likelihood ratio test. *Stratum-specific P values. †P value from multi–degree of freedom LRT test for overall significance of interaction. Pairwise comparisons of each ancestry group with non-Hispanic white as the reference were not significant. The P values for a comparison of Hispanic Native American with non-Hispanic white were 0.13, 0.75, 0.11, and 0.15 for positions 1, 2, 3, and the average, respectively. The P values for a comparison of Hispanic white with non-Hispanic white were 0.82, 0.90, 0.60, and 0.79 for positions 1, 2, 3, and the average, respectively.
or epigenetic events12 is hypothesized to affect the variety, abundance, and subcellular localization of NOS1 transcripts in particular tissue types.37 Our CpG locus of interest resides near the translation initiation start site in exon 2 between 2 CTCF transcription factor binding sites, and exonic DNA methylation was recently shown to influence CTCF-promoted spliceosome assembly, rates of transcription elongation, and differential inclusion of upstream exons through methylation-dependent inhibition of CTCF binding.38 Because inclusion of different NOS1 first exons is known to impact NOS1 transcript abundance, it is conceivable that differential methylation of our CpG locus in exon 2 may similarly affect the variety and abundance of NOS1 transcripts and NO bioavailability and thus affect vascular health through heritable epigenetic mechanisms. Previous studies illustrate the importance of considering genetic ancestry when evaluating cardiovascular outcomes such as hypertension, peripheral arterial disease, and atherosclerosis,38–40 and emerging literature suggests that ancestry may influence the epigenome.41,42 Moreover, the rates of risk factors for CVD in Native American populations have increased in the last several decades.43 We evaluated whether the association between DNA methylation in NOS and ARG genes would vary by genetic ancestry and found that the association between DNA methylation in NOS1 and CIMT seemed strongest in Hispanic white children who were predominately of Native American ancestry. Currently little is known about how DNA methylation patterns may vary by ancestry.41 However, differences in diet or other exposures that affect epigenetic patterns may be differentially distributed across ancestry groups and may explain our findings. Alternatively, different genetic polymorphisms in NOS1 may exist across these groups, which may be correlated with DNA methylation in our measured locus. Nonetheless, our results provide the intriguing suggestion that epigenetic patterns associated with disease may vary by ancestry and thus warrant further consideration in epigenetic association studies. We observed no associations between CIMT and DNA methylation in ARG genes or in NOS2A and NOS3. The limitation of a small cohort may have prevented us from detecting potential significant results. The use of buccal cells to obtain DNA methylation is another limitation. Because we used a tissue source not directly related to the vasculature,
tissue-specific associations have likely been missed. Obtaining such a sample in our cohort of children was not feasible. Therefore, noninvasive buccal cell samples were used as a proxy to assess non–tissue-specific epigenetic changes at a locus thought to be related to cardiovascular health in children. Moreover, CpG methylation in NOS1 is consistent across multiple tissues derived from all 3 germ layers (Figure II in the Data Supplement; Marmal-aid R package available at http://marmal-aid.org/visualise.html) and thus could reflect a feature of CVD pathobiology at a tissue level that warrants further follow-up. This consistency of NOS1 methylation values across tissue types also raises intriguing questions about the role for environmental influences that might affect CIMT through epigenetic mechanisms and points to the early prenatal period as a potentially important window of susceptibility from such early life environmental influences. One limitation of the current study, however, is that an NO-generated decrease in vascular tone might also result as a consequence of atherosclerosis rather than a precursor. Although DNA methylation was measured 1 to 3 years before CIMT assessment in our study, the amount of time necessary for systemic changes in NO production to alter the structure of the carotid artery in children is not known. We conducted tests on multiple loci within 5 different genes; thus, consideration for multiple testing is warranted. Even with the use of a conservative Bonferroni correction, the association between high versus low average methylation in NOS1 remains significant. Last, we did not have data on flow-mediated dilation, and so a direct correlation between NOS1 methylation and changes in NO bioactivity could not be made. In this study, we provide evidence that differences in percentage DNA methylation in NOS1 are associated with subclinical atherosclerosis in children. We observed a stronger association between NOS1 and CIMT in children with Native American ancestry. These results suggest the possibility that buccal cell NOS1 methylation is biomarker of an epigenetic process for regulation of NO, a key molecule in vascular health and atherogenesis.
Sources of Funding This work was supported by the Southern California Environmental Health Sciences Center (grant No. 5P30ES007048) funded by
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Breton et al NOS1 Methylation and Carotid IMT 121 National Institute of Environmental Health Sciences and grants 5R01ES014708, 1K01ES017801, 5P01ES009581, R826708-01, and RD831861-01.
Disclosures None.
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CLINICAL PERSPECTIVE Nitric oxide (NO) plays an important role in cardiovascular health by maintaining and regulating vascular tone and blood flow. Epigenetic regulation of NO synthase, the genes responsible for NO production, may affect cardiovascular disease. In this study, we provide evidence that differences in percentage DNA methylation in NOS1 are associated with carotid artery intima-media thickness in children. A stronger association was observed in Hispanic children with Native American ancestry as compared with Hispanic and non-Hispanic children of white ancestry. Because DNA methylation in NOS1 is consistent across multiple tissues derived from all 3 germ layers, NOS1 methylation measured in easily accessible buccal cell samples may have usefulness as a biomarker of NO regulation. Such a biomarker might help inform cardiovascular risk, particularly in the context of genetic ancestry.
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SUPPLEMENTAL MATERIAL
Figure Legend Figure 1. Schematic view of CpG loci depicting exon-intron structure and position of selected PCR amplicons. NOS1(a), NOS2 ‘non-CpG islands’(b), NOS2 ‘CpG islands shore’(c), NOS2 ‘CpG islands’(d), NOS3 (e), ARG1 (f), ARG2 (g). The chromosomal location of first CpG that we examined is marked in left side of gene map. Figure legend is shown in below.
Figure 2. Distribution of methylation patterns across multiple tissue types for NOS1 (chr12:117643947117891975) based on publicly available data using the Marmal-aid R package (available at http://marmalaid.org/visualise.html). Yellow represents unmethylated and blue represents methylated CpGs.
Figure 1. a.
b.
c.
d.
e.
f.
g.
NOS1 (nNOS) Chr12:117,769,145 (GRCH37/hg19)
Figure 2.
Supplemental Tables
Table 1. Primer sequences and reaction conditions for NOS and ARG genes Gene Primer Sequence Annealing PCR Temp size(bp ) o NOS1 PCR NOS156.7 C 223 Forward F:AGGTTGGTAATGAAGATATTTAGAGAAT AG
NOS2 A
NOS2 A
PCR Reverse
NOS1-R(biotin) : TCACCCACTCATAACTAATAACCC
PSQ sequencing PCR Forward
NOS1-SP:TTTTAGGGATA
PCR Reverse
iNOS(23151567)-R(biotin): AAACTATCTAAAACTACCCAATCCC
PSQ sequencing PCR Forward
iNOS(23151671)-SP:TTTATAATTTTGTAG
iNOS(23151743)-F: AAAAATAATTTTTTGGATGGTATGG
iNOS(23150425)-F: TTAGGGTTAGGTAAAGGTATTTTTGTTT
Location*
chr12:117,769,145
TDOWN5 3
177
chr17: 26,127,523
TDOWN5 3
212
chr17: 26,126,267
NOS2 A
NOS3
ARG1
PCR Reverse
iNOS(23150214)-R(biotin): CAATTCTATAAAACCACCTAATAATCTTAA
PSQ sequencing
iNOS(23150395)-SP: TAAAGGTATTTTTGTTTTAA
PCR Forward
iNOS(23145018)-F: GGAAGGTAGGGAAGGAGGGGTAGTT
PCR Reverse
iNOS(23144776)-R(biotin): AAAAATCCTACAAAACAACCTACACAACC
PSQ sequencing PCR Forward
iNOS(23144840)-SP: GAGGGGTTGGG NOS3-F: GGATATTTGGGTTTTTATTTA
PCR Reverse
NOS3-R(biotin): CAATAAAAAAAAACTCTCCA
PSQ sequencing PCR Forward
NOS3-SP: TGGGATAGGGG
PCR Reverse
ARG1R(biotin):TTTTTCCTTACCTATCCCTTTA
ARG1-F: GGAGTTAGTTGTTTTTATTAGA
TNCTD
243
chr17:26,120,703
TDOWN5 3
187
chr7:150,690,770
56.7oC
200
chr6: 131,894,428
ARG2
PSQ sequencing PCR Forward
ARG1-SP: TGTTAGAGTATGAG
PCR Reverse
ARG2-R(biotin): AAAAACTACCCCTTAAAAAC
PSQ sequencing
ARG2-SP: GGGGTTGGTTGGAGG
ARG2-F: GGAGAGTATAGGTTAGAGTG
56.7oC
274
chr14: 68,086,547
*The chromosomal location of the first CpG that we examined according to assembly of GRCh37/hg19
Table 2. Distribution of percent methylation of CpG loci in NOS and ARG genes Gene Loci Location N Min Q1 Median
Q3
Max
NOS1 Position 1
Non-island
364 45.5 64.1
68.5
72.4
85.7
Position 2
Non-island
358 75.0 86.9
89.9
92.3
100.0
Position 3
Non-island
353 39.3 57.9
62.0
65.8
88.7
Average
Non-island
364 57.8 70.1
73.4
76.4
85.3
Position 1
Non-island
360 79.2 90.5
92.1
93.3
97.4
Position 2
Non-island
360 84.2 95.7
98.3
100.0
100.0
Position 3
Non-island
367 35.1 49.1
51.7
54.6
63.3
Promoter Average*
Non-island
360 82.3 93.4
95.1
96.2
98.3
NOS2A
Position 4
Island
377
0
0.7
1.5
2.5
25.6
Position 5
Island
377
0
0
1.1
2.1
27.1
Position 6
Island
377
0
0
0.5
1.2
21.3
Position 7
Island
377
0
0
0.7
1.2
22.6
Island
377
0
0.6
1.0
1.6
23.8
CpG Island Average† NOS3 Position 1
Non-island
368 43.1 86.7
90.5
93.4
100.0
Position 2
Non-island
368 67.6 88.0
91.3
94.2
100.0
Average
Non-island
368 65.9 87.6
90.7
93.2
100.0
ARG1
Position 1
Non-island
375 50.8 60.8
63.9
67.2
79.8
ARG2 Position 1
Island
357
0
0
0.7
1.4
29.7
Position 2
Island
356
0
0
0.8
1.9
32.3
Position 3
Island
356
0
1.0
1.5
3.5
28.7
Average
Island
357
0
0.7
1.1
2.2
29.1
Q1: 1st quartile (25th percentile), Q3: 3rd quartile (75th percentile). *
Promoter average of position 1 and 2.
†
CpG Island average of position 4 to 7.
Table 3. Spearman pairwise correlations for NOS1 and NOS3 CpG loci. NOS1 NOS3 Position Position Position Position Position 1 2 3 1 2 Position 1.0 0.5* 0.6* 0.0 -0.1 NOS1 1 Position 2 1.0 0.5* 0.0 0.0 Position 3 1.0 -0.1 -0.1* Position 1.0 0.4* NOS3 1 Position 2 1.0 * p
