IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0227881.html
   My bibliography  Save this article

Compartmentalized profiling of amniotic fluid cytokines in women with preterm labor

Author

Listed:
  • Gaurav Bhatti
  • Roberto Romero
  • Gregory Edward Rice
  • Wendy Fitzgerald
  • Percy Pacora
  • Nardhy Gomez-Lopez
  • Mahendra Kavdia
  • Adi L Tarca
  • Leonid Margolis

Abstract

Objective: Amniotic fluid cytokines have been implicated in the mechanisms of preterm labor and birth. Cytokines can be packaged within or on the surface of extracellular vesicles. The main aim of this study was to test whether the protein abundance internal to and on the surface of extracellular vesicles changes in the presence of sterile intra-amniotic inflammation and proven intra-amniotic infection in women with preterm labor as compared to the women with preterm labor without either intra-amniotic inflammation or proven intra-amniotic infection. Study design: Women who had an episode of preterm labor and underwent an amniocentesis for the diagnosis of intra-amniotic infection or intra-amniotic inflammation were classified into three groups: 1) preterm labor without either intra-amniotic inflammation or proven intra-amniotic infection, 2) preterm labor with sterile intra-amniotic inflammation, and 3) preterm labor with intra-amniotic infection. The concentrations of 38 proteins were determined on the extracellular vesicle surface, within the vesicles, and in the soluble fraction of amniotic fluid. Results: 1) Intra-amniotic inflammation, regardless of detected microbes, was associated with an increased abundance of amniotic fluid cytokines on the extracellular vesicle surface, within vesicles, and in the soluble fraction. These changes were most prominent in women with proven intra-amniotic infection. 2) Cytokine changes on the surface of extracellular vesicles were correlated with those determined in the soluble fraction; yet the magnitude of the increase was significantly different between these compartments. 3) The performance of prediction models of early preterm delivery based on measurements on the extracellular vesicle surface was equivalent to those based on the soluble fraction. Conclusions: Differential packaging of amniotic fluid cytokines in extracellular vesicles during preterm labor with sterile intra-amniotic inflammation or proven intra-amniotic infection is reported herein for the first time. The current study provides insights into the biology of the intra-amniotic fluid ad may aid in the development of biomarkers for obstetrical disease.

Suggested Citation

  • Gaurav Bhatti & Roberto Romero & Gregory Edward Rice & Wendy Fitzgerald & Percy Pacora & Nardhy Gomez-Lopez & Mahendra Kavdia & Adi L Tarca & Leonid Margolis, 2020. "Compartmentalized profiling of amniotic fluid cytokines in women with preterm labor," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-29, January.
  • Handle: RePEc:plo:pone00:0227881
    DOI: 10.1371/journal.pone.0227881
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227881
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0227881&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0227881?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Yao & Zhan, Shuwei & Zhan, Minghua, 2024. "Has FinTech changed the sensitivity of corporate investment to interest rates?—Evidence from China," Research in International Business and Finance, Elsevier, vol. 68(C).
    2. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    3. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    4. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    5. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
    6. Dimelis, Sophia & Giotopoulos, Ioannis & Louri, Helen, 2015. "Can firms grow without credit?: evidence from the Euro Area, 2005-2011: a quantile panel analysis," LSE Research Online Documents on Economics 61157, London School of Economics and Political Science, LSE Library.
    7. Inanoglu, Hulusi & Jacobs, Michael, Jr. & Liu, Junrong & Sickles, Robin, 2015. "Analyzing Bank Efficiency: Are "Too-Big-to-Fail" Banks Efficient?," Working Papers 15-016, Rice University, Department of Economics.
    8. Ibrahim Mohamed Ali Ali & Imed Attiaoui & Rabeh Khalfaoui & Aviral Kumar Tiwari, 2022. "The Effect of Urbanization and Industrialization on Income Inequality: An Analysis Based on the Method of Moments Quantile Regression," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(1), pages 29-50, May.
    9. Hemant Kulkarni & Jayabrata Biswas & Kiranmoy Das, 2019. "A joint quantile regression model for multiple longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 453-473, December.
    10. Lin, Hsin-Yi & Chu, Hao-Pang, 2013. "Are fiscal deficits inflationary?," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 214-233.
    11. Łukasz Jarosław Kozar & Robert Matusiak & Marta Paduszyńska & Adam Sulich, 2022. "Green Jobs in the EU Renewable Energy Sector: Quantile Regression Approach," Energies, MDPI, vol. 15(18), pages 1-21, September.
    12. Gnangnon, Sèna Kimm, 2023. "The Least developed countries' TRIPS Waiver and the Strength of Intellectual Property Protection," EconStor Preprints 271537, ZBW - Leibniz Information Centre for Economics.
    13. Jing Lv & Chaohui Guo, 2017. "Efficient parameter estimation via modified Cholesky decomposition for quantile regression with longitudinal data," Computational Statistics, Springer, vol. 32(3), pages 947-975, September.
    14. Yu, Linyue & Wilcox-Gök, Virginia, 2015. "The impact of maternal depression on children’s cognitive development: An analysis based on panel quantile regressions," Economics Letters, Elsevier, vol. 126(C), pages 107-109.
    15. Miao, Yang & Razzaq, Asif & Adebayo, Tomiwa Sunday & Awosusi, Abraham Ayobamiji, 2022. "Do renewable energy consumption and financial globalisation contribute to ecological sustainability in newly industrialized countries?," Renewable Energy, Elsevier, vol. 187(C), pages 688-697.
    16. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    17. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    18. Monica-Lavinia DAN, 2022. "The Impact Of Public-Private Partnership In The Energy Field On Economic Growth," Romanian Journal of Economics, Institute of National Economy, vol. 54(1(63)), pages 24-33, June.
    19. Pei-Ing Wu & Je-Liang Liou & Hung-Yi Chang, 2015. "Alternative exploration of EKC for $$\hbox {CO}_{2}$$ CO 2 emissions: inclusion of meta-technical ratio in quantile regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 57-73, January.
    20. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 292-308.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0227881. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.