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The plasma metabolome of women in early pregnancy differs from that of non-pregnant women


Autoři: Samuel K. Handelman aff001;  Roberto Romero aff001;  Adi L. Tarca aff001;  Percy Pacora aff001;  Brian Ingram aff009;  Eli Maymon aff001;  Tinnakorn Chaiworapongsa aff001;  Sonia S. Hassan aff001;  Offer Erez aff001
Působiště autorů: Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICH aff001;  Department of Internal Medicine, Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan, United States of America aff002;  Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan, United States of America aff003;  Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, United States of America aff004;  Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, United States of America aff005;  Detroit Medical Center, Detroit, Michigan, United States of America aff006;  Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, United States of America aff007;  Department of Computer Science, Wayne State University College of Engineering, Detroit, Michigan, United States of America aff008;  Metabolon Inc., Raleigh-Durham, North Carolina, United States of America aff009;  Department of Obstetrics and Gynecology, Soroka University Medical Center, School of Medicine, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel aff010;  Department of Physiology, Wayne State University School of Medicine, Detroit, Michigan, United States of America aff011;  Maternity Department "D," Division of Obstetrics and Gynecology, Soroka University Medical Center, School of Medicine, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer-Sheva, Israel aff012
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0224682

Souhrn

Background

In comparison to the non-pregnant state, the first trimester of pregnancy is characterized by systemic adaptation of the mother. The extent to which these adaptive processes are reflected in the maternal blood metabolome is not well characterized.

Objective

To determine the differences between the plasma metabolome of non-pregnant and pregnant women before 16 weeks gestation.

Study design

This study included plasma samples from 21 non-pregnant women and 50 women with a normal pregnancy (8–16 weeks of gestation). Combined measurements by ultrahigh performance liquid chromatography/tandem mass spectrometry and by gas chromatography/mass spectrometry generated molecular abundance measurements for each sample. Molecular species detected in at least 10 samples were included in the analysis. Differential abundance was inferred based on false discovery adjusted p-values (FDR) from Mann-Whitney-Wilcoxon U tests <0.1 and a minimum median abundance ratio (fold change) of 1.5. Alternatively, metabolic data were quantile normalized to remove sample-to-sample differences in the overall metabolite abundance (adjusted analysis).

Results

Overall, 637 small molecules met the inclusion criteria and were tested for association with pregnancy; 44% (281/637) of small molecules had significantly different abundance, of which 81% (229/281) were less abundant in pregnant than in non-pregnant women. Eight percent (14/169) of the metabolites that remained significant in the adjusted analysis also changed as a function of gestational age. A pathway analysis revealed enrichment in steroid metabolites related to sex hormones, caffeine metabolites, lysolipids, dipeptides, and polypeptide bradykinin derivatives (all, FDR < 0.1).

Conclusions

This high-throughput mass spectrometry study identified: 1) differences between pregnant vs. non-pregnant women in the abundance of 44% of the profiled plasma metabolites, including known and novel molecules and pathways; and 2) specific metabolites that changed with gestational age.

Klíčová slova:

Pregnancy – Steroids – Metabolites – Steroid hormones – Metabolomics – Metabolic networks – Metabolic pathways – Small molecules


Zdroje

1. Lee J, Romero R, Xu Y, Kim J-S, Topping V, Yoo W, et al. A signature of maternal anti-fetal rejection in spontaneous preterm birth: chronic chorioamnionitis, anti-human leukocyte antigen antibodies, and C4d. PloS one. 2011;6(2):e16806. doi: 10.1371/journal.pone.0016806 21326865

2. Mor G, Romero R, Aldo PB, Abrahams VM. Is the trophoblast an immune regulator?: the role of toll-like receptors during pregnancy. Critical Reviews™ in Immunology. 2005;25(5).

3. Macy IG, Hunscher HA, Nims B, McCosh SS. METABOLISM OF WOMEN DURING THE REPRODUCTIVE CYCLE I. CALCIUM AND PHOSPHORUS UTILIZATION IN PREGNANCY. Journal of Biological Chemistry. 1930;86(1):17–35.

4. Macy IG. Metabolic and biochemical changes in normal pregnancy. Journal of the American Medical Association. 1958;168(17):2265–71. doi: 10.1001/jama.1958.63000170009013 13610621

5. Hennen G, Pierce J, Freychet P. Human Chorionic Thyrotropin: Further Characterization and Study of Its Secretion During Pregnancy 1. The Journal of Clinical Endocrinology & Metabolism. 1969;29(4):581–94.

6. Browning HC. The evolutionary history of the corpus luteum. Biology of reproduction. 1973;8(2):128–57. doi: 10.1093/biolreprod/8.2.128 4598083

7. Romero R, Romero R. Prenatal medicine: The child is the father of the man*. The Journal of Maternal-Fetal & Neonatal Medicine. 2009;22(8):636–9.

8. Romero R, Tarca AL, Tromp G. Insights into the physiology of childbirth using transcriptomics. PLoS Med. 2006;3(6):e276. doi: 10.1371/journal.pmed.0030276 16752954

9. Smith JM. Evolutionary genetics: Oxford University Press; 1989.

10. Gibson HM. Plasma volume and glomerular filtration rate in pregnancy and their relation to differences in fetal growth. BJOG: An International Journal of Obstetrics & Gynaecology. 1973;80(12):1067–74.

11. de Haas S, Ghossein‐Doha C, van Kuijk SM, van Drongelen J, Spaanderman ME. Physiologic adaptation of plasma volume during pregnancy: a systematic review and meta‐analysis. Ultrasound in Obstetrics & Gynecology. 2016.

12. Hunter S, Robson SC. Adaptation of the maternal heart in pregnancy. British heart journal. 1992;68(6):540. doi: 10.1136/hrt.68.12.540 1467047

13. Cunningham MW, Williams JM, Amaral L, Usry N, Wallukat G, Dechend R, et al. Agonistic Autoantibodies to the Angiotensin II Type 1 Receptor Enhance Angiotensin II–Induced Renal Vascular Sensitivity and Reduce Renal Function During PregnancyNovelty and Significance. Hypertension. 2016;68(5):1308–13. doi: 10.1161/HYPERTENSIONAHA.116.07971 27698062

14. Hall JG, Pauli RM, Wilson KM. Maternal and fetal sequelae of anticoagulation during pregnancy. The American journal of medicine. 1980;68(1):122–40. doi: 10.1016/0002-9343(80)90181-3 6985765

15. Sibai BM, Ramadan MK, Usta I, Salama M, Mercer BM, Friedman SA. Maternal morbidity and mortality in 442 pregnancies with hemolysis, elevated liver enzymes, and low platelets (HELLP syndrome). American journal of obstetrics and gynecology. 1993;169(4):1000–6. doi: 10.1016/0002-9378(93)90043-i 8238109

16. Pritchard JA, Cunningham FG, Mason RA. Coagulation changes in eclampsia: their frequency and pathogenesis. American journal of obstetrics and gynecology. 1976;124(8):855–64. doi: 10.1016/s0002-9378(16)33390-7 1258945

17. Stimson W, Strachan A, Shepherd A. Studies on the maternal immune response to placental antigens: Absence of a blocking factor from the blood of abortion‐prone women. BJOG: An International Journal of Obstetrics & Gynaecology. 1979;86(1):41–5.

18. Gomez‐Lopez N, Romero R, Arenas‐Hernandez M, Ahn H, Panaitescu B, Vadillo‐Ortega F, et al. In vivo T‐cell activation by a monoclonal αCD3ε antibody induces preterm labor and birth. American Journal of Reproductive Immunology. 2016;76(5):386–90. doi: 10.1111/aji.12562 27658719

19. Della Torre S, Maggi A. Sex Differences: A Resultant of an Evolutionary Pressure? Cell Metabolism. 2017;25(3):499–505. doi: 10.1016/j.cmet.2017.01.006 28190772

20. Ahn AC, Tewari M, Poon C-S, Phillips RS. The limits of reductionism in medicine: could systems biology offer an alternative? PLoS Med. 2006;3(6):e208. doi: 10.1371/journal.pmed.0030208 16681415

21. Romero R, Espinoza J, Gotsch F, Kusanovic J, Friel L, Erez O, et al. The use of high‐dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome. BJOG: An International Journal of Obstetrics & Gynaecology. 2006;113(s3):118–35.

22. Romero R, Mazaki-Tovi S, Vaisbuch E, Kusanovic JP, Chaiworapongsa T, Gomez R, et al. Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery. The Journal of Maternal-Fetal & Neonatal Medicine. 2010;23(12):1344–59.

23. Schena M, Shalon D, Heller R, Chai A, Brown PO, Davis RW. Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. Proceedings of the National Academy of Sciences. 1996;93(20):10614–9.

24. Ryals J, Lawton K, Stevens D, Milburn M. Metabolon, Inc. 2007.

25. Luan H, Meng N, Liu P, Feng Q, Lin S, Fu J, et al. Pregnancy-induced metabolic phenotype variations in maternal plasma. Journal of proteome research. 2014;13(3):1527–36. doi: 10.1021/pr401068k 24450375

26. Luan H, Meng N, Liu P, Feng Q, Lin S, Fu J, et al. Correction to “Pregnancy-Induced Metabolic Phenotype Variations in Maternal Plasma”. Journal of proteome research. 2015;14(7):3005-. doi: 10.1021/acs.jproteome.5b00430 26035232

27. Luan H, Meng N, Liu P, Fu J, Chen X, Rao W, et al. Non-targeted metabolomics and lipidomics LC–MS data from maternal plasma of 180 healthy pregnant women. GigaScience. 2015;4(1):1.

28. Orczyk-Pawilowicz M, Jawien E, Deja S, Hirnle L, Zabek A, Mlynarz P. Metabolomics of Human Amniotic Fluid and Maternal Plasma during Normal Pregnancy. PloS one. 2016;11(4):e0152740. doi: 10.1371/journal.pone.0152740 27070784

29. Lindsay KL, Hellmuth C, Uhl O, Buss C, Wadhwa PD, Koletzko B, 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 26716698

30. Gil AM, Duarte D, Pinto J, Barros AnS. Assessing Exposome Effects on Pregnancy through Urine Metabolomics of a Portuguese (Estarreja) Cohort. Journal of proteome research. 2018;17(3):1278–89. doi: 10.1021/acs.jproteome.7b00878 29424227

31. Yan Q, Liew Z, Uppal K, Jones D, Ritz B, editors. Air Pollution and Metabolomics in Maternal Serum. ISEE Conference Abstracts; 2018.

32. Wang M, Xia W, Li H, Liu F, Li Y, Sun X, et al. Normal pregnancy induced glucose metabolic stress in a longitudinal cohort of healthy women: Novel insights generated from a urine metabolomics study. Medicine. 2018;97(40).

33. Dessì A, Marincola FC, Fanos V. Metabolomics and the great obstetrical syndromes–GDM, PET, and IUGR. Best Practice & Research Clinical Obstetrics & Gynaecology. 2015;29(2):156–64.

34. Vora N, Kalagiri R, Mallett LH, Oh JH, Wajid U, Munir S, et al. Proteomics and Metabolomics in Pregnancy—An Overview. Obstetrical & gynecological survey. 2019;74(2):111–25.

35. Dunn WB, Brown M, Worton SA, Davies K, Jones RL, Kell DB, et al. The metabolome of human placental tissue: investigation of first trimester tissue and changes related to preeclampsia in late pregnancy. Metabolomics. 2012;8(4):579–97.

36. Bahado-Singh RO, Akolekar R, Mandal R, Dong E, Xia J, Kruger M, et al. Metabolomics and first-trimester prediction of early-onset preeclampsia. The journal of maternal-fetal & neonatal medicine. 2012;25(10):1840–7.

37. Carty DM, Delles C, Dominiczak AF. Novel biomarkers for predicting preeclampsia. Trends in cardiovascular medicine. 2008;18(5):186–94. doi: 10.1016/j.tcm.2008.07.002 18790389

38. Odibo AO, Goetzinger KR, Odibo L, Cahill AG, Macones GA, Nelson DM, et al. First‐trimester prediction of preeclampsia using metabolomic biomarkers: a discovery phase study. Prenatal diagnosis. 2011;31(10):990–4. doi: 10.1002/pd.2822 21744367

39. Kenny LC, Broadhurst D, Brown M, Dunn WB, Redman CW, Kell DB, et al. Detection and identification of novel metabolomic biomarkers in preeclampsia. Reproductive Sciences. 2008;15(6):591–7. doi: 10.1177/1933719108316908 18492697

40. Kenny LC, Dunn WB, Ellis DI, Myers J, Baker PN, Kell DB, et al. Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning. Metabolomics. 2005;1(3):227.

41. Kenny LC, Broadhurst DI, Dunn W, Brown M, North RA, McCowan L, et al. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers. Hypertension. 2010;56(4):741–9. doi: 10.1161/HYPERTENSIONAHA.110.157297 20837882

42. Bahado-Singh RO, Akolekar R, Mandal R, Dong E, Xia J, Kruger M, et al. First-trimester metabolomic detection of late-onset preeclampsia. American journal of obstetrics and gynecology. 2013;208(1):58. e1-. e7.

43. Tarca AL, Lauria M, Unger M, Bilal E, Boue S, Kumar Dey K, et al. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinformatics. 2013;29(22):2892–9. Epub 2013/08/24. doi: 10.1093/bioinformatics/btt492 23966112

44. Higgins JR, Quinlivan EP, McPartlin J, Scott JM, Weir DG, Darling MR. The relationship between increased folate catabolism and the increased requirement for folate in pregnancy. BJOG: an international journal of obstetrics and gynaecology. 2000;107(9):1149–54. Epub 2000/09/26. doi: 10.1111/j.1471-0528.2000.tb11115.x 11002960.

45. Koller O. The clinical significance of hemodilution during pregnancy. Obstet Gynecol Surv. 1982;37(11):649–52. Epub 1982/11/01. doi: 10.1097/00006254-198211000-00001 7145246.

46. Virgiliou C, Gika HG, Witting M, Bletsou AA, Athanasiadis A, Zafrakas M, et al. Amniotic fluid and maternal serum metabolic signatures in the 2nd trimester associated with pre-term delivery. Journal of Proteome Research. 2017.

47. Thomas MM, Sulek K, McKenzie EJ, Jones B, Han T-L, Villas-Boas SG, et al. Metabolite Profile of Cervicovaginal Fluids from Early Pregnancy Is Not Predictive of Spontaneous Preterm Birth. International journal of molecular sciences. 2015;16(11):27741–8. doi: 10.3390/ijms161126052 26610472

48. Borowski KS, Murray J, Ryckman KK. Metabolomic markers for preterm birth. Google Patents; 2014.

49. Hill M, Pařízek A, Kancheva R, Dušková M, Velíková M, Kříž L, et al. Steroid metabolome in plasma from the umbilical artery, umbilical vein, maternal cubital vein and in amniotic fluid in normal and preterm labor. The Journal of steroid biochemistry and molecular biology. 2010;121(3):594–610.

50. Auray-Blais C, Raiche E, Gagnon R, Berthiaume M, Pasquier J-C. Metabolomics and preterm birth: What biomarkers in cervicovaginal secretions are predictive of high-risk pregnant women? International Journal of Mass Spectrometry. 2011;307(1):33–8.

51. Ghartey J, Bastek JA, Brown AG, Anglim L, Elovitz MA. Women with preterm birth have a distinct cervicovaginal metabolome. American journal of obstetrics and gynecology. 2015;212(6):776. e1-. e12.

52. Caboni P, Meloni A, Lussu M, Carta E, Barberini L, Noto A, et al. Urinary metabolomics of pregnant women at term: a combined GC/MS and NMR approach. The Journal of Maternal-Fetal & Neonatal Medicine. 2014;27(sup2):4–12.

53. Dessì A, Atzori L, Noto A, Adriaan Visser GH, Gazzolo D, Zanardo V, et al. Metabolomics in newborns with intrauterine growth retardation (IUGR): urine reveals markers of metabolic syndrome. The Journal of Maternal-Fetal & Neonatal Medicine. 2011;24(sup2):35–9.

54. Favretto D, Cosmi E, Ragazzi E, Visentin S, Tucci M, Fais P, et al. Cord blood metabolomic profiling in intrauterine growth restriction. Analytical and bioanalytical chemistry. 2012;402(3):1109–21. doi: 10.1007/s00216-011-5540-z 22101423

55. Nissen PM, Nebel C, Oksbjerg N, Bertram HC. Metabolomics reveals relationship between plasma inositols and birth weight: possible markers for fetal programming of type 2 diabetes. BioMed research international. 2010;2011.

56. 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 24312458

57. Scholtens DM, Bain JR, Reisetter AC, Muehlbauer MJ, Nodzenski M, Stevens RD, et al. Metabolic networks and metabolites underlie associations between maternal glucose during pregnancy and newborn size at birth. Diabetes. 2016;65(7):2039–50. doi: 10.2337/db15-1748 27207545

58. Bahado-Singh RO, Yilmaz A, Bisgin H, Turkoglu O, Kumar P, Sherman E, et al. Artificial intelligence and the analysis of multi-platform metabolomics data for the detection of intrauterine growth restriction. PloS one. 2019;14(4):e0214121. doi: 10.1371/journal.pone.0214121 30998683

59. Pinto J, Almeida LM, Martins AS, Duarte D, Domingues MRM, Barros AS, et al. Impact of fetal chromosomal disorders on maternal blood metabolome: toward new biomarkers? American journal of obstetrics and gynecology. 2015;213(6):841. e1-. e15.

60. Morrow AL, Lagomarcino AJ, Schibler KR, Taft DH, Yu Z, Wang B, et al. Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants. Microbiome. 2013;1(1):13. doi: 10.1186/2049-2618-1-13 24450576

61. Pinto JIM. Healthy pregnancy and prenatal disorders followed by blood plasma metabolomics. 2015.

62. Sandler V, Reisetter AC, Bain JR, Muehlbauer MJ, Nodzenski M, Stevens RD, et al. Associations of maternal BMI and insulin resistance with the maternal metabolome and newborn outcomes. Diabetologia. 2017;60(3):518–30. doi: 10.1007/s00125-016-4182-2 27981358

63. Kadakia R, Nodzenski M, Talbot O, Kuang A, Bain JR, Muehlbauer MJ, et al. Maternal metabolites during pregnancy are associated with newborn outcomes and hyperinsulinaemia across ancestries. Diabetologia. 2019;62(3):473–84. doi: 10.1007/s00125-018-4781-1 30483859

64. White SL, Lawlor DA, Briley AL, Godfrey KM, Nelson SM, Oteng-Ntim E, et al. Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention. PloS one. 2016;11(12):e0167846. doi: 10.1371/journal.pone.0167846 27930697

65. Cui Y, Xu B, Zhang X, He Y, Shao Y, Ding M. Diagnostic and therapeutic profiles of serum bile acids in women with intrahepatic cholestasis of pregnancy-a pseudo-targeted metabolomics study. Clinica Chimica Acta. 2018;483:135–41.

66. Wang Q, Würtz P, Auro K, Mäkinen V-P, Kangas AJ, Soininen P, et al. Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence. BMC medicine. 2016;14(1):205. doi: 10.1186/s12916-016-0733-0 27955712

67. Pinto J, Barros AnS, Domingues MRrM, Goodfellow BJ, Galhano El, Pita C, et al. Following healthy pregnancy by NMR metabolomics of plasma and correlation to urine. Journal of proteome research. 2015;14(2):1263–74. doi: 10.1021/pr5011982 25529102

68. Scalbert A, Brennan L, Fiehn O, Hankemeier T, Kristal BS, van Ommen B, et al. Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics. 2009;5(4):435. doi: 10.1007/s11306-009-0168-0 20046865

69. Gomez R, Romero R, Ghezzi F, Yoon BH, Mazor M, Berry SM. The fetal inflammatory response syndrome. American journal of obstetrics and gynecology. 1998;179(1):194–202. doi: 10.1016/s0002-9378(98)70272-8 9704787

70. Tarca AL, Hernandez-Andrade E, Ahn H, Garcia M, Xu Z, Korzeniewski SJ, et al. Single and Serial Fetal Biometry to Detect Preterm and Term Small-and Large-for-Gestational-Age Neonates: A Longitudinal Cohort Study. PloS one. 2016;11(11):e0164161. doi: 10.1371/journal.pone.0164161 27802270

71. Alexander GR, Himes JH, Kaufman RB, Mor J, Kogan M. A United States national reference for fetal growth. Obstetrics & Gynecology. 1996;87(2):163–8.

72. La Frano MR, Carmichael SL, Ma C, Hardley M, Shen T, Wong R, et al. Impact of post-collection freezing delay on the reliability of serum metabolomics in samples reflecting the California mid-term pregnancy biobank. Metabolomics. 2018;14(11):151. doi: 10.1007/s11306-018-1450-9 30830400

73. Ohta T, Masutomi N, Tsutsui N, Sakairi T, Mitchell M, Milburn MV, et al. Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats. Toxicologic pathology. 2009;37(4):521–35. doi: 10.1177/0192623309336152 19458390

74. Evans AM, DeHaven CD, Barrett T, Mitchell M, Milgram E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Analytical chemistry. 2009;81(16):6656–67. doi: 10.1021/ac901536h 19624122

75. Li M, Zeng T, Liu R, Chen L. Detecting tissue-specific early warning signals for complex diseases based on dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis. Briefings in bioinformatics. 2014;15(2):229–43. doi: 10.1093/bib/bbt027 23620135

76. Fok WC, Bokov A, Gelfond J, Yu Z, Zhang Y, Doderer M, et al. Combined treatment of rapamycin and dietary restriction has a larger effect on the transcriptome and metabolome of liver. Aging cell. 2014;13(2):311–9. doi: 10.1111/acel.12175 24304444

77. Bolstad BM, Irizarry RA, Åstrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19(2):185–93. doi: 10.1093/bioinformatics/19.2.185 12538238

78. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome biology. 2004;5(10):R80. doi: 10.1186/gb-2004-5-10-r80 15461798

79. Beger RD, Dunn WB, Bandukwala A, Bethan B, Broadhurst D, Clish CB, et al. Towards quality assurance and quality control in untargeted metabolomics studies. Metabolomics. 2019;15(1):4. doi: 10.1007/s11306-018-1460-7 30830465

80. Shin SY, Fauman EB, Petersen AK, Krumsiek J, Santos R, Huang J, et al. An atlas of genetic influences on human blood metabolites. Nat Genet. 2014;46(6):543–50. Epub 2014/05/13. doi: 10.1038/ng.2982 24816252

81. DeHaven CD, Evans AM, Dai H, Lawton KA. Software techniques for enabling high-throughput analysis of metabolomic datasets. Metabolomics. 2012:167–92.

82. Pappas A, Chaiworapongsa T, Romero R, Korzeniewski SJ, Cortez JC, Bhatti G, et al. Transcriptomics of maternal and fetal membranes can discriminate between gestational-age matched preterm neonates with and without cognitive impairment diagnosed at 18–24 months. PloS one. 2015;10(3):e0118573. Epub 2015/03/31. doi: 10.1371/journal.pone.0118573 25822971

83. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic acids research. 2000;28(1):27–30. doi: 10.1093/nar/28.1.27 10592173

84. Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, et al. HMDB 3.0—the human metabolome database in 2013. Nucleic acids research. 2012:gks1065.

85. Romero P, Wagg J, Green ML, Kaiser D, Krummenacker M, Karp PD. Computational prediction of human metabolic pathways from the complete human genome. Genome biology. 2004;6(1):R2. doi: 10.1186/gb-2004-6-1-r2 15642094

86. Galili T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics. 2015:btv428.

87. Friesen RW, Novak EM, Hasman D, Innis SM. Relationship of dimethylglycine, choline, and betaine with oxoproline in plasma of pregnant women and their newborn infants. The Journal of nutrition. 2007;137(12):2641–6. doi: 10.1093/jn/137.12.2641 18029477

88. Su K-P, Huang S-Y, Chiu T-H, Huang K-C, Huang C-L, Chang H-C, et al. Omega-3 fatty acids for major depressive disorder during pregnancy: results from a randomized, double-blind, placebo-controlled trial. Journal of Clinical Psychiatry. 2008;69(4):644. doi: 10.4088/jcp.v69n0418 18370571

89. Xiao Q, Moore SC, Keadle SK, Xiang Y-B, Zheng W, Peters TM, et al. Objectively measured physical activity and plasma metabolomics in the Shanghai Physical Activity Study. International journal of epidemiology. 2016:dyw033.

90. Nakajima-Kambe T, Nozue T, Mukouyama M, Nakahara T. Bioconversion of maleic acid to fumaric acid by Pseudomonas alcaligenes strain XD-1. Journal of fermentation and bioengineering. 1997;84(2):165–8.

91. Joya X, Friguls B, Ortigosa S, Papaseit E, Martínez S, Manich A, et al. Determination of maternal-fetal biomarkers of prenatal exposure to ethanol: a review. Journal of pharmaceutical and biomedical analysis. 2012;69:209–22. doi: 10.1016/j.jpba.2012.01.006 22300909

92. Jilek JL, Sant KE, Cho KH, Reed MS, Pohl J, Hansen JM, et al. Ethanol attenuates histiotrophic nutrition pathways and alters the intracellular redox environment and thiol proteome during rat organogenesis. Toxicological Sciences. 2015;147(2):475–89. doi: 10.1093/toxsci/kfv145 26185205

93. Goedert JJ, Sampson JN, Moore SC, Xiao Q, Xiong X, Hayes RB, et al. Fecal metabolomics: assay performance and association with colorectal cancer. Carcinogenesis. 2014;35(9):2089–96. doi: 10.1093/carcin/bgu131 25037050

94. Raijmakers MT, Zusterzeel PL, Roes EM, Steegers EA, Mulder TP, Peters WH. Oxidized and free whole blood thiols in preeclampsia. Obstetrics & Gynecology. 2001;97(2):272–6.

95. Genazzani A, Petraglia F, Bernardi F, Casarosa E, Salvestroni C, Tonetti A, et al. Circulating levels of allopregnanolone in humans: gender, age, and endocrine influences. The Journal of Clinical Endocrinology & Metabolism. 1998;83(6):2099–103.

96. Mondul AM, Moore SC, Weinstein SJ, Karoly ED, Sampson JN, Albanes D. Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha‐tocolpherol, beta‐carotene cancer prevention (ATBC) study. International journal of cancer. 2015;137(9):2124–32. doi: 10.1002/ijc.29576 25904191

97. Olney JW, Misra CH, De Gubareff T. Cysteine-S-Sulfate: Brain Damaging Metabolite in Sulfite Oxidase Deficiency1. Journal of Neuropathology & Experimental Neurology. 1975;34(2):167–77.

98. Coetzee E, Jackson W, Berman P. Ketonuria in pregnancy—with special reference to calorie-restricted food intake in obese diabetics. Diabetes. 1980;29(3):177–81. doi: 10.2337/diab.29.3.177 6769724

99. Lanza IR, Zhang S, Ward LE, Karakelides H, Raftery D, Nair KS. Quantitative metabolomics by 1 H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes. PloS one. 2010;5(5):e10538. doi: 10.1371/journal.pone.0010538 20479934

100. Li Y, Shan Z, Teng W, Yu X, Li Y, Fan C, et al. Abnormalities of maternal thyroid function during pregnancy affect neuropsychological development of their children at 25–30 months. Clinical endocrinology. 2010;72(6):825–9. doi: 10.1111/j.1365-2265.2009.03743.x 19878506

101. Khalil A, Tsikas D, Akolekar R, Jordan J, Nicolaides K. Asymmetric dimethylarginine, arginine and homoarginine at 11–13 weeks’ gestation and preeclampsia: a case–control study. Journal of human hypertension. 2013;27(1):38–43. doi: 10.1038/jhh.2011.109 22158463

102. Khalil A, Hardman L. The role of arginine, homoarginine and nitric oxide in pregnancy. Amino acids. 2015;47(9):1715–27. doi: 10.1007/s00726-015-2014-1 26092522

103. Valtonen P, Laitinen T, Lyyra-Laitinen T, Raitakari OT, Juonala M, Viikari JS, et al. Serum L-homoarginine concentration is elevated during normal pregnancy and is related to flow-mediated vasodilatation. Circulation Journal. 2008;72(11):1879–84. doi: 10.1253/circj.cj-08-0240 18802314

104. Ananth CV, Elsasser DA, Kinzler WL, Peltier MR, Getahun D, Leclerc D, et al. Polymorphisms in methionine synthase reductase and betaine-homocysteine S-methyltransferase genes: risk of placental abruption. Molecular genetics and metabolism. 2007;91(1):104–10. doi: 10.1016/j.ymgme.2007.02.004 17376725

105. Reiner JM. The study of metabolic turnover rates by means of isotopic tracers: I. Fundamental relations. Archives of biochemistry and biophysics. 1953;46(1):53–79. doi: 10.1016/0003-9861(53)90170-2 13092947

106. Seely AJ, Christou NV. Multiple organ dysfunction syndrome: exploring the paradigm of complex nonlinear systems. Critical care medicine. 2000;28(7):2193–200. doi: 10.1097/00003246-200007000-00003 10921540

107. Pařízek A, Hill M, Dušková M, Vítek L, Velíková M, Kancheva R, et al. A Comprehensive Evaluation of Steroid Metabolism in Women with Intrahepatic Cholestasis of Pregnancy. PLoS One. 2016;11(8):e0159203. doi: 10.1371/journal.pone.0159203 27494119

108. Mickan H, Zander J. Pregnanolones, pregnenolone and progesterone in the human feto-placental circulation at term of pregnancy. Journal of steroid biochemistry. 1979;11(4):1461–6. doi: 10.1016/0022-4731(79)90122-5 513764

109. Hirst JJ, Kelleher MA, Walker DW, Palliser HK. Neuroactive steroids in pregnancy: key regulatory and protective roles in the foetal brain. The Journal of steroid biochemistry and molecular biology. 2014;139:144–53. doi: 10.1016/j.jsbmb.2013.04.002 23669456

110. Osborne LM, Gispen F, Sanyal A, Yenokyan G, Meilman S, Payne JL. Lower allopregnanolone during pregnancy predicts postpartum depression: An exploratory study. Psychoneuroendocrinology. 2017;79:116–21. doi: 10.1016/j.psyneuen.2017.02.012 28278440

111. Borrow A, Stranahan A, Suchecki D, Yunes R. Neuroendocrine Regulation of Anxiety: Beyond the Hypothalamic‐Pituitary‐Adrenal Axis. Journal of neuroendocrinology. 2016;28(7).

112. Pařízek An, Hill M, Kancheva R, Havlíková H, Kancheva L, Cindr J, et al. Neuroactive pregnanolone isomers during pregnancy. The Journal of Clinical Endocrinology & Metabolism. 2005;90(1):395–403.

113. Adibi S, Krzysik B, Drash A. Metabolism of intravenously administered dipeptides in rats: effects on amino acid pools, glucose concentration and insulin and glucagon secretion. Clinical Science. 1977;52(2):193–204.

114. Fox R, Hilton S. Bradykinin formation in human skin as a factor in heat vasodilatation. The Journal of Physiology. 1958;142(2):219. doi: 10.1113/jphysiol.1958.sp006011 13564431

115. Fulton D, McGiff J, Quilley J. Contribution of NO and cytochrome P450 to the vasodilator effect of bradykinin in the rat kidney. British journal of pharmacology. 1992;107(3):722–5. doi: 10.1111/j.1476-5381.1992.tb14513.x 1472970

116. Li P, Chappell MC, Ferrario CM, Brosnihan KB. Angiotensin-(1–7) augments bradykinin-induced vasodilation by competing with ACE and releasing nitric oxide. Hypertension. 1997;29(1):394–8.

117. Regoli D, Barabe J. Pharmacology of bradykinin and related kinins. Pharmacological reviews. 1980;32(1):1–46. 7015371

118. Knock GA, Poston L. Bradykinin-mediated relaxation of isolated maternal resistance arteries in normal pregnancy and preeclampsia. American journal of obstetrics and gynecology. 1996;175(6):1668–74. doi: 10.1016/s0002-9378(96)70123-0 8987958

119. KENNY LC, BAKER PN, KENDALL DA, RANDALL MD. Differential mechanisms of endothelium-dependent vasodilator responses in human myometrial small arteries in normal pregnancy and pre-eclampsia. Clinical Science. 2002;103(1):67–73. doi: 10.1042/cs1030067 12095405

120. Kenny LC, Baker PN, Kendall DA, Randall MD, Dunn WR. The role of gap junctions in mediating endothelium‐dependent responses to bradykinin in myometrial small arteries isolated from pregnant women. British journal of pharmacology. 2002;136(8):1085–8. doi: 10.1038/sj.bjp.0704817 12163339

121. Sowerbutts S, Jarvis L, Setchell B. © THE INCREASE IN TESTICULAR VASCULAR PERMEABILITY INDUCED BY HUMAN CHORIONIC GONADOTROPHIN INVOLVES 5-HYDROXYTRYPTAMINE AND POSSIBLY OESTROGENS, BUT NOT TESTOSTERONE, PROSTAGLANDINS, HISTAMINE OR BRADYKININ. Australian Journal of Experimental Biology & Medical Science. 1986;64(2).

122. Félétou M, Staczek J, Duhault J. Vascular endothelial growth factor and the in vivo increase in plasma extravasation in the hamster cheek pouch. British journal of pharmacology. 2001;132(6):1342–8. doi: 10.1038/sj.bjp.0703941 11250886

123. Fraenkel M, Shafat T, Erez O, Lichtenstein Y, Awesat J, Novack V, et al. Maternal First Trimester TSH Concentrations: Do They Affect Perinatal and Endocrine Outcomes? Hormone and Metabolic Research. 2016;48(07):427–32.

124. Contempré B, Jauniaux E, Calvo R, Jurkovic D, Campbell S, De Escobar GM. Detection of thyroid hormones in human embryonic cavities during the first trimester of pregnancy. The Journal of Clinical Endocrinology & Metabolism. 1993;77(6):1719–22.

125. GUILLAUME J, SCHUSSLER GC, GOLDMAN J, WASSEL P, BACH L. Components of the Total Serum Thyroid Hormone Concentrations during Pregnancy: HighFree Thyroxine and Blunted Thyrotropin (TSH) Response to TSHReleasing Hormone in the First Trimester. The Journal of Clinical Endocrinology & Metabolism. 1985;60(4):678–84.

126. YAMAMOTO T, AMINO N, TANIZAWA O, ICHIHARA K, AZUKIZAWA M, MIYAI K. Longitudinal study or serum thyroid hormones, chorionic gonadotrophin and thyrotrophin during and after normal pregnancy. Clinical endocrinology. 1979;10(5):459–68. doi: 10.1111/j.1365-2265.1979.tb02102.x 113141

127. Morel Y, Roucher F, Plotton I, Goursaud C, Tardy V, Mallet D, editors. Evolution of steroids during pregnancy: Maternal, placental and fetal synthesis. Annales d’endocrinologie; 2016: Elsevier.

128. Levitz M, Young BK. Estrogens in pregnancy. Vitamins & Hormones. 1978;35:109–47.

129. Loriaux DL, Ruder H, Knab D, Lipsett M. Estrone sulfate, estrone, estradiol and estriol plasma levels in human pregnancy. The Journal of Clinical Endocrinology & Metabolism. 1972;35(6):887–91.

130. CSAPO AI, WIEST WG. An examination of the quantitative relationship between progesterone and the maintenance of pregnancy. Endocrinology. 1969;85(4):735–46. doi: 10.1210/endo-85-4-735 5803131

131. Garfield R, Kannan M, Daniel E. Gap junction formation in myometrium: control by estrogens, progesterone, and prostaglandins. Am J Physiol. 1980;238(3):C81–9. doi: 10.1152/ajpcell.1980.238.3.C81 7369350

132. Levy C, Robel P, Gautray J, De Brux J, Verma U, Descomps B, et al. Estradiol and progesterone receptors in human endometrium: normal and abnormal menstrual cycles and early pregnancy. American journal of obstetrics and gynecology. 1980;136(5):646–51. doi: 10.1016/0002-9378(80)91018-2 7355944

133. Pinto RM, Rabow W, Votta RA. Uterine cervix ripening in term pregnancy due to the action of estradiol-17β: A histological and histochemical study. American journal of obstetrics and gynecology. 1965;92(3):319–24.

134. Yoshinaga K, Hawkins R, Stocker J. Estrogen secretion by the rat ovary in vivo during the estrous cycle and pregnancy. Endocrinology. 1969;85(1):103–12. doi: 10.1210/endo-85-1-103 5815010

135. Gidley-Baird AA, O’Neill C, Sinosich MJ, Porter RN, Pike IL, Saunders DM. Failure of implantation in human in vitro fertilization and embryo transfer patients: the effects of altered progesterone/estrogen ratios in humans and mice. Fertility and sterility. 1986;45(1):69–74. doi: 10.1016/s0015-0282(16)49099-0 3943652

136. Forman R, Belaisch-Allart J, Fries N, Hazout A, Testart J, Frydman R. Evidence for an adverse effect of elevated serum estradiol concentrations on embryo implantation. Fertility and sterility. 1988;49(1):118–22. doi: 10.1016/s0015-0282(16)59661-7 3335258

137. Klopper A. THE ASSESSMENT OF FETO-PLACENTAL FUNCTION BY ESTRIOL ASSAY. Obstetrical & Gynecological Survey. 1968;23(9):813–38.

138. VILLEE DB, ENGEL LL, LORING JM, VILLEE CA. STEROID HYDROXYLATION IN HUMAN FETAL ADRENALS: FORMATION OF 16±-HYDROXYPROGESTERONE, 17-HYDROXYPROGESTERONE AND DEOXYCORTICOSTERONE 1. Endocrinology. 1961;69(2):354–72.

139. LEVITZ M. Conjugation and Transfer of Fetal-Placental Steroid Hormones 1. The Endocrine Society; 1966.

140. Anderson R, Baillie TA, Axelson M, Cronholm T, Sjövall K, Sjövall J. Stable isotope studies on steroid metabolism and kinetics: sulfates of 3α-hydroxy-5α-pregnane derivatives in human pregnancy. Steroids. 1990;55(10):443–57. doi: 10.1016/0039-128x(90)90013-2 2281511

141. Higashi T, Shimada K. Derivatization of neutral steroids to enhance their detection characteristics in liquid chromatography–mass spectrometry. Analytical and bioanalytical chemistry. 2004;378(4):875–82. doi: 10.1007/s00216-003-2252-z 14598004

142. Pulkkinen M, Hämäläinen MM. Myometrial estrogen and progesterone receptor binding in pregnancy: inhibition by the detergent action of phospholipids. The Journal of steroid biochemistry and molecular biology. 1995;52(3):287–94. doi: 10.1016/0960-0760(94)00175-l 7696151

143. Sandra O, Constant F, Carvalho AV, Eozénou C, Valour D, Mauffré V, et al. Maternal organism and embryo biosensoring: insights from ruminants. Journal of reproductive immunology. 2015;108:105–13. doi: 10.1016/j.jri.2014.12.005 25617112

144. Petronini PG, De Angelis E, Borghetti P, Borghetti A, Wheeler KP. Modulation by betaine of cellular responses to osmotic stress. Biochemical Journal. 1992;282(1):69–73.

145. Ericson L, Williams J, Elvehjem C. Studies on partially purified betaine-homocysteine transmethylase of liver. Journal of Biological Chemistry. 1955;212(2):537–44. 14353854

146. Miller TJ, Hanson RD, Yancey PH. Developmental changes in organic osmolytes in prenatal and postnatal rat tissues. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology. 2000;125(1):45–56.

147. Dasarathy J, Gruca LL, Bennett C, Parimi PS, Duenas C, Marczewski S, et al. Methionine metabolism in human pregnancy. The American journal of clinical nutrition. 2010;91(2):357–65. doi: 10.3945/ajcn.2009.28457 19939983

148. Altmaier E, Kastenmüller G, Römisch-Margl W, Thorand B, Weinberger KM, Illig T, et al. Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics. European journal of epidemiology. 2011;26(2):145–56. doi: 10.1007/s10654-010-9524-7 21116839

149. Verbeke W, De Bourdeaudhuij I. Dietary behaviour of pregnant versus non-pregnant women. Appetite. 2007;48(1):78–86. doi: 10.1016/j.appet.2006.07.078 17005297

150. Luan H, Ji F, Chen Y, Cai Z. statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data. Analytica chimica acta. 2018;1036:66–72. doi: 10.1016/j.aca.2018.08.002 30253838

151. Brosens I, Pijnenborg R, Vercruysse L, Romero R. The “Great Obstetrical Syndromes” are associated with disorders of deep placentation. American journal of obstetrics and gynecology. 2011;204(3):193–201. doi: 10.1016/j.ajog.2010.08.009 21094932

152. Rachakonda V, Gabbert C, Raina A, Bell LN, Cooper S, Malik S, et al. Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways. PloS one. 2014;9(12):e113860. doi: 10.1371/journal.pone.0113860 25461442

153. Barnes V, Ciancio S, Shibly O, Xu T, Devizio W, Trivedi H, et al. Metabolomics reveals elevated macromolecular degradation in periodontal disease. Journal of dental research. 2011;90(11):1293–7. doi: 10.1177/0022034511416240 21856966


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