Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-27T11:51:50.832Z Has data issue: false hasContentIssue false
  • English
  • Français

The role of genetics in fetal programming of adult cardiometabolic disease

Published online by Cambridge University Press:  28 June 2021

Carlos Sánchez-Soriano Open the ORCID record for Carlos Sánchez-Soriano [Opens in a new window] ,
Ewan R. Pearson Open the ORCID record for Ewan R. Pearson [Opens in a new window]  and
Rebecca M. Reynolds Open the ORCID record for Rebecca M. Reynolds [Opens in a new window]
Carlos Sánchez-Soriano
Affiliation:
The University of Edinburgh, The Queen’s Medical Research Institute, Deanery of Molecular, Genetic and Population Health Sciences, Edinburgh, Midlothian, EH16 4TJ, UK
Ewan R. Pearson
Affiliation:
The University of Dundee, Ninewells Hospital and School of Medicine, Division of Population Health and Genomics, Dundee, Tayside, DD2 1UB, UK
Rebecca M. Reynolds*
Affiliation:
The University of Edinburgh, The Queen’s Medical Research Institute, Deanery of Molecular, Genetic and Population Health Sciences, Edinburgh, Midlothian, EH16 4TJ, UK
*
*Address for correspondence: Rebecca M. Reynolds, Queen’s Medical Research Institute, Edinburgh Bioquarter, 47 Little France Crescent, Edinburgh EH164TJ. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Disturbances affecting early development have broad repercussions on the individual’s health during infancy and adulthood. Multiple observational studies throughout the years have shown that alterations of fetal growth are associated with increased cardiometabolic disease risks. However, the genetic component of this association only started to be investigated in the last 40 years, when single genes with distinct effects were investigated. Birth weight (BW), commonly reported as the outcome of developmental growth, has been estimated to be 20% to 60% heritable. Through Genome-Wide Association (GWA) meta-analyses, 190 different loci have been identified being associated with BW, and while many of these loci designate genes involved in glucose and lipid metabolism, with clear ties to fetal development, the role of others is not yet understood. In addition, due to its influence over the intrauterine environment, the maternal genotype also plays an important part in the determination of offspring BW, with the same loci having independent effects of different magnitude or even direction. There is still much to uncover regarding the genetic determinants of BW and the interactions between maternal, offspring, and even paternal genotype. To fully understand these, diverse and novel cohorts from multiple ancestries collecting extensive neonatal phenotype will be needed. This review compiles, chronologically, the main findings in the investigation of the genetics of BW.

Keywords

Fetal programminggeneticsbirth weightmetabolic disease
Type
Review
Information
Journal of Developmental Origins of Health and Disease , Volume 13 , Issue 3 , June 2022 , pp. 292 - 299
Check for updates
Copyright
© The Author(s), 2021. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alambert, RP, de Gusmão Correia, ML. Effects of fetal programming on metabolic syndrome. In Diet Nutrition and Fetal Programming (eds. Rajendram, R, Preedy, VR, Patel, VB), 2017; pp. 439–451. Springer International Publishing, Cham.CrossRefGoogle Scholar
Hoffman, DJ, Reynolds, RM, Hardy, DB. Developmental origins of health and disease: current knowledge and potential mechanisms. Nutr Rev. 2017; 75, 951–970.CrossRefGoogle ScholarPubMed
Gluckman, PD, Buklijas, T, Hanson, MA. The developmental origins of health and disease (DOHaD) concept. In   Epigenome and Developmental Origins of Health and Disease (eds. Rosenfeld CS), 2016; pp. 1–15. Elsevier, Amsterdam.Google Scholar
Waterland, RA, Garza, C. Potential mechanisms of metabolic imprinting that lead to chronic disease. Am J Clin Nutr. 1999; 69, 179–197.CrossRefGoogle ScholarPubMed
Bateson, P, Barker, D, Clutton-Brock, T, et al. Developmental plasticity and human health. Nature. 2004; 430, 419–421.CrossRefGoogle ScholarPubMed
Workalemahu, T, Grantz, KL, Grewal, J, Zhang, C, Louis, GMB, Tekola-Ayele, F. Genetic and environmental influences on fetal growth vary during sensitive periods in pregnancy. Sci Rep. 2018; 8, 7274.CrossRefGoogle ScholarPubMed
Madden, RA, McCartney, DL, Walker, RM, et al. Birth weight associations with psychiatric and physical health, cognitive function, and DNA methylation differences in an adult population. Genomics. 2019; 16, 783–796.Google Scholar
Lumey, LH, Stein, AD, Susser, E. Prenatal famine and adult health. Annu Rev Public Health. 2011; 32, 237–262.CrossRefGoogle ScholarPubMed
Sutton, EF, Gilmore, LA, Dunger, DB, et al. Developmental programming: state-of-the-science and future directions-summary from a Pennington biomedical symposium: nutritional developmental programming. Obesity. 2016; 24, 1018–1026.CrossRefGoogle Scholar
Langley-Evans, SC. Developmental programming of health and disease. Proc Nutr Soc. 2006; 65, 97–105.CrossRefGoogle ScholarPubMed
Nathanielsz, PW. Animal models that elucidate basic principles of the developmental origins of adult diseases. ILAR J. 2006; 47, 73–82.CrossRefGoogle ScholarPubMed
de Gusmão Correia, ML, Volpato, AM, Águila, MB, Mandarim-de-Lacerda, CA. Developmental origins of health and disease: experimental and human evidence of fetal programming for metabolic syndrome. J Hum Hypertens. 2012; 26, 405–419.CrossRefGoogle ScholarPubMed
Ozanne, SE, Constância, M. Mechanisms of disease: the developmental origins of disease and the role of the epigenotype. Nat Clin Pract Endocrinol Metab. 2007; 3, 539–546.CrossRefGoogle ScholarPubMed
Zhu, Z, Cao, F, Li, X. Epigenetic programming and fetal metabolic programming. Front Endocrinol. 2019; 10, 764.CrossRefGoogle ScholarPubMed
Hocher, B. More than genes: the advanced fetal programming hypothesis. J Reprod Immunol. 2014; 104–105, 8–11.CrossRefGoogle ScholarPubMed
Wang, Q, Lu, Q, Zhao, H. A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing. Front Genet. 2015; 6, 149.CrossRefGoogle ScholarPubMed
Stark, Z, Dolman, L, Manolio, TA, et al. Integrating genomics into healthcare: a global responsibility. Am J Hum Genet. 2019; 104, 13–20.CrossRefGoogle ScholarPubMed
Hackman, E, Emanuel, I, Van Belle, B, Daling, J. Maternal birth weight and subsequent pregnancy outcome. JAMA. 1983; 250, 2016–2019.CrossRefGoogle ScholarPubMed
Emanuel, I, Filakti, H, Alberman, E, Evans, SJ. Intergenerational studies of human birthweight from the 1958 birth cohort. 1. Evidence for a multigenerational effect. Br J Obstet Gynaecol. 1992; 99, 67–74.CrossRefGoogle ScholarPubMed
Magnus, P. Paternal contribution to birth weight. J Epidemiol Community Health. 2001; 55, 873–877.CrossRefGoogle ScholarPubMed
Breschi, MC, Seghieri, G, Bartolomei, G, Gironi, A, Baldi, S, Ferrannini, E. Relation of birthweight to maternal plasma glucose and insulin concentrations during normal pregnancy. Diabetologia. 1993; 36, 1315–1321.CrossRefGoogle ScholarPubMed
Valero de Bernabé, J, Soriano, T, Alb aladejo, R, et al. Risk factors for low birth weight: a review. Eur J Obstet Gynecol Reprod Biol. 2004; 116, 3–15.CrossRefGoogle ScholarPubMed
Sacks, DA, Liu, AI, Wolde-Tsadik, G, Amini, SB, Huston-Presley, L, Catalano, PM. What proportion of birth weight is attributable to maternal glucose among infants of diabetic women? Am J Obstet Gynecol. 2006; 194, 501–507.CrossRefGoogle ScholarPubMed
Magnus, P. Causes of variation in birth weight: a study of offspring of twins. Clin Genet. 1984; 25, 15–24.CrossRefGoogle ScholarPubMed
Clausson, B, Lichtenstein, P, Cnattingius, S. Genetic influence on birthweight and gestational length determined by studies in offspring of twins. BJOG Int J Obstet Gynaecol. 2000; 107, 375–381.CrossRefGoogle ScholarPubMed
Lunde, A, Melve, KK, Gjessing, HK, Skjaerven, R, Irgens, LM. Genetic and environmental influences on birth weight, birth length, head circumference, and gestational age by use of population-based parent-offspring data. Am J Epidemiol. 2007; 165, 734–741.CrossRefGoogle ScholarPubMed
Mook-Kanamori, DO, van Beijsterveldt, CEM, Steegers, EAP, et al. Heritability estimates of body size in fetal life and early childhood. PLoS One. 2012; 7, e39901.CrossRefGoogle ScholarPubMed
Horikoshi, M, Beaumont, RN, Day, FR, et al. Genome-wide associations for birth weight and correlations with adult disease. Nature. 2016; 538, 248–252.CrossRefGoogle ScholarPubMed
Beaumont, RN, Warrington, NM, Cavadino, A, et al. Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics. Hum Mol Genet. 2018; 27, 742–756.CrossRefGoogle ScholarPubMed
Warrington, NM, Beaumont, RN, Horikoshi, M, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 2019; 51, 804–814.CrossRefGoogle ScholarPubMed
Hales, CN, Barker, DJ, Clark, PM. Fetal and infant growth and impaired glucose tolerance at age 64. BMJ. 1991; 303, 1019–1022.CrossRefGoogle ScholarPubMed
Phipps, K, Barker, D, Hales, C, Fall, C, Osmond, C, Clark, P. Fetal growth and impaired glucose tolerance in men and women. Diabetologia. 1993; 36, 225–228.CrossRefGoogle ScholarPubMed
Hattersley, AT, Beards, F, Ballantyne, E, Appleton, M, Harvey, R, Ellard, S. Mutations in the glucokinase gene of the fetus result in reduced birth weight. Nat Genet. 1998; 19, 268–270.CrossRefGoogle ScholarPubMed
Weedon, MN, Frayling, TM, Shields, B, et al. Genetic regulation of birth weight and fasting glucose by a common polymorphism in the islet cell promoter of the glucokinase gene. Diabetes. 2005; 54, 576–581.CrossRefGoogle ScholarPubMed
Pawlowski, M, Kouklinos, A, Jopp-Petzina, G, et al. G/A polymorphism at –258 of the hepatic glucokinase promoter is not associated with decreased birth weight in preterm neonates. Neonatology. 2008; 94, 71–74.CrossRefGoogle Scholar
Hattersley, AT, Tooke, JE. The fetal insulin hypothesis: an alternative explanation of the association of low birthweight with diabetes and vascular disease. Lancet. 1999; 353, 1789–1792.CrossRefGoogle ScholarPubMed
Dunger, DB, Ong, KKL, Huxtable, SJ, et al. Association of the INS VNTR with size at birth. Nat Genet. 1998; 19, 98–100.CrossRefGoogle ScholarPubMed
Bennett, AJ, Sovio, U, Ruokonen, A, et al. Variation at the insulin gene VNTR (variable number tandem repeat) polymorphism and early growth: studies in a large Finnish birth cohort. Diabetes. 2004; 53, 2126–2131.CrossRefGoogle Scholar
Rasmussen, SK. Variability of the insulin receptor substrate-1, hepatocyte nuclear factor-1 (HNF-1), HNF-4, and HNF-6 genes and size at birth in a population-based sample of young Danish subjects. J Clin Endocrinol Metab. 2000; 85, 2951–2953.Google Scholar
Weedon, MN, Gloyn, AL, Davey Smith, G, Ben-Shlomo, Y, Frayling, TM, Hattersley, AT. Quantitative traits associated with the Type 2 diabetes susceptibility allele in Kir6.2. Diabetologia. 2003; 46, 1021–1023.CrossRefGoogle ScholarPubMed
Pfab, T, Poralla, C, Richter, C-M, et al. Fetal and maternal peroxisome proliferator-activated receptor γ2 pro12ala does not influence birth weight. Obesity. 2006; 14, 1880–1885.CrossRefGoogle Scholar
Bennett, AJ, Sovio, U, Ruokonen, A, et al. No evidence that established type 2 diabetes susceptibility variants in the PPARG and KCNJ11 genes have pleiotropic effects on early growth. Diabetologia. 2007; 51, 82–85.CrossRefGoogle ScholarPubMed
Kaku, K, Osada, H, Seki, K, Sekiya, S. Insulin-like growth factor 2 (IGF2) and IGF2 receptor gene variants are associated with fetal growth. Acta Paediatr. 2007; 96, 363–367.CrossRefGoogle ScholarPubMed
Petry, CJ, Ong, KK, Barratt, BJ, et al. Common polymorphism in H19 associated with birthweight and cord blood IGF-II levels in humans. BMC Genet. 2005; 6, 22.CrossRefGoogle ScholarPubMed
Zhang, C, Qi, L, Hunter, DJ, et al. Variant of transcription factor 7-like 2 (TCF7L2) Gene and the risk of type 2 diabetes in large cohorts of U.S. women and men. Diabetes. 2006; 55, 2645–2648.CrossRefGoogle ScholarPubMed
Freathy, RM, Weedon, MN, Bennett, A, et al. Type 2 diabetes TCF7L2 risk genotypes alter birth weight: a study of 24,053 individuals. Am J Hum Genet. 2007; 80, 1150–1161.CrossRefGoogle ScholarPubMed
Bernstein, IM, Mongeon, JA, Badger, GJ, Solomon, L, Heil, SH, Higgins, ST. Maternal smoking and its association with birth weight. Obstet Gynecol. 2005; 106, 986–991.CrossRefGoogle ScholarPubMed
Prokopenko, I, McCarthy, MI, Lindgren, CM. Type 2 diabetes: new genes, new understanding. Trends Genet. 2008; 24, 613–621.CrossRefGoogle ScholarPubMed
Pulizzi, N, Lyssenko, V, Jonsson, A, et al. Interaction between prenatal growth and high-risk genotypes in the development of type 2 diabetes. Diabetologia. 2009; 52, 825–829.CrossRefGoogle ScholarPubMed
Freathy, RM, Bennett, AJ, Ring, SM, et al. Type 2 diabetes risk alleles are associated with reduced size at birth. Diabetes. 2009; 58, 1428–1433.CrossRefGoogle ScholarPubMed
Zhao, J, Li, M, Bradfield, JP, et al. Examination of type 2 diabetes loci implicates CDKAL1 as a birth weight gene. Diabetes. 2009; 58, 2414–2418.CrossRefGoogle ScholarPubMed
Adkins, RM, Somes, G, Morrison, JC, et al. Association of birth weight with polymorphisms in the IGF2, H19 and IGF2R genes. Pediatr Res. 2010; 68, 429–434.Google ScholarPubMed
Gomes, MVM, Soares, MR, Pasqualim-Neto, A, Marcondes, CR, Lôbo, RB, Ramos, ES. Association between birth weight, body mass index and IGF2/ApaI polymorphism. Growth Horm IGF Res. 2005; 15, 360–362.CrossRefGoogle ScholarPubMed
Heude, B, Ong, KK, Luben, R, Wareham, NJ, Sandhu, MS. Study of association between common variation in the insulin-like growth factor 2 gene and indices of obesity and body size in middle-aged men and women. J Clin Endocrinol Metab. 2007; 92, 2734–2738.CrossRefGoogle ScholarPubMed
Magnus, P. Further evidence for a significant effect of fetal genes on variation in birth weight. Clin Genet. 1984; 26, 289–296.CrossRefGoogle ScholarPubMed
Eaves, LJ, Pourcain, BST, Smith, GD, York, TP, Evans, DM. Resolving the effects of maternal and offspring genotype on dyadic outcomes in genome wide complex trait analysis (“M-GCTA”). Behav Genet. 2014; 44, 445–455.CrossRefGoogle Scholar
Hughes, AE, Nodzenski, M, Beaumont, RN, et al. Fetal genotype and maternal glucose have independent and additive effects on birth weight. Diabetes. 2018; 67, 1024–1029.CrossRefGoogle ScholarPubMed
Jak, S. Introduction to meta-analysis and structural equation modeling. In Meta-Analytic Structural Equation Modeling (ed. Jak S), 2015; pp. 1–14. Springer International Publishing, Cham.Google Scholar
Warrington, NM, Freathy, RM, Neale, MC, Evans, DM. Using structural equation modelling to jointly estimate maternal and fetal effects on birthweight in the UK Biobank. Int J Epidemiol. 2018; 47, 1229–1241.CrossRefGoogle ScholarPubMed
Davey Smith, G, Ebrahim, S. Mendelian randomization: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003; 32, 1–22.CrossRefGoogle Scholar
Pierce, BL, Burgess, S. Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am J Epidemiol. 2013; 178, 1177–1184.CrossRefGoogle ScholarPubMed
Freathy, RM, The Genetic Investigation of Anthropometric Traits (GIANT) Consortium, The Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), et al. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight. Nat Genet. 2010; 42, 430–435.CrossRefGoogle ScholarPubMed
Dupuis, J, DIAGRAM Consortium, GIANT Consortium, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010; 42, 105–116.CrossRefGoogle ScholarPubMed
Horikoshi, M, The Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), Early Growth Genetics (EGG) Consortium, et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat Genet. 2013; 45, 76–82.CrossRefGoogle ScholarPubMed
Kasuga, M. KCNQ1, a susceptibility gene for type 2 diabetes: editorial. J Diabetes Investig. 2011; 2, 413–414.CrossRefGoogle Scholar
Liao, S, Liu, Y, Tan, Y, et al. Association of genetic variants of melatonin receptor 1B with gestational plasma glucose level and risk of glucose intolerance in pregnant Chinese women. PLoS One. 2012; 7, e40113.CrossRefGoogle ScholarPubMed
Johnson, AD, Newton-Cheh, C, Chasman, DI, et al. Association of hypertension drug target genes with blood pressure and hypertension in 86 588 individuals. Hypertension. 2011; 57, 903–910.CrossRefGoogle ScholarPubMed
Weedon, MN, The Diabetes Genetics Initiative, The Wellcome Trust Case Control Consortium, et al. A common variant of HMGA2 is associated with adult and childhood height in the general population. Nat Genet. 2007; 39, 1245–1250.CrossRefGoogle ScholarPubMed
Weedon, MN, Diabetes Genetics Initiative, The Wellcome Trust Case Control Consortium, et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet. 2008; 40, 575–583.CrossRefGoogle ScholarPubMed
Zhang, G, Feenstra, B, Bacelis, J, et al. Genetic associations with gestational duration and spontaneous preterm birth. N Engl J Med. 2017; 377, 1156–1167.CrossRefGoogle ScholarPubMed
Qiao, Z, Zheng, J, Helgeland, Ø, et al. Introducing M-GCTA a software package to estimate maternal (or paternal) genetic effects on offspring phenotypes. Behav Genet. 2020; 50, 51–66.CrossRefGoogle ScholarPubMed
Wang, T, Huang, T, Li, Y, et al. Low birthweight and risk of type 2 diabetes: a Mendelian randomisation study. Diabetologia. 2016; 59, 1920–1927.CrossRefGoogle ScholarPubMed
Zanetti, D, Tikkanen, E, Gustafsson, S, Priest, JR, Burgess, S, Ingelsson, E. Birthweight, type 2 diabetes mellitus, and cardiovascular disease: addressing the barker hypothesis with Mendelian randomization. Circ Genomic Precis Med. 2018; 11, e0020504.CrossRefGoogle ScholarPubMed
Zeng, P, Zhou, X. Causal association between birth weight and adult diseases: evidence from a Mendelian randomization analysis. Front Genet. 2019; 10, 618.CrossRefGoogle ScholarPubMed
Huang, T, Wang, T, Zheng, Y, et al. Association of birth weight with type 2 diabetes and glycemic traits: a Mendelian randomization study. JAMA Netw Open. 2019; 2, e1910915.Google ScholarPubMed
Kember, RL, Levin, MG, Cousminer, DL, et al. Genetically determined birthweight associates with atrial fibrillation: a Mendelian randomization study. Circ Genomic Precis Med. 2020; 13, e002553.CrossRefGoogle ScholarPubMed
Lawlor, DA, Richmond, R, Warrington, N, et al. Using Mendelian randomization to determine causal effects of maternal pregnancy (intrauterine) exposures on offspring outcomes: Sources of bias and methods for assessing them. Wellcome Open Res. 2017; 2, 11.CrossRefGoogle Scholar
Evans, DM, Moen, G-H, Hwang, L-D, Lawlor, DA, Warrington, NM. Elucidating the role of maternal environmental exposures on offspring health and disease using two-sample Mendelian randomization. Int J Epidemiol. 2019; 48, 861–875.CrossRefGoogle ScholarPubMed
D’Urso, S, Wang, G, Hwang, L-D, Moen, G-H, Warrington, NM, Evans, DM. A cautionary note on using Mendelian randomization to examine the Barker hypothesis and developmental origins of health and disease (DOHaD). J Dev Orig Health Dis. 2020; 1–6 First View.Google Scholar
Moen, G-H, Brumpton, B, Willer, C, et al. Mendelian randomization study of maternal influences on birthweight and future cardiometabolic risk in the HUNT cohort. Nat Commun. 2020; 11, 5404.CrossRefGoogle ScholarPubMed
Chen, J, Bacelis, J, Sole-Navais, P, et al. Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes, and adult phenotypes: a Mendelian-randomization and haplotype-based genetic score analysis in 10,734 mother–infant pairs. PLOS Med. 2020; 17, e1003305.CrossRefGoogle ScholarPubMed
Tyrrell, J, Richmond, RC, Palmer, TM, et al. Genetic evidence for causal relationships between maternal obesity-related traits and birth weight. JAMA. 2016; 315, 1129.CrossRefGoogle ScholarPubMed
Zhang, G, Bacelis, J, Lengyel, C, et al. Assessing the causal relationship of maternal height on birth size and gestational age at birth: a Mendelian randomization analysis. PLOS Med. 2015; 12, e1001865.CrossRefGoogle ScholarPubMed
Middeldorp, CM, Early Genetics Lifecourse Epidemiology (EAGLE) Consortium, EArly Growth Genetics (EGG) consortium, Felix, JF, Mahajan, A, McCarthy, MI. The early growth genetics (EGG) and EArly genetics and lifecourse epidemiology (EAGLE) consortia: design, results and future prospects. Eur J Epidemiol. 2019; 34, 279–300.CrossRefGoogle ScholarPubMed
Wilcox, AJ, Weinberg, CR, Basso, O. On the pitfalls of adjusting for gestational age at birth. Am J Epidemiol. 2011; 174, 1062–1068.CrossRefGoogle ScholarPubMed
Griffiths, LJ, Dezateux, C, Cole, TJ, Millennium Cohort Study Child Health Group. Differential parental weight and height contributions to offspring birthweight and weight gain in infancy. Int J Epidemiol. 2007; 36, 104–107.CrossRefGoogle ScholarPubMed
Rice, F, Thapar, A. Estimating the relative contributions of maternal genetic, paternal genetic and intrauterine factors to offspring birth weight and head circumference. Early Hum Dev. 2010; 86, 425–432.CrossRefGoogle ScholarPubMed
Fowden, AL, Coan, PM, Angiolini, E, Burton, GJ, Constancia, M. Imprinted genes and the epigenetic regulation of placental phenotype. Prog Biophys Mol Biol. 2011; 106, 281–288.CrossRefGoogle ScholarPubMed
Koukoura, O, Sifakis, S, Spandidos, DA. DNA methylation in the human placenta and fetal growth (Review). Mol Med Rep. 2012; 5, 883–889.CrossRefGoogle Scholar
Wang, X, Miller, DC, Harman, R, Antczak, DF, Clark, AG. Paternally expressed genes predominate in the placenta. Proc Natl Acad Sci. 2013; 110, 10705–10710.CrossRefGoogle ScholarPubMed
Herzog, EM, Eggink, AJ, Willemsen, SP, et al. The tissue-specific aspect of genome-wide DNA methylation in newborn and placental tissues: implications for epigenetic epidemiologic studies. J Dev Orig Health Dis. 2020; 12, 1–11.Google ScholarPubMed
Haig, D. Genetic conflicts in human pregnancy. Q Rev Biol. 1993; 68, 495–532.CrossRefGoogle ScholarPubMed
Simpkin, AJ, Suderman, M, Gaunt, TR, et al. Longitudinal analysis of DNA methylation associated with birth weight and gestational age. Hum Mol Genet. 2015; 24, 3752–3763.CrossRefGoogle ScholarPubMed
Agha, G, Hajj, H, Rifas-Shiman, SL, et al. Birth weight-for-gestational age is associated with DNA methylation at birth and in childhood. Clin Epigenetics. 2016; 8, 118.CrossRefGoogle ScholarPubMed
Küpers, LK, Monnereau, C, Sharp, GC, et al. Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight. Nat Commun. 2019; 10, 1893.CrossRefGoogle ScholarPubMed
Yokoyama, Y, Jelenkovic, A, Hur, Y-M, et al. Genetic and environmental factors affecting birth size variation: a pooled individual-based analysis of secular trends and global geographical differences using 26 twin cohorts. Int J Epidemiol. 2018; 47, 1195–1206.CrossRefGoogle ScholarPubMed