A randomized controlled trial of the effects of whole grains versus refined grains diets on the microbiome in pregnancy

Haipeng Sun, Pamella Yamada, Alexandra Paetow, Michael Chan, Alan Arslan, Rikard Landberg, Maria Gloria Dominguez-Bello, Bruce K Young, Haipeng Sun, Pamella Yamada, Alexandra Paetow, Michael Chan, Alan Arslan, Rikard Landberg, Maria Gloria Dominguez-Bello, Bruce K Young

Abstract

Dietary whole grain consumption has been postulated to have metabolic benefits. The purpose of this study was to compare a pregnancy diet containing 75% of total carbohydrates as refined grains with a diet of 75% of total carbohydrates as whole grains for pregnancy outcomes and effects on the microbiome. Gestational weight gain, glucose tolerance and newborn outcomes were measured on 248 enrolled compliant women from whom a subset of 103 women consented to give 108 vaginal and 109 anal swabs. The data presented here are limited to the patients from whom the vaginal and anal swabs were obtained in order to study the microbiome. A microbiome-16SrRNA survey-was characterized in these samples. Samples and measurements were obtained at the first obstetrical visit, before beginning a prescribed diet (T1-baseline) and after 17-32 weeks on the prescribed diet (T3). Food frequency questionnaires and total plasma alkylresorcinols were used as a measure of whole grain consumption. There were no dietary differences in maternal weight gain, birth weight, or glucose tolerance test. Mothers consuming the whole grains diet showed a trend of gestational decrease in vaginal bacterial alpha diversity, with increasing Lactobacillus-dominance. No significant difference was observed for the anal microbiome. The results suggest that diet modulations of the vaginal microbiome during gestation may have important implications for maternal and neonatal health and in the intergenerational transfer of maternal microbiome. Trial registration: ClinicalTrials.gov Identifier: NCT03232762.

Conflict of interest statement

Bruce K. Young is a member of the scientific advisory board of the Grain Foods Foundation and receives compensation from the foundation. None of the other authors disclosed any conflicts of interest.

© 2022. The Author(s).

Figures

Figure 1
Figure 1
Alpha diversity in the vaginal and anal microbiota of 103 mothers. Faith PD, Observed ASVs, and Shannon index was presented respectively, Kruskal–Wallis test performed between the three groups. (a) Vaginal microbiome. (b) Anal microbiome.
Figure 2
Figure 2
LEfSe cladogram of differing taxa. Significantly enriched taxa colored in purple for refined grains diet, green for whole grains diet. g_ for genus level, f_ for family level, o_ for order level, c_ for class level, and p_ for phylum level. (a) Vaginal overrepresented taxa in each group. (b) Anal overrepresented taxa in each group.
Figure 3
Figure 3
Vaginal and anal microbiome beta diversity. PCoA generated on weighted Unifrac distance. (a) Vaginal, (b) anal. Table shows the PERMANOVA result effect between baseline, whole grains T3, and refined grains T3. Ellipses represent 95% CI of center of each group under multivariate t-distribution.

References

    1. Goldstein RF, et al. Association of gestational weight gain with maternal and infant outcomes: A systematic review and meta-analysis. JAMA. 2017;317:2207–2225. doi: 10.1001/jama.2017.3635.
    1. Muktabhant B, Lawrie TA, Lumbiganon P, Laopaiboon M. Diet or exercise, or both, for preventing excessive weight gain in pregnancy. Cochrane Database Syst. Rev. 2015 doi: 10.1002/14651858.CD007145.pub3.
    1. Jonnalagadda SS, et al. Putting the whole grain puzzle together: Health benefits associated with whole grains—Summary of American Society for Nutrition 2010 Satellite Symposium. J. Nutr. 2011;141:1011S–1022S. doi: 10.3945/jn.110.132944.
    1. WHO recommendation on counselling on healthy eating and physical activity during pregnancy. (2018).
    1. Agriculture, U. S. D. o. H. a. H. S. a. U. S. D. o. 2015–2020 Dietary Guidelines for Americans. 8th ed. (2015).
    1. Daniels SR. The Barker hypothesis revisited. J. Pediatr. 2016;173:1–3. doi: 10.1016/j.jpeds.2016.04.031.
    1. de Boo HA, Harding JE. The developmental origins of adult disease (Barker) hypothesis. Aust. N. Z. J. Obstet. Gynaecol. 2006;46:4–14. doi: 10.1111/j.1479-828X.2006.00506.x.
    1. Kimm SYS. Fetal origins of adult disease: The Barker hypothesis revisited—2004. Curr. Opin. Endocrinol. Diabetes Obes. 2004;11:192–196. doi: 10.1097/01.med.0000140938.39925.4c.
    1. Slavin JL. The challenges of nutrition policymaking. Nutr. J. 2015;14:15. doi: 10.1186/s12937-015-0001-8.
    1. Hess J, Latulippe ME, Ayoob K, Slavin J. The confusing world of dietary sugars: Definitions, intakes, food sources and international dietary recommendations. Food Funct. 2012;3:477–486. doi: 10.1039/c2fo10250a.
    1. Crume TL, et al. Maternal dietary intake during pregnancy and offspring body composition: The Healthy Start Study. Am. J. Obstet. Gynecol. 2016;215:609.e601–609.e608. doi: 10.1016/j.ajog.2016.06.035.
    1. In Weight Gain During Pregnancy: Reexamining the Guidelines The National Academies Collection: Reports funded by National Institutes of Health (eds K. M. Rasmussen & A. L. Yaktine) (2009).
    1. Yamada P, et al. Pregnancy outcomes with differences in grain consumption: A randomized controlled trial. J. Perinat. Med. 2022 doi: 10.1515/jpm-2021-0479.
    1. Papanikolaou Y, Fulgoni VL. Certain grain foods can be meaningful contributors to nutrient density in the diets of U.S. children and adolescents: Data from the National Health and Nutrition Examination Survey, 2009–2012. Nutrients. 2017;9:160. doi: 10.3390/nu9020160.
    1. Asemi Z, Tabassi Z, Samimi M, Fahiminejad T, Esmaillzadeh A. Favourable effects of the dietary approaches to stop hypertension diet on glucose tolerance and lipid profiles in gestational diabetes: A randomised clinical trial. Br. J. Nutr. 2013;109:2024–2030. doi: 10.1017/S0007114512004242.
    1. Beulen YH, et al. Dietary interventions for healthy pregnant women: A systematic review of tools to promote a healthy antenatal dietary intake. Nutrients. 2020;12:1981. doi: 10.3390/nu12071981.
    1. Gross RS, Mendelsohn AL, Gross MB, Scheinmann R, Messito MJ. Randomized controlled trial of a primary care-based child obesity prevention intervention on infant feeding practices. J. Pediatr. 2016;174:171–177.e172. doi: 10.1016/j.jpeds.2016.03.060.
    1. International Weight Management in Pregnancy Collaborative, G Effect of diet and physical activity based interventions in pregnancy on gestational weight gain and pregnancy outcomes: Meta-analysis of individual participant data from randomised trials. BMJ. 2017;358:j3119. doi: 10.1136/bmj.j3119.
    1. Thangaratinam S, et al. Effects of interventions in pregnancy on maternal weight and obstetric outcomes: Meta-analysis of randomised evidence. BMJ. 2012;344:e2088. doi: 10.1136/bmj.e2088.
    1. Timmermans S, et al. The Mediterranean diet and fetal size parameters: The Generation R Study. Br. J. Nutr. 2012;108:1399–1409. doi: 10.1017/S000711451100691X.
    1. Wiertsema CJ, et al. Associations of DASH diet in pregnancy with blood pressure patterns, placental hemodynamics, and gestational hypertensive disorders. J. Am. Heart Assoc. 2021;10:e017503. doi: 10.1161/JAHA.120.017503.
    1. Blaser MJ, Dominguez-Bello MG. The human microbiome before birth. Cell Host Microbe. 2016;20:558–560. doi: 10.1016/j.chom.2016.10.014.
    1. Jasarevic E, Bale TL. Prenatal and postnatal contributions of the maternal microbiome on offspring programming. Front. Neuroendocrinol. 2019;55:100797. doi: 10.1016/j.yfrne.2019.100797.
    1. De Angelis M, et al. Effect of whole-grain barley on the human fecal microbiota and metabolome. Appl. Environ. Microbiol. 2015;81:7945–7956. doi: 10.1128/AEM.02507-15.
    1. Roager HM, et al. Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: A randomised cross-over trial. Gut. 2019;68:83–93. doi: 10.1136/gutjnl-2017-314786.
    1. Neggers YH, et al. Dietary intake of selected nutrients affects bacterial vaginosis in women. J. Nutr. 2007;137:2128–2133. doi: 10.1093/jn/137.9.2128.
    1. Song SD, et al. Daily vaginal microbiota fluctuations associated with natural hormonal cycle, contraceptives, diet, and exercise. mSphere. 2020;5:e00593-20. doi: 10.1128/mSphere.00593-20.
    1. Whyte JJ, et al. Maternal diet composition alters serum steroid and free fatty acid concentrations and vaginal pH in mice. J. Endocrinol. 2006;192:75–81. doi: 10.1677/JOE-06-0095.
    1. Aagaard K, et al. A metagenomic approach to characterization of the vaginal microbiome signature in pregnancy. PLoS ONE. 2012;7:e36466. doi: 10.1371/journal.pone.0036466.
    1. Freitas AC, et al. The vaginal microbiome of pregnant women is less rich and diverse, with lower prevalence of Mollicutes, compared to non-pregnant women. Sci. Rep. 2017;7:9212. doi: 10.1038/s41598-017-07790-9.
    1. Boskey ER, Cone RA, Whaley KJ, Moench TR. Origins of vaginal acidity: High d/l lactate ratio is consistent with bacteria being the primary source. Hum. Reprod. 2001;16:1809–1813. doi: 10.1093/humrep/16.9.1809.
    1. MacIntyre DA, et al. The vaginal microbiome during pregnancy and the postpartum period in a European population. Sci. Rep. 2015;5:8988. doi: 10.1038/srep08988.
    1. Koren O, et al. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell. 2012;150:470–480. doi: 10.1016/j.cell.2012.07.008.
    1. Stout MJ, et al. Early pregnancy vaginal microbiome trends and preterm birth. Am. J. Obstet. Gynecol. 2017;217:356.e351–356.e318. doi: 10.1016/j.ajog.2017.05.030.
    1. DiGiulio DB, et al. Temporal and spatial variation of the human microbiota during pregnancy. Proc. Natl. Acad. Sci. USA. 2015;112:11060–11065. doi: 10.1073/pnas.1502875112.
    1. Berry ASF, et al. Remodeling of the maternal gut microbiome during pregnancy is shaped by parity. Microbiome. 2021;9:146. doi: 10.1186/s40168-021-01089-8.
    1. Verstraelen H, et al. Subclinical iron deficiency is a strong predictor of bacterial vaginosis in early pregnancy. BMC Infect. Dis. 2005;5:55. doi: 10.1186/1471-2334-5-55.
    1. Neuman H, Koren O. The pregnancy microbiome. Nestle Nutr. Inst. Workshop Ser. 2017;88:1–9. doi: 10.1159/000455207.
    1. Obstetrics committee of the American College of Obstetricians and Gynecologists and their publications Clinical updates in women’s health care: Nutrition. Am. Coll. Obstet. Gynecol. 2014;13:3.
    1. Block G, Woods M, Potosky A, Clifford C. Validation of a self-administered diet history questionnaire using multiple diet records. J. Clin. Epidemiol. 1990;43:1327–1335. doi: 10.1016/0895-4356(90)90099-b.
    1. American College of Obstetricians and Gynecologists ACOG practice Bulletin No 156: Obesity in pregnancy. Obstet. Gynecol. 2015;126:e112–e126. doi: 10.1097/AOG.0000000000001211.
    1. Carmichael S, Abrams B, Selvin S. The pattern of maternal weight gain in women with good pregnancy outcomes. Am. J. Public Health. 1997;87:1984–1988. doi: 10.2105/ajph.87.12.1984.
    1. Dominguez-Bello MG, et al. Partial restoration of the microbiota of cesarean-born infants via vaginal microbial transfer. Nat. Med. 2016;22:250–253. doi: 10.1038/nm.4039.
    1. Andersson A, Marklund M, Diana M, Landberg R. Plasma alkylresorcinol concentrations correlate with whole grain wheat and rye intake and show moderate reproducibility over a 2- to 3-month period in free-living Swedish adults. J. Nutr. 2011;141:1712–1718. doi: 10.3945/jn.111.139238.
    1. Landberg R, et al. Biomarkers of cereal food intake. Genes Nutr. 2019;14:28. doi: 10.1186/s12263-019-0651-9.
    1. Bolyen E, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 2019;37:852–857. doi: 10.1038/s41587-019-0209-9.
    1. Callahan BJ, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods. 2016;13:581–583. doi: 10.1038/nmeth.3869.
    1. Price MN, Dehal PS, Arkin AP. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE. 2010;5:e9490. doi: 10.1371/journal.pone.0009490.
    1. Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome. 2018;6:226. doi: 10.1186/s40168-018-0605-2.
    1. Faith DP. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 1992;61:1–10. doi: 10.1016/0006-3207(92)91201-3.
    1. Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl. Environ. Microbiol. 2007;73:1576–1585. doi: 10.1128/AEM.01996-06.
    1. Paradis E, Schliep K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–528. doi: 10.1093/bioinformatics/bty633.
    1. Oksanen, J. et al. vegan: Community Ecology Package. (2020).
    1. Segata N, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12:R60. doi: 10.1186/gb-2011-12-6-r60.

Source: PubMed

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