Literature DB >> 23858477

Prediction of spontaneous preterm labour in at-risk pregnant women.

Stella Liong1, Megan K W Di Quinzio, Gabrielle Fleming, Michael Permezel, Gregory E Rice, Harry M Georgiou.   

Abstract

The ability to recognise women who are at-risk of preterm labour (PTL) is often difficult. Over 50% of women who are identified with factors associated with an increased risk of preterm birth will ultimately deliver at term. The cervicovaginal fluid (CVF) comprises a range of proteins secreted by gestational tissues, making it an ideal candidate for the screening of differentially expressed proteins associated with PTL. CVF samples were collected from at-risk asymptomatic women. Two-dimensional gel electrophoresis techniques were used to examine the CVF proteome of women who spontaneously delivered preterm 11-22 days later compared with gestation-matched women who delivered at term. Five candidate biomarkers were selected for further validation in a larger independent cohort of asymptomatic women. Thioredoxin (TXN) and interleukin 1 receptor antagonist (IL1RN) concentrations in the CVF were found to be significantly reduced up to 90 days prior to spontaneous PTL compared with women who subsequently delivered at term. TXN was able to predict spontaneous PTL within 28 days after sampling with a high positive predictive value (PPV) and negative predictive value (NPV) of 75.0% and 96.4% respectively. IL1RN also showed comparable PPV and NPV of 72.7% and 95.7% respectively. The discovery of these differentially expressed proteins may assist in the development of a new predictive bedside test in identifying asymptomatic women who have an increased risk of spontaneous PTL.

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Year:  2013        PMID: 23858477     DOI: 10.1530/REP-13-0175

Source DB:  PubMed          Journal:  Reproduction        ISSN: 1470-1626            Impact factor:   3.906


  9 in total

1.  Paternal DNA Methylation May Be Associated With Gestational Age at Birth.

Authors:  Rui Luo; Nandini Mukherjee; Su Chen; Yu Jiang; S Hasan Arshad; John W Holloway; Anna Hedman; Olena Gruzieva; Ellika Andolf; Goran Pershagen; Catarina Almqvist; Wilfried Jj Karmaus
Journal:  Epigenet Insights       Date:  2020-09-10

2.  Cervicovaginal fluid proteomic analysis to identify potential biomarkers for preterm birth.

Authors:  Samuel Parry; Rita Leite; M Sean Esplin; Radek Bukowski; Heping Zhang; Michael Varner; William W Andrews; George R Saade; John Ilekis; Uma M Reddy; Hao Huang; Yoel Sadovsky; Ian A Blair; Joseph Biggio
Journal:  Am J Obstet Gynecol       Date:  2019-11-20       Impact factor: 8.661

Review 3.  Utility of proteomics in obstetric disorders: a review.

Authors:  Jónathan Hernández-Núñez; Magel Valdés-Yong
Journal:  Int J Womens Health       Date:  2015-04-13

Review 4.  Predicting Preterm Labour: Current Status and Future Prospects.

Authors:  Harry M Georgiou; Megan K W Di Quinzio; Michael Permezel; Shaun P Brennecke
Journal:  Dis Markers       Date:  2015-06-15       Impact factor: 3.434

Review 5.  Human cervicovaginal fluid biomarkers to predict term and preterm labor.

Authors:  Yujing J Heng; Stella Liong; Michael Permezel; Gregory E Rice; Megan K W Di Quinzio; Harry M Georgiou
Journal:  Front Physiol       Date:  2015-05-13       Impact factor: 4.566

Review 6.  Applying Precision Public Health to Prevent Preterm Birth.

Authors:  John P Newnham; Matthew W Kemp; Scott W White; Catherine A Arrese; Roger J Hart; Jeffrey A Keelan
Journal:  Front Public Health       Date:  2017-04-04

Review 7.  Uric acid participating in female reproductive disorders: a review.

Authors:  Junhao Hu; Wenyi Xu; Haiyan Yang; Liangshan Mu
Journal:  Reprod Biol Endocrinol       Date:  2021-04-27       Impact factor: 5.211

8.  Metabolite Profile of Cervicovaginal Fluids from Early Pregnancy Is Not Predictive of Spontaneous Preterm Birth.

Authors:  Melinda M Thomas; Karolina Sulek; Elizabeth J McKenzie; Beatrix Jones; Ting-Li Han; Silas G Villas-Boas; Louise C Kenny; Lesley M E McCowan; Philip N Baker
Journal:  Int J Mol Sci       Date:  2015-11-19       Impact factor: 5.923

9.  New model for predicting preterm delivery during the second trimester of pregnancy.

Authors:  Ya-Zhi Zhu; Guo-Qin Peng; Gui-Xiang Tian; Xue-Ling Qu; Shui-Yuan Xiao
Journal:  Sci Rep       Date:  2017-09-12       Impact factor: 4.379

  9 in total

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