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Chapter 14 - Visualizing Structural Underpinnings of DOHaD

from 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
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Summary

Structural compromises are one of the important underpinnings of the developmental origins of health and disease. Quantifying anatomic changes during development is difficult but improved technology for clinical imaging has brought new research opportunities for visualizing such alterations. During prenatal life, maternal malnutrition, toxic social stress and exposure to toxic chemicals change fetal organ structures in specific ways. High placental resistance suppresses cardiomyocyte endowment. New imaging techniques allow quantification of nephrons in cadaverous kidneys without tedious dissection. High fat diets can lead to fatty liver and fibrosis. Pancreatic islet numbers and function are compromised by poor maternal diets. Both social and nutritional stressors change wiring and cellular composition of the brain for life. Advances in optical imaging also offer exciting new technologies for viewing structure and function in cells stressed during development.

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Publisher: Cambridge University Press
Print publication year: 2022

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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.CrossRefGoogle 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

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