Published online before print March 31, 2008, doi: 10.1161/CIRCULATIONAHA.107.726067
(Circulation. 2008;117:1802-1809.)
© 2008 American Heart Association, Inc.
Epidemiology |
Cardiac Autonomic Dysfunction
Effects From Particulate Air Pollution and Protection by Dietary Methyl Nutrients and Metabolic Polymorphisms
From the Department of Environmental Health, Harvard School of Public Health, Boston, Mass (A.B., H.S., J.S.); Department of Environmental and Occupational Health, University of Milan and IRCCS Maggiore Hospital, Mangiagalli and Regina Elena Foundation, Milan, Italy (A.B.); Division of Nutritional Sciences, Cornell University, Ithaca, NY (P.A.C.); Channing Laboratory, Brigham and Women’s Hospital and Harvard Medical School, Boston, Mass (A.L.); Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor (S.K.P.); and VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, Mass (D.S., P.V.).
Correspondence to Andrea Baccarelli, MD, PhD, Exposure, Epidemiology and Risk Program, Harvard School of Public Health, 401 Park Dr, Landmark Center, 415G-West, PO Box 15698, Boston, MA 02215. E-mail abaccare{at}hsph.harvard.edu
Received July 13, 2007; accepted January 29, 2008.
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Abstract |
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Background— Particulate air pollution is associated with cardiovascular mortality and morbidity. To help identify mechanisms of action and protective/susceptibility factors, we evaluated whether the effect of particulate matter <2.5 µm in aerodynamic diameter (PM2.5) on heart rate variability was modified by dietary intakes of methyl nutrients (folate, vitamins B6 and B12, methionine) and related gene polymorphisms (C677T methylenetetrahydrofolate reductase [MTHFR] and C1420T cytoplasmic serine hydroxymethyltransferase [cSHMT]).
Methods and Results— Heart rate variability and dietary data were obtained between 2000 and 2005 from 549 elderly men from the Normative Aging Study. In carriers of [CT/TT] MTHFR genotypes, the SD of normal-to-normal intervals was 17.1% (95% CI, 6.5 to 26.4; P=0.002) lower than in CC MTHFR subjects. In the same [CT/TT] MTHFR subjects, each 10-µg/m3 increase in PM2.5 in the 48 hours before the examination was associated with a further 8.8% (95% CI, 0.2 to 16.7; P=0.047) decrease in the SDNN. In [CC] cSHMT carriers, PM2.5 was associated with an 11.8% (95% CI, 1.8 to 20.8; P=0.02) decrease in SDNN. No PM2.5-SSDN association was found in subjects with either [CC] MTHFR or [CT/TT] cSHMT genotypes. The negative effects of PM2.5 were abrogated in subjects with higher intakes (above median levels) of B6, B12, or methionine. PM2.5 was negatively associated with heart rate variability in subjects with lower intakes, but no PM2.5 effect was found in the higher intake groups.
Conclusion— Genetic and nutritional variations in the methionine cycle affect heart rate variability either independently or by modifying the effects of PM2.5.
Key Words: aging • epidemiology • heart rate • metabolism • nervous system, autonomic
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Introduction |
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Reductions in heart rate variability (HRV), a noninvasive measure of cardiac autonomic dysfunction that independently predicts cardiovascular mortality,1 have been related to short-term exposure to particulate air pollution (PM), particularly to fine-particulate air pollution of <2.5 µmol/L in aerodynamic diameter (PM2.5).2–6 This relation has been investigated to clarify mechanisms underlying the increased risk of cardiovascular disease (CVD) associated with PM2.5 exposure observed in multiple investigations.7,8
Clinical Perspective p 1809
Dietary methyl nutrients, including folate, the B vitamins pyridoxine (B6) and cyanocobalamin (B12), and methionine, are coenzymes or substrates in the methionine cycle that contribute to controlling biological processes9,10 such as methyl group transfers, homocysteine synthesis, and redox states that may be affected by PM exposure.11–14 The activity of the methionine cycle depends on the availability of dietary methyl nutrients15,16 and is modified by genetic variations in metabolic genes.17,18 In particular, the CT and TT genotypes of the C677T methylenetetrahydrofolate reductase (MTHFR) polymorphism have been associated with reduced enzyme activity17,19 and linked, although not consistently, with increased risk of CVD.20 Conversely, the TT genotype of the C1420T cytoplasmic serine hydroxymethyltransferase (cSHMT) polymorphism has been associated with higher homocysteine levels21 and has been found to interact with MTHFR polymorphisms in determining increased CVD risk.18
Whether differences in dietary intakes of methyl nutrients or genetic variation in the methionine cycle modify the effects of PM2.5 exposure on cardiovascular outcomes has never been tested. In the present study, we examined how the association of PM2.5 with HRV in the Normative Aging Study, a repeated-measures investigation of elderly subjects from the Boston metropolitan area, was affected by C677T MTHFR and C1420T cSHMT polymorphisms and by variations in dietary intakes of folate, vitamin B6, vitamin B12, and methionine.
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Methods |
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Study Population
Our study population consisted of 549 men from the Normative Aging Study, a longitudinal study of aging established in 1963 by the US Veterans Administration.22 Between November 2000 and June 2005, all participants still presenting for examination (n=676) were evaluated for HRV. Of these, 127 subjects were excluded because of heart arrhythmias, measurement time <3.5 minutes, or missing potential confounding data. The remaining 549 subjects had HRV measured in either 1 (n=363) or 2 (n=186) visits. None of the subjects had a recent (
6 months) myocardial infarction. The study participants were all male, and 539 of them (97.3%) were white. The present was approved by the Institutional Review boards of all participating institutions, and all participants gave written informed consent to the study.
HRV Measurement
HRV was measured for 7 minutes with a 2-channel (5-lead) ECG monitor (Trillium 3000 model, Forest Medical, East Syracuse, NY) while the subject was seated. The SD of normal-to-normal intervals (SDNN), high frequency (HF; 0.15 to 0.4 Hz), and low frequency (LF; 0.04 to 0.15 Hz) were computed with a fast Fourier transform using software (Trillium-3000, PC-Companion Software, Forest Medical) complying with established guidelines.23 We selected for the analysis the 4 consecutive minutes of ECG reading with the lowest number of artifacts.
Air Pollution and Weather Data
Continuous PM2.5 was measured at a stationary monitoring site on the roof of Countway Library, Harvard University in downtown Boston (Mass) with a tapered-element oscillating microbalance (model 1400A, Rupprecht & Pataschnick Co, East Greenbush, NY). Meteorological data were obtained from the Boston airport weather station. The 48-hour moving average of PM2.5 was used as the exposure index because this exposure period has shown the strongest association in previous studies.6
Semiquantitative Food-Frequency Questionnaires
Study subjects completed a food-frequency questionnaire referring to intake in the prior year at every visit.18 Food-frequency questionnaire data were available for 713 of the total 735 visits. Estimates of dietary intake, including folate, vitamin B6, vitamin B12, and methionine, were derived from the frequency and dosage information on the food-frequency questionnaire using software developed by the Nurses’ Health Study24 and processed by Nurses’ Health Study operators. Validity and reliability of this food-frequency questionnaire for estimating daily vitamin intakes have been described previously.24,25
Genotyping Methods
We performed genotyping of the C677T MTHFR (rs1801133) and C1420T cSHMT (rs1979277) polymorphisms on a subset of 362 of the 549 subjects included in the study. These 362 subjects were part of a prior analysis of a nested case-control study of CVD and controls selected by risk set sampling.18 We estimated that data from the 362 subjects with available genotyping provided us with statistical power to detect effect modifications in the association between PM2.5 and HRV equal to 86% for C677T MTHFR and 77% for C1420T cSHMT. These power calculations were performed on potential PM2.5 effects on the HF component of HRV, which was associated with PM2.5 exposure in a previous study on this population,13 assuming the same HF SD and effect modification size as those observed in our recent work on hemochromatosis (HFE) gene polymorphisms.26
DNA was extracted from stored frozen buffy coat of 7 mL whole blood using the QiAmp DNA blood kits (QIAGEN, Germantown, Md). Genotypes of C677T MTHFR and C1420T cSHMT were determined by the TaqMan procedure using the allelic discrimination technique (ABI Prism 7900 Sequence Detection System, Applied Biosystems, Foster City, Calif). Details of the genotyping are given elsewhere.18
Statistical Analysis
HRV measurements were log10 transformed to improve normality. The following potential confounders were chosen a priori and included in the analysis: age, past/current coronary heart disease (CHD), body mass index, mean arterial pressure, fasting blood glucose, cigarette smoking (never/former/current), alcohol consumption (
2 drinks per day, yes/no), use of β-blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, room temperature, season, and 48-hour moving average of outdoor apparent temperature. Potential nonlinearity between apparent temperature and HRV was accounted for by the use of linear and quadratic terms. All independent variables were fitted as time-varying covariates.
Because our data included repeated measures of HRV for many participants, our data may lack independence. Thus, we fit a mixed-effects model (PROC MIXED in SAS version 9.0, SAS Institute Inc, Cary, NC). We assumed the following: Yit=b0+ui+ b1X1it+...+bpXpit+ßPollutionit+
it, where Yit is the logarithm of HRV in subject i at time t, bo is the overall intercept, and ui is the separate random intercept for subject i. In this equation, Xlit to Xpit are the covariates. We used this model to assess the effect of PM2.5 on HRV. To evaluate the effect modification of PM2.5 effect by gene polymorphisms or dietary intakes, we added interaction terms to a model that included the main effects for both PM2.5 and the genetic/dietary factors. Dietary factors were entered in the model as time-varying variables.
Because MTHFR and SHMT genotype data were obtained from a convenience sample that represented a subset of our study population, stratum-weighted regression was used to obtain unbiased estimates, as indicated in a recent work on the use of extant case-control data for the analysis of additional outcomes.27 All results including genotype data presented throughout this article are obtained from mixed models that used weights equal to 1 for cases and equal to the reciprocal of the probability of being sampled into the study for controls.27 As a sensitivity analysis, we fitted nonweighted mixed models that also included the original case status variable or were restricted only to the original control series, with no notable differences in the results.
All regression analyses presented here were repeated after heart rate was included as an independent variable. Such adjustment by heart rate did not modify, compared with the results presented here, the significance of the gene polymorphism main effects and of the interactions of PM2.5 with gene polymorphisms or dietary intakes.
The authors had full access to and take responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.
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Results |
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Table 1 shows the characteristics of the entire study group and of the subjects with and without genotype data. Genotype distributions were in Hardy-Weinberg equilibrium for both C677T MTHFR (P=0.95) and C1420T cSHMT (P=0.35). Subjects with genotype data, which included CVD cases and age-matched controls from a previous study on CVD,19 had older age, higher fasting blood glucose, and, presumably because of tighter control or other changes in cases after the CVD event, lower blood pressure and total cholesterol, as also suggested by the more frequent use of β-blockers (Table 1). Consistently, controls from the original study did not show differences compared with subjects without genotype data except for older age and, because body mass index is negatively associated with age in healthy elderly individuals, moderately lower body mass index (Table I of the online Data Supplement). Table 2 shows dietary intakes of methyl nutrients, HRV measures, and environmental data for the 735 visits included in the study. No differences were observed in the subset of visits (n=485) with available C677T MTHFR and C1420T cSHMT genotyping compared with the entire study population.
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We calculated in multivariate models the adjusted percent change in HRV associated with the C677T MTHFR and C1420T cSHMT genotypes (Table 3). Subjects carrying the MTHFR 677 CT/TT genotypes exhibited a reduction of 17.1% in SDNN (95% CI, –25.4 to –6.5; P=0.002), 33.6% in HF (95% CI, –50.7 to –10.4; P=0.008), and 36.2% in LF (95% CI, –50.1 to –18.3; P<0.001) relative to the CC genotype. cSHMT genotypes were not associated with HRV (Table 3).
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The association between MTHFR genotypes and HRV remained significant after ambient PM2.5 was added as an independent variable to the models (supplementary Table III).
We estimated the association of PM2.5 with HRV overall and by C677T MTHFR and C1420T cSHMT genotypes (Table 4). In all subjects with genotype data, a 10-µg/m3 increase in ambient PM2.5 level in the 48 hours before the HRV measurement was negatively but nonsignificantly associated with SDNN, HF, and LF. In the full data set (Table 5), PM2.5 was significantly associated with SDNN (–7.1%; 95% CI, –13.2 to –0.6%; P=0.03) and HF (–18.7%; 95% CI, –31.1 to –4.0; P=0.01).
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In subjects carrying the MTHFR 677 CT/TT genotypes (Table 4), PM2.5 level was associated with significant decreases in both SDNN (–8.8%; 95% CI, –16.7 to –0.2; P=0.047) and HF (–22.8%; 95% CI, –38.2 to –3.5; P=0.02), whereas no PM2.5-related change was found in MTHFR 677 CC subjects. However, the statistical interactions between PM2.5 level and C1420T cSHMT genotypes were not statistically significant (P0.19).
In subjects carrying the cSHMT 1420 CC genotype, PM2.5 level was associated with significant decreases in SDNN (–11.8%; 95% CI, –20.8 to –1.8; P=0.02) and HF (–30.8%; 95% CI, –46.9 to –9.8; P=0.007), whereas no significant PM2.5-related change was found in CT/TT subjects (Table 4). The statistical interactions between PM2.5 level and C1420T cSHMT genotypes were statistically significant for both SDNN (P=0.02) and HF (P=0.03).
In our data, the MTHFR 677 CT/TT genotypes were associated with increased risk of CVD (supplementary Table IV), as defined for the original case-control study.18
When subjects were divided according to their dietary intakes of folate, vitamin B6, vitamin B12, or methionine, we found that the negative effect of PM2.5 on HRV was abrogated in subjects with B6, B12, or methionine higher than the median daily intake of the study population (Table 5). In particular, the association of PM2.5 with SDDN was significantly modified by B6, B12, and methionine intakes (P for interaction <0.05). The modification of the association of PM2.5 with HF and LF was statistically significant for differences in methionine intake (P for interaction 0.03) and only borderline significant for B6 and B12 (P for interaction, between 0.06 and 0.07). When we evaluated the association of dietary intakes with HRV regardless of PM2.5 exposure (supplementary Table V), vitamin B6, vitamin B12, and methionine intakes exhibited positive associations, generally nonsignificant, with HRV. A significant increase in SDNN was found in association with methionine intake above the median (11.4%; 95% CI, 2.0 to 21.7; P=0.02). Other potential modifiers of the PM2.5-HRV association such as CHD, obesity, diabetes, or hypertension were not associated with methyl nutrient intakes in this population (supplementary Table VI).
Throughout this article, we have presented modifications in HRV as percent changes. Changes on the original scale are presented in supplementary Tables VII to IX.
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Discussion |
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The present study, based on an elderly population in Boston (Mass), showed that genetic and nutritional variations in the methionine cycle metabolism modified HRV either independently or by modifying the effects of PM2.5. We demonstrated that HRV outcomes were affected by multiple components of the methionine cycle, including polymorphisms in genes coding for enzyme proteins (MTHFR and cSHMT) and dietary intakes of enzyme cofactors (B6, B12) and cycle substrates (methionine).
We found that subjects with MTHFR 677 CT/TT genotypes had lower HRV than subjects with the CC genotypes. This finding is in the same direction as the results of a comprehensive meta-analysis20 based on 11 162 CHD cases and 12 758 controls from 40 different studies that showed that TT carriers had significantly higher risk of CHD. However, the MTHFR 677 TT genotype appeared to be associated with increased CHD risk only in European populations, and there has been speculation as to whether dietary or other characteristics abrogated the C677T MTHFR effect in North American populations.20 Our findings in this elderly population suggest that at least some age groups of the US population may not be protected against the negative effects of C677T MTHFR on cardiac function.
The negative association between PM2.5 and HRV was modified by both C677T MTHFR and C1420T cSHMT polymorphisms, although the effect modification was significant for the C1420T cSHMT polymorphism only. PM2.5 effects on HRV were stronger in subjects with the MTHFR 677 CT/TT and cSHMT 1420 CC genotypes, which have been associated with reduced enzyme activity17,19,21 and increased risk of CVD.18,20 MTHFR, although not directly part of the methionine cycle, is the key limiting enzyme required for the conversion of 5-10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, the methyl group donor required for the remethylation of homocysteine to methionine.28 cSHMT produces the MTHFR substrate 5-10-methylenetetrahydrofolate from tetrahydrofolate in a B6-dependent reaction. Thus, the effects of both the MTHFR 677 CT/TT and cSHMT 1420 CC genotypes may be mediated through a reduction in the methionine cycle activity.
The reduction in HRV associated with PM2.5 level was abrogated in subjects with intakes of B6, B12, and methionine higher than the median level of our study population. Conversely, PM2.5 level was negatively associated with all measures of HRV in subjects with lower intakes. These results suggest that lower availability of B6, B12, or methionine, as well as genetically determined reductions in key enzymatic activities, may reduce methionine cycle–dependent cell functions that counteract PM2.5 effects. The methionine cycle communicates with different pathways presiding over various cell functions, including DNA methylation and glutathione synthesis.9,15 The methyl donors produced by the methionine cycle contribute to DNA methylation as substrates of DNA methyl transferases. Global DNA methylation content in blood leukocytes and other tissues decreases with aging, a finding that has been related to the age-associated increase in cardiovascular risk,29 and oxidative DNA damage such as that following PM2.5 exposure may interfere with methylation processes,30 thus also resulting in genomic hypomethylation. Genetic or dietary factors that increase the production of methyl donors may prevent the potential loss of DNA methylation that may be caused by PM2.5 exposure.
In our previous work in the Normative Aging Study, we showed that the association of PM2.5 with reduced HRV was stronger in subjects with glutathione S-transferase deletion, a common polymorphism that impairs glutathione-related responses to oxidative stress.13 Glutathione is synthesized from homocysteine, also a substrate of the methionine cycle, through additional B6-dependent reactions.9 Rodents exposed to concentrated urban particles evinced increased reactive oxygen species in both the lung and heart,31 an effect muted by preadministration of N-acetyl cysteine, a glutathione precursor and potent antioxidant.32 Experimental evidence has shown that a meal rich in methionine shifts the cycle activity toward glutathione production.9 Thus, a reduction in methionine cycle activity may represent an additional mechanism modulating particle effects by reducing oxidative stress defenses.
The median intakes in our populations were above the current dietary reference intakes of folate, B6, B12, and methionine. However, a relatively high percentage of individuals had daily intakes of methionine lower than the dietary reference intakes. The nutritional profile of the study subjects, which also included a large majority showing adequate B6 and B12 intakes, indicates that the usual diet in the study population was rich in meat with less intake of vegetables and dairy products. Our findings indicate that differences in B6 and B12 intakes in the range above the current dietary reference intake levels may modify the cardiovascular effects of air pollution. This finding, together with the increased particle-related risk in subjects with lower methionine intake, would warrant, if confirmed, a reassessment of current strategies for methyl nutrient supplementation.
A potential limitation of this study is that we used ambient PM2.5 concentrations from a single monitoring site as a surrogate for recent exposure to PM2.5. A recent study comparing ambient concentrations at this site with personal exposures in Boston has shown a high longitudinal correlation33 between the 2 measurements; the study also reported that PM2.5 concentrations were spatially homogeneous over the Boston area. This suggests that our use of ambient concentrations is reasonable and that the resulting exposure error is likely to be nondifferential. In our analyses, we considered several potential confounding factors that may have influenced HRV measures; we adjusted our models for age, existing diagnosis of CHD, body mass index, mean arterial pressure, fasting blood glucose, cigarette smoking, alcohol consumption, room temperature, outdoor apparent temperature, season, and use of β-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors. Therefore, chances that the observed associations reflected bias resulting from confounders are minimized.
Our analyses of C677T MTHFR and C1420T cSHMT polymorphisms were based on a subset of the study population that had previously been included in a case-control study on CVD nested in the Normative Aging Study cohort.18 The use of such a convenience sample with extant genotype data did not appear to have produced bias in our results because analyses restricted to controls from the original case-control series or adjusted by CVD case status confirmed our findings.27
Our results can be generalized only to an aged population that consists of older men who are almost all white. The effect on women, children, and different ethnic groups should be addressed in future studies, particularly in relation to the exposure of different population groups to PM2.5 with various geographical locations, occupations, socioeconomic status, and behavioral characteristics. Other health outcomes of PM2.5, including respiratory responses, also may be modified by genetic variations in the methionine pathway or differences in B6, B12, and methionine intake. Our findings provide novel hypotheses to pursue further research to investigate the mechanisms of action of air particles and ultimately to identify measures to prevent CVD and to reduce the effects of air pollution in human populations.34,35
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Acknowledgments |
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Sources of Funding
This work was supported by the Environmental Protection Agency grants EPA R83241601 and R827353 and the National Institute of Environmental Health Sciences grants ES00002, ES015172-01, and PO1 ES009825U.S. The VA Normative Aging Study, a component of the Massachusetts Veterans Epidemiology Research and Information Center, Boston, Mass, is supported by the Cooperative Studies Program/Epidemiology Research and Information Center of the US Department of Veterans Affairs.
Disclosures
None.
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References |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Tsuji H, Larson MG, Venditti FJ Jr, Manders ES, Evans JC, Feldman CL, Levy D. Impact of reduced heart rate variability on risk for cardiac events: the Framingham Heart Study. Circulation. 1996; 94: 2850–2855.
2. Gold DR, Litonjua A, Schwartz J, Lovett E, Larson A, Nearing B, Allen G, Verrier M, Cherry R, Verrier R. Ambient pollution and heart rate variability. Circulation. 2000; 101: 1267–1273.
3. Devlin RB, Ghio AJ, Kehrl H, Sanders G, Cascio W. Elderly humans exposed to concentrated air pollution particles have decreased heart rate variability. Eur Respir J Suppl. 2003; 40: 76s–80s.[CrossRef][Medline] [Order article via Infotrieve]
4. Pope CA 3rd, Hansen ML, Long RW, Nielsen KR, Eatough NL, Wilson WE, Eatough DJ. Ambient particulate air pollution, heart rate variability, and blood markers of inflammation in a panel of elderly subjects. Environ Health Perspect. 2004; 112: 339–345.[Medline] [Order article via Infotrieve]
5. Schwartz J, Litonjua A, Suh H, Verrier M, Zanobetti A, Syring M, Nearing B, Verrier R, Stone P, MacCallum G, Speizer FE, Gold DR. Traffic related pollution and heart rate variability in a panel of elderly subjects. Thorax. 2005; 60: 455–461.
6. Park SK, O’Neill MS, Vokonas PS, Sparrow D, Schwartz J. Effects of air pollution on heart rate variability: the VA Normative Aging Study. Environ Health Perspect. 2005; 113: 304–309.[Medline] [Order article via Infotrieve]
7. Brook RD, Franklin B, Cascio W, Hong Y, Howard G, Lipsett M, Luepker R, Mittleman M, Samet J, Smith SC Jr, Tager I. Air pollution and cardiovascular disease: a statement for healthcare professionals from the Expert Panel on Population and Prevention Science of the American Heart Association. Circulation. 2004; 109: 2655–2671.
8. Samet JM, Zeger SL, Dominici F, Curriero F, Coursac I, Dockery DW, Schwartz J, Zanobetti A. The National Morbidity, Mortality, and Air Pollution Study, part II: morbidity and mortality from air pollution in the United States. Res Rep Health Eff Inst. 2000; 94 (pt 2): 5–70.[Medline] [Order article via Infotrieve]
9. Aguilar B, Rojas JC, Collados MT. Metabolism of homocysteine and its relationship with cardiovascular disease. J Thromb Thrombolysis. 2004; 18: 75–87.[CrossRef][Medline] [Order article via Infotrieve]
10. Friso S, Choi SW. Gene-nutrient interactions in one-carbon metabolism. Curr Drug Metab. 2005; 6: 37–46.[CrossRef][Medline] [Order article via Infotrieve]
11. Belinsky SA, Snow SS, Nikula KJ, Finch GL, Tellez CS, Palmisano WA. Aberrant CpG island methylation of the p16(INK4a) and estrogen receptor genes in rat lung tumors induced by particulate carcinogens. Carcinogenesis. 2002; 23: 335–339.
12. Baccarelli A, Zanobetti A, Martinelli I, Grillo P, Hou L, Lanzani G, Mannucci PM, Bertazzi PA, Schwartz J. Air pollution, smoking, and plasma homocysteine. Environ Health Perspect. 2007; 115: 176–181.[Medline] [Order article via Infotrieve]
13. Schwartz J, Park SK, O’Neill MS, Vokonas PS, Sparrow D, Weiss S, Kelsey K. Glutathione-S-transferase M1, obesity, statins, and autonomic effects of particles: gene-by-drug-by-environment interaction. Am J Respir Crit Care Med. 2005; 172: 1529–1533.
14. Baccarelli A, Zanobetti A, Martinelli I, Grillo P, Hou L, Giacomini S, Bonzini M, Lanzani G, Mannucci PM, Bertazzi PA, Schwartz J. Effects of exposure to air pollution on blood coagulation. J Thromb Haemost. 2007; 5: 252–260.[CrossRef][Medline] [Order article via Infotrieve]
15. Reed MC, Nijhout HF, Neuhouser ML, Gregory JF 3rd, Shane B, James SJ, Boynton A, Ulrich CM. A mathematical model gives insights into nutritional and genetic aspects of folate-mediated one-carbon metabolism. J Nutr. 2006; 136: 2653–2661.
16. Koury MJ, Ponka P. New insights into erythropoiesis: the roles of folate, vitamin B12, and iron. Annu Rev Nutr. 2004; 24: 105–131.[CrossRef][Medline] [Order article via Infotrieve]
17. Frosst P, Blom HJ, Milos R, Goyette P, Sheppard CA, Matthews RG, Boers GJ, den Heijer M, Kluijtmans LA, van den Heuvel LP, Rozen R. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet. 1995; 10: 111–113.[CrossRef][Medline] [Order article via Infotrieve]
18. Lim U, Peng K, Shane B, Stover PJ, Litonjua AA, Weiss ST, Gaziano JM, Strawderman RL, Raiszadeh F, Selhub J, Tucker KL, Cassano PA. Polymorphisms in cytoplasmic serine hydroxymethyltransferase and methylenetetrahydrofolate reductase affect the risk of cardiovascular disease in men. J Nutr. 2005; 135: 1989–1994.
19. Goyette P, Sumner JS, Milos R, Duncan AM, Rosenblatt DS, Matthews RG, Rozen R. Human methylenetetrahydrofolate reductase: isolation of cDNA, mapping and mutation identification. Nat Genet. 1994; 7: 195–200.[CrossRef][Medline] [Order article via Infotrieve]
20. Klerk M, Verhoef P, Clarke R, Blom HJ, Kok FJ, Schouten EG. MTHFR 677C
T polymorphism and risk of coronary heart disease: a meta-analysis. JAMA. 2002; 288: 2023–2031.
21. Heil SG, Van der Put NM, Waas ET, den Heijer M, Trijbels FJ, Blom HJ. Is mutated serine hydroxymethyltransferase (SHMT) involved in the etiology of neural tube defects? Mol Genet Metab. 2001; 73: 164–172.[CrossRef][Medline] [Order article via Infotrieve]
22. Bell B, Rose C, Damon A. The normative aging study: an interdisciplinary and longitudinal study of health and aging. Aging Hum Dev. 1972; 3: 4–17.
23. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Eur Heart J. 1996; 17: 354–381.
24. Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hennekens CH, Speizer FE. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol. 1985; 122: 51–65.
25. Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol. 1992; 135: 1114–1126.
26. Park SK, O’Neill MS, Wright RO, Hu H, Vokonas PS, Sparrow D, Suh H, Schwartz J. HFE genotype, particulate air pollution, and heart rate variability: a gene-environment interaction. Circulation. 2006; 114: 2798–2805.
27. Richardson DB, Rzehak P, Klenk J, Weiland SK. Analyses of case-control data for additional outcomes. Epidemiology. 2007; 18: 441–445.[CrossRef][Medline] [Order article via Infotrieve]
28. Welch GN, Loscalzo J. Homocysteine and atherothrombosis. N Engl J Med. 1998; 338: 1042–1050.
29. Richardson B. Impact of aging on DNA methylation. Ageing Res Rev. 2003; 2: 245–261.[CrossRef][Medline] [Order article via Infotrieve]
30. Valinluck V, Tsai HH, Rogstad DK, Burdzy A, Bird A, Sowers LC. Oxidative damage to methyl-CpG sequences inhibits the binding of the methyl-CpG binding domain (MBD) of methyl-CpG binding protein 2 (MeCP2). Nucleic Acids Res. 2004; 32: 4100–4108.
31. Gurgueira SA, Lawrence J, Coull B, Murthy GG, Gonzalez-Flecha B. Rapid increases in the steady-state concentration of reactive oxygen species in the lungs and heart after particulate air pollution inhalation. Environ Health Perspect. 2002; 110: 749–755.[Medline] [Order article via Infotrieve]
32. Rhoden CR, Lawrence J, Godleski JJ, Gonzalez-Flecha B. N-acetylcysteine prevents lung inflammation after short-term inhalation exposure to concentrated ambient particles. Toxicol Sci. 2004; 79: 296–303.
33. Sarnat JA, Brown KW, Schwartz J, Coull BA, Koutrakis P. Ambient gas concentrations and personal particulate matter exposures: implications for studying the health effects of particles. Epidemiology. 2005; 16: 385–395.[CrossRef][Medline] [Order article via Infotrieve]
34. National Academy of Science, Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin, and Choline. Washington, DC: National Academy Press; 2000.
35. Institute of Medicine. Proteins and amino acids. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, DC: National Academy Press; 2005: 589–768.
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The online Data Supplement, which contains tables, can be found with this article at http://circ.ahajournals.org/cgi/content/full/CIRCULATIONAHA.107.726067/DC1.
Guest Editor for this article was Russell V. Luepker, MD, MS.
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Circulation 2008 117: 1769.
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