PDF herunterladen
CC BY 4.0 · Rev Bras Ginecol Obstet 2019; 41(07): 454-462
DOI: 10.1055/s-0039-1692126
Review Article
Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil

New Approaches to Fetal Growth Restriction: The Time for Metabolomics Has Come

Novas abordagens para a restrição de crescimento fetal: é chegada a hora da metabolômica
Debora Farias Batista Leite
1   Departament of Obstetrics and Gynecology, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, São Paulo, SP, Brazil
2   Department of Mother and Child Health, Universidade Federal de Pernambuco, Recife, PE, Brazil
3   Hospital Clínico, Universidade Federal de Pernambuco, Recife, PE, Brazil
,
José Guilherme Cecatti 
1   Departament of Obstetrics and Gynecology, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, São Paulo, SP, Brazil
› Institutsangaben
Weitere Informationen

Publikationsverlauf

26. Januar 2019

16. April 2019

Publikationsdatum:
27. Juni 2019 (online)

   Lizenzen und Reprints

Abstract

Fetal growth restriction (FGR) diagnosis is often made by fetal biometric ultrasound measurements or Doppler evaluation, but most babies are only diagnosed after birth, using the birth weight as a proxy for intrauterine development. The higher risks of neurodevelopmental delay, metabolic syndrome, and cardiovascular illness associated with FGR impose a shift on the focus during pregnancy. New methodological approaches, like metabolomics, can provide novel biomarkers for intrauterine fetal development. Recent evidence on metabolites involved with fetal growth and weight show a consistent role played by lipids (especially fatty acids), amino acids, vitamin D and folic acid. Fetal energy source and metabolism, structural functions, and nervous system functioning need further evaluations in different populations. In the near future, the establishment of a core set of outcomes for FGR studies may improve the identification of the role of each metabolite in its development. Thus, we will concretely progress with the perspective of a translational capacity of metabolomics for this condition.

Resumo

O diagnóstico da restrição do crescimento fetal (RCF) é frequentemente feito por medidas biométricas ultrassonográficas ou por avaliação pela Dopplervelocimetria, mas, na maioria dos casos, o diagnóstico é apenas pós-natal, usando o peso ao nascimento como um marcador para o desenvolvimento intrauterino. Riscos maiores de atraso do neurodesenvolvimento, síndrome metabólica e doenças cardiovasculares associadas com a RCF impõem uma mudança no foco durante a gestação. Novas abordagens metodológicas, como a metabolômica, podem fornecer novos biomarcadores para o desenvolvimento fetal intrauterino. As evidências recentes sobre os metabolitos envolvidos com o crescimento e peso fetal mostram um papel consistente desempenhado pelos lipídios (especialmente os ácidos graxos), aminoácidos, vitamina D e ácido fólico. A fonte de energia fetal e seu metabolismo, a função estrutural e o funcionamento do sistema nervoso devem ser detalhadamente investigados nos próximos estudos de validação. Em breve, o estabelecimento de um conjunto de desfechos a serem descritos para os estudos de RCF pode melhorar a identificação do papel de cada metabolito no seu desenvolvimento. Assim, iremos progredir no entendimento da RCF numa perspectiva da capacidade translacional da metabolômica para este transtorno.

Keywords

fetal growth restriction - small for gestational age - prediction metabolomics

Palavras-chave

restrição do crescimento fetal - pequeno para a idade gestacional - previsão metabolômica
 

  • References

  • 1 Meher S, Hernandez-Andrade E, Basheer SN, Lees C. Impact of cerebral redistribution on neurodevelopmental outcome in small-for-gestational-age or growth-restricted babies: a systematic review. Ultrasound Obstet Gynecol 2015; 46 (04) 398-404 . Doi: 10.1002/uog.14818
    CrossrefPubMedGoogle Scholar
  • 2 Barker DJ, Osmond C, Simmonds SJ, Wield GA. The relation of small head circumference and thinness at birth to death from cardiovascular disease in adult life. BMJ 1993; 306 (6875): 422-426 . Doi: 10.1136/bmj.306.6875.422
    CrossrefPubMedGoogle Scholar
  • 3 Prioreschi A, Munthali RJ, Kagura J. , et al. The associations between adult body composition and abdominal adiposity outcomes, and relative weight gain and linear growth from birth to age 22 in the Birth to Twenty Plus cohort, South Africa. PLoS One 2018; 13 (01) e0190483 . Doi: 10.1371/journal.pone.0190483
    CrossrefPubMedGoogle Scholar
  • 4 Araújo de França GV, Restrepo-Méndez MC, Loret de Mola C, Victora CG. Size at birth and abdominal adiposity in adults: a systematic review and meta-analysis. Obes Rev 2014; 15 (02) 77-91 . Doi: 10.1111/obr.12109
    CrossrefPubMedGoogle Scholar
  • 5 Wang N, Wang X, Li Q. , et al. The famine exposure in early life and metabolic syndrome in adulthood. Clin Nutr 2017; 36 (01) 253-259 . Doi: 10.1016/j.clnu.2015.11.010
    CrossrefPubMedGoogle Scholar
  • 6 Roseboom TJ, Painter RC, van Abeelen AFM, Veenendaal MVE, de Rooij SR. Hungry in the womb: what are the consequences? Lessons from the Dutch famine. Maturitas 2011; 70 (02) 141-145 . Doi: 10.1016/j.maturitas.2011.06.017
    CrossrefPubMedGoogle Scholar
  • 7 Warkany J, Monroe BB, Sutherland BS. Intrauterine growth retardation. Am J Dis Child 1961; 102: 249-279
    PubMedGoogle Scholar
  • 8 McCowan LM, Figueras F, Anderson NH. Evidence-based national guidelines for the management of suspected fetal growth restriction: comparison, consensus, and controversy. Am J Obstet Gynecol 2018; 218 (2S): S855-S868 . Doi: 10.1016/j.ajog.2017.12.004
    CrossrefPubMedGoogle Scholar
  • 9 Lubchenco LO, Hansman C, Dressler M, Boyd E. Intrauterine growth as estimated from liveborn birth-weight data at 24 to 42 weeks of gestation. Pediatrics 1963; 32: 793-800
    CrossrefPubMedGoogle Scholar
  • 10 Dessì A, Atzori L, Noto A. , et al. Metabolomics in newborns with intrauterine growth retardation (IUGR): urine reveals markers of metabolic syndrome. J Matern Fetal Neonatal Med 2011; 24 (Suppl. 02) 35-39 . Doi: 10.3109/14767058.2011.605868
    CrossrefPubMedGoogle Scholar
  • 11 Favretto D, Cosmi E, Ragazzi E. , et al. Cord blood metabolomic profiling in intrauterine growth restriction. Anal Bioanal Chem 2012; 402 (03) 1109-1121 . Doi: 10.1007/s00216-011-5540-z
    CrossrefPubMedGoogle Scholar
  • 12 Sanz-Cortés M, Carbajo RJ, Crispi F, Figueras F, Pineda-Lucena A, Gratacós E. Metabolomic profile of umbilical cord blood plasma from early and late intrauterine growth restricted (IUGR) neonates with and without signs of brain vasodilation. PLoS One 2013; 8 (12) e80121 . Doi: 10.1371/journal.pone.0080121
    CrossrefPubMedGoogle Scholar
  • 13 Miranda J, Simões RV, Paules C. , et al. Metabolic profiling and targeted lipidomics reveals a disturbed lipid profile in mothers and fetuses with intrauterine growth restriction. Sci Rep 2018; 8 (01) 13614 . Doi: 10.1038/s41598-018-31832-5
    CrossrefPubMedGoogle Scholar
  • 14 Visentin S, Crotti S, Donazzolo E. , et al. Medium chain fatty acids in intrauterine growth restricted and small for gestational age pregnancies. Metabolomics 2017; 13 (05) 1-9 . Doi: 10.1007/s11306-017-1197-8
    CrossrefPubMedGoogle Scholar
  • 15 Horgan RP, Broadhurst DI, Walsh SK. , et al. Metabolic profiling uncovers a phenotypic signature of small for gestational age in early pregnancy. J Proteome Res 2011; 10 (08) 3660-3673 . Doi: 10.1021/pr2002897
    CrossrefPubMedGoogle Scholar
  • 16 Chou D, Daelmans B, Jolivet RR, Kinney M, Say L. ; Every Newborn Action Plan (ENAP) and Ending Preventable Maternal Mortality (EPMM) working groups. Ending preventable maternal and newborn mortality and stillbirths. BMJ 2015; 351: h4255 . Doi: 10.1136/bmj.h4255
    Google Scholar
  • 17 Mendez-Figueroa H, Chauhan SP, Barrett T, Truong VTT, Pedroza C, Blackwell SC. Population versus customized growth curves: prediction of composite neonatal morbidity. Am J Perinatol 2018; ••• DOI: 10.1055/s-0038-1675161.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 18 Lindqvist PG, Molin J. Does antenatal identification of small-for-gestational age fetuses significantly improve their outcome?. Ultrasound Obstet Gynecol 2005; 25 (03) 258-264 . Doi: 10.1002/uog.1806
    CrossrefPubMedGoogle Scholar
  • 19 Patti GJ, Yanes O, Siuzdak G. Innovation: Metabolomics: the apogee of the omics trilogy. Nat Rev Mol Cell Biol 2012; 13 (04) 263-269 . Doi: 10.1038/nrm3314
    CrossrefPubMedGoogle Scholar
  • 20 Xia J, Broadhurst DI, Wilson M, Wishart DS. Translational biomarker discovery in clinical metabolomics: an introductory tutorial. Metabolomics 2013; 9 (02) 280-299 . Doi: 10.1007/s11306-012-0482-9
    CrossrefPubMedGoogle Scholar
  • 21 Lindsay KL, Hellmuth C, Uhl O. , et al. Longitudinal metabolomic profiling of amino acids and lipids across healthy pregnancy. PLoS One 2015; 10 (12) e0145794 . Doi: 10.1371/journal.pone.0145794
    CrossrefPubMedGoogle Scholar
  • 22 Delplancke TDJ, de Seymour JV, Tong C. , et al. Analysis of sequential hair segments reflects changes in the metabolome across the trimesters of pregnancy. Sci Rep 2018; 8 (01) 36 . Doi: 10.1038/s41598-017-18317-7
    CrossrefPubMedGoogle Scholar
  • 23 Robinson O, Keski-Rahkonen P, Chatzi L. , et al. Cord blood metabolic signatures of birth weight: a population-based study. J Proteome Res 2018; 17 (03) 1235-1247 . Doi: 10.1021/acs.jproteome.7b00846
    CrossrefPubMedGoogle Scholar
  • 24 Lu YP, Reichetzeder C, Prehn C. , et al. Cord blood lysophosphatidylcholine 16:1 is positively associated with birth weight. Cell Physiol Biochem 2018; 45 (02) 614-624 . Doi: 10.1159/000487118
    CrossrefPubMedGoogle Scholar
  • 25 McKeating DR, Fisher JJ, Perkins AV. Elemental metabolomics and pregnancy outcomes. Nutrients 2019; 11 (01) E73 . Doi: 10.3390/nu11010073
    CrossrefPubMedGoogle Scholar
  • 26 Oliver SG, Winson MK, Kell DB, Baganz F. Systematic functional analysis of the yeast genome. Trends Biotechnol 1998; 16 (09) 373-378 . Doi: 10.1016/S0167-7799(98)01214-1
    CrossrefPubMedGoogle Scholar
  • 27 Dunn WB, Broadhurst DI, Atherton HJ, Goodacre R, Griffin JL. Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem Soc Rev 2011; 40 (01) 387-426 . Doi: 10.1039/b906712b
    CrossrefPubMedGoogle Scholar
  • 28 Wishart DS, Feunang YD, Marcu A. , et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res 2018; 46 (D1): D608-D617 . Doi: 10.1093/nar/gkx1089
    CrossrefPubMedGoogle Scholar
  • 29 Longo N, Frigeni M, Pasquali M. Carnitine transport and fatty acid oxidation. Biochim Biophys Acta 2016; 1863 (10) 2422-2435 . Doi: 10.1016/j.bbamcr.2016.01.023
    CrossrefPubMedGoogle Scholar
  • 30 Badawy AAB. Kynurenine pathway of tryptophan metabolism: regulatory and functional aspects. Int J Tryptophan Res 2017; 10: 1-20 . Doi: 10.1177/1178646917691938
    PubMedGoogle Scholar
  • 31 Lingwood CA. Glycosphingolipid functions. Cold Spring Harb Perspect Biol 2011; 3 (07) a004788 . Doi: 10.1101/cshperspect.a004788
    CrossrefPubMedGoogle Scholar
  • 32 Lenters V, Portengen L, Rignell-Hydbom A. , et al. Prenatal phthalate, perfluoroalkyl acid, and organochlorine exposures and term birth weight in three birth cohorts: multi-pollutant models based on elastic net regression. Environ Health Perspect 2016; 124 (03) 365-372 . Doi: 10.1289/ehp.1408933
    CrossrefPubMedGoogle Scholar
  • 33 Wang Y, Adgent M, Su PH. , et al. Prenatal exposure to perfluorocarboxylic acids (PFCAs) and fetal and postnatal growth in the Taiwan maternal and infant cohort study. Environ Health Perspect 2016; 124 (11) 1794-1800 . Doi: 10.1289/ehp.1509998
    CrossrefPubMedGoogle Scholar
  • 34 Diaz SO, Barros AS, Goodfellow BJ. , et al. Second trimester maternal urine for the diagnosis of trisomy 21 and prediction of poor pregnancy outcomes. J Proteome Res 2013; 12 (06) 2946-2957 . Doi: 10.1021/pr4002355
    CrossrefPubMedGoogle Scholar
  • 35 Heazell AEP, Bernatavicius G, Warrander L, Brown MC, Dunn WB. A metabolomic approach identifies differences in maternal serum in third trimester pregnancies that end in poor perinatal outcome. Reprod Sci 2012; 19 (08) 863-875 . Doi: 10.1177/1933719112438446
    CrossrefPubMedGoogle Scholar
  • 36 Bobiński R, Mikulska M, Mojska H, Simon M. Comparison of the fatty acid composition of transitional and mature milk of mothers who delivered healthy full-term babies, preterm babies and full-term small for gestational age infants. Eur J Clin Nutr 2013; 67 (09) 966-971 . Doi: 10.1038/ejcn.2013.96
    CrossrefPubMedGoogle Scholar
  • 37 Barberini L, Noto A, Fattuoni C. , et al. Urinary metabolomics (GC-MS) reveals that low and high birth weight infants share elevated inositol concentrations at birth. J Matern Fetal Neonatal Med 2014; 27 (Suppl. 02) 20-26 . Doi: 10.3109/14767058.2014.954786
    CrossrefPubMedGoogle Scholar
  • 38 Dessì A, Marincola FC, Pattumelli MG. , et al. Investigation of the 1H-NMR based urine metabolomic profiles of IUGR, LGA and AGA newborns on the first day of life. J Matern Fetal Neonatal Med 2014; 27 (Suppl. 02) 13-19 . Doi: 10.3109/14767058.2014.955674
    CrossrefPubMedGoogle Scholar
  • 39 Liu J, Chen XX, Li XW, Fu W, Zhang WQ. Metabolomic research on newborn infants with intrauterine growth restriction. Medicine (Baltimore) 2016; 95 (17) e3564 . Doi: 10.1097/MD.0000000000003564
    CrossrefPubMedGoogle Scholar
  • 40 Leite DFB, Morillon AC, Melo Júnior EF. , et al. Metabolomics for predicting fetal growth restriction: protocol for a systematic review and meta-analysis. BMJ Open 2018; 8 (12) e022743 . Doi: 10.1136/bmjopen-2018-022743
    CrossrefPubMedGoogle Scholar
  • 41 Sulek K, Han TL, Villas-Boas SG. , et al. Hair metabolomics: identification of fetal compromise provides proof of concept for biomarker discovery. Theranostics 2014; 4 (09) 953-959 . Doi: 10.7150/thno.9265
    CrossrefPubMedGoogle Scholar
  • 42 Bernard JY, Tint MT, Aris IM. , et al. Maternal plasma phosphatidylcholine polyunsaturated fatty acids during pregnancy and offspring growth and adiposity. Prostaglandins Leukot Essent Fatty Acids 2017; 121: 21-29 . Doi: 10.1016/j.plefa.2017.05.006
    CrossrefPubMedGoogle Scholar
  • 43 Sivashanmugam M. J J, v U, K N S. Ornithine and its role in metabolic diseases: An appraisal. Biomed Pharmacother 2017; 86: 185-194 . Doi: 10.1016/j.biopha.2016.12.024
    CrossrefPubMedGoogle Scholar
  • 44 Montesinos Guevara C, Mani AR. The role of D-serine in peripheral tissues. Eur J Pharmacol 2016; 780: 216-223 . Doi: 10.1016/j.ejphar.2016.03.054
    CrossrefPubMedGoogle Scholar
  • 45 Murray PG, Butcher I, Dunn WB. , et al. Metabolites involved in glycolysis and amino acid metabolism are altered in short children born small for gestational age. Pediatr Res 2016; 80 (02) 299-305 . Doi: 10.1038/pr.2016.72
    CrossrefPubMedGoogle Scholar
  • 46 Unfer V, Facchinetti F, Orrù B, Giordani B, Nestler J. Myo-inositol effects in women with PCOS: a meta-analysis of randomized controlled trials. Endocr Connect 2017; 6 (08) 647-658 . Doi: 10.1530/ec-17-0243
    CrossrefPubMedGoogle Scholar
  • 47 Evagelidou EN, Giapros VI, Challa AS, Kiortsis DN, Tsatsoulis AA, Andronikou SK. Serum adiponectin levels, insulin resistance, and lipid profile in children born small for gestational age are affected by the severity of growth retardation at birth. Eur J Endocrinol 2007; 156 (02) 271-277 . Doi: 10.1530/eje.1.02337
    CrossrefPubMedGoogle Scholar
  • 48 Evagelidou EN, Giapros VI, Challa AS. , et al. Prothrombotic state, cardiovascular, and metabolic syndrome risk factors in prepubertal children born large for gestational age. Diabetes Care 2010; 33 (11) 2468-2470 . Doi: 10.2337/dc10-1190
    CrossrefPubMedGoogle Scholar
  • 49 Agarwal S, Kovilam O, Agrawal DK. Vitamin D and its impact on maternal-fetal outcomes in pregnancy: A critical review. Crit Rev Food Sci Nutr 2018; 58 (05) 755-769 . Doi: 10.1080/10408398.2016.1220915
    CrossrefPubMedGoogle Scholar
  • 50 Bi WG, Nuyt AM, Weiler H, Leduc L, Santamaria C, Wei SQ. Association between Vitamin D supplementation during pregnancy and offspring growth, morbidity, and mortality: a systematic review and meta-analysis. JAMA Pediatr 2018; 172 (07) 635-645 . Doi: 10.1001/jamapediatrics.2018.0302
    CrossrefPubMedGoogle Scholar
  • 51 Kiely M, O'Donovan SM, Kenny LC, Hourihane JOB, Irvine AD, Murray DM. Vitamin D metabolite concentrations in umbilical cord blood serum and associations with clinical characteristics in a large prospective mother-infant cohort in Ireland. J Steroid Biochem Mol Biol 2017; 167: 162-168 . Doi: 10.1016/j.jsbmb.2016.12.006
    CrossrefPubMedGoogle Scholar
  • 52 Ertl R, Yu CKH, Samaha R, Akolekar R, Nicolaides KH. Maternal serum vitamin D at 11-13 weeks in pregnancies delivering small for gestational age neonates. Fetal Diagn Ther 2012; 31 (02) 103-108 . Doi: 10.1159/000333810
    CrossrefPubMedGoogle Scholar
  • 53 Gernand AD, Simhan HN, Caritis S, Bodnar LM. Maternal vitamin D status and small-for-gestational-age offspring in women at high risk for preeclampsia. Obstet Gynecol 2014; 123 (01) 40-48 . Doi: 10.1097/AOG.0000000000000049
    CrossrefPubMedGoogle Scholar
  • 54 Kiely ME, Zhang JY, Kinsella M, Khashan AS, Kenny LC. Vitamin D status is associated with uteroplacental dysfunction indicated by pre-eclampsia and small-for-gestational-age birth in a large prospective pregnancy cohort in Ireland with low vitamin D status. Am J Clin Nutr 2016; 104 (02) 354-361 . Doi: 10.3945/ajcn.116.130419
    CrossrefPubMedGoogle Scholar
  • 55 Hemmingway A, Kenny LC, Malvisi L, Kiely ME. Exploring the concept of functional vitamin D deficiency in pregnancy: impact of the interaction between 25-hydroxyvitamin D and parathyroid hormone on perinatal outcomes. Am J Clin Nutr 2018; 108 (04) 821-829 . Doi: 10.1093/ajcn/nqy150
    CrossrefPubMedGoogle Scholar
  • 56 Cosmi E, Visentin S, Favretto D. , et al. Selective intrauterine growth restriction in monochorionic twin pregnancies: markers of endothelial damage and metabolomic profile. Twin Res Hum Genet 2013; 16 (04) 816-826 . Doi: 10.1017/thg.2013.33
    CrossrefPubMedGoogle Scholar
  • 57 World Health Organization. Guideline: Daily Iron and Folic Acid Supplementation in Pregnant Women. Geneva: WHO; 2012
    Google Scholar
  • 58 van Eijsden M, Smits LJ, van der Wal MF, Bonsel GJ. Association between short interpregnancy intervals and term birth weight: the role of folate depletion. Am J Clin Nutr 2008; 88 (01) 147-153 . Doi: 10.1093/ajcn/88.1.147
    CrossrefPubMedGoogle Scholar
  • 59 Hodgetts VA, Morris RK, Francis A, Gardosi J, Ismail KM. Effectiveness of folic acid supplementation in pregnancy on reducing the risk of small-for-gestational age neonates: a population study, systematic review and meta-analysis. BJOG 2015; 122 (04) 478-490 . Doi: 10.1111/1471-0528.13202
    CrossrefPubMedGoogle Scholar
  • 60 Ding YX, Cui H. Integrated analysis of genome-wide DNA methylation and gene expression data provide a regulatory network in intrauterine growth restriction. Life Sci 2017; 179: 60-65 . Doi: 10.1016/j.lfs.2017.04.020
    CrossrefPubMedGoogle Scholar
  • 61 Bjørke-Jenssen A, Ueland PM, Bjørke-Monsen AL. Amniotic fluid arginine from gestational weeks 13 to 15 is a predictor of birth weight, length, and head circumference. Nutrients 2017; 9 (12) E1357 . Doi: 10.3390/nu9121357
    CrossrefPubMedGoogle Scholar
  • 62 Chen J, Gong X, Chen P, Luo K, Zhang X. Effect of L-arginine and sildenafil citrate on intrauterine growth restriction fetuses: a meta-analysis. BMC Pregnancy Childbirth 2016; 16: 225 . Doi: 10.1186/s12884-016-1009-6
    CrossrefPubMedGoogle Scholar
  • 63 Bauchart-Thevret C, Cui L, Wu G, Burrin DG. Arginine-induced stimulation of protein synthesis and survival in IPEC-J2 cells is mediated by mTOR but not nitric oxide. Am J Physiol Endocrinol Metab 2010; 299 (06) E899-E909 . Doi: 10.1152/ajpendo.00068.2010
    CrossrefPubMedGoogle Scholar
  • 64 von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. ; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61 (04) 344-349 . Doi: 10.1016/j.jclinepi.2007.11.008
    CrossrefPubMedGoogle Scholar
  • 65 Goodacre R, Broadhurst D, Smilde AK. , et al. Proposed minimum reporting standards for data analysis in metabolomics. Metabolomics 2007; 3 (03) 231-241 . Doi: 10.1007/s11306-007-0081-3
    CrossrefPubMedGoogle Scholar