1,826
Views
0
CrossRef citations to date
0
Altmetric
Meta Analysis

Maternal Caffeine Consumption During Pregnancy and Offspring Cord Blood DNA Methylation: An Epigenome-Wide Association Study Meta-Analysis

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, , ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon show all
Pages 1179-1193 | Received 20 Jul 2023, Accepted 02 Nov 2023, Published online: 29 Nov 2023

References

  • Grosso LM , BrackenMB. Caffeine metabolism, genetics, and perinatal outcomes: a review of exposure assessment considerations during pregnancy. Ann. Epidemiol.15(6), 460–466 (2005).
  • EFSA Panel on Dietetic Products, Nutrition, Allergies (NDA) . Scientific opinion on the safety of caffeine. EFSA J.13(5), 4102 (2015).
  • Reyes CM , CornelisM. Caffeine in the diet: country-level consumption and guidelines. Nutrients10(11), 1772 (2018).
  • Greenwood DC , ThatcherNJ , YeJet al. Caffeine intake during pregnancy and adverse birth outcomes: a systematic review and dose–response meta-analysis. Eur. J. Epidemiol.29(10), 725–734 (2014).
  • Rhee J , KimR , KimYet al. Maternal caffeine consumption during pregnancy and risk of low birth weight: a dose-response meta-analysis of observational studies. PLOS ONE10(7), e0132334 (2015).
  • Chen L-W , WuY , NeelakantanN , ChongMF-F , PanA , van DamRM. Maternal caffeine intake during pregnancy is associated with risk of low birth weight: a systematic review and dose-response meta-analysis. BMC Med.12(1), 174 (2014).
  • Soltani S , Salari-MoghaddamA , SaneeiPet al. Maternal caffeine consumption during pregnancy and risk of low birth weight: a dose–response meta-analysis of cohort studies. Crit. Rev. Food Sci. Nutr.63(2), 224–233 (2023).
  • Poole R , KennedyOJ , RoderickP , FallowfieldJA , HayesPC , ParkesJ. Coffee consumption and health: umbrella review of meta-analyses of multiple health outcomes. BMJ359 (2017).
  • Askari M , BazshahiE , PayandeN , MobaderiT , FahimfarN , AzadbakhtL. Relationship between caffeine intake and small for gestational age and preterm birth: a dose–response meta-analysis. Crit. Rev. Food Sci. Nutr.1–11 (2023).
  • Jin F , QiaoC. Association of maternal caffeine intake during pregnancy with low birth weight, childhood overweight, and obesity: a meta-analysis of cohort studies. Int. J. Obes.45(2), 279–287 (2021).
  • Hammerton G , MunafòMR. Causal inference with observational data: the need for triangulation of evidence. Psychol. Med.51(4), 563–578 (2021).
  • Treur JL , TaylorAE , WareJJet al. Associations between smoking and caffeine consumption in two European cohorts: smoking and caffeine consumption. Addiction111(6), 1059–1068 (2016).
  • Ding Q , XuY-M , LauATY. The epigenetic effects of coffee. Molecules28(4), 1770 (2023).
  • Bird A . Perceptions of epigenetics. Nature447(7143), 396–398 (2007).
  • Felix JF , JoubertBR , BaccarelliAAet al. Cohort profile: Pregnancy And Childhood Epigenetics (PACE) consortium. Int. J. Epidemiol.47(1), 22–23u (2018).
  • Huang J , ZhouS , PingJet al. Role of p53-dependent placental apoptosis in the reproductive and developmental toxicities of caffeine in rodents. Clin. Exp. Pharmacol. Physiol.39(4), 357–363 (2012).
  • Fang X , MeiW , BarbazukWB , RivkeesSA , WendlerCC. Caffeine exposure alters cardiac gene expression in embryonic cardiomyocytes. Am. J. Physiol. Regul. Integr. Comp. Physiol.307(12), R1471–R1487 (2014).
  • Buscariollo DL , FangX , GreenwoodV , XueH , RivkeesSA , WendlerCC. Embryonic caffeine exposure acts via A1 adenosine receptors to alter adult cardiac function and DNA methylation in mice. PLOS ONE9(1), (2014).
  • Ping J , WangJ , LiuLet al. Prenatal caffeine ingestion induces aberrant DNA methylation and histone acetylation of steroidogenic factor 1 and inhibits fetal adrenal steroidogenesis. Toxicology321, 53–61 (2014).
  • Wu D-M , HeZ , MaL-P , WangL-L , PingJ , WangH. Increased DNA methylation of scavenger receptor class B type I contributes to inhibitory effects of prenatal caffeine ingestion on cholesterol uptake and steroidogenesis in fetal adrenals. Toxicol. Appl. Pharmacol.285(2), 89–97 (2015).
  • Xu D , ZhangB , LiangGet al. Caffeine-induced activated glucocorticoid metabolism in the hippocampus causes hypothalamic–pituitary–adrenal axis inhibition in fetal rats. PLOS ONE7(9), (2012).
  • Polinski KJ , Purdue-SmitheA , RobinsonSLet al. Maternal caffeine intake and DNA methylation in newborn cord blood. Am. J. Clin. Nutr.115(2), 482–491 (2022).
  • Karabegović I , Portilla-FernandezE , LiYet al. Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption. Nat. Commun.12(1), 2830 (2021).
  • Boyd A , GoldingJ , MacleodJet al. Cohort profile: the ‘Children of the 90s’ – the index offspring of the Avon Longitudinal Study of Parents and Children. Int. J. Epidemiol.42(1), 111–127 (2013).
  • Fraser A , Macdonald-WallisC , TillingKet al. Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int. J. Epidemiol.42(1), 97–110 (2013).
  • Wright J , SmallN , RaynorPet al. Cohort profile: the Born in Bradford multi-ethnic family cohort study. Int. J. Epidemiol.42(4), 978–991 (2013).
  • Raynor P . Born in Bradford Collaborative Group. Born in Bradford, a cohort study of babies born in Bradford, and their parents: protocol for the recruitment phase. BMC Public Health8, 327 (2008).
  • Kooijman MN , KruithofCJ , van DuijnCMet al. The Generation R Study: design and cohort update 2017. Eur. J. Epidemiol.31(12), 1243–1264 (2016).
  • Kruithof CJ , KooijmanMN , van DuijnCMet al. The Generation R Study: biobank update 2015. Eur. J. Epidemiol.29(12), 911–927 (2014).
  • Magnus P , BirkeC , VejrupKet al. Cohort profile update: the Norwegian Mother and Child Cohort Study (MoBa). Int. J. Epidemiol.45(2), 382–388 (2016).
  • Guxens M , BallesterF , EspadaMet al. Cohort profile: the INMA – Infancia y Medio Ambiente – (Environment and Childhood) Project. Int. J. Epidemiol.41(4), 930–940 (2012).
  • Heude B , ForhanA , SlamaRet al. Cohort profile: the EDEN mother–child cohort on the prenatal and early postnatal determinants of child health and development. Int. J. Epidemiol.45(2), 353–363 (2016).
  • Thompson FE , SubarAF. Dietary assessment methodology. In: Nutrition in the Prevention and Treatment of Disease.Elsevier Inc., 5–48 (2017).
  • Farrow A , SheaKM , LittleRE. Birthweight of term infants and maternal occupation in a prospective cohort of pregnant women. the ALSPAC study team. Occup. Environ. Med.55(1), 18–23 (1998).
  • James JE . Maternal caffeine consumption and pregnancy outcomes: a narrative review with implications for advice to mothers and mothers-to-be. BMJ Evid. Based Med.26(3), 114–115 (2021).
  • Chen YA , LemireM , ChoufaniSet al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics8(2), 203–209 (2013).
  • Gervin K , PageCM , AassHCDet al. Cell type specific DNA methylation in cord blood: a 450K-reference data set and cell count-based validation of estimated cell type composition. Epigenetics11(9), 690–698 (2016).
  • Houseman EA , AccomandoWP , KoestlerDCet al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics13(1), (2012).
  • Yousefi P , HuenK , DavéV , BarcellosL , EskenaziB , HollandN. Sex differences in DNA methylation assessed by 450 K BeadChip in newborns. BMC Genomics16 (2015).
  • Merid SK , NovoloacaA , SharpGCet al. Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age. Genome Med.12(1), 25 (2020).
  • York TP , LatendresseSJ , Jackson-CookCet al. Replicated umbilical cord blood DNA methylation loci associated with gestational age at birth. Epigenetics15(11), 1243–1258 (2020).
  • Bakker R , SteegersEA , ObradovA , RaatH , HofmanA , JaddoeVW. Maternal caffeine intake from coffee and tea, fetal growth, and the risks of adverse birth outcomes: the Generation R Study. Am. J. Clin. Nutr.91(6), 1691–1698 (2010).
  • Hoyt AT , BrowneM , RichardsonS , RomittiP , DruschelC. Maternal caffeine consumption and small for gestational age births: results from a population-based case–control study. Matern. Child Health J.18(6), 1540–1551 (2014).
  • Elwert F , WinshipC. Endogenous selection bias: the problem of conditioning on a collider variable. Annu. Rev. Sociol.40, 31–53 (2014).
  • Sharp GC , AlfanoR , GhantousAet al. Paternal body mass index and offspring DNA methylation: findings from the PACE consortium. Int. J. Epidemiol.50(4), 1297–1315 (2021).
  • Joubert BR , FelixJF , YousefiPet al. DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis. Am. J. Hum. Genet.98(4), 680–696 (2016).
  • Tukey JW . Biometric Journal. Exploratory Data Analysis. Addison-Wesley Publishing Company Reading, Mass23( 4), 413–414 (1981).
  • Leek JT , JohnsonWE , ParkerHSet al. sva: Surrogate Variable Analysis. R package version 3.38.0. (2020). https://bioconductor.org/packages/release/bioc/html/sva.html
  • Ritchie ME , PhipsonB , WuDet al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res.43(7), e47 (2015).
  • Van der Most PJ , KüpersLK , SniederH , NolteI. QCEWAS: automated quality control of results of epigenome-wide association studies. Bioinformatics33(8), 1243–1245 (2017).
  • Suderman M , StaleyJR , FrenchR , ArathimosR , SimpkinA , TillingK. dmrff: identifying differentially methylated regions efficiently with power and control. bioRxiv doi:10.1101/508556 (2018).
  • Odintsova VV , SudermanM , HagenbeekFAet al. DNA methylation in peripheral tissues and left-handedness. Sci. Rep.12, 5606 (2022).
  • Suderman M , HemaniG , MinJL. meffil: Efficient algorithms for DNA methylation. R package version 1.1.1 (2021). https://github.com/perishky/meffil
  • Willer CJ , LiY , AbecasisGR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics26(17), 2190–2191 (2010).
  • Benjamini Y , HochbergY. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological)57(1), 289–300 (1995).
  • Viechtbauer W . Conducting meta-analyses in R with the metafor package. J. Stat. Softw.36(3), 1–48 (2010).
  • Phipson B , MaksimovicJ , OshlackA. missMethyl: an R package for analysing methylation data from Illumina’s HumanMethylation450 platform. Bioinformaticsbtv560 doi:10.1093/bioinformatics/btv560 (2015).
  • Stelzer G , RosenN , PlaschkesIet al. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr. Protoc. Bioinformatics54(1), (2016).
  • The Coffee and Caffeine Genetics Consortium, International Parkinson’s Disease Genomics Consortium, North American Brain Expression Consortium et al. Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption. Mol. Psychiatry20(5), 647–656 (2015).
  • Chen L , BellEM , BrowneML , DruschelCM , RomittiPA. Exploring maternal patterns of dietary caffeine consumption before conception and during pregnancy. Matern. Child Health J.18(10), 2446–2455 (2014).
  • Lawson CC , LeMastersGK , WilsonKA. Changes in caffeine consumption as a signal of pregnancy. Reprod. Toxicol.18(5), 625–633 (2004).
  • Schreiber GB , MaffeoCE , RobinsM , MastersMN , BondAP. Measurement of coffee and caffeine intake: implications for epidemiologic research. Prev. Med.17(3), 280–294 (1988).
  • Sharp GC , LawlorDA , RichardsonSS. It’s the mother!: how assumptions about the causal primacy of maternal effects influence research on the developmental origins of health and disease. Soc. Sci. Med.213, 20–27 (2018).
  • Murphy C , BrownT , TrickeyHet al. It remains unclear whether caffeine causes adverse pregnancy outcomes; but naive policy recommendations could cause harm [Letter to the editor] (2020). https://ebm.bmj.com/content/26/3/114.responses#it-remains-unclear-whether-caffeine-causes-adverse-pregnancy-outcomes-but-naive-policy-recommendations-could-cause-harm
  • Verster JC , KoenigJ. Caffeine intake and its sources: a review of national representative studies. Crit. Rev. Food Sci. Nutr.58(8), 1250–1259 (2018).
  • van Dam RM , HuFB , WillettWC. Coffee, caffeine, and health. N. Engl. J. Med.383(4), 369–378 (2020).
  • Lövkvist C , DoddIB , SneppenK , HaerterJO. DNA methylation in human epigenomes depends on local topology of CpG sites. Nucleic Acids Res.44(11), 5123–5132 (2016).
  • Walton E , ReltonCL , CaramaschiD. Using openly accessible resources to strengthen causal inference in epigenetic epidemiology of neurodevelopment and mental health. Genes10(3), 193 (2019).
  • Rakyan VK , DownTA , BaldingDJ , BeckS. Epigenome-wide association studies for common human diseases. Nat. Rev. Genet.12(8), 529–541 (2011).
  • Boylan SM , CadeJE , KirkSFLet al. Assessing caffeine exposure in pregnant women. Br. J. Nutr.100(4), 875–882 (2008).
  • Cornelis M , KacprowskiT , MenniCet al. Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior. Hum. Mol. Genet.5472–5482 doi:10.1093/hmg/ddw334 (2016).
  • Davey-Smith G . Assessing intrauterine influences on offspring health outcomes: can epidemiological studies yield robust findings?Basic Clin. Pharmacol. Toxicol.102(2), 245–256 (2008).
  • Easey KE , SharpGC. The impact of paternal alcohol, tobacco, caffeine use and physical activity on offspring mental health: a systematic review and meta-analysis. Reprod. Health18, 214 (2021).