Longitudinal profiles of plasma eicosanoids during pregnancy and size for gestational age at delivery: A nested case-control study

Autoři: Barrett M. Welch aff001;  Alexander P. Keil aff002;  Thomas J. van ‘t Erve aff001;  Leesa J. Deterding aff003;  Jason G. Williams aff003;  Fred B. Lih aff003;  David E. Cantonwine aff004;  Thomas F. McElrath aff004;  Kelly K. Ferguson aff001
Působiště autorů: Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle, North Carolina, United States of America aff001;  Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America aff002;  Mass Spectrometry Research and Support Group, National Institute of Environmental Health Sciences, Research Triangle, North Carolina, United States of America aff003;  Division of Maternal-Fetal Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America aff004
Vyšlo v časopise: Longitudinal profiles of plasma eicosanoids during pregnancy and size for gestational age at delivery: A nested case-control study. PLoS Med 17(8): e32767. doi:10.1371/journal.pmed.1003271
Kategorie: Research Article
doi: 10.1371/journal.pmed.1003271



Inflammation during pregnancy is hypothesized to influence fetal growth. Eicosanoids, an important class of lipid mediators derived from polyunsaturated fatty acids, can act as both direct influences and biomarkers of inflammation through a variety of biological pathways. However, quantifying these distinct inflammatory pathways has proven difficult. We aimed to characterize a comprehensive panel of plasma eicosanoids longitudinally across gestation in pregnant women and to determine whether levels differed by infant size at delivery.

Methods and findings

Our data come from a case–control study of 90 pregnant women nested within the LIFECODES prospective birth cohort study conducted at Brigham and Women’s Hospital in Boston, Massachusetts. This study included 31 women who delivered small for gestational age (SGA) babies (SGA, ≤10th percentile), 28 who delivered large for gestational age (LGA) babies (≥90th percentile), and 31 who delivered appropriate for gestational age (AGA) babies (controls, >10th to <90th percentile). All deliveries occurred between 2010 and 2017. Most participants were in their early 30s (median age: 33 years), of white (60%) or black (20%) race/ethnicity, and of normal pre-pregnancy BMI (median BMI: 23.5 kg/m2). Women provided non-fasting plasma samples during 3 prenatal study visits (at median 11, 25, and 35 weeks gestation) and were analyzed for a panel of eicosanoids. Eicosanoids were grouped by biosynthetic pathway, defined by (1) the fatty acid precursor, including linoleic acid (LA), arachidonic acid (AA), docosahexaenoic acid (DHA), or eicosapentaenoic acid (EPA), and (2) the enzyme group, including cyclooxygenase (COX), lipoxygenase (LOX), or cytochrome P450 (CYP). Additionally, the concentrations of the 4 fatty acids (LA, AA, DHA, and EPA) were measured in maternal plasma. Analytes represent lipids from non-esterified plasma. We examined correlations among eicosanoids and trajectories across pregnancy. Differences in longitudinal concentrations between case groups were examined using Bayesian linear mixed effects models, which included participant-specific random intercepts and penalized splines on gestational age. Results showed maternal plasma levels of eicosanoids and fatty acids generally followed U-shaped curve patterns across gestation. Bayesian models showed that associations between eicosanoids and case status varied by biosynthetic pathway. Eicosanoids derived from AA via the CYP and LOX biosynthetic pathways were positively associated with SGA. The adjusted mean concentration of 12-HETE, a LOX pathway product, was 56.2% higher (95% credible interval 6.6%, 119.1%) among SGA cases compared to AGA controls. Eicosanoid associations with LGA were mostly null, but negative associations were observed with eicosanoids derived from AA by LOX enzymes. The fatty acid precursors had estimated mean concentrations 41%–97% higher among SGA cases and 33%–39% lower among LGA cases compared to controls. Primary limitations of the study included the inability to explore the potential periods of susceptibility of eicosanoids on infant size due to limited sample size, along with the use of infant size at delivery instead of longitudinal ultrasound measures to estimate fetal growth.


In this nested case–control study, we found that eicosanoids and fatty acids systematically change in maternal plasma over pregnancy. Eicosanoids from specific inflammation-related pathways were higher in mothers of SGA cases and mostly similar in mothers of LGA cases compared to controls. These findings can provide deeper insight into etiologic mechanisms of abnormal fetal growth outcomes.

Klíčová slova:

Blood plasma – Eicosanoids – Enzyme precursors – Fatty acids – Infants – Inflammation – Labor and delivery – Pregnancy


1. McCormick MC. The contribution of low birth weight to infant mortality and childhood morbidity. N Engl J Med. 1985;312(2):82–90. doi: 10.1056/NEJM198501103120204 3880598

2. Barker DJ. Adult consequences of fetal growth restriction. Clin Obstet Gynecol. 2006;49(2):270–83. doi: 10.1097/00003081-200606000-00009 16721106

3. Oral E, Cagdas A, Gezer A, Kaleli S, Aydinli K, Ocer F. Perinatal and maternal outcomes of fetal macrosomia. Eur J Obstet Gynecol Reprod Biol. 2001;99(2):167–71. doi: 10.1016/s0301-2115(01)00416-x 11788165

4. Jolly MC, Sebire NJ, Harris JP, Regan L, Robinson S. Risk factors for macrosomia and its clinical consequences: a study of 350,311 pregnancies. Eur J Obstet Gynecol Reprod Biol. 2003;111(1):9–14. doi: 10.1016/s0301-2115(03)00154-4 14557004

5. Mandy GT. Infants with fetal (intrauterine) growth restriction. UpToDate; 2019 [cited 2019 Dec 19]. Available from: https://www.uptodate.com/contents/infants-with-fetal-intrauterine-growth-restriction.

6. Rodrigues S, Robinson EJ, Kramer MS, Gray-Donald K. High rates of infant macrosomia: a comparison of a Canadian native and a non-native population. J Nutr. 2000;130(4):806–12. doi: 10.1093/jn/130.4.806 10736334

7. Boulet SL, Alexander GR, Salihu HM, Pass M. Macrosomic births in the United States: determinants, outcomes, and proposed grades of risk. Am J Obstet Gynecol. 2003;188(5):1372–8. doi: 10.1067/mob.2003.302 12748514

8. Abramowicz JS, Ahn JT. Fetal macrosomia. UpToDate; 2019 [cited 2019 Dec 19]. Available from: https://www.uptodate.com/contents/fetal-macrosomia#H4.

9. Ernst GD, de Jonge LL, Hofman A, Lindemans J, Russcher H, Steegers EA, et al. C-reactive protein levels in early pregnancy, fetal growth patterns, and the risk for neonatal complications: the Generation R Study. Am J Obstet Gynecol. 2011;205(2):132.e1–12. doi: 10.1016/j.ajog.2011.03.049 21575931

10. Thompson LP, Al-Hasan Y. Impact of oxidative stress in fetal programming. J Pregnancy. 2012;2012:582748. doi: 10.1155/2012/582748 22848830

11. Ferguson KK, Kamai EM, Cantonwine DE, Mukherjee B, Meeker JD, McElrath TF. Associations between repeated ultrasound measures of fetal growth and biomarkers of maternal oxidative stress and inflammation in pregnancy. Am J Reprod Immunol. 2018;80(4):e13017. doi: 10.1111/aji.13017 29984454

12. Buczynski MW, Dumlao DS, Dennis EA. Thematic review series: proteomics. An integrated omics analysis of eicosanoid biology. J Lipid Res. 2009;50(6):1015–38. doi: 10.1194/jlr.R900004-JLR200 19244215

13. Dennis EA, Norris PC. Eicosanoid storm in infection and inflammation. Nat Rev Immunol. 2015;15(8):511–23. doi: 10.1038/nri3859 26139350

14. Afshinnia F, Zeng L, Byun J, Wernisch S, Deo R, Chen J, et al. Elevated lipoxygenase and cytochrome P450 products predict progression of chronic kidney disease. Nephrol Dial Transplant. 2020;35(2):303–12. doi: 10.1093/ndt/gfy232 30137494

15. Jiang H, McGiff JC, Fava C, Amen G, Nesta E, Zanconato G, et al. Maternal and fetal epoxyeicosatrienoic acids in normotensive and preeclamptic pregnancies. Am J Hypertens. 2013;26(2):271–8. doi: 10.1093/ajh/hps011 23382413

16. Dalle Vedove F, Fava C, Jiang H, Zanconato G, Quilley J, Brunelli M, et al. Increased epoxyeicosatrienoic acids and reduced soluble epoxide hydrolase expression in the preeclamptic placenta. J Hypertens. 2016;34(7):1364–70. doi: 10.1097/HJH.0000000000000942 27115337

17. Aung MT, Yu Y, Ferguson KK, Cantonwine DE, Zeng L, McElrath TF, et al. Prediction and associations of preterm birth and its subtypes with eicosanoid enzymatic pathways and inflammatory markers. Sci Rep. 2019;9(1):17049. doi: 10.1038/s41598-019-53448-z 31745121

18. Hong JS, Romero R, Lee DC, Than NG, Yeo L, Chaemsaithong P, et al. Umbilical cord prostaglandins in term and preterm parturition. J Matern Fetal Neonatal Med. 2016;29(4):523–31. doi: 10.3109/14767058.2015.1011120 25758616

19. Pearson T, Zhang J, Arya P, Warren AY, Ortori C, Fakis A, et al. Measurement of vasoactive metabolites (hydroxyeicosatetraenoic and epoxyeicosatrienoic acids) in uterine tissues of normal and compromised human pregnancy. J Hypertens. 2010;28(12):2429–37. doi: 10.1097/HJH.0b013e32833e86aa 20852449

20. Gouveia-Figueira S, Martens DS, Nawrot TS, Nording ML. Cord blood eicosanoid signatures and newborn gestational age. Prostaglandins Other Lipid Mediat. 2017;133:123–7. doi: 10.1016/j.prostaglandins.2017.07.003 28736329

21. Martens DS, Gouveia S, Madhloum N, Janssen BG, Plusquin M, Vanpoucke C, et al. Neonatal cord blood oxylipins and exposure to particulate matter in the early-life environment: an ENVIRONAGE birth cohort study. Environ Health Perspect. 2017;125(4):691–8. doi: 10.1289/EHP291 27814242

22. Committee on Obstetric Practice, American Institute of Ultrasound Medicine, Society for Maternal–Fetal Medicine. Committee Opinion No 700: methods for estimating the due date. Obstet Gynecol. 2017;129(5):e150–4.

23. Oken E, Kleinman KP, Rich-Edwards J, Gillman MW. A nearly continuous measure of birth weight for gestational age using a United States national reference. BMC Pediatr. 2003;3:6. doi: 10.1186/1471-2431-3-6 12848901

24. R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2018.

25. Atenafu EG, Hamid JS, To T, Willan AR, Feldman BM, Beyene J. Bias-corrected estimator for intraclass correlation coefficient in the balanced one-way random effects model. BMC Med Res Methodol. 2012;12:126. doi: 10.1186/1471-2288-12-126 22905752

26. Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 1979;86(2):420–8. doi: 10.1037//0033-2909.86.2.420 18839484

27. Burkner PC. brms: an R package for Bayesian multilevel models using Stan. J Stat Softw. 2017;80(1):1–28. doi: 10.18637/jss.v080.i01

28. Simopoulos AP. An increase in the omega-6/omega-3 fatty acid ratio increases the risk for obesity. Nutrients. 2016;8(3):128. doi: 10.3390/nu8030128 26950145

29. Miller ER 3rd, Appel LJ, Jiang L, Risby TH. Association between cigarette smoking and lipid peroxidation in a controlled feeding study. Circulation. 1997;96(4):1097–101. doi: 10.1161/01.cir.96.4.1097 9286935

30. Zivkovic AM, Yang J, Georgi K, Hegedus C, Nording ML, O’Sullivan A, et al. Serum oxylipin profiles in IgA nephropathy patients reflect kidney functional alterations. Metabolomics. 2012;8(6):1102–13. doi: 10.1007/s11306-012-0417-5 23833568

31. Zhu YY, Li MY, Rahman ML, Hinkle SN, Wu J, Weir NL, et al. Plasma phospholipid n-3 and n-6 polyunsaturated fatty acids in relation to cardiometabolic markers and gestational diabetes: a longitudinal study within the prospective NICHD Fetal Growth Studies. PLoS Med. 2019;16(9):e1002910. doi: 10.1371/journal.pmed.1002910 31518348

32. Wilson NA, Mantzioris E, Middleton PT, Muhlhausler BS. Gestational age and maternal status of DHA and other polyunsaturated fatty acids in pregnancy: a systematic review. Prostaglandins Leukot Essent Fatty Acids. 2019;144:16–31. doi: 10.1016/j.plefa.2019.04.006 31088623

33. Meher A, Randhir K, Mehendale S, Wagh G, Joshi S. Maternal fatty acids and their association with birth outcome: a prospective study. PLoS ONE. 2016;11(1):e0147359. doi: 10.1371/journal.pone.0147359 26815428

34. Rump P, Mensink RP, Kester AD, Hornstra G. Essential fatty acid composition of plasma phospholipids and birth weight: a study in term neonates. Am J Clin Nutr. 2001;73(4):797–806. doi: 10.1093/ajcn/73.4.797 11273856

35. Haggarty P. Effect of placental function on fatty acid requirements during pregnancy. Eur J Clin Nutr. 2004;58(12):1559–70. doi: 10.1038/sj.ejcn.1602016 15266306

36. Haggarty P. Placental regulation of fatty acid delivery and its effect on fetal growth—a review. Placenta. 2002;23(Suppl A):S28–38. doi: 10.1053/plac.2002.0791 11978057

37. Dobrian AD, Lieb DC, Cole BK, Taylor-Fishwick DA, Chakrabarti SK, Nadler JL. Functional and pathological roles of the 12- and 15-lipoxygenases. Prog Lipid Res. 2011;50(1):115–31. doi: 10.1016/j.plipres.2010.10.005 20970452

38. Wu CC, Gupta T, Garcia V, Ding Y, Schwartzman ML. 20-HETE and blood pressure regulation: clinical implications. Cardiol Rev. 2014;22(1):1–12. doi: 10.1097/CRD.0b013e3182961659 23584425

39. Williams JM, Murphy S, Burke M, Roman RJ. 20-hydroxyeicosatetraeonic acid: a new target for the treatment of hypertension. J Cardiovasc Pharmacol. 2010;56(4):336–44. doi: 10.1097/FJC.0b013e3181f04b1c 20930591

40. O’Brien WF. The role of prostaglandins in labor and delivery. Clin Perinatol. 1995;22(4):973–84. 8665768

41. Challis JR, Sloboda DM, Alfaidy N, Lye SJ, Gibb W, Patel FA, et al. Prostaglandins and mechanisms of preterm birth. Reproduction. 2002;124(1):1–17. doi: 10.1530/rep.0.1240001 12090913

42. Walsh SW. Preeclampsia: an imbalance in placental prostacyclin and thromboxane production. Am J Obstet Gynecol. 1985;152(3):335–40. doi: 10.1016/s0002-9378(85)80223-4 3923838

43. Pai CH, Yen CT, Chen CP, Yu IS, Lin SW, Lin SR. Lack of thromboxane synthase prevents hypertension and fetal growth restriction after high salt treatment during pregnancy. PLoS ONE. 2016;11(3):e0151617. doi: 10.1371/journal.pone.0151617 26974824

44. Wu X, Cai H, Xiang YB, Cai Q, Yang G, Liu D, et al. Intra-person variation of urinary biomarkers of oxidative stress and inflammation. Cancer Epidemiol Biomarkers Prev. 2010;19(4):947–52. doi: 10.1158/1055-9965.EPI-10-0046 20332256

45. Mitchell JA, Knowles RB, Kirkby NS, Reed DM, Edin ML, White WE, et al. Kidney transplantation in a patient lacking cytosolic phospholipase A2 proves renal origins of urinary PGI-M and TX-M. Circ Res. 2018;122(4):555–9. doi: 10.1161/CIRCRESAHA.117.312144 29298774

46. Grosser T, Naji A, FitzGerald GA. Urinary prostaglandin metabolites: an incomplete reckoning and a flush to judgment. Circ Res. 2018;122(4):537–9. doi: 10.1161/CIRCRESAHA.118.312616 29449357

47. Fares S, Sethom MM, Hammami MB, Cheour M, Kacem S, Hadj-Taieb S, et al. Increased docosahexaenoic acid and n-3 polyunsaturated fatty acids in milk from mothers of small for gestational age preterm infants. Prostaglandins Leukot Essent Fatty Acids. 2018;135:42–6. doi: 10.1016/j.plefa.2018.07.003 30103931

48. Agostoni C, Marangoni F, Stival G, Gatelli I, Pinto F, Rise P, et al. Whole blood fatty acid composition differs in term versus mildly preterm infants: small versus matched appropriate for gestational age. Pediatr Res. 2008;64(3):298–302. doi: 10.1203/PDR.0b013e31817d9c23 18458653

49. Cinelli G, Fabrizi M, Rava L, Signore F, Vernocchi P, Semeraro M, et al. Association between maternal and foetal erythrocyte fatty acid profiles and birth weight. nutrients. 2018;10(4):402. doi: 10.3390/nu10040402 29570689

50. Wang X, Guan Q, Zhao J, Yang F, Yuan Z, Yin Y, et al. Association of maternal serum lipids at late gestation with the risk of neonatal macrosomia in women without diabetes mellitus. Lipids Health Dis. 2018;17(1):78. doi: 10.1186/s12944-018-0707-7 29642923

51. Ortega-Senovilla H, Alvino G, Taricco E, Cetin I, Herrera E. Gestational diabetes mellitus upsets the proportion of fatty acids in umbilical arterial but not venous plasma. Diabetes Care. 2009;32(1):120–2. doi: 10.2337/dc08-0679 18852337

52. Hodson L, Skeaff CM, Fielding BA. Fatty acid composition of adipose tissue and blood in humans and its use as a biomarker of dietary intake. Prog Lipid Res. 2008;47(5):348–80. doi: 10.1016/j.plipres.2008.03.003 18435934

53. Gelman A, Hill J, Yajima M. Why we (usually) don’t have to worry about multiple comparisons. J Res Educ Eff. 2012;5(2):189–211. doi: 10.1080/19345747.2011.618213

54. Greenland S. Bayesian perspectives for epidemiological research. II. Regression analysis. Int J Epidemiol. 2007;36(1):195–202. doi: 10.1093/ije/dyl289 17329317

55. ACOG Committee Opinion No. 743: low-dose aspirin use during pregnancy. Obstet Gynecol. 2018;132(1):e44–52. doi: 10.1097/AOG.0000000000002708 29939940

Článek vyšel v časopise

PLOS Medicine

2020 Číslo 8

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…

Kurzy Doporučená témata Časopisy
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.


Nemáte účet?  Registrujte se

VIRTUÁLNÍ ČEKÁRNA ČR Jste praktický lékař nebo pediatr? Zapojte se! Jste praktik nebo pediatr? Zapojte se!