Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-25T20:18:50.907Z Has data issue: false hasContentIssue false

Section IV - Mechanisms

Published online by Cambridge University Press:  01 December 2022

Lucilla Poston
Affiliation:
King's College London
Keith M. Godfrey
Affiliation:
University of Southampton
Peter D. Gluckman
Affiliation:
University of Auckland
Mark A. Hanson
Affiliation:
University of Southampton
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2022

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

References

Gluckman, PD, Hanson, MA, Cooper, C, Thornburg, KL. Effect of in Utero and Early-Life Conditions on Adult Health and Disease. The New England Journal of Medicine. 2008;359(1), 61–73.Google Scholar
Yach, D, Leeder SR, Bell J, Kistnasamy B. Global chronic diseases. Science. 2005 Jan 21;307(5708):317. doi: 10.1126/science.1108656. PMID: 15661976.Google Scholar
Burton, GJ, Fowden, AL, Thornburg, KL. Placental origins of chronic disease. Physiological Reviews. 2016; 96(4), 1509–1565.Google Scholar
Jonker, SS, Louey, S, Giraud, GD, Thornburg, KL, Faber, JJ. Timing of cardiomyocyte growth, maturation, and attrition in perinatal sheep. FASEB Journal: Official Publication of the Federation of American Societies for Experimental Biology. 2015; 29(10), 4346–4357.Google Scholar
Jiang, B, Godfrey, KM, Martyn, CN, Gale, CR. Birth weight and cardiac structure in children. Pediatrics. 2006; 117(2), e257261.Google Scholar
Mygind, ND, Michelsen, MM, Penna, A, et al. Coronary microvascular function and cardiovascular risk factors in women with angina pectoris and no obstructive coronary artery disease: the iPOWER study. Journal of the American Heart Association. 2016.Google Scholar
Martyn, CN, Barker, DJ, Jespersen, S, Greenwald, S, Osmond, C, Berry, C. Growth in utero, adult blood pressure, and arterial compliance. British Heart Journal. 1995; 73(2), 116–121.Google Scholar
Thornburg, KL, Drake, R, Valent, AM. Maternal hypertension affects heart growth in offspring. Journal of the American Heart Association. 2020; 9(9), e016538.Google Scholar
Tibayan, FA, Louey, S, Jonker, S, et al. Increased systolic load causes adverse remodeling of fetal aortic and mitral valves. American Journal of Physiology Regulatory, Integrative and Comparative Physiology. 2015; 309(12), R14901498.Google Scholar
Brenner, BM, Garcia, DL, Anderson, S. Glomeruli and blood pressure. Less of one, more the other? American Journal of Hypertension. 1988; 1(4 Pt 1), 335–347.Google Scholar
Cullen-McEwen, LA, Armitage, JA, Nyengaard, JR, Bertram, JF. Estimating nephron number in the developing kidney using the physical disector/fractionator combination. Methods in Molecular Biology (Clifton, NJ). 2012; 886, 109–119.Google Scholar
Beeman, SC, Cullen-McEwen, LA, Puelles, VG, et al. MRI-based glomerular morphology and pathology in whole human kidneys. American Journal of Physiology. Renal Physiology. 2014; 306(11), F13811390.Google Scholar
Baldelomar, EJ, Charlton, JR, Beeman, SC, Bennett, KM. Measuring rat kidney glomerular number and size in vivo with MRI. American Journal of Physiology. Renal Physiology. 2018; 314(3), F399f406.Google Scholar
Denic, A, Mathew, J, Lerman, LO, et al. Single-nephron glomerular filtration rate in healthy adults. The New England Journal of Medicine. 2017; 376(24), 2349–2357.Google Scholar
Sasaki, T, Tsuboi, N, Okabayashi, Y, et al. Estimation of nephron number in living humans by combining unenhanced computed tomography with biopsy-based stereology. Scientific Reports. 2019; 9(1), 14400.Google Scholar
Klingberg, A, Hasenberg, A, Ludwig-Portugall, I, et al. Fully automated evaluation of total glomerular number and capillary tuft size in nephritic kidneys using lightsheet microscopy. Journal of the American Society of Nephrology: JASN. 2017; 28(2), 452–459.Google Scholar
Gonçalves, GD, Walton, SL, Gazzard, SE, et al. Maternal hypoxia developmentally programs low podocyte endowment in male, but not female offspring. Anatomical Record (Hoboken, NJ: 2007). 2020; doi: 10.1002/ar.24369.Google Scholar
Wesolowski, SR, Kasmi, KC, Jonscher, KR, Friedman, JE. Developmental origins of NAFLD: a womb with a clue. Nature Reviews Gastroenterology & Hepatology. 2017; 14(2), 81–96.Google Scholar
Bush, H, Golabi, P, Younossi, ZM. Pediatric non-alcoholic fatty liver disease. Children (Basel, Switzerland). 2017; 4(6), 48.Google Scholar
Higashi, T, Friedman, SL, Hoshida, Y. Hepatic stellate cells as key target in liver fibrosis. Advanced Drug Delivery Reviews. 2017;121, 27–42.Google Scholar
Mikkola, HK, Orkin, SH. The journey of developing hematopoietic stem cells. Development. 2006; 133 (19), 3733–3744.Google Scholar
Koyama, Y, Brenner, DA. Liver inflammation and fibrosis. The Journal of Clinical Investigation. 2017; 127(1), 55–64.Google Scholar
Thiele, K, Kessler, T, Arck, P, Erhardt, A, Tiegs, G. Acetaminophen and pregnancy: short- and long-term consequences for mother and child. Journal of Reproductive Immunology. 2013; 97(1), 128–139.Google Scholar
Karimi, K, Keßler, T, Thiele, K, et al. Prenatal acetaminophen induces liver toxicity in dams, reduces fetal liver stem cells, and increases airway inflammation in adult offspring. Journal of Hepatology. 2015; 62(5), 1085–1091.Google Scholar
Nathanielsz, PW, Hanson, MA. The fetal dilemma: spare the brain and spoil the liver. The Journal of Physiology. 2003; 548(Pt 2), 333.Google Scholar
Gao, F, Liu, Y, Li, L, et al. Effects of maternal undernutrition during late pregnancy on the development and function of ovine fetal liver. Animal Reproduction Science. 2014; 147(3–4), 99–105.Google Scholar
Chamson-Reig, A, Thyssen, SM, Arany, E, Hill, DJ. Altered pancreatic morphology in the offspring of pregnant rats given reduced dietary protein is time and gender specific. The Journal of Endocrinology. 2006; 191(1), 83–92.Google Scholar
Cox, AR, Gottheil, SK, Arany, EJ, Hill, DJ. The effects of low protein during gestation on mouse pancreatic development and beta cell regeneration. Pediatric Research. 2010; 68(1), 16–22.Google Scholar
Rodriguez-Trejo, A, Ortiz-Lopez, MG, Zambrano, E, et al. Developmental programming of neonatal pancreatic beta-cells by a maternal low-protein diet in rats involves a switch from proliferation to differentiation. American Journal of Physiology Endocrinology and Metabolism. 2012; 302(11), E14311439.Google Scholar
Beamish, CA, Strutt, BJ, Arany, EJ, Hill, DJ. Insulin-positive, Glut2-low cells present within mouse pancreas exhibit lineage plasticity and are enriched within extra-islet endocrine cell clusters. Islets. 2016; 8(3), 65–82.Google Scholar
Boujendar, S, Reusens, B, Merezak, S, et al. Taurine supplementation to a low protein diet during foetal and early postnatal life restores a normal proliferation and apoptosis of rat pancreatic islets. Diabetologia. 2002; 45(6), 856–866.Google Scholar
Trudeau, JD, Dutz, JP, Arany, E, Hill, DJ, Fieldus, WE, Finegood, DT. Neonatal beta-cell apoptosis: a trigger for autoimmune diabetes? Diabetes. 2000;49(1), 1–7.Google Scholar
Filiputti, E, Rafacho, A, Araújo, EP, et al. Augmentation of insulin secretion by leucine supplementation in malnourished rats: possible involvement of the phosphatidylinositol 3-phosphate kinase/mammalian target protein of rapamycin pathway. Metabolism. 2010;59(5), 635–644.Google Scholar
Jaafar, R, Tran, S, Shah, AN, et al. mTORC1 to AMPK switching underlies beta-cell metabolic plasticity during maturation and diabetes. The Journal of Clinical Investigation. 2019; 130, 4124–4137.Google Scholar
Van Assche, FA, Aerts, L, De Prins, F. A morphological study of the endocrine pancreas in human pregnancy. British Journal of Obstetrics and Gynaecology. 1978; 85(11), 818–820.Google Scholar
Szlapinski, SK, King, RT, Retta, G, Yeo, E, Strutt, BJ, Hill, DJ. A mouse model of gestational glucose intolerance through exposure to a low protein diet during fetal and neonatal development. The Journal of Physiology. 2019; 597(16), 4237–4250.Google Scholar
Van den Bergh, BRH, van den Heuvel, MI, Lahti, M, et al. Prenatal developmental origins of behavior and mental health: the influence of maternal stress in pregnancy. Neuroscience and Biobehavioral Reviews. 2017; doi: 10.1016/j.neubiorev.2017.07.003.Google Scholar
Markham, JA, Koenig, JI. Prenatal stress: role in psychotic and depressive diseases. Psychopharmacology. 2011; 214(1), 89–106.Google Scholar
Marecková, K, Klasnja, A, Bencurova, P, Andrýsková, L, Brázdil, M, Paus, T. Prenatal stress, mood, and gray matter volume in young adulthood. Cerebral Cortex (New York, NY : 1991). 2019; 29(3), 1244–1250.Google Scholar
Lautarescu, A, Pecheva, D, Nosarti, C, et al. Maternal prenatal stress is associated with altered uncinate fasciculus microstructure in premature neonates. Biological Psychiatry. 2020; 87(6), 559–569.Google Scholar
Faa, G, Manchia, M, Pintus, R, Gerosa, C, Marcialis, MA, Fanos, V. Fetal programming of neuropsychiatric disorders. Birth Defects Research Part C, Embryo Today: Reviews. 2016; 108(3), 207–223.Google Scholar
Monk, C, Georgieff, MK, Osterholm, EA. Research review: maternal prenatal distress and poor nutrition – mutually influencing risk factors affecting infant neurocognitive development. Journal of Child Psychology and Psychiatry, and Allied Disciplines. 2013; 54(2), 115–130.Google Scholar
Pineda, RG, Neil, J, Dierker, D, et al. Alterations in brain structure and neurodevelopmental outcome in preterm infants hospitalized in different neonatal intensive care unit environments. The Journal of Pediatrics. 2014; 164(1), 52–60.e52.Google Scholar
Woodward, LJ, Anderson, PJ, Austin, NC, Howard, K, Inder, TE. Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. The New England Journal of Medicine. 2006; 355(7), 685–694.Google Scholar
Farber, NB, Olney, JW. Drugs of abuse that cause developing neurons to commit suicide. Brain research Developmental Brain Research. 2003; 147(1–2), 37–45.Google Scholar
Lebel, C, Roussotte, F, Sowell, ER. Imaging the impact of prenatal alcohol exposure on the structure of the developing human brain. Neuropsychology Review. 2011; 21(2), 102–118.Google Scholar
Galbraith, CG, Galbraith, JA. Super-resolution microscopy at a glance. Journal of Cell Science. 2011; 124(Pt 10), 1607–1611.Google Scholar
Gustafsson, MG. Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. Proceedings of the National Academy of Sciences of the United States of America. 2005; 102(37), 13081–13086.Google Scholar
Gustafsson, MG. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. Journal of Microscopy. 2000; 198(Pt 2), 82–87.Google Scholar
Jones, SA, Shim, SH, He, J, Zhuang, X. Fast, three-dimensional super-resolution imaging of live cells. Nature Methods. 2011; 8(6), 499–508.Google Scholar
Nienhaus, K, Nienhaus, GU. Where do we stand with super-resolution optical microscopy? Journal of Molecular Biology. 2016; 428(2 Pt A), 308–322.Google Scholar
Scipioni, L, Lanzanó, L, Diaspro, A, Gratton, E. Comprehensive correlation analysis for super-resolution dynamic fingerprinting of cellular compartments using the Zeiss Airyscan detector. Nature Communications. 2018; 9(1), 5120.Google Scholar
Keller, PJ, Schmidt, AD, Wittbrodt, J, Stelzer, EH. Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science (New York, NY). 2008; 322(5904), 1065–1069.Google Scholar
Ahrens, MB, Orger, MB, Robson, DN, Li, JM, Keller, PJ. Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nature Methods. 2013; 10(5), 413–420.Google Scholar
Chen, BC, Legant, WR, Wang, K, et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science (New York, NY). 2014; 346(6208), 1257998.Google Scholar
Dickinson, ME, Bearman, G, Tille, S, Lansford, R, Fraser, SE. Multi-spectral imaging and linear unmixing add a whole new dimension to laser scanning fluorescence microscopy. BioTechniques. 2001; 31(6), 1272, 1274–1276, 1278.Google Scholar
Keren, L, Bosse, M, Thompson, S, et al. MIBI-TOF: a multiplexed imaging platform relates cellular phenotypes and tissue structure. ScienceAadvances. 2019; 5(10), eaax5851.Google Scholar
Kagami, K, Shinmyo, Y, Ono, M, Kawasaki, H, Fujiwara, H. Three-dimensional visualization of intrauterine conceptus through the uterine wall by tissue clearing method. Scientific Reports. 2017; 7(1), 5964.Google Scholar
Jahr, W, Schmid, B, Schmied, C, Fahrbach, FO, Huisken, J. Hyperspectral light sheet microscopy. Nature Communications. 2015; 6, 7990.Google Scholar
Lavagnino, Z, Dwight, J, Ustione, A, Nguyen, TU, Tkaczyk, TS, Piston, DW. Snapshot hyperspectral light-sheet imaging of signal transduction in live pancreatic islets. Biophysical Journal. 2016;111(2), 409–417.Google Scholar
Kolahi, K, Louey, S, Varlamov, O, Thornburg, K. Real-time tracking of BODIPY-C12 long-chain fatty acid in human term placenta reveals unique lipid dynamics in cytotrophoblast cells. PloS one. 2016;11(4), e0153522.Google Scholar
Fu, Q, Martin, BL, Matus, DQ, Gao, L. Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy. Nature Communications. 2016;7, 11088.Google Scholar
Mir, M, Reimer, A, Stadler, M, et al. Single molecule imaging in live embryos using lattice light-sheet microscopy. Methods in Molecular Biology (Clifton, NJ). 2018; 1814, 541–559.Google Scholar
Sundgren, NC, Giraud, GD, Stork, PJ, Maylie, JG, Thornburg, KL. Angiotensin II stimulates hyperplasia but not hypertrophy in immature ovine cardiomyocytes. The Journal of Physiology. 2003; 548(Pt 3), 881–891.Google Scholar
Bennett, KM, Bertram, JF, Beeman, SC, Gretz, N. The emerging role of MRI in quantitative renal glomerular morphology. American Journal of Physiology. Renal Physiology. 2013; 304(10), F12521257.Google Scholar
Workman, AD, Charvet, CJ, Clancy, B, Darlington, RB, Finlay, BL. Modeling transformations of neurodevelopmental sequences across mammalian species. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2013; 33(17), 7368–7383.Google Scholar
Gholipour, A, Rollins, CK, Velasco-Annis, C, et al. A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Scientific Reports. 2017; 7(1), 476.Google Scholar
Isaacson, D, Shen, J, McCreedy, D, Calvey, M, McDevitt, T, Cunha, G, Baskin, L. Lightsheet fluorescence microscopy of branching human fetal kidney. Kidney International. 2018; 93, 55Google Scholar

References

Weaver, I. C. G., et al., Epigenetic programming by maternal behavior. Nature Neuroscience, 2004. 7(8): pp. 847–854.Google Scholar
Anway, M. D., et al., Toxicology: Epigenetic transgenerational actions of endocrine disruptors and male fertility. Science, 2005. 308(5727): pp. 1466–1469.Google Scholar
Cropley, J. E., et al., Germ-line epigenetic modification of the murine Avy allele by nutritional supplementation. Proceedings of the National Academy of Sciences of the United States of America, 2006. 103 (46): pp. 17308–17312.Google Scholar
Waddington, C. H., The epigenotype. 1942. International Journal of Epidemiology, 2012. 41(1): pp. 10–13.Google Scholar
Bird, A., Perceptions of epigenetics. Nature, 2007. 447(7143): pp. 396–398.Google Scholar
Kouzarides, T., Chromatin modifications and their function. Cell, 2007. 128(4): pp. 693–705.Google Scholar
Lyko, F., The DNA methyltransferase family: A versatile toolkit for epigenetic regulation. Nature Reviews Genetics, 2018. 19(2): pp. 81–92.Google Scholar
Kohli, R. M. and Zhang, Y., TET enzymes, TDG and the dynamics of DNA demethylation. Nature, 2013. 502(7472): pp. 472–479.Google Scholar
He, Y. and Ecker, J. R., Non-CG Methylation in the human genome. Annual Review of Genomics and Human Genetics, 2015. 16: pp. 55–77.Google Scholar
Mattick, J. S. and Makunin, I. V., Non-coding RNA. Human Molecular Genetics, 2006. 15 Spec No 1: pp. R17–29.Google Scholar
Lee, J. T., Epigenetic regulation by long noncoding RNAs. Science, 2012. 338(6113): pp. 1435–1439.Google Scholar
Mendell, J. T., MicroRNAs: Critical regulators of development, cellular physiology and malignancy. Cell Cycle, 2005. 4(9): pp. 1179–1184.Google Scholar
Lucifero, D., et al., Gene-specific timing and epigenetic memory in oocyte imprinting. Human molecular genetics, 2004. 13(8): pp. 839–849.Google Scholar
Monk, D., Genomic imprinting in the human placenta. American Journal of Obstetrics and Gynecology, 2015. 213(4): pp. S152S162.Google Scholar
Fleming, T. P., et al., Origins of lifetime health around the time of conception: Causes and consequences. Obstetrical and Gynecological Survey, 2018. 73(10): pp. 555–557.Google Scholar
Guo, H., et al., The DNA methylation landscape of human early embryos. Nature, 2014. 511(7511): pp. 606–610.Google Scholar
Cantone, I. and Fisher, A. G., Epigenetic programming and reprogramming during development. Nature Structural and Molecular Biology, 2013. 20(3): pp. 282–289.Google Scholar
Hanna, C. W., Demond, H., and Kelsey, G., Epigenetic regulation in development: Is the mouse a good model for the human? Human Reproduction Update, 2018. 24(5): pp. 556–576.Google Scholar
Xia, W., et al., Resetting histone modifications during human parental-to-zygotic transition. Science, 2019. 365(6451): pp. 353–360.Google Scholar
Jambhekar, A., Dhall, A., and Shi, Y., Roles and regulation of histone methylation in animal development. Nature Reviews Molecular Cell Biology, 2019. 20(10): pp. 625–641.Google Scholar
Gross, N., Kropp, J., and Khatib, H., MicroRNA signaling in embryo development. Biology, 2017. 6(3).CrossRefGoogle Scholar
Fraga, M. F., et al., Epigenetic differences arise during the lifetime of monozygotic twins. Proceedings of the National Academy of Sciences, 2005. 102(30): pp. 10604–10609.Google Scholar
Hannum, G., et al., Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular cell, 2013. 49(2): pp. 359–367.Google Scholar
Pignolo, R. J., et al., Reducing senescent cell burden in aging and disease. Trends in Molecular Medicine, 2020. 26(7): pp. 630–638.Google Scholar
Horvath, S., DNA methylation age of human tissues and cell types. Genome Biology, 2013. 14(10):R115. doi: 10.1186/gb-2013-14-10-r115.Google Scholar
Knight, A. K., et al., An epigenetic clock for gestational age at birth based on blood methylation data. Genome Biology, 2016. 17(1):206. doi: 10.1186/s13059-016-1068-z.Google Scholar
Lee, Y., et al., Placental epigenetic clocks: Estimating gestational age using placental DNA methylation levels. Aging, 2019. 11(12): pp. 4238–4253.Google Scholar
Girchenko, P., et al., Associations between maternal risk factors of adverse pregnancy and birth outcomes and the offspring epigenetic clock of gestational age at birth. Clinical Epigenetics, 2017. May 8, 9:49. doi: 10.1186/s13148-017-0349-z. eCollection 2017.Google Scholar
Lu, A. T., et al., Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nature Communications, 2017. 8(1): pp. 1–14.Google Scholar
Bjornsson, H. T., et al., Intra-individual change over time in DNA methylation with familial clustering. Jama, 2008. 299(24): pp. 2877–2883.Google Scholar
Gordon, L., et al., Neonatal DNA methylation profile in human twins is specified by a complex interplay between intrauterine environmental and genetic factors, subject to tissue-specific influence. Genome Research, 2012. 22(8): pp. 1395–1406.Google Scholar
Gaunt, T. R., et al., Systematic identification of genetic influences on methylation across the human life course. Genome Biology, 2016. 17(1): pp. 1–14.Google Scholar
Czamara, D., et al., Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns. Nature Communications, 2019. 10(1): pp. 1–18.Google Scholar
Hannon, E., et al., Characterizing genetic and environmental influences on variable DNA methylation using monozygotic and dizygotic twins. PLoS Genetics, 2018. 14(8):e1007544. doi: 10.1371/journal.pgen.1007544. eCollection 2018 Aug.PMID: 30091980.Google Scholar
Teh, A. L., et al., The effect of genotype and in utero environment on interindividual variation in neonate DNA methylomes. Genome Research, 2014. 24(7): pp. 1064–1074.Google Scholar
Luijk, R., et al., Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation. Nature Communications, 2018. 9(1): pp. 1–9.Google Scholar
Gibson, J., et al., A meta-analysis of genome-wide association studies of epigenetic age acceleration. PLoS Genetics, 2019. 15(11): p. e1008104.Google Scholar
Reynolds, C. A., et al., A decade of epigenetic change in aging twins: Genetic and environmental contributions to longitudinal DNA methylation. Aging Cell, 2020. 19(8): p. e13197.Google Scholar
Ley, T. J., et al., DNMT3A mutations in acute myeloid leukemia. New England Journal of Medicine, 2010. 363(25): pp. 2424–2433.Google Scholar
Dagar, V., et al., Genetic variation affecting DNA methylation and the human imprinting disorder, Beckwith-Wiedemann syndrome. Clinical Epigenetics, 2018. 10(1): pp. 1–13.Google Scholar
Yousefi, P., et al., Sex differences in DNA methylation assessed by 450 K BeadChip in newborns. BMC Genomics, 2015. 16(1): p. 911.Google Scholar
McCarthy, N. S., et al., Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns. BMC Genomics, 2014. 15(1): pp. 1–11.Google Scholar
Tobi, E. W., et al., DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Human Molecular Genetics, 2009. 18(21): pp. 4046–4053.Google Scholar
Murphy, S. K., et al., Gender-specific methylation differences in relation to prenatal exposure to cigarette smoke. Gene, 2012. 494(1): pp. 36–43.Google Scholar
Kippler, M., et al., Sex-specific effects of early life cadmium exposure on DNA methylation and implications for birth weight. Epigenetics, 2013. 8(5): pp. 494–503.Google Scholar
Yamagata, Y., et al., DNA methyltransferase expression in the human endometrium: Down-regulation by progesterone and estrogen. Human Reproduction, 2009. 24(5): pp. 1126–1132.Google Scholar
Clifton, V., Sex and the human placenta: Mediating differential strategies of fetal growth and survival. Placenta, 2010. 31: pp. S33S39.Google Scholar
Beyan, H., et al., Guthrie card methylomics identifies temporally stable epialleles that are present at birth in humans. Genome Research, 2012. 22(11): pp. 2138–2145.Google Scholar
Joubert, B., 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environmental Health Perspectives, 2012. 120(10): pp. 1425–1431. doi: 10.1289/ehp.1205412. Epub 2012 Jul 31.Google Scholar
Joubert, B. R., et al., DNA methylation in newborns and maternal smoking in pregnancy: Genome-wide consortium meta-analysis. The American Journal of Human Genetics, 2016. 98(4): pp. 680–696.Google Scholar
Felix, J. F., et al., Cohort profile: Pregnancy and Childhood Epigenetics (PACE) consortium. International Journal of Epidemiology, 2018. 47(1): pp. 2223u.Google Scholar
Yeung, E. H., et al., Cord blood DNA methylation reflects cord blood C-reactive protein levels but not maternal levels: A longitudinal study and meta-analysis. Clinical Epigenetics, 2020. 12: pp. 1–10.Google Scholar
Feinberg, A. P. and Tycko, B., The history of cancer epigenetics. Nature Reviews Cancer, 2004. 4(2): pp. 143–153.Google Scholar
McRae, A. F., et al., Identification of 55,000 replicated DNA methylation QTL. Scientific Reports, 2018. 8(1): pp. 1–9.Google Scholar
Huan, T., et al., Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nature Communications, 2019. 10(1): pp. 1–14.Google Scholar
Jamieson, E., et al., Smoking, DNA methylation, and lung function: A mendelian randomization analysis to investigate causal pathways. The American Journal of Human Genetics, 2020. 106(3): pp. 315–326.Google Scholar
Merid, S. K., et al., Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age. Genome Medicine, 2020. 12(1): pp. 1–17.Google Scholar
Küpers, L. K., et al., Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight. Nature Communications, 2019. 10(1): pp. 1–11.Google Scholar
Reese, S. E., et al., Epigenome-wide meta-analysis of DNA methylation and childhood asthma. Journal of Allergy and Clinical Immunology, 2019. 143(6): pp. 2062–2074.Google Scholar
Neumann, A., et al., Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysis. Translational Psychiatry, 2020. 10(1): pp. 1–11.Google Scholar
Vehmeijer, F. O., et al., DNA methylation and body mass index from birth to adolescence: Meta-analyses of epigenome-wide association studies. Genome Medicine, 2020. 12(1): pp. 1–15.Google Scholar
Gruzieva, O., et al., Epigenome-wide meta-analysis of methylation in children related to prenatal NO2 air pollution exposure. Environmental Health Perspectives, 2017. 125(1): pp. 104–110.Google Scholar
Sikdar, S., et al., Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking. Epigenomics, 2019. 11(13): pp. 1487–1500.Google Scholar
Huang, R., et al., Adiposity associated DNA methylation signatures in adolescents are related to leptin and perinatal factors. Epigenetics, 2021: pp. 1–18.Google Scholar
Saffery, R., Epigenetic change as the major mediator of fetal programming in humans: Are we there yet? Annals of Nutrition & Metabolism, 2014. 64(3–4): pp. 203–207.Google Scholar
Saffery, R. and Novakovic, B., Epigenetics as the mediator of fetal programming of adult onset disease: What is the evidence? Acta Obstetricia et Gynecologica Scandinavica, 2014. 93(11): pp. 1090–1098.Google Scholar
Relton, C. L. and Davey Smith, G., Mendelian randomization: Applications and limitations in epigenetic studies. Epigenomics, 2015;7(8):1239-43. doi: 10.2217/epi.15.88. Epub 2015 Dec 7.Google Scholar

References

Fleming, T. P., Watkins, A. J., Velazquez, M. A., Mathers, J. C., Prentice, A. M., Stephenson, J., Barker, M., Saffery, R., Yajnik, C. S., Eckert, J. J., Hanson, M. A., Forrester, T., Gluckman, P. D., and Godfrey, K. M. (2018) Origins of lifetime health around the time of conception: causes and consequences. Lancet 391, 1842–1852Google Scholar
Burton, G. J., Fowden, A. L., and Thornburg, K. L. (2016) Placental origins of chronic disease. Physiol Rev 96, 1509–1565Google Scholar
Sferruzzi-Perri, A. N., and Camm, E. J. (2016) The programming power of the placenta. Front Physiol 7, 33Google Scholar
Lewis, R. M., Cleal, J. K., and Hanson, M. A. (2012) Review: placenta, evolution and lifelong health. Placenta 33 Suppl, S28–32Google Scholar
Sibley, C. P. (2009) Understanding placental nutrient transfer – why bother? New biomarkers of fetal growth. Journal of Physiology 587, 3431–3440CrossRefGoogle Scholar
Stirrat, L. I., Sengers, B. G., Norman, J. E., Homer, N. Z. M., Andrew, R., Lewis, R. M., and Reynolds, R. M. (2018) Transfer and metabolism of cortisol by the isolated perfused human placenta. J Clin Endocrinol Metab 103, 640–648Google Scholar
Sferruzzi-Perri, A. N., Vaughan, O. R., Forhead, A. J., and Fowden, A. L. (2013) Hormonal and nutritional drivers of intrauterine growth. Curr Opin Clin Nutr Metab Care 16, 298–309Google Scholar
Bloise, E., Ortiga-Carvalho, T. M., Reis, F. M., Lye, S. J., Gibb, W., and Matthews, S. G. (2016) ATP-binding cassette transporters in reproduction: a new frontier. Hum Reprod Update 22, 164–181Google Scholar
Whitley, G. S., and Cartwright, J. E. (2010) Cellular and molecular regulation of spiral artery remodelling: lessons from the cardiovascular field. Placenta 31, 465–474Google Scholar
Camm, E. J., Botting, K. J., and Sferruzzi-Perri, A. N. (2018) Near to one’s heart: the intimate relationship between the placenta and fetal heart. Front Physiol 9, 629Google Scholar
Lewis, R. M., Cleal, J. K., and Sengers, B. G. (2020) Placental perfusion and mathematical modelling. Placenta 93, 43–48Google Scholar
Schumacher, A., Sharkey, D. J., Robertson, S. A., and Zenclussen, A. C. (2018) Immune cells at the fetomaternal interface: how the microenvironment modulates immune cells to foster fetal development. J Immunol 201, 325–334Google Scholar
Napso, T., Yong, H. E., Lopez-Tello, J., and Sferruzzi-Perri, A. N. (2018) The role of placental hormones in mediating maternal adaptations to support pregnancy and lactation. Front Physiol 9, 1091Google Scholar
Sferruzzi-Perri, A. N., Lopez-Tello, J., Napso, T., and Yong, H. E. (2020) Exploring the causes and consequences of maternal metabolic maladaptations during pregnancy. Placenta 98, 43–51Google Scholar
Handwerger, S., and Freemark, M. (2000) The roles of placental growth hormone and placental lactogen in the regulation of human fetal growth and development. J Pediatr Endocrinol Metab 13, 343–356Google Scholar
Turco, M. Y., Gardner, L., Kay, R. G., Hamilton, R. S., Prater, M., Hollinshead, M. S., McWhinnie, A., Esposito, L., Fernando, R., Skelton, H., Reimann, F., Gribble, F. M., Sharkey, A., Marsh, S. G. E., O’Rahilly, S., Hemberger, M., Burton, G. J., and Moffett, A. (2018) Trophoblast organoids as a model for maternal-fetal interactions during human placentation. Nature 564, 263–267Google Scholar
Vento-Tormo, R., Efremova, M., Botting, R. A., Turco, M. Y., Vento-Tormo, M., Meyer, K. B., Park, J. E., Stephenson, E., Polanski, K., Goncalves, A., Gardner, L., Holmqvist, S., Henriksson, J., Zou, A., Sharkey, A. M., Millar, B., Innes, B., Wood, L., Wilbrey-Clark, A., Payne, R. P., Ivarsson, M. A., Lisgo, S., Filby, A., Rowitch, D. H., Bulmer, J. N., Wright, G. J., Stubbington, M. J. T., Haniffa, M., Moffett, A., and Teichmann, S. A. (2018) Single-cell reconstruction of the early maternal-fetal interface in humans. Nature 563, 347–353Google Scholar
Michelsen, T. M., Henriksen, T., Reinhold, D., Powell, T. L., and Jansson, T. (2019) The human placental proteome secreted into the maternal and fetal circulations in normal pregnancy based on 4-vessel sampling. FASEB J 33, 2944–2956Google Scholar
Sferruzzi-Perri, A. N. (2018) Assessment of placental transport function in studies of disease programming. Methods Mol Biol Chapter 14, 1735, 1239–1250Google Scholar
Roseboom, T., de Rooij, S., and Painter, R. (2006) The Dutch famine and its long-term consequences for adult health. Early Hum Dev 82, 485–491Google Scholar
Roseboom, T. J., Painter, R. C., de Rooij, S. R., van Abeelen, A. F., Veenendaal, M. V., Osmond, C., and Barker, D. J. (2011) Effects of famine on placental size and efficiency. Placenta 32, 395–399Google Scholar
van Abeelen, A. F., de Rooij, S. R., Osmond, C., Painter, R. C., Veenendaal, M. V., Bossuyt, P. M., Elias, S. G., Grobbee, D. E., van der Schouw, Y. T., Barker, D. J., and Roseboom, T. J. (2011) The sex-specific effects of famine on the association between placental size and later hypertension. Placenta 32, 694–698Google Scholar
Glazier, J. D., Hayes, D. J. L., Hussain, S., D’Souza, S. W., Whitcombe, J., Heazell, A. E. P., and Ashton, N. (2018) The effect of Ramadan fasting during pregnancy on perinatal outcomes: a systematic review and meta-analysis. BMC Pregnancy Childbirth 18, 421Google Scholar
Lewis, R. M., Wadsack, C., and Desoye, G. (2018) Placental fatty acid transfer. Curr Opin Clin Nutr Metab Care 21, 78–82Google Scholar
Vaughan, O. R., Rosario, F. J., Powell, T., and Jansson, T. (2017) Regulation of placental amino acid transport and fetal growth. Prog Mol Biol Transl Sci. 2017;145:217–251. doi: 10.1016/bs.pmbts.2016.12.008. Epub 2017 Jan 16.Google Scholar
Cleal, J. K., Day, P. E., Simner, C. L., Barton, S. J., Mahon, P. A., Inskip, H. M., Godfrey, K. M., Hanson, M. A., Cooper, C., Lewis, R. M., Harvey, N. C., and Group, S. W. S. S. (2015) Placental amino acid transport may be regulated by maternal vitamin D and vitamin D-binding protein: results from the Southampton Women’s Survey. Br J Nutr 113, 1903–1910Google Scholar
Fowden, A. L., Camm, E. J., and Sferruzzi-Perri, A. N. (2020) Effects of maternal obesity on placental phenotype. Curr Vasc Pharmacol 19, 113–131Google Scholar
Myatt, L., and Thornburg, K. L. (2018) Effects of prenatal nutrition and the role of the placenta in health and disease. Methods Mol Biol 1735, 19–46Google Scholar
Lewis, R. M., and Desoye, G. (2017) Placental lipid and fatty acid transfer in maternal overnutrition. Ann Nutr Metab 70, 228–231Google Scholar
Rad, H. S., Rohl, J., Stylianou, N., Allenby, M. C., Bazaz, S. R., Warkiani, M. E., Guimaraes, F. S. F., Clifton, V. L., and Kulasinghe, A. (2021) The effects of COVID-19 on the placenta during pregnancy. Front Immunol 12, 743022Google Scholar
Nelson, S. M., Coan, P. M., Burton, G. J., and Lindsay, R. S. (2009) Placental structure in Type 1 Diabetes 58, 2634–2641Google Scholar
Calderon, I. M., Damasceno, D. C., Amorin, R. L., Costa, R. A., Brasil, M. A., and Rudge, M. V. (2007) Morphometric study of placental villi and vessels in women with mild hyperglycemia or gestational or overt diabetes. Diabetes Res Clin Pract 78, 65–71Google Scholar
Castillo-Castrejon, M., and Powell, T. L. (2017) Placental nutrient transport in gestational diabetic pregnancies. Front Endocrinol (Lausanne) 8, 306Google Scholar
Mayhew, T. M., Wijesekara, J., Baker, P. N., and Ong, S. S. (2004) Morphometric evidence that villous development and fetoplacental angiogenesis are compromised by intrauterine growth restriction but not by pre-eclampsia. Placenta 25, 829–833Google Scholar
Hayward, C. E., Greenwood, S. L., Sibley, C. P., Baker, P. N., Challis, J. R., and Jones, R. L. (2012) Effect of maternal age and growth on placental nutrient transport: potential mechanisms for teenagers’ predisposition to small-for-gestational-age birth? Am J Physiol Endocrinol Metab 302, E233242Google Scholar
Palomba, S., de Wilde, M. A., Falbo, A., Koster, M. P., La Sala, G. B., and Fauser, B. C. (2015) Pregnancy complications in women with polycystic ovary syndrome. Hum Reprod Update 21, 575–592Google Scholar
Maliqueo, M., Lara, H. E., Sanchez, F., Echiburu, B., Crisosto, N., and Sir-Petermann, T. (2013) Placental steroidogenesis in pregnant women with polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 166, 151–155Google Scholar
Clapp, J. F. (2006) Influence of endurance exercise and diet on human placental development and fetal growth. Placenta 27, 527–534Google Scholar
Brett, K. E., Ferraro, Z. M., Holcik, M., and Adamo, K. B. (2015) Prenatal physical activity and diet composition affect the expression of nutrient transporters and mTOR signaling molecules in the human placenta. Placenta 36, 204–212Google Scholar
Day, P. E., Ntani, G., Crozier, S. R., Mahon, P. A., Inskip, H. M., Cooper, C., Harvey, N. C., Godfrey, K. M., Hanson, M. A., Lewis, R. M., and Cleal, J. K. (2015) Maternal Factors are associated with the expression of placental genes involved in amino acid metabolism and transport. PloS one 10, e0143653Google Scholar
Mayhew, T. M. (2003) Changes in fetal capillaries during preplacental hypoxia: growth, shape remodelling and villous capillarization in placentae from high-altitude pregnancies. Placenta 24, 191–198Google Scholar
Zamudio, S., Baumann, M. U., and Illsley, N. P. (2006) Effects of chronic hypoxia in vivo on the expression of human placental glucose transporters. Placenta 27, 49–55Google Scholar
Jauniaux, E., and Burton, G. J. (2007) Morphological and biological effects of maternal exposure to tobacco smoke on the feto-placental unit. Early Hum Dev 83, 699–706Google Scholar
Hayward, C. E., Greenwood, S. L., Sibley, C. P., Baker, P. N., and Jones, R. L. (2011) Effect of young maternal age and skeletal growth on placental growth and development. Placenta 32, 990–998Google Scholar
Lean, S. C., Heazell, A. E. P., Dilworth, M. R., Mills, T. A., and Jones, R. L. (2017) Placental dysfunction underlies increased risk of fetal growth restriction and stillbirth in advanced maternal age women. Sci Rep 7, 9677Google Scholar
Perazzolo, S., Lewis, R. M., and Sengers, B. G. (2017) Modelling the effect of intervillous flow on solute transfer based on 3D imaging of the human placental microstructure. Placenta 60, 21–27Google Scholar
Sferruzzi-Perri, A. N., Owens, J. A., Pringle, K. G., and Roberts, C. T. (2010) The neglected role of insulin-like growth factors in the maternal circulation regulating fetal growth. J Physiol 589, 7–20Google Scholar
Fowden, A. L., Forhead, A. J., Sferruzzi-Perri, A. N., Burton, G. J., and Vaughan, O. R. (2015) Endocrine regulation of placental phenotype. Placenta 36, S5059Google Scholar
Paulsen, M. E., Rosario, F. J., Wesolowski, S. R., Powell, T. L., and Jansson, T. (2019) Normalizing adiponectin levels in obese pregnant mice prevents adverse metabolic outcomes in offspring. FASEB J 33, 2899–2909Google Scholar
Vaughan, O. R., Sferruzzi-Perri, A. N., and Fowden, A. L. (2012) Maternal corticosterone regulates nutrient allocation to fetal growth in mice. J Physiol 590, 5529–5540Google Scholar
Sferruzzi-Perri, A. N., Vaughan, O. R., Coan, P. M., Suciu, M. C., Darbyshire, R., Constancia, M., Burton, G. J., and Fowden, A. L. (2011) Placental-specific Igf2 deficiency alters developmental adaptations to undernutrition in mice. Endocrinology 152, 3202–3212Google Scholar
Yong, H. E., Lopez-Tello, J., Sandovici, I., Constancia, M., and Sferruzzi-Perri, A. N. (2017) Mice with placental junctional zone Igf2 deletion fail to metabolically adapt to pregnancy. Placenta 57, 247–248Google Scholar
Aykroyd, B. R. L., Tunster, S. J., and Sferruzzi-Perri, A. N. (2020) Igf2 deletion alters mouse placenta endocrine capacity in a sexually-dimorphic manner. J Endocrinol 246, 93–108Google Scholar
Hemberger, M., Hanna, C. W., and Dean, W. (2020) Mechanisms of early placental development in mouse and humans. Nat Rev Genet 21, 27–43Google Scholar
Vlahos, A., Mansell, T., Saffery, R., and Novakovic, B. (2019) Human placental methylome in the interplay of adverse placental health, environmental exposure, and pregnancy outcome. PLoS Genet 15, e1008236Google Scholar
Wen, X., Triche, E. W., Hogan, J. W., Shenassa, E. D., and Buka, S. L. (2011) Association between placental morphology and childhood systolic blood pressure. Hypertension 57, 48–55Google Scholar
Hemachandra, A. H., Klebanoff, M. A., Duggan, A. K., Hardy, J. B., and Furth, S. L. (2006) The association between intrauterine growth restriction in the full-term infant and high blood pressure at age 7 years: results from the collaborative perinatal project. Int J Epidemiol 35, 871–877Google Scholar
Risnes, K. R., Romundstad, P. R., Nilsen, T. I., Eskild, A., and Vatten, L. J. (2009) Placental weight relative to birth weight and long-term cardiovascular mortality: findings from a cohort of 31,307 men and women. Am J Epidemiol 170, 622–631Google Scholar
Barker, D. J., Larsen, G., Osmond, C., Thornburg, K. L., Kajantie, E., and Eriksson, J. G. (2012) The placental origins of sudden cardiac death. Int J Epidemiol 41, 1394–1399Google Scholar
Poston, L. (2010) Developmental programming and diabetes – The human experience and insight from animal models. Best Pract Res Clin Endocrinol Metab 24, 541–552Google Scholar
Reynolds, L. P., Borowicz, P. P., Caton, J. S., Vonnahme, K. A., Luther, J. S., Hammer, C. J., Maddock Carlin, K. R., Grazul-Bilska, A. T., and Redmer, D. A. (2010) Developmental programming: the concept, large animal models, and the key role of uteroplacental vascular development. J Anim Sci 88, E6172Google Scholar
Lopez-Tello, J., Arias-Alvarez, M., Gonzalez-Bulnes, A., and Sferuzzi-Perri, A. N. (2019) Models of Intrauterine growth restriction and fetal programming in rabbits. Mol Reprod Dev 86, 1781–1809Google Scholar
Carter, A. M. (2012) Evolution of placental function in mammals: the molecular basis of gas and nutrient transfer, hormone secretion, and immune responses. Physiol Rev 92, 1543–1576Google Scholar
Mikaelsson, M. A., Constancia, M., Dent, C. L., Wilkinson, L. S., and Humby, T. (2013) Placental programming of anxiety in adulthood revealed by Igf2-null models. Nat Commun 4, 2311Google Scholar
Harrison, D. J., Creeth, H. D. J., Tyson, H. R., Boque-Sastre, R., Hunter, S., Dwyer, D. M., Isles, A. R., and John, R. M. (2021) Placental endocrine insufficiency programs anxiety, deficits in cognition and atypical social behaviour in offspring. Hum Mol Genet Sep 15; 30(19):1863-1880. doi: 10.1093/hmg/ddab154.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×