Letters to the Editor
Considering the effect of sleep disorders on the relation between obesity and cardiometabolic risk Dear Sir:
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We acknowledge the Associac xa˜o Fundo de Incentivo a` Pesquisa and the Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´gico (CNPq) of Brazil for financial support. ST and MLA are recipients of fellowships from the CNPq. The authors declared that they had no conflicts of interest.
Daniel Ninello Polesel Karen Tieme Nozoe Sergio Tufik Monica Levy Andersen Department of Psychobiology Universidade Federal de Sa˜o Paulo Sa˜o Paulo Brazil E-mail: [email protected] or [email protected]
REFERENCES 1. Abbasi F, Blasey C, Reaven GM. Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity? Am J Clin Nutr 2013;98:637–40. 2. Tufik S, Santos-Silva R, Taddei JA, Bittencourt LR. Obstructive sleep apnea syndrome in the Sao Paulo Epidemiologic Sleep Study. Sleep Med 2010;11:441–6. 3. Carneiro G, Fontes FH, Togeiro SM. Metabolic consequences of untreated obstructive sleep apnea syndrom. J Bras Pneumol 2010;36: 43–6. 4. Drager LF, Togeiro SM, Polotsky VY, Lorenzi-Filho G. Obstructive sleep apnea: a cardiometabolic risk in obesity and the metabolic syndrome. J Am Coll Cardiol 2013;62:569–76. 5. Vgontzas AN, Tan TL, Bixler EO, Martin LF, Shubert D, Kales A. Sleep apnea and sleep disruption in obese patients. Arch Intern Med 1994;154: 1705–11. 6. Chung F, Yegneswaran B, Liao P, Chung SA, Vairavanathan S, Islam S, Khajehdehi A, Shapiro CM. STOP questionnaire: a tool to screen patients for obstructive sleep apnea. Anesthesiology 2008;108: 812–21. 7. Liang Y, Yan Z, Song A, Cai C, Sun B, Jiang H, Qiu C. Metabolic syndrome and cardiovascular disease in elderly people in rural china: a population-based study. J Am Geriatr Soc 2013;61:1036–7. 8. Nevajda B, Havelka-Mestrovic´ A, Bilic´ M, Nevajda AP, Romic´ D, Vuletic´ V, Cukljek S, Sicaja M, Bocina Z. Prevalence of the metabolic syndrome in the old institutionalized people in Zagreb, Croatia. Coll Antropol 2013;37:203–6. 9. Shochat T, Loredo J, Ancoli-Israel S. Sleep disorders in the elderly. Curr Treat Options Neurol 2001;3:19–36. 10. Amato MC, Giordano C. Clinical indications and proper use of visceral adiposity index. Nutr Metab Cardiovasc Dis 2013;23:e31–2. doi: 10.3945/ajcn.113.072637.
Am J Clin Nutr 2013;98:1592–9. Printed in USA. Ó 2013 American Society for Nutrition
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In a recent issue of the Journal, Abbasi et al (1) presented an article entitled ‘‘Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity?’’, which showed an association between measures of obesity and cardiometabolic risk. This association was observed through the relation of both BMI and waist circumference with systolic blood pressure, fasting plasma glucose, triglycerides, and HDL cholesterol. First, we commend the authors for presenting important results regarding the association of easily obtained measures of weight status with cardiometabolic risk. However, we believe there are some additional considerations that should be mentioned. The authors did not indicate the possible effect caused by comorbidities or the use of medication to treat any previous conditions. Monitoring these factors is essential for elderly patients who frequently have chronic diseases, such as cardiovascular disease and dyslipidemia. Sleep disorders may also coexist in this sample, because there is a high incidence of these disorders in older and/or obese individuals (2). Studies on sleep have shown the close relation of sleep problems, such as obstructive sleep apnea syndrome (OSAS), to metabolic syndrome and dyslipidemia (3, 4). Furthermore, it was found that ;70% of patients with OSAS are obese (5). However, OSAS is commonly underdiagnosed, which may negatively affect the health of patients and predispose them to the development and exacerbation of metabolic syndrome. Thus, greater attention must be given to the diagnosis and treatment of OSAS. Moreover, verifying the presence of sleep disorders in the sample discussed by Abbasi et al may provide additional insights. This information could be obtained by collecting the patient’s medical history and performing a polysomnographic examination, which is considered a gold standard in the diagnosis of sleep disorders. However, other evaluation alternatives could be used to identify individuals at risk, such as the use of a classic questionnaire (eg, STOP-BANG), which allows for individuals at risk of obstructive sleep apnea to be identified (6). No significant differences were found between men and women in the study sample with regard to age. However, the authors should consider age as a predisposing risk factor for obesity because older individuals are more susceptible to developing age-related diseases with important clinical implications, such as obesity, metabolic syndrome, and sleep disorders (7–9). In addition, it would be interesting to evaluate the visceral adiposity index for these individuals, because this index includes other factors that complement health risk evaluation (10). Moreover, other biochemical analyses could enhance the diagnosis of metabolic syndrome, such as measurements of albumin, uric acid, and inflammation (C-reactive protein). Finally, we emphasize the importance of the study by Abbasi et al (1), which used anthropometric measurements to conduct a study of
associative factors relating obesity with metabolic impairment and thoroughly considered the consequences of global problems, such as obesity.
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Reply to DN Polesel et al Dear Sir:
AL was supported by NIH grant K23 DK088877. None of the authors had a potential conflict of interest.
Alice Liu Division of Endocrinology, Gerontology, and Metabolism Department of Medicine Stanford University School of Medicine Stanford, CA 94305-5103 Gerald M Reaven Fahim Abbasi Division of Cardiovascular Medicine Department of Medicine Stanford University School of Medicine Falk Cardiovascular Research Center 300 Pasteur Drive Stanford, CA 94305-5406 E-mail: [email protected]
REFERENCES 1. Abbasi F, Blasey C, Reaven GM. Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity? Am J Clin Nutr 2013;98:637–40. 2. Liu A, Kushida CA, Reaven GM. Risk for obstructive sleep apnea in obese, nondiabetic adults varies with insulin resistance status. Sleep Breath 2013;17:333–8. 3. Gangwisch JE, Malaspina D, Boden-Albala B, Heymsfield SB. Inadequate sleep as a risk factor for obesity: analyses of the NHANES I. Sleep 2005;28:1289–96. 4. Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, Nieto FJ. Association of sleep time with diabetes mellitus and impaired glucose tolerance. Arch Intern Med 2005;165:863–7. 5. Liu A, Kushida CA, Reaven GM. Habitual shortened sleep and insulin resistance: an independent relationship in obese individuals. Metabolism 2013;Jul 10 (Epub ahead of print; DOI:10.1016/j.metabol.2013.06.003). 6. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, Galluzzo A; AlkaMeSy Study Group. Visceral adiposity index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 2010;33:920–2. 7. Salazar MR, Carbajal HA, Espeche WG, Aizpurua M, Leiva Sisnieguez CE, March CE, Balbin E, Stavile RN, Reaven GM. Identifying cardiovascular disease risk and outcome: use of the plasma triglyceride/highdensity lipoprotein cholesterol concentration ratio versus metabolic syndrome criteria. J Intern Med 2013;273:595–601. 8. McLaughlin T, Reaven G, Abbasi F, Lamendola C, Saad M, Waters D, Simon J, Krauss RM. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol 2005;96:399–404. 9. Salazar MR, Carbajal HA, Espeche WG, Leiva Sisnieguez CE, Balbin E, Dulbecco CA, Aizpurua M, Marillet AG, Reaven GM. Relation among the plasma triglyceride/high-density lipoprotein cholesterol concentration ratio, insulin resistance, and associated cardio-metabolic risk factors in men and women. Am J Cardiol 2012;109:1749–53. 10. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003;139:802–9. doi: 10.3945/ajcn.113.072876.
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We thank Polesel et al for their comments on our study (1) and agree that the relation between obesity and cardiometabolic risk factors is modulated by comorbidities and/or by medications for treating chronic diseases. In this context, as rightly pointed out, sleep disorders are known to be associated with cardiometabolic abnormalities, and because sleep-disordered breathing is more common in overweight/obese individuals, it will certainly influence the association of obesity indexes and cardiometabolic risk factors. Unfortunately, when our study was performed, we did not collect information on diagnoses of sleep disorders, perform polysomnography, or determine by questionnaires whether or not the individuals were at risk of having obstructive sleep apnea (OSA). However, since then, our research group has become interested in these issues; and along with Dr Alice Liu, we are actively investigating associations between OSA, obesity, and cardiometabolic risk factors, with an emphasis on how differences in insulin-mediated glucose disposal influence these relations in nondiabetic individuals. OSA is well established as a comorbidity in obese individuals, yet the breadth of the obesity epidemic and cost of polysomnography are barriers to universal testing. In an attempt to address this issue, we recently published data showing that insulin-resistant, nondiabetic individuals without known OSA were more likely to be at high risk of OSA, as determined by screening questionnaires, than insulinsensitive individuals of similar adiposity (2). We proposed that administering questionnaires to the insulin-resistant subset of obese individuals would be a clinically useful and a cost-effective way to identify those at the greatest risk of having OSA who will benefit the most from referral for polysomnography. Short sleep duration has also been reported to be associated with obesity and dysglycemia (3, 4). We extended these findings by showing in an obese group of subjects with a high prevalence of impaired fasting glucose and glucose intolerance that insulin resistance was independently associated with habitual shortened sleep, defined as fewer than 7 h of sleep per night (5). Thus, our findings are consistent with the notion that disordered sleep may play an important role in modulating cardiometabolic diseases. That said, it is doubtful that accounting for OSA diagnoses in our present study population would have altered our primary results—namely, that BMI and waist circumference were similar in their associations with markers of increased cardiometabolic risk. In both studies referenced above (2, 5), BMI and waist circumference did not differ between insulin-resistant and insulinsensitive groups, suggesting that the differences seen in OSA risk and sleep duration were attributed to insulin resistance rather than obesity per se. Nonetheless, further studies are necessary to characterize these relations. Polesel et al’s comments with regard to age and the visceral adiposity index (VAI) are also of interest. The median (IQR) age of our study participants was 51 (44–57) y, and 85% of the participants were younger than 60 y, indicating that our sample did not include a large proportion of older individuals who are more prone to developing age-related diseases. The VAI is based on measurements of waist circumference, BMI, and triglyceride and HDL-cholesterol concentrations (6). We have been interested in the utility of the plasma concentration ratio of triglyceride:HDL cholesterol to identify apparently healthy individuals at increased risk of cardiovascular disease (7–10), and the comments of Polesel et al have stimulated us to the point that we are initiating efforts to compare the relative
abilities of the VAI and the triglyceride:HDL-cholesterol ratio to identify individuals at increased cardiometabolic risk.
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DHA supplementation during pregnancy and DNA methylation in cord blood leukocytes Dear Sir:
The author did not declare any conflicts of interest.
Graham C Burdge Academic Unit of Human Development and Health Faculty of Medicine University of Southampton Southampton General Hospital (MP 887) Tremona Road Southampton, SO16 6YD United Kingdom E-mail: [email protected]
REFERENCES 1. Falvo JV, Jasenosky LD, Kruidenier L, Goldfeld AE. Epigenetic control of cytokine gene expression: regulation of the TNF/LT locus and T helper cell differentiation. Adv Immunol 2013;118:37–128. 2. Prescott SL, Clifton V. Asthma and pregnancy: emerging evidence of epigenetic interactions in utero. Curr Opin Allergy Clin Immunol 2009; 9:417–26. 3. Ceccarelli V, Racanicchi S, Martelli MP, Nocentini G, Fettucciari K, Riccardi C, Marconi P, Di Nardo P, Grignani F, Binaglia L, et al. Eicosapentaenoic acid demethylates a single CpG that mediates expression of tumor suppressor CCAAT/enhancer-binding protein delta in U937 leukemia cells. J Biol Chem 2011;286:27092–102. 4. Sadli N, Ackland ML, De Mel D, Sinclair AJ, Suphioglu C. Effects of zinc and DHA on the epigenetic regulation of human neuronal cells. Cell Physiol Biochem 2012;29:87–98. 5. Hoile SP, Irvine NA, Kelsall CJ, Sibbons C, Feunteun A, Collister A, Torrens C, Calder PC, Hanson MA, Lillycrop KA, et al. Maternal fat intake in rats alters 20:4n-6 and 22:6n-3 status and the epigenetic regulation of Fads2 in offspring liver. J Nutr Biochem 2013;24:1213–20. 6. Noakes PS, Vlachava M, Kremmyda LS, Diaper ND, Miles EA, Erlewyn-Lajeunesse M, Williams AP, Godfrey KM, Calder PC. Increased intake of oily fish in pregnancy: effects on neonatal immune
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Modulation of the level of methylation of CpG nucleotide pairs in the 5#-regulatory regions of genes is an important mechanism in the differentiation of T cells into T helper (Th) 1 or Th2 phenotypes (1). Altered epigenetic regulation of T cell differentiation during fetal development has been implicated as an important mechanism in the etiology of allergic diseases in childhood (2). Therefore, nutritional interventions during pregnancy that may prevent or reverse impaired epigenetic regulation of genes that influence T cell phenotype may be of considerable health benefit. Relatively few studies have reported the effect of supplementation with n–3 PUFAs present in fish oil, specifically EPA and DHA, on the epigenetic regulation of genes. The addition of EPA to U937 leukemia cells induced demethylation of specific CpG loci in the promoter of the CCAAT/enhancer-binding protein d (3), whereas treatment of M17 neuroblastoma cells with DHA increased global H3K9 acetylation and decreased levels of transcriptionally repressive histone marks (4). Furthermore, feeding adult rats fish oil induced a reversible increase in the methylation level of specific CpG loci in the Fads2 promoter (5). Increased intake of oily fish during pregnancy has been shown to alter markers of immune function in infants at 6 mo of age (6). Therefore, it is possible that increased intakes of EPA and DHA during pregnancy may induce persistent changes in immune function in the offspring via changes in the epigenetic regulation of T cell phenotypes. In the August 2013 issue of the Journal, Lee et al (7) reported the findings of a study of the effect of supplementation of the diet of pregnant women with 200 mg/d DHA from midgestation until delivery on the methylation status of CpG loci within the promoter regions of genes involved in immune function in umbilical cord blood mononuclear cells. They showed a nonsignificant trend toward an effect of DHA supplementation on the methylation status of the interferon-c and IL-13 promoters. They also found significantly higher methylation of long interspersed element (LINE) 1 sequences in women who took the DHA supplement and who smoked, which became nonsignificant when the data were adjusted for sex, gestational duration, BMI, and batch of laboratory analyses. Unfortunately, there are elements in the design of the study that suggest that the findings should be interpreted with caution. Different cell types have different patterns of DNA methylation. Thus, in mixed-cell preparations such as cord blood mononuclear cells, variation in the relative numbers of different leukocyte populations may confound the interpretation of differences in DNA methylation (8). It is usual to account for variation in leukocyte numbers in the analysis of DNA methylation in blood, particularly during development when leukocyte numbers change dynamically. However, Lee et al (7) did not test for any potential association between variation in the relative size of leukocyte populations and variation in DNA methylation. Because DNA methylation is an important process in immune function, the incidence of infection should have been recorded and incorporated into the data analysis. There is no statement of statistical power for any of the outcome variables. The addition of 61 selected samples ‘‘to strengthen the association between smoking and DNA methylation’’ (7) to 200 randomly selected samples may have introduced bias into the study. Furthermore, the proportion of atopic mothers was ‘‘reasonably balanced’’ (7), although the
numbers were not disclosed, rather than using a case-control design. The difference in the level of methylation of LINE-1 sequences between women who took the DHA supplement and those who did not was ;1%. Because previous reports have shown the precision of the analysis of LINE-1 sequences by pyrosequencing to vary between 1% and 4% (9), it is possible that variation in methylation of 1% may represent analytic error. This view is supported by the loss of statistical significance where the data were adjusted for potential confounders including sample batch. Furthermore, the detection limit of analysis of DNA methylation by pyrosequencing is ;5% (10). Thus, values ,5% should be treated with caution, and the level of precision reported for GATA3 (mean methylation: 0.04– 0.28%) is unlikely to be robust. The apparently lower methylation of LINE-1 sequences in women in the control group who smoked appears to be a result of a single outlying sample. To date, there have not been any reports that show that the level of methylation of LINE-1 sequences is an important determinant of T cell differentiation and phenotype. Unfortunately, the study by Lee et al did not include experiments to show whether variations in LINE-1 methylation alter T cell function (7). Therefore, because of the possible confounding factors discussed above, the lack of experiments to show a causal association between variation in LINE-1 methylation and T cell differentiation or function, and the absence of statistically robust results, the conclusion stated by the authors that ‘‘Our results indicate that maternal supplementation with n–3 PUFA during pregnancy may modulate global methylation levels and the Th1/Th2 balance in infants’’ (7) appears to be an overinterpretation of the findings.
LETTERS TO THE EDITOR
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8.
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responses and on clinical outcomes in infants at 6 mo. Am J Clin Nutr 2012;95:395–404. Lee HS, Barraza-Villarreal A, Hernandez-Vargas H, Sly PD, Biessy C, Ramakrishnan U, Romieu I, Herceg Z. Modulation of DNA methylation states and infant immune system by dietary supplementation with omega-3 PUFA during pregnancy in an intervention study. Am J Clin Nutr 2013;98:480–7. Adalsteinsson BT, Gudnason H, Aspelund T, Harris TB, Launer LJ, Eiriksdottir G, Smith AV, Gudnason V. Heterogeneity in white blood cells has potential to confound DNA methylation measurements. PLoS ONE 2012;7:e46705. Irahara N, Nosho K, Baba Y, Shima K, Lindeman NI, Hazra A, Schernhammer ES, Hunter DJ, Fuchs CS, Ogino S. Precision of pyrosequencing assay to measure LINE-1 methylation in colon cancer, normal colonic mucosa, and peripheral blood cells. J Mol Diagn 2010;12:177–83. Tsiatis AC, Norris-Kirby A, Rich RG, Hafez MJ, Gocke CD, Eshleman JR, Murphy KM. Comparison of Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS mutations: diagnostic and clinical implications. J Mol Diagn 2010;12:425–32. doi: 10.3945/ajcn.113.072074.
Dear Sir: We appreciate Burdge’s thoughtful comments, and we thank you for the opportunity to reply to his concerns. We agree with Burdge’s suggestion that the variability of the epigenome among different cells in tissues can confound the findings. Indeed, the intrinsic variability of the DNA methylome among different cell types in umbilical cord blood mononuclear cells (CBMCs) may confound the results because the methylation levels obtained represent the average methylation levels in a given cell population analyzed (1). To rule out potential confounding factors that may be derived from heterogeneous cell populations, it would be necessary to collect a larger volume of cord blood at birth and perform analysis of DNA methylation in fresh fluorescence-activated cell sorting (FACS) sorted cell subpopulations. In our study, the original design did not allow us to collect a larger volume of fresh cord blood and perform analysis of FACS-sorted CBMC subpopulations. Therefore, future studies on CBMCs should exploit a recently developed set of analytic tools (2) for inferring changes in the distribution of different white blood cell subpopulations by using DNA methylation patterns (such as the regression calibration algorithm), an approach that circumvents the need for fresh blood cells and extensive flow cytometry sorting (3, 4). Although we were not able (similarly to the vast majority of other studies) to resolve the problem of mixed populations of cells (which could only be addressed by a single-cell methylomics approach) and examine whether x-3 PUFAs may alter epigenetic states indirectly, we were careful in our statements that our study shows that prenatal x-3 PUFA supplementation can modulate immune response in infants, which correlates with, and not necessarily causes, changes in epigenetic states. Importantly, we have analyzed mRNA levels as a direct measure of gene transcription and the functional impact of DNA methylation changes on gene activity. We found that mRNA levels of IFNc were markedly higher (although marginally significant) in the x-3 PUFA group than in controls, consistent with many previous studies showing an inverse correlation between the expression and DNA methylation levels (H-S Lee and Z Herceg, unpublished data, 2013). Therefore, our results support the notion that x-3 PUFA supple-
mentation could modulate IFNc expression through promoter methylation changes, which may ultimately affect the inflammatory response. These results also argue that gene expression changes indeed accompanied the changes in DNA methylation, which is unlikely to happen if the observed changes represented analytic error in estimating DNA methylation. Burdge also draws attention to potential infections that may cause spurious effects on the immune system and DNA methylation. In this study we analyzed methylation levels in DNA extracted from CBMCs. Although the mothers were not checked for the presence of infection at delivery, all mothers and offspring were healthy at the time of birth without any clinical signs of infection. It is important to mention that all pregnancies were low risk (the inclusion criterion for the study was pregnancy without risk) and that the mean birth weight of the offspring was in the normal range, attesting to the lack of major fetal suffering. Although we agree with the remark that the presence of infections may, in principle, affect the immune system and alter blood cell composition, it is unlikely that such an event would affect specifically one group of subjects and that our results are an indirect consequence of changes in the immune system of newborns. We agree that the statistical power of our study is limited by the sample size, although we included additional samples (n ¼ 261). This is particularly true when conducting stratified analyses. Therefore, our analyses have focused on only the major strata of maternal characteristics. Despite these limitations, we could detect significant changes in DNA methylation and hence believe that our study is sufficiently powered to detect moderate to large changes in DNA methylation, although we might have missed minor changes. We agree that further studies with a larger sample size are needed to confirm our results and evaluate methylation changes in a larger array of genes. We respectfully disagree with Burdge’s suggestion that the addition of 61 selected samples to 200 randomly selected samples could have introduced bias in the analysis. For clarification, we first randomly selected 100 CBMC samples from supplemented mothers and 100 CBMC samples from controls, and our analysis already showed an association between smoking and x-3 PUFAs and DNA methylation. However, because the sample size in the maternal smoking group was rather small, we subsequently analyzed an additional 61 samples (to increase sample size, as requested by the reviewers). Importantly, after we significantly increased the sample size in the maternal smoking group, the overall trend with lower methylation levels associated with smoking remained unchanged. Therefore, our findings of the association between smoking and x-3 PUFAs and DNA methylation are unlikely to be influenced by the analysis of additional samples. We also disagree with Burdge’s assertion that the precision of the analysis of long interspersed element (LINE) 1 sequences by pyrosequencing may not be sufficiently robust to reliably detect small differences between different groups. To avoid potential biases, in our study for each pyrosequencing assay the samples were randomized and analyzed blindly with respect to supplementation and smoking status. In addition, all assays were performed at the same time and on the same aliquot of bisulfite-converted DNAs with the use of the same batch of pyrosequencing reagents, thus avoiding a potential batch effect. The quality control for DNA methylation analysis further included a regular assessment of pyrosequencing quality (including peak heights, deviation from the reference sequencing pattern, and unexpected peak heights). Furthermore, although in our analysis we did not routinely include methylation standards, it is to be noted that for a given gene we obtained relatively homogeneous DNA methylation levels across
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Reply to GC Burdge
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LETTERS TO THE EDITOR
None of the authors declared a conflict of interest.
Ho-Sun Lee Hector Hernandez-Vargas Carine Biessy Isabelle Romieu Zdenko Herceg International Agency for Research on Cancer 150 Cours Albert Thomas 69372 Lyon CEDEX 08 France E-mail: [email protected] or [email protected] Albino Barraza-Villarreal Instituto Nacional de Salud Pu´blica Centro de Investigaciones en Salud Poblacional Cuernavaca, Morelos Mexico
Peter D Sly Queensland Children’s Medical Research Institute Royal Children’s Hospital Herston, Queensland Australia Usha Ramakrishnan Nutrition and Health Sciences and the Hubert Department of Global Health Rollins School of Public Health Emory University Atlanta, GA
REFERENCES 1. Herceg Z, Hernandez-Vargas H. New concepts of old epigenetic phenomena and their implications for selecting specific cell populations for epigenomic research. Epigenomics 2011;3:383–6. 2. Bock C. Analysing and interpreting DNA methylation data. Nat Rev Genet 2012;13:705–19. 3. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 2012;13:86. 4. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, Reinius L, Acevedo N, Taub M, Ronninger M, et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol 2013;31:142–7. 5. Lee HS, Barraza-Villarreal A, Hernandez-Vargas H, Sly PD, Biessy C, Ramakrishnan U, Romieu I, Herceg Z. Modulation of DNA methylation states and infant immune system by dietary supplementation with omega-3 PUFA during pregnancy in an intervention study. Am J Clin Nutr 2013; 98:480–7. doi: 10.3945/ajcn.113.072272.
Fetal vitamin B-12: a modulator of folate-dependent homocysteine remethylation? Dear Sir: We recently read with interest an article by McNulty et al (1) reporting outcomes of a double-blinded randomized controlled trial of folic acid (FA) supplementation (400 lg/d), taken from the start of the second trimester over 14–36 gestational weeks (GWs), in women who also used FA supplements in the first trimester (400 lg/d) and whose dietary intakes compared favorably with current UK reference values, with no difference in total dietary folate intake between groups. In the trial, FA intervention increased maternal folate status, preventing the gestational decline observed at 36 GWs in the placebo group, and this was associated with a significant increase in cord blood folate concentration at birth, which is entirely consistent with the concept that fetal folate concentration reflects trends in maternal folate concentration, underscored by active transport of folate across the placenta (2). Perhaps not unexpectedly, FA intervention had no significant impact on infant size at birth, according well with studies that have also shown a relative lack of dependency with maternal folate status (3) or improvement in birth weight in randomized controlled trials of FA supplementation (4). What is intriguing about the observations in this article is that, whereas a change in maternal folate status after the intervention of FA supplementation prevented the gestational increase in maternal homocysteine concentration of ;1 lmol/L at 36 GWs observed in
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different sample categories, despite the fact that average methylation levels were strikingly different among the assays, ranging from ;0% for GATA3 and STAT3 to as high as 70% and 100% for LINE1 and FOXP3, respectively (our Table 3) (5). These observations strongly rule out the existence of incomplete bisulfite converted DNA, which would otherwise result in increased methylation levels in all genomic regions with no genes exhibiting methylation levels as low as 0% methylation. We are thus confident that our methylation assays were quantitatively sensitive and that the impact of different biases could be ruled out. With regard to the impact of the outliers, as one can see from our Figure 1A, even after including additional 61 samples in the analysis the scatter for the nonsmokers is markedly greater than for smokers. Whereas the reason for this observation is unknown (one can speculate that it is the result of smoking status), a single outlying sample cannot result in significantly lower methylation of LINE-1 sequences of the entire group, especially considering the number of samples in each group. Furthermore, the numbers of atopic mothers in the experimental groups were provided in our Table 1 (n ¼ 72 in the control group compared with n ¼ 70 in the x-3 PUFA group) (5), and thus the proportion of atopic mothers was indeed balanced. We also confirmed that interaction between maternal smoking and x-3 PUFA on LINE-1 methylation was significant when adjusted for sex, gestational duration, BMI, and batch of laboratory analyses. This result supports x-3 PUFA involvement in LINE-1 methylation changes depending on smoking status. We appreciated Burdge’s point with regard to the need to take our study a step further in mechanistic terms. Indeed, one limitation of our study is the lack of experiments to show a causal link between changes in LINE-1 methylation and T cell differentiation/ function. Because we had a limited amount of frozen CBMCs, there was a technical challenge in performing functional tests and thus we were not able to carry out mechanistic experiments with the use of CBMC samples. Because x-3 PUFA-supplemented and control groups were well balanced for all main covariates (including maternal age, height, weight, BMI, educational level, socioeconomic level, maternal smoking during pregnancy, paternal smoking status, sex, birth weight, and gestational duration), these are unlikely to be confounding factors. Therefore, the main findings of our study are unlikely to be influenced by confounding factors and technical biases.
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newborn infants of healthy, nonvegetarian mothers, impaired vitamin B-12 function appears to be related to their low vitamin B-12 tissue reserves (8). Against this background, the reduction in maternal vitamin B12 concentrations by 36 GWs mentioned in the FA supplementation trial has particular relevance, because it is consistent with the notion that fetal vitamin B-12 requirements may well have exceeded the capacity for placental vitamin B-12 transport to meet fetal demand. This commentary supports the view that vitamin B-12 transported by the placenta has relative importance, particularly with regard to the fetal remethylation of homocysteine to methionine, as well as the influence on the prevalence of impaired vitamin B-12 status in the neonatal period. This should motivate vitamin B-12 intervention studies in pregnancy and in newborn infants. None of the authors declared a conflict of interest.
Stephen W D’Souza Maternal and Fetal Research Centre Institute of Human Development Faculty of Medical and Human Sciences University of Manchester Manchester M13 9WL United Kingdom E-mail: stephen.w.d’[email protected] Stuart J Moat Department of Medical Biochemistry and Immunology University Hospital of Wales and Cardiff School of Medicine Cardiff University Heath Park Cardiff CF14 4XW United Kingdom Jocelyn D Glazier Maternal and Fetal Health Research Centre Institute of Human Development Faculty of Medical and Human Sciences University of Manchester Manchester M13 9WL United Kingdom
REFERENCES 1. McNulty B, McNulty H, Marshall B, Ward M, Molloy AM, Scott JM, Dorman J, Pentieva K. Impact of continuing folic acid after the first trimester of pregnancy: findings of a randomized trial of folic acid supplementation in the second and third trimesters. Am J Clin Nutr 2013;98:92–8. 2. Solanky N, Requena Jimenez A, D’Souza SW, Sibley CP, Glazier JD. Expression of folate transporters in human placenta and implications for homocysteine metabolism. Placenta 2010;31:134–43. 3. Hay G, Clausen T, Whitelaw A, Trygg K, Johnston C, Henriksen T, Refsum H. Maternal folate and cobalamin status predicts vitamin status in newborns and 6-month-old infants. J Nutr 2010;140:557–64. 4. Scholl TO, Johnson WG. Folic acid: influence on the outcome of pregnancy. Am J Clin Nutr 2000;71(suppl):1295S–303S. 5. Tsitsiou E, Sibley CP, D’Souza SW, Catanescu O, Jacobsen DW, Glazier JD. Homocysteine transported by systems L, A and y1L across the microvillous plasma membrane of human placenta. J Physiol 2009; 587:4001–13.
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unsupplemented mothers (placebo group), this treatment had no significant impact on fetal homocysteine concentration, with similar homocysteine concentrations in the cord blood of both study groups (the authors’ Table 3). We would comment that maternal homocysteine concentrations reported in the study groups between 14 and 36 GWs could, in part, also be modulated by placental uptake and transport of homocysteine to the fetus (5), a concept not alluded to in the article. Previous studies by Molloy et al (6) have shown that maternal homocysteine concentration had the strongest effect on fetal homocysteine concentration in women with normal pregnancies who routinely took FA supplements, evidenced also by the positive correlation between maternal and cord blood homocysteine concentrations (6). It should be further noted that the authors comment that maternal and fetal vitamin B-12 concentrations had additional effects (6). It is presently unclear whether homocysteine entering the fetal circulation is partly derived from the maternal circulation after transplacental passage (5) and/or from placental methionine metabolism (2). However, homocysteine concentrations in umbilical cord venous plasma are ;1 lmol/L higher than in cord arterial plasma, with these variables being highly correlated to each other (7). Such findings suggest that homocysteine delivered by the placenta into cord venous blood is extracted by the fetus, resulting in fetal uptake of homocysteine, akin to other amino acids (2, 5). This leads to an interesting question: why does the fetal response to increased maternal plasma homocysteine concentration exhibit divergence between these studies? This is an important aspect to understand mechanistically if the capacity of folate to lower maternal homocysteine concentration is conceived to be of positive benefit with respect to pregnancy outcomes, including those of the neonate, as commented on by the authors. We speculate that one possibility underlying this discordance relates to the impact on folate-dependent homocysteine metabolism, which had become limited by vitamin B-12. We suggest this because we note that some mothers at 14 GWs had remarkably low serum vitamin B-12 concentrations (,150 pmol/L; the authors’ Table 1) and that advancing gestational age (14–36 GWs) was associated with a significant decline in maternal vitamin B-12 concentration, which could represent a reduction in maternal reserves during pregnancy (8), and a subclinical deficit limiting the amount transported by the placenta (9) to the fetal circulation. Hence, women with low vitamin B-12 status may not be able to provide the optimum amount of this micronutrient required by the fetus (10), with implications for newborn infants including low reserves of vitamin B-12 and possibly a risk of vitamin B-12 deficiency (8). The maternal data concerning vitamin B-12 concentration at 36 GWs were not provided, and although cord vitamin B-12 concentrations were not different between study groups at delivery, the reduction seen in maternal homocysteine concentration with FA treatment was not reflected in the fetal compartment, suggesting limitation by another modulatory factor. The emergence of vitamin B-12 as an additional factor of importance influencing folate-dependent homocysteine metabolism toward the end of gestation would be in agreement with earlier studies (6). An efficient use of vitamin B-12 both by the placenta and the fetus has been implicated (2, 8), particularly with regard to directing vitamin B-12 to favor methionine synthase activity, providing methionine and tetrahydrofolate to support cell growth. The trial was not extended to the neonatal period to examine the potential impact of maternal FA supplementation intervention during pregnancy on newborn infants. Other studies have reported that over the first few weeks of birth an increase in homocysteine concentration in newborn infants is strongly associated with a reduction in vitamin B-12 concentration, consistent with impaired vitamin B-12 function and not correlated with serum or whole-blood folate (8). Indeed, in
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6. Molloy AM, Mills JL, McPartlin J, Kirke PN, Scott JM, Daly S. Maternal and fetal plasma homocysteine concentrations at birth: the influence of folate, vitamin B12 and the 5,10-methylenetetrahydrofolate reductase 677C/T variant. Am J Obstet Gynecol 2002;186:499–503. 7. Malinow MR, Rajkovic A, Duell PB, Hess DL, Upson BM. The relationship between maternal and neonatal umbilical cord plasma homocyst(e)ine suggests a potential role for maternal homocyst(e)ine in fetal metabolism. Am J Obstet Gynecol 1998;178:228–33. 8. Bjørke Monsen AL, Ueland PM, Vollset SE, Guttormsen AB, Markestad T, Solheim E, Refsum H. Determinants of cobalamin status in newborns. Pediatrics 2001;108:624–30. 9. Schneider H, Miller RK. Receptor-mediated uptake and transport of macromolecules in the human placenta. J Dev Biol 2010;54:367–75. 10. Relton CL, Pearce MS, Parker L. The influence of erythrocyte folate and serum vitamin B12 status on birthweight. Br J Nutr 2005;93:593–9. doi: 10.3945/ajcn.113.073262.
Reply to SW D’Souza et al
D’Souza et al share some interesting thoughts regarding our article on the effects of folic acid supplementation in the second and third trimesters of pregnancy (1). They point out, quite rightly, that whereas folic acid supplementation influenced maternal homocysteine by preventing the increase in homocysteine usually observed in the third trimester (2), we did not observe a difference in cord blood homocysteine concentrations between the placebo and folic acid treatment groups. D’Souza et al suggest that low vitamin B-12 status might explain the anomaly. Serum total vitamin B-12 is known to decrease by ;30% over the course of pregnancy (3), and in this study between gestational weeks 14 and 36 we observed (although did not report) a decline in maternal vitamin B-12 concentrations of 22% (from 211 6 82 pmol/L to 165 6 59 pmol/L; P ¼ 0.001) in the placebo group and 25% (from 235 6 94 pmol/L to 176 6 75 pmol/L; P ¼ 0.001) in the folic acid–supplemented group, with no significant treatment effect (P ¼ 0.59). We interpret this as indicating that vitamin B-12 affected the relation between maternal and cord blood homocysteine in both groups, although this was not an outcome of primary interest to the study. Although it was not included in the article, we used multiple regression analysis to examine each of the measured variables in our study as determinants of the fetal (cord blood) homocysteine. Neither folate nor vitamin B-12 were significant predictors of cord blood homocysteine in either the placebo or the folic acid treatment group (P ¼ 0.98 and 0.09 for cord blood folate and vitamin B-12, respectively, in the placebo group; and P ¼ 0.26 and 0.45, respectively, in the treatment group). The only significant predictor of fetal homocysteine was the maternal homocysteine concentration, but the overall relation in the multiple regression analysis was much weaker in the folic acid treatment group (adjusted R2 ¼ 13.7% compared with 54.7% in the placebo group). D’Souza et al suggest that the cord blood homocysteine concentration may be limited by another modulatory factor, and we agree. As in our previous observational study (4), in the current randomized controlled trial we found that maternal homocysteine was significantly associated with fetal homocysteine, but this relation was relatively weaker in the folic acid treatment group. However, the data do not indicate that the limiting factor in our study is vitamin B-12. Although we would not deny the importance of vitamin B-12 in pregnancy and in early neonatal life, there are many gaps in our understanding of vitamin B-12 status at these critical times. Several
None of the authors had a conflict of interest.
Anne M Molloy Department of Clinical Medicine Trinity College Dublin Dublin Ireland Kristina Pentieva Breige McNulty Helene McNulty Northern Ireland Centre for Food and Health (NICHE) School of Biomedical Sciences University of Ulster Cromore Road Coleraine BT52 1SA Northern Ireland E-mail: [email protected]
REFERENCES 1. McNulty B, McNulty H, Marshall B, Ward M, Molloy AM, Scott JM, Dornan J, Pentieva K. Impact of continuing folic acid after the first trimester of pregnancy: findings of a randomized trial of folic acid supplementation in the second and third trimesters. Am J Clin Nutr 2013; 98:92–8. 2. Holmes VA, Wallace JM, Alexander HD, Gilmore WS, Bradbury I, Ward M, Scott JM, McFaul P, McNulty H. Homocysteine is lower in the third trimester of pregnancy in women with enhanced folate status from continued folic acid supplementation. Clin Chem 2005;51: 629–34. 3. Murphy MM, Molloy AM, Ueland PM, Fernandez-Ballart JD, Schneede J, Arija V, Scott JM. Longitudinal study of the effect of pregnancy on maternal and fetal cobalamin status in healthy women and their offspring. J Nutr 2007;137:1863–7. 4. Molloy AM, Mills JL, McPartlin J, Kirke PN, Scott JM, Daly S. Maternal and fetal plasma homocysteine concentrations at birth: the influence
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Dear Sir:
studies have shown that, whereas the total serum vitamin B-12 decreases dramatically during pregnancy, the fraction of vitamin B-12 that is available for uptake into tissue (ie, holotranscobalamin) does not appear to decline (3, 5), indicating that the interpretation of biomarkers of vitamin B-12 during pregnancy is complex, a point made by others in earlier studies (6, 7). This appears to be the case in our study, in which low maternal concentrations of vitamin B-12 at gestational week 36 do not predict functional vitamin B-12 deficiency in the fetus at birth, at least where the functional biomarker homocysteine is concerned. We would also comment that although D’Souza et al consider the importance of transplacental transfer of homocysteine and placental methionine metabolism, they have overlooked other pregnancy-related factors that affect maternal and fetal homocysteine (8). One relevant micronutrient not considered by D’Souza et al, and not measured in our study, is choline, for which there is a very high fetal requirement. We previously found maternal homocysteine concentration to be strongly associated with cord blood choline, consistent with a high maternal de novo synthesis of choline through hepatic phosphatidylethanolamine methyltransferase (9). Clearly, all of these factors need to be considered, and although the call for intervention studies with vitamin B-12 in pregnancy and newborns is well made, we need first to know how to interpret the relevant biomarkers of vitamin B-12 status in pregnancy.
LETTERS TO THE EDITOR of folate, vitamin B12, and the 5,10-methylenetetrahydrofolate reductase 677C/T variant. Am J Obstet Gynecol 2002;186:499–503. 5. Morkbak AL, Hvas AM, Milman N, Nexo E. Holotranscobalamin remains unchanged during pregnancy: longitudinal changes of cobalamins and their binding proteins during pregnancy and postpartum. Haematologica 2007;92:1711–2. 6. Pardo J, Peled Y, Bar J, Hod M, Sela BA, Rafael ZB, Orvieto R. Evaluation of low serum vitamin B(12) in the non-anaemic pregnant patient. Hum Reprod 2000;15:224–6. 7. Metz J, McGrath K, Bennett M, Hyland K, Bottiglieri T. Biochemical indices of vitamin B12 nutrition in pregnant patients with subnormal serum vitamin B12 levels. Am J Hematol 1995;48:251–5.
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8. Murphy MM, Scott JM, Arija V, Molloy AM, Fernandez-Ballart JD. Maternal homocysteine before conception and throughout pregnancy predicts fetal homocysteine and birth weight. Clin Chem 2004;50:1406–12. 9. Molloy AM, Mills JL, Cox C, Daly SF, Conley M, Brody LC, Kirke PN, Scott JM, Ueland PM. Choline and homocysteine interrelations in umbilical cord and maternal plasma at delivery. Am J Clin Nutr 2005;82: 836–42.
doi: 10.3945/ajcn.113.073593.
Tate DF, Turner-McGrievy G, Lyons E, Stevens J, Erickson K, Polzien K, Diamond M, Wang X, Popkin B. Replacing caloric beverages with water or diet beverages for weight loss in adults: main results of the Choose Healthy Options Consciously Everyday (CHOICE) randomized clinical trial. Am J Clin Nutr 2012;95:555–63. In the print version of the article, the second sentence of the Results section of the abstract contains a copyediting error. Negative signs should be included in the DB and Water percent results, so that the sentence reads as follows: ‘‘Mean (6SEM) weight losses at 6 mo were 22.5 6 0.45% in the DB group, 22.03 6 0.40% in the Water group, and 21.76 6 0.35% in the AC group; there were no significant differences between groups.’’ The online version of this article was corrected at final publication. doi: 10.3945/ajcn.113.075432.
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Erratum
Considering the effect of sleep disorders on the relation between obesity and cardiometabolic risk Dear Sir:
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We acknowledge the Associac xa˜o Fundo de Incentivo a` Pesquisa and the Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´gico (CNPq) of Brazil for financial support. ST and MLA are recipients of fellowships from the CNPq. The authors declared that they had no conflicts of interest.
Daniel Ninello Polesel Karen Tieme Nozoe Sergio Tufik Monica Levy Andersen Department of Psychobiology Universidade Federal de Sa˜o Paulo Sa˜o Paulo Brazil E-mail: [email protected] or [email protected]
REFERENCES 1. Abbasi F, Blasey C, Reaven GM. Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity? Am J Clin Nutr 2013;98:637–40. 2. Tufik S, Santos-Silva R, Taddei JA, Bittencourt LR. Obstructive sleep apnea syndrome in the Sao Paulo Epidemiologic Sleep Study. Sleep Med 2010;11:441–6. 3. Carneiro G, Fontes FH, Togeiro SM. Metabolic consequences of untreated obstructive sleep apnea syndrom. J Bras Pneumol 2010;36: 43–6. 4. Drager LF, Togeiro SM, Polotsky VY, Lorenzi-Filho G. Obstructive sleep apnea: a cardiometabolic risk in obesity and the metabolic syndrome. J Am Coll Cardiol 2013;62:569–76. 5. Vgontzas AN, Tan TL, Bixler EO, Martin LF, Shubert D, Kales A. Sleep apnea and sleep disruption in obese patients. Arch Intern Med 1994;154: 1705–11. 6. Chung F, Yegneswaran B, Liao P, Chung SA, Vairavanathan S, Islam S, Khajehdehi A, Shapiro CM. STOP questionnaire: a tool to screen patients for obstructive sleep apnea. Anesthesiology 2008;108: 812–21. 7. Liang Y, Yan Z, Song A, Cai C, Sun B, Jiang H, Qiu C. Metabolic syndrome and cardiovascular disease in elderly people in rural china: a population-based study. J Am Geriatr Soc 2013;61:1036–7. 8. Nevajda B, Havelka-Mestrovic´ A, Bilic´ M, Nevajda AP, Romic´ D, Vuletic´ V, Cukljek S, Sicaja M, Bocina Z. Prevalence of the metabolic syndrome in the old institutionalized people in Zagreb, Croatia. Coll Antropol 2013;37:203–6. 9. Shochat T, Loredo J, Ancoli-Israel S. Sleep disorders in the elderly. Curr Treat Options Neurol 2001;3:19–36. 10. Amato MC, Giordano C. Clinical indications and proper use of visceral adiposity index. Nutr Metab Cardiovasc Dis 2013;23:e31–2. doi: 10.3945/ajcn.113.072637.
Am J Clin Nutr 2013;98:1592–9. Printed in USA. Ó 2013 American Society for Nutrition
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In a recent issue of the Journal, Abbasi et al (1) presented an article entitled ‘‘Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity?’’, which showed an association between measures of obesity and cardiometabolic risk. This association was observed through the relation of both BMI and waist circumference with systolic blood pressure, fasting plasma glucose, triglycerides, and HDL cholesterol. First, we commend the authors for presenting important results regarding the association of easily obtained measures of weight status with cardiometabolic risk. However, we believe there are some additional considerations that should be mentioned. The authors did not indicate the possible effect caused by comorbidities or the use of medication to treat any previous conditions. Monitoring these factors is essential for elderly patients who frequently have chronic diseases, such as cardiovascular disease and dyslipidemia. Sleep disorders may also coexist in this sample, because there is a high incidence of these disorders in older and/or obese individuals (2). Studies on sleep have shown the close relation of sleep problems, such as obstructive sleep apnea syndrome (OSAS), to metabolic syndrome and dyslipidemia (3, 4). Furthermore, it was found that ;70% of patients with OSAS are obese (5). However, OSAS is commonly underdiagnosed, which may negatively affect the health of patients and predispose them to the development and exacerbation of metabolic syndrome. Thus, greater attention must be given to the diagnosis and treatment of OSAS. Moreover, verifying the presence of sleep disorders in the sample discussed by Abbasi et al may provide additional insights. This information could be obtained by collecting the patient’s medical history and performing a polysomnographic examination, which is considered a gold standard in the diagnosis of sleep disorders. However, other evaluation alternatives could be used to identify individuals at risk, such as the use of a classic questionnaire (eg, STOP-BANG), which allows for individuals at risk of obstructive sleep apnea to be identified (6). No significant differences were found between men and women in the study sample with regard to age. However, the authors should consider age as a predisposing risk factor for obesity because older individuals are more susceptible to developing age-related diseases with important clinical implications, such as obesity, metabolic syndrome, and sleep disorders (7–9). In addition, it would be interesting to evaluate the visceral adiposity index for these individuals, because this index includes other factors that complement health risk evaluation (10). Moreover, other biochemical analyses could enhance the diagnosis of metabolic syndrome, such as measurements of albumin, uric acid, and inflammation (C-reactive protein). Finally, we emphasize the importance of the study by Abbasi et al (1), which used anthropometric measurements to conduct a study of
associative factors relating obesity with metabolic impairment and thoroughly considered the consequences of global problems, such as obesity.
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Reply to DN Polesel et al Dear Sir:
AL was supported by NIH grant K23 DK088877. None of the authors had a potential conflict of interest.
Alice Liu Division of Endocrinology, Gerontology, and Metabolism Department of Medicine Stanford University School of Medicine Stanford, CA 94305-5103 Gerald M Reaven Fahim Abbasi Division of Cardiovascular Medicine Department of Medicine Stanford University School of Medicine Falk Cardiovascular Research Center 300 Pasteur Drive Stanford, CA 94305-5406 E-mail: [email protected]
REFERENCES 1. Abbasi F, Blasey C, Reaven GM. Cardiometabolic risk factors and obesity: does it matter whether BMI or waist circumference is the index of obesity? Am J Clin Nutr 2013;98:637–40. 2. Liu A, Kushida CA, Reaven GM. Risk for obstructive sleep apnea in obese, nondiabetic adults varies with insulin resistance status. Sleep Breath 2013;17:333–8. 3. Gangwisch JE, Malaspina D, Boden-Albala B, Heymsfield SB. Inadequate sleep as a risk factor for obesity: analyses of the NHANES I. Sleep 2005;28:1289–96. 4. Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, Nieto FJ. Association of sleep time with diabetes mellitus and impaired glucose tolerance. Arch Intern Med 2005;165:863–7. 5. Liu A, Kushida CA, Reaven GM. Habitual shortened sleep and insulin resistance: an independent relationship in obese individuals. Metabolism 2013;Jul 10 (Epub ahead of print; DOI:10.1016/j.metabol.2013.06.003). 6. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, Galluzzo A; AlkaMeSy Study Group. Visceral adiposity index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 2010;33:920–2. 7. Salazar MR, Carbajal HA, Espeche WG, Aizpurua M, Leiva Sisnieguez CE, March CE, Balbin E, Stavile RN, Reaven GM. Identifying cardiovascular disease risk and outcome: use of the plasma triglyceride/highdensity lipoprotein cholesterol concentration ratio versus metabolic syndrome criteria. J Intern Med 2013;273:595–601. 8. McLaughlin T, Reaven G, Abbasi F, Lamendola C, Saad M, Waters D, Simon J, Krauss RM. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol 2005;96:399–404. 9. Salazar MR, Carbajal HA, Espeche WG, Leiva Sisnieguez CE, Balbin E, Dulbecco CA, Aizpurua M, Marillet AG, Reaven GM. Relation among the plasma triglyceride/high-density lipoprotein cholesterol concentration ratio, insulin resistance, and associated cardio-metabolic risk factors in men and women. Am J Cardiol 2012;109:1749–53. 10. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003;139:802–9. doi: 10.3945/ajcn.113.072876.
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We thank Polesel et al for their comments on our study (1) and agree that the relation between obesity and cardiometabolic risk factors is modulated by comorbidities and/or by medications for treating chronic diseases. In this context, as rightly pointed out, sleep disorders are known to be associated with cardiometabolic abnormalities, and because sleep-disordered breathing is more common in overweight/obese individuals, it will certainly influence the association of obesity indexes and cardiometabolic risk factors. Unfortunately, when our study was performed, we did not collect information on diagnoses of sleep disorders, perform polysomnography, or determine by questionnaires whether or not the individuals were at risk of having obstructive sleep apnea (OSA). However, since then, our research group has become interested in these issues; and along with Dr Alice Liu, we are actively investigating associations between OSA, obesity, and cardiometabolic risk factors, with an emphasis on how differences in insulin-mediated glucose disposal influence these relations in nondiabetic individuals. OSA is well established as a comorbidity in obese individuals, yet the breadth of the obesity epidemic and cost of polysomnography are barriers to universal testing. In an attempt to address this issue, we recently published data showing that insulin-resistant, nondiabetic individuals without known OSA were more likely to be at high risk of OSA, as determined by screening questionnaires, than insulinsensitive individuals of similar adiposity (2). We proposed that administering questionnaires to the insulin-resistant subset of obese individuals would be a clinically useful and a cost-effective way to identify those at the greatest risk of having OSA who will benefit the most from referral for polysomnography. Short sleep duration has also been reported to be associated with obesity and dysglycemia (3, 4). We extended these findings by showing in an obese group of subjects with a high prevalence of impaired fasting glucose and glucose intolerance that insulin resistance was independently associated with habitual shortened sleep, defined as fewer than 7 h of sleep per night (5). Thus, our findings are consistent with the notion that disordered sleep may play an important role in modulating cardiometabolic diseases. That said, it is doubtful that accounting for OSA diagnoses in our present study population would have altered our primary results—namely, that BMI and waist circumference were similar in their associations with markers of increased cardiometabolic risk. In both studies referenced above (2, 5), BMI and waist circumference did not differ between insulin-resistant and insulinsensitive groups, suggesting that the differences seen in OSA risk and sleep duration were attributed to insulin resistance rather than obesity per se. Nonetheless, further studies are necessary to characterize these relations. Polesel et al’s comments with regard to age and the visceral adiposity index (VAI) are also of interest. The median (IQR) age of our study participants was 51 (44–57) y, and 85% of the participants were younger than 60 y, indicating that our sample did not include a large proportion of older individuals who are more prone to developing age-related diseases. The VAI is based on measurements of waist circumference, BMI, and triglyceride and HDL-cholesterol concentrations (6). We have been interested in the utility of the plasma concentration ratio of triglyceride:HDL cholesterol to identify apparently healthy individuals at increased risk of cardiovascular disease (7–10), and the comments of Polesel et al have stimulated us to the point that we are initiating efforts to compare the relative
abilities of the VAI and the triglyceride:HDL-cholesterol ratio to identify individuals at increased cardiometabolic risk.
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DHA supplementation during pregnancy and DNA methylation in cord blood leukocytes Dear Sir:
The author did not declare any conflicts of interest.
Graham C Burdge Academic Unit of Human Development and Health Faculty of Medicine University of Southampton Southampton General Hospital (MP 887) Tremona Road Southampton, SO16 6YD United Kingdom E-mail: [email protected]
REFERENCES 1. Falvo JV, Jasenosky LD, Kruidenier L, Goldfeld AE. Epigenetic control of cytokine gene expression: regulation of the TNF/LT locus and T helper cell differentiation. Adv Immunol 2013;118:37–128. 2. Prescott SL, Clifton V. Asthma and pregnancy: emerging evidence of epigenetic interactions in utero. Curr Opin Allergy Clin Immunol 2009; 9:417–26. 3. Ceccarelli V, Racanicchi S, Martelli MP, Nocentini G, Fettucciari K, Riccardi C, Marconi P, Di Nardo P, Grignani F, Binaglia L, et al. Eicosapentaenoic acid demethylates a single CpG that mediates expression of tumor suppressor CCAAT/enhancer-binding protein delta in U937 leukemia cells. J Biol Chem 2011;286:27092–102. 4. Sadli N, Ackland ML, De Mel D, Sinclair AJ, Suphioglu C. Effects of zinc and DHA on the epigenetic regulation of human neuronal cells. Cell Physiol Biochem 2012;29:87–98. 5. Hoile SP, Irvine NA, Kelsall CJ, Sibbons C, Feunteun A, Collister A, Torrens C, Calder PC, Hanson MA, Lillycrop KA, et al. Maternal fat intake in rats alters 20:4n-6 and 22:6n-3 status and the epigenetic regulation of Fads2 in offspring liver. J Nutr Biochem 2013;24:1213–20. 6. Noakes PS, Vlachava M, Kremmyda LS, Diaper ND, Miles EA, Erlewyn-Lajeunesse M, Williams AP, Godfrey KM, Calder PC. Increased intake of oily fish in pregnancy: effects on neonatal immune
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Modulation of the level of methylation of CpG nucleotide pairs in the 5#-regulatory regions of genes is an important mechanism in the differentiation of T cells into T helper (Th) 1 or Th2 phenotypes (1). Altered epigenetic regulation of T cell differentiation during fetal development has been implicated as an important mechanism in the etiology of allergic diseases in childhood (2). Therefore, nutritional interventions during pregnancy that may prevent or reverse impaired epigenetic regulation of genes that influence T cell phenotype may be of considerable health benefit. Relatively few studies have reported the effect of supplementation with n–3 PUFAs present in fish oil, specifically EPA and DHA, on the epigenetic regulation of genes. The addition of EPA to U937 leukemia cells induced demethylation of specific CpG loci in the promoter of the CCAAT/enhancer-binding protein d (3), whereas treatment of M17 neuroblastoma cells with DHA increased global H3K9 acetylation and decreased levels of transcriptionally repressive histone marks (4). Furthermore, feeding adult rats fish oil induced a reversible increase in the methylation level of specific CpG loci in the Fads2 promoter (5). Increased intake of oily fish during pregnancy has been shown to alter markers of immune function in infants at 6 mo of age (6). Therefore, it is possible that increased intakes of EPA and DHA during pregnancy may induce persistent changes in immune function in the offspring via changes in the epigenetic regulation of T cell phenotypes. In the August 2013 issue of the Journal, Lee et al (7) reported the findings of a study of the effect of supplementation of the diet of pregnant women with 200 mg/d DHA from midgestation until delivery on the methylation status of CpG loci within the promoter regions of genes involved in immune function in umbilical cord blood mononuclear cells. They showed a nonsignificant trend toward an effect of DHA supplementation on the methylation status of the interferon-c and IL-13 promoters. They also found significantly higher methylation of long interspersed element (LINE) 1 sequences in women who took the DHA supplement and who smoked, which became nonsignificant when the data were adjusted for sex, gestational duration, BMI, and batch of laboratory analyses. Unfortunately, there are elements in the design of the study that suggest that the findings should be interpreted with caution. Different cell types have different patterns of DNA methylation. Thus, in mixed-cell preparations such as cord blood mononuclear cells, variation in the relative numbers of different leukocyte populations may confound the interpretation of differences in DNA methylation (8). It is usual to account for variation in leukocyte numbers in the analysis of DNA methylation in blood, particularly during development when leukocyte numbers change dynamically. However, Lee et al (7) did not test for any potential association between variation in the relative size of leukocyte populations and variation in DNA methylation. Because DNA methylation is an important process in immune function, the incidence of infection should have been recorded and incorporated into the data analysis. There is no statement of statistical power for any of the outcome variables. The addition of 61 selected samples ‘‘to strengthen the association between smoking and DNA methylation’’ (7) to 200 randomly selected samples may have introduced bias into the study. Furthermore, the proportion of atopic mothers was ‘‘reasonably balanced’’ (7), although the
numbers were not disclosed, rather than using a case-control design. The difference in the level of methylation of LINE-1 sequences between women who took the DHA supplement and those who did not was ;1%. Because previous reports have shown the precision of the analysis of LINE-1 sequences by pyrosequencing to vary between 1% and 4% (9), it is possible that variation in methylation of 1% may represent analytic error. This view is supported by the loss of statistical significance where the data were adjusted for potential confounders including sample batch. Furthermore, the detection limit of analysis of DNA methylation by pyrosequencing is ;5% (10). Thus, values ,5% should be treated with caution, and the level of precision reported for GATA3 (mean methylation: 0.04– 0.28%) is unlikely to be robust. The apparently lower methylation of LINE-1 sequences in women in the control group who smoked appears to be a result of a single outlying sample. To date, there have not been any reports that show that the level of methylation of LINE-1 sequences is an important determinant of T cell differentiation and phenotype. Unfortunately, the study by Lee et al did not include experiments to show whether variations in LINE-1 methylation alter T cell function (7). Therefore, because of the possible confounding factors discussed above, the lack of experiments to show a causal association between variation in LINE-1 methylation and T cell differentiation or function, and the absence of statistically robust results, the conclusion stated by the authors that ‘‘Our results indicate that maternal supplementation with n–3 PUFA during pregnancy may modulate global methylation levels and the Th1/Th2 balance in infants’’ (7) appears to be an overinterpretation of the findings.
LETTERS TO THE EDITOR
7.
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responses and on clinical outcomes in infants at 6 mo. Am J Clin Nutr 2012;95:395–404. Lee HS, Barraza-Villarreal A, Hernandez-Vargas H, Sly PD, Biessy C, Ramakrishnan U, Romieu I, Herceg Z. Modulation of DNA methylation states and infant immune system by dietary supplementation with omega-3 PUFA during pregnancy in an intervention study. Am J Clin Nutr 2013;98:480–7. Adalsteinsson BT, Gudnason H, Aspelund T, Harris TB, Launer LJ, Eiriksdottir G, Smith AV, Gudnason V. Heterogeneity in white blood cells has potential to confound DNA methylation measurements. PLoS ONE 2012;7:e46705. Irahara N, Nosho K, Baba Y, Shima K, Lindeman NI, Hazra A, Schernhammer ES, Hunter DJ, Fuchs CS, Ogino S. Precision of pyrosequencing assay to measure LINE-1 methylation in colon cancer, normal colonic mucosa, and peripheral blood cells. J Mol Diagn 2010;12:177–83. Tsiatis AC, Norris-Kirby A, Rich RG, Hafez MJ, Gocke CD, Eshleman JR, Murphy KM. Comparison of Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS mutations: diagnostic and clinical implications. J Mol Diagn 2010;12:425–32. doi: 10.3945/ajcn.113.072074.
Dear Sir: We appreciate Burdge’s thoughtful comments, and we thank you for the opportunity to reply to his concerns. We agree with Burdge’s suggestion that the variability of the epigenome among different cells in tissues can confound the findings. Indeed, the intrinsic variability of the DNA methylome among different cell types in umbilical cord blood mononuclear cells (CBMCs) may confound the results because the methylation levels obtained represent the average methylation levels in a given cell population analyzed (1). To rule out potential confounding factors that may be derived from heterogeneous cell populations, it would be necessary to collect a larger volume of cord blood at birth and perform analysis of DNA methylation in fresh fluorescence-activated cell sorting (FACS) sorted cell subpopulations. In our study, the original design did not allow us to collect a larger volume of fresh cord blood and perform analysis of FACS-sorted CBMC subpopulations. Therefore, future studies on CBMCs should exploit a recently developed set of analytic tools (2) for inferring changes in the distribution of different white blood cell subpopulations by using DNA methylation patterns (such as the regression calibration algorithm), an approach that circumvents the need for fresh blood cells and extensive flow cytometry sorting (3, 4). Although we were not able (similarly to the vast majority of other studies) to resolve the problem of mixed populations of cells (which could only be addressed by a single-cell methylomics approach) and examine whether x-3 PUFAs may alter epigenetic states indirectly, we were careful in our statements that our study shows that prenatal x-3 PUFA supplementation can modulate immune response in infants, which correlates with, and not necessarily causes, changes in epigenetic states. Importantly, we have analyzed mRNA levels as a direct measure of gene transcription and the functional impact of DNA methylation changes on gene activity. We found that mRNA levels of IFNc were markedly higher (although marginally significant) in the x-3 PUFA group than in controls, consistent with many previous studies showing an inverse correlation between the expression and DNA methylation levels (H-S Lee and Z Herceg, unpublished data, 2013). Therefore, our results support the notion that x-3 PUFA supple-
mentation could modulate IFNc expression through promoter methylation changes, which may ultimately affect the inflammatory response. These results also argue that gene expression changes indeed accompanied the changes in DNA methylation, which is unlikely to happen if the observed changes represented analytic error in estimating DNA methylation. Burdge also draws attention to potential infections that may cause spurious effects on the immune system and DNA methylation. In this study we analyzed methylation levels in DNA extracted from CBMCs. Although the mothers were not checked for the presence of infection at delivery, all mothers and offspring were healthy at the time of birth without any clinical signs of infection. It is important to mention that all pregnancies were low risk (the inclusion criterion for the study was pregnancy without risk) and that the mean birth weight of the offspring was in the normal range, attesting to the lack of major fetal suffering. Although we agree with the remark that the presence of infections may, in principle, affect the immune system and alter blood cell composition, it is unlikely that such an event would affect specifically one group of subjects and that our results are an indirect consequence of changes in the immune system of newborns. We agree that the statistical power of our study is limited by the sample size, although we included additional samples (n ¼ 261). This is particularly true when conducting stratified analyses. Therefore, our analyses have focused on only the major strata of maternal characteristics. Despite these limitations, we could detect significant changes in DNA methylation and hence believe that our study is sufficiently powered to detect moderate to large changes in DNA methylation, although we might have missed minor changes. We agree that further studies with a larger sample size are needed to confirm our results and evaluate methylation changes in a larger array of genes. We respectfully disagree with Burdge’s suggestion that the addition of 61 selected samples to 200 randomly selected samples could have introduced bias in the analysis. For clarification, we first randomly selected 100 CBMC samples from supplemented mothers and 100 CBMC samples from controls, and our analysis already showed an association between smoking and x-3 PUFAs and DNA methylation. However, because the sample size in the maternal smoking group was rather small, we subsequently analyzed an additional 61 samples (to increase sample size, as requested by the reviewers). Importantly, after we significantly increased the sample size in the maternal smoking group, the overall trend with lower methylation levels associated with smoking remained unchanged. Therefore, our findings of the association between smoking and x-3 PUFAs and DNA methylation are unlikely to be influenced by the analysis of additional samples. We also disagree with Burdge’s assertion that the precision of the analysis of long interspersed element (LINE) 1 sequences by pyrosequencing may not be sufficiently robust to reliably detect small differences between different groups. To avoid potential biases, in our study for each pyrosequencing assay the samples were randomized and analyzed blindly with respect to supplementation and smoking status. In addition, all assays were performed at the same time and on the same aliquot of bisulfite-converted DNAs with the use of the same batch of pyrosequencing reagents, thus avoiding a potential batch effect. The quality control for DNA methylation analysis further included a regular assessment of pyrosequencing quality (including peak heights, deviation from the reference sequencing pattern, and unexpected peak heights). Furthermore, although in our analysis we did not routinely include methylation standards, it is to be noted that for a given gene we obtained relatively homogeneous DNA methylation levels across
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Reply to GC Burdge
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None of the authors declared a conflict of interest.
Ho-Sun Lee Hector Hernandez-Vargas Carine Biessy Isabelle Romieu Zdenko Herceg International Agency for Research on Cancer 150 Cours Albert Thomas 69372 Lyon CEDEX 08 France E-mail: [email protected] or [email protected] Albino Barraza-Villarreal Instituto Nacional de Salud Pu´blica Centro de Investigaciones en Salud Poblacional Cuernavaca, Morelos Mexico
Peter D Sly Queensland Children’s Medical Research Institute Royal Children’s Hospital Herston, Queensland Australia Usha Ramakrishnan Nutrition and Health Sciences and the Hubert Department of Global Health Rollins School of Public Health Emory University Atlanta, GA
REFERENCES 1. Herceg Z, Hernandez-Vargas H. New concepts of old epigenetic phenomena and their implications for selecting specific cell populations for epigenomic research. Epigenomics 2011;3:383–6. 2. Bock C. Analysing and interpreting DNA methylation data. Nat Rev Genet 2012;13:705–19. 3. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 2012;13:86. 4. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, Reinius L, Acevedo N, Taub M, Ronninger M, et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol 2013;31:142–7. 5. Lee HS, Barraza-Villarreal A, Hernandez-Vargas H, Sly PD, Biessy C, Ramakrishnan U, Romieu I, Herceg Z. Modulation of DNA methylation states and infant immune system by dietary supplementation with omega-3 PUFA during pregnancy in an intervention study. Am J Clin Nutr 2013; 98:480–7. doi: 10.3945/ajcn.113.072272.
Fetal vitamin B-12: a modulator of folate-dependent homocysteine remethylation? Dear Sir: We recently read with interest an article by McNulty et al (1) reporting outcomes of a double-blinded randomized controlled trial of folic acid (FA) supplementation (400 lg/d), taken from the start of the second trimester over 14–36 gestational weeks (GWs), in women who also used FA supplements in the first trimester (400 lg/d) and whose dietary intakes compared favorably with current UK reference values, with no difference in total dietary folate intake between groups. In the trial, FA intervention increased maternal folate status, preventing the gestational decline observed at 36 GWs in the placebo group, and this was associated with a significant increase in cord blood folate concentration at birth, which is entirely consistent with the concept that fetal folate concentration reflects trends in maternal folate concentration, underscored by active transport of folate across the placenta (2). Perhaps not unexpectedly, FA intervention had no significant impact on infant size at birth, according well with studies that have also shown a relative lack of dependency with maternal folate status (3) or improvement in birth weight in randomized controlled trials of FA supplementation (4). What is intriguing about the observations in this article is that, whereas a change in maternal folate status after the intervention of FA supplementation prevented the gestational increase in maternal homocysteine concentration of ;1 lmol/L at 36 GWs observed in
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different sample categories, despite the fact that average methylation levels were strikingly different among the assays, ranging from ;0% for GATA3 and STAT3 to as high as 70% and 100% for LINE1 and FOXP3, respectively (our Table 3) (5). These observations strongly rule out the existence of incomplete bisulfite converted DNA, which would otherwise result in increased methylation levels in all genomic regions with no genes exhibiting methylation levels as low as 0% methylation. We are thus confident that our methylation assays were quantitatively sensitive and that the impact of different biases could be ruled out. With regard to the impact of the outliers, as one can see from our Figure 1A, even after including additional 61 samples in the analysis the scatter for the nonsmokers is markedly greater than for smokers. Whereas the reason for this observation is unknown (one can speculate that it is the result of smoking status), a single outlying sample cannot result in significantly lower methylation of LINE-1 sequences of the entire group, especially considering the number of samples in each group. Furthermore, the numbers of atopic mothers in the experimental groups were provided in our Table 1 (n ¼ 72 in the control group compared with n ¼ 70 in the x-3 PUFA group) (5), and thus the proportion of atopic mothers was indeed balanced. We also confirmed that interaction between maternal smoking and x-3 PUFA on LINE-1 methylation was significant when adjusted for sex, gestational duration, BMI, and batch of laboratory analyses. This result supports x-3 PUFA involvement in LINE-1 methylation changes depending on smoking status. We appreciated Burdge’s point with regard to the need to take our study a step further in mechanistic terms. Indeed, one limitation of our study is the lack of experiments to show a causal link between changes in LINE-1 methylation and T cell differentiation/ function. Because we had a limited amount of frozen CBMCs, there was a technical challenge in performing functional tests and thus we were not able to carry out mechanistic experiments with the use of CBMC samples. Because x-3 PUFA-supplemented and control groups were well balanced for all main covariates (including maternal age, height, weight, BMI, educational level, socioeconomic level, maternal smoking during pregnancy, paternal smoking status, sex, birth weight, and gestational duration), these are unlikely to be confounding factors. Therefore, the main findings of our study are unlikely to be influenced by confounding factors and technical biases.
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newborn infants of healthy, nonvegetarian mothers, impaired vitamin B-12 function appears to be related to their low vitamin B-12 tissue reserves (8). Against this background, the reduction in maternal vitamin B12 concentrations by 36 GWs mentioned in the FA supplementation trial has particular relevance, because it is consistent with the notion that fetal vitamin B-12 requirements may well have exceeded the capacity for placental vitamin B-12 transport to meet fetal demand. This commentary supports the view that vitamin B-12 transported by the placenta has relative importance, particularly with regard to the fetal remethylation of homocysteine to methionine, as well as the influence on the prevalence of impaired vitamin B-12 status in the neonatal period. This should motivate vitamin B-12 intervention studies in pregnancy and in newborn infants. None of the authors declared a conflict of interest.
Stephen W D’Souza Maternal and Fetal Research Centre Institute of Human Development Faculty of Medical and Human Sciences University of Manchester Manchester M13 9WL United Kingdom E-mail: stephen.w.d’[email protected] Stuart J Moat Department of Medical Biochemistry and Immunology University Hospital of Wales and Cardiff School of Medicine Cardiff University Heath Park Cardiff CF14 4XW United Kingdom Jocelyn D Glazier Maternal and Fetal Health Research Centre Institute of Human Development Faculty of Medical and Human Sciences University of Manchester Manchester M13 9WL United Kingdom
REFERENCES 1. McNulty B, McNulty H, Marshall B, Ward M, Molloy AM, Scott JM, Dorman J, Pentieva K. Impact of continuing folic acid after the first trimester of pregnancy: findings of a randomized trial of folic acid supplementation in the second and third trimesters. Am J Clin Nutr 2013;98:92–8. 2. Solanky N, Requena Jimenez A, D’Souza SW, Sibley CP, Glazier JD. Expression of folate transporters in human placenta and implications for homocysteine metabolism. Placenta 2010;31:134–43. 3. Hay G, Clausen T, Whitelaw A, Trygg K, Johnston C, Henriksen T, Refsum H. Maternal folate and cobalamin status predicts vitamin status in newborns and 6-month-old infants. J Nutr 2010;140:557–64. 4. Scholl TO, Johnson WG. Folic acid: influence on the outcome of pregnancy. Am J Clin Nutr 2000;71(suppl):1295S–303S. 5. Tsitsiou E, Sibley CP, D’Souza SW, Catanescu O, Jacobsen DW, Glazier JD. Homocysteine transported by systems L, A and y1L across the microvillous plasma membrane of human placenta. J Physiol 2009; 587:4001–13.
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unsupplemented mothers (placebo group), this treatment had no significant impact on fetal homocysteine concentration, with similar homocysteine concentrations in the cord blood of both study groups (the authors’ Table 3). We would comment that maternal homocysteine concentrations reported in the study groups between 14 and 36 GWs could, in part, also be modulated by placental uptake and transport of homocysteine to the fetus (5), a concept not alluded to in the article. Previous studies by Molloy et al (6) have shown that maternal homocysteine concentration had the strongest effect on fetal homocysteine concentration in women with normal pregnancies who routinely took FA supplements, evidenced also by the positive correlation between maternal and cord blood homocysteine concentrations (6). It should be further noted that the authors comment that maternal and fetal vitamin B-12 concentrations had additional effects (6). It is presently unclear whether homocysteine entering the fetal circulation is partly derived from the maternal circulation after transplacental passage (5) and/or from placental methionine metabolism (2). However, homocysteine concentrations in umbilical cord venous plasma are ;1 lmol/L higher than in cord arterial plasma, with these variables being highly correlated to each other (7). Such findings suggest that homocysteine delivered by the placenta into cord venous blood is extracted by the fetus, resulting in fetal uptake of homocysteine, akin to other amino acids (2, 5). This leads to an interesting question: why does the fetal response to increased maternal plasma homocysteine concentration exhibit divergence between these studies? This is an important aspect to understand mechanistically if the capacity of folate to lower maternal homocysteine concentration is conceived to be of positive benefit with respect to pregnancy outcomes, including those of the neonate, as commented on by the authors. We speculate that one possibility underlying this discordance relates to the impact on folate-dependent homocysteine metabolism, which had become limited by vitamin B-12. We suggest this because we note that some mothers at 14 GWs had remarkably low serum vitamin B-12 concentrations (,150 pmol/L; the authors’ Table 1) and that advancing gestational age (14–36 GWs) was associated with a significant decline in maternal vitamin B-12 concentration, which could represent a reduction in maternal reserves during pregnancy (8), and a subclinical deficit limiting the amount transported by the placenta (9) to the fetal circulation. Hence, women with low vitamin B-12 status may not be able to provide the optimum amount of this micronutrient required by the fetus (10), with implications for newborn infants including low reserves of vitamin B-12 and possibly a risk of vitamin B-12 deficiency (8). The maternal data concerning vitamin B-12 concentration at 36 GWs were not provided, and although cord vitamin B-12 concentrations were not different between study groups at delivery, the reduction seen in maternal homocysteine concentration with FA treatment was not reflected in the fetal compartment, suggesting limitation by another modulatory factor. The emergence of vitamin B-12 as an additional factor of importance influencing folate-dependent homocysteine metabolism toward the end of gestation would be in agreement with earlier studies (6). An efficient use of vitamin B-12 both by the placenta and the fetus has been implicated (2, 8), particularly with regard to directing vitamin B-12 to favor methionine synthase activity, providing methionine and tetrahydrofolate to support cell growth. The trial was not extended to the neonatal period to examine the potential impact of maternal FA supplementation intervention during pregnancy on newborn infants. Other studies have reported that over the first few weeks of birth an increase in homocysteine concentration in newborn infants is strongly associated with a reduction in vitamin B-12 concentration, consistent with impaired vitamin B-12 function and not correlated with serum or whole-blood folate (8). Indeed, in
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6. Molloy AM, Mills JL, McPartlin J, Kirke PN, Scott JM, Daly S. Maternal and fetal plasma homocysteine concentrations at birth: the influence of folate, vitamin B12 and the 5,10-methylenetetrahydrofolate reductase 677C/T variant. Am J Obstet Gynecol 2002;186:499–503. 7. Malinow MR, Rajkovic A, Duell PB, Hess DL, Upson BM. The relationship between maternal and neonatal umbilical cord plasma homocyst(e)ine suggests a potential role for maternal homocyst(e)ine in fetal metabolism. Am J Obstet Gynecol 1998;178:228–33. 8. Bjørke Monsen AL, Ueland PM, Vollset SE, Guttormsen AB, Markestad T, Solheim E, Refsum H. Determinants of cobalamin status in newborns. Pediatrics 2001;108:624–30. 9. Schneider H, Miller RK. Receptor-mediated uptake and transport of macromolecules in the human placenta. J Dev Biol 2010;54:367–75. 10. Relton CL, Pearce MS, Parker L. The influence of erythrocyte folate and serum vitamin B12 status on birthweight. Br J Nutr 2005;93:593–9. doi: 10.3945/ajcn.113.073262.
Reply to SW D’Souza et al
D’Souza et al share some interesting thoughts regarding our article on the effects of folic acid supplementation in the second and third trimesters of pregnancy (1). They point out, quite rightly, that whereas folic acid supplementation influenced maternal homocysteine by preventing the increase in homocysteine usually observed in the third trimester (2), we did not observe a difference in cord blood homocysteine concentrations between the placebo and folic acid treatment groups. D’Souza et al suggest that low vitamin B-12 status might explain the anomaly. Serum total vitamin B-12 is known to decrease by ;30% over the course of pregnancy (3), and in this study between gestational weeks 14 and 36 we observed (although did not report) a decline in maternal vitamin B-12 concentrations of 22% (from 211 6 82 pmol/L to 165 6 59 pmol/L; P ¼ 0.001) in the placebo group and 25% (from 235 6 94 pmol/L to 176 6 75 pmol/L; P ¼ 0.001) in the folic acid–supplemented group, with no significant treatment effect (P ¼ 0.59). We interpret this as indicating that vitamin B-12 affected the relation between maternal and cord blood homocysteine in both groups, although this was not an outcome of primary interest to the study. Although it was not included in the article, we used multiple regression analysis to examine each of the measured variables in our study as determinants of the fetal (cord blood) homocysteine. Neither folate nor vitamin B-12 were significant predictors of cord blood homocysteine in either the placebo or the folic acid treatment group (P ¼ 0.98 and 0.09 for cord blood folate and vitamin B-12, respectively, in the placebo group; and P ¼ 0.26 and 0.45, respectively, in the treatment group). The only significant predictor of fetal homocysteine was the maternal homocysteine concentration, but the overall relation in the multiple regression analysis was much weaker in the folic acid treatment group (adjusted R2 ¼ 13.7% compared with 54.7% in the placebo group). D’Souza et al suggest that the cord blood homocysteine concentration may be limited by another modulatory factor, and we agree. As in our previous observational study (4), in the current randomized controlled trial we found that maternal homocysteine was significantly associated with fetal homocysteine, but this relation was relatively weaker in the folic acid treatment group. However, the data do not indicate that the limiting factor in our study is vitamin B-12. Although we would not deny the importance of vitamin B-12 in pregnancy and in early neonatal life, there are many gaps in our understanding of vitamin B-12 status at these critical times. Several
None of the authors had a conflict of interest.
Anne M Molloy Department of Clinical Medicine Trinity College Dublin Dublin Ireland Kristina Pentieva Breige McNulty Helene McNulty Northern Ireland Centre for Food and Health (NICHE) School of Biomedical Sciences University of Ulster Cromore Road Coleraine BT52 1SA Northern Ireland E-mail: [email protected]
REFERENCES 1. McNulty B, McNulty H, Marshall B, Ward M, Molloy AM, Scott JM, Dornan J, Pentieva K. Impact of continuing folic acid after the first trimester of pregnancy: findings of a randomized trial of folic acid supplementation in the second and third trimesters. Am J Clin Nutr 2013; 98:92–8. 2. Holmes VA, Wallace JM, Alexander HD, Gilmore WS, Bradbury I, Ward M, Scott JM, McFaul P, McNulty H. Homocysteine is lower in the third trimester of pregnancy in women with enhanced folate status from continued folic acid supplementation. Clin Chem 2005;51: 629–34. 3. Murphy MM, Molloy AM, Ueland PM, Fernandez-Ballart JD, Schneede J, Arija V, Scott JM. Longitudinal study of the effect of pregnancy on maternal and fetal cobalamin status in healthy women and their offspring. J Nutr 2007;137:1863–7. 4. Molloy AM, Mills JL, McPartlin J, Kirke PN, Scott JM, Daly S. Maternal and fetal plasma homocysteine concentrations at birth: the influence
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Dear Sir:
studies have shown that, whereas the total serum vitamin B-12 decreases dramatically during pregnancy, the fraction of vitamin B-12 that is available for uptake into tissue (ie, holotranscobalamin) does not appear to decline (3, 5), indicating that the interpretation of biomarkers of vitamin B-12 during pregnancy is complex, a point made by others in earlier studies (6, 7). This appears to be the case in our study, in which low maternal concentrations of vitamin B-12 at gestational week 36 do not predict functional vitamin B-12 deficiency in the fetus at birth, at least where the functional biomarker homocysteine is concerned. We would also comment that although D’Souza et al consider the importance of transplacental transfer of homocysteine and placental methionine metabolism, they have overlooked other pregnancy-related factors that affect maternal and fetal homocysteine (8). One relevant micronutrient not considered by D’Souza et al, and not measured in our study, is choline, for which there is a very high fetal requirement. We previously found maternal homocysteine concentration to be strongly associated with cord blood choline, consistent with a high maternal de novo synthesis of choline through hepatic phosphatidylethanolamine methyltransferase (9). Clearly, all of these factors need to be considered, and although the call for intervention studies with vitamin B-12 in pregnancy and newborns is well made, we need first to know how to interpret the relevant biomarkers of vitamin B-12 status in pregnancy.
LETTERS TO THE EDITOR of folate, vitamin B12, and the 5,10-methylenetetrahydrofolate reductase 677C/T variant. Am J Obstet Gynecol 2002;186:499–503. 5. Morkbak AL, Hvas AM, Milman N, Nexo E. Holotranscobalamin remains unchanged during pregnancy: longitudinal changes of cobalamins and their binding proteins during pregnancy and postpartum. Haematologica 2007;92:1711–2. 6. Pardo J, Peled Y, Bar J, Hod M, Sela BA, Rafael ZB, Orvieto R. Evaluation of low serum vitamin B(12) in the non-anaemic pregnant patient. Hum Reprod 2000;15:224–6. 7. Metz J, McGrath K, Bennett M, Hyland K, Bottiglieri T. Biochemical indices of vitamin B12 nutrition in pregnant patients with subnormal serum vitamin B12 levels. Am J Hematol 1995;48:251–5.
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8. Murphy MM, Scott JM, Arija V, Molloy AM, Fernandez-Ballart JD. Maternal homocysteine before conception and throughout pregnancy predicts fetal homocysteine and birth weight. Clin Chem 2004;50:1406–12. 9. Molloy AM, Mills JL, Cox C, Daly SF, Conley M, Brody LC, Kirke PN, Scott JM, Ueland PM. Choline and homocysteine interrelations in umbilical cord and maternal plasma at delivery. Am J Clin Nutr 2005;82: 836–42.
doi: 10.3945/ajcn.113.073593.
Tate DF, Turner-McGrievy G, Lyons E, Stevens J, Erickson K, Polzien K, Diamond M, Wang X, Popkin B. Replacing caloric beverages with water or diet beverages for weight loss in adults: main results of the Choose Healthy Options Consciously Everyday (CHOICE) randomized clinical trial. Am J Clin Nutr 2012;95:555–63. In the print version of the article, the second sentence of the Results section of the abstract contains a copyediting error. Negative signs should be included in the DB and Water percent results, so that the sentence reads as follows: ‘‘Mean (6SEM) weight losses at 6 mo were 22.5 6 0.45% in the DB group, 22.03 6 0.40% in the Water group, and 21.76 6 0.35% in the AC group; there were no significant differences between groups.’’ The online version of this article was corrected at final publication. doi: 10.3945/ajcn.113.075432.
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Erratum
