Evidence map›Paper›PMID 26874302›Full record

ArticleAmerican journal of obstetrics and gynecology2016

Evaluation of proteomic biomarkers associated with circulating microparticles as an effective means to stratify the risk of spontaneous preterm birth.

David E Cantonwine, Zhen Zhang, Kevin Rosenblatt, Kevin S Goudy, Robert C Doss, Alan M Ezrin, Gail Page, Brian Brohman, Thomas F McElrath

Open access · bronzeAbstract read
In one paragraph

Article in American journal of obstetrics and gynecology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
4.1field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  12. Extracellular Vesicles as Biomarkers of Pregnancy Complications.International journal of molecular sciences · 2024
    Review
  13. Article
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  15. Article
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  17. Article
  18. Article
  19. Preterm Birth: Screening and Prediction.International journal of women's health · 2023
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

David E CantonwineDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Boston, MA. Electronic address: dcantonwine@partners.org.
Zhen ZhangCenter for Biomarker Discovery and Translation, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
Kevin RosenblattDivision of Oncology, Department of Internal Medicine, University of Texas Health at Houston, Houston, TX.
Kevin S GoudyNX Prenatal Inc, Louisville, KY.
Robert C DossNX Prenatal Inc, Louisville, KY.
Alan M EzrinNX Prenatal Inc, Louisville, KY.
Gail PageNX Prenatal Inc, Louisville, KY.
Brian BrohmanNX Prenatal Inc, Louisville, KY.
Thomas F McElrathDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Boston, MA.
Brigham and Women's Hospital · USJohns Hopkins Medicine · USThe University of Texas Health Science Center at Houston · US

Funding

Bisphenol A and Phthalate Exposure in Relation to Fetal Growth and Preterm BirthR01ES018872 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MEEKER, JOHN D. · 2010 to 2014
$2.6M
NIEHS NIH HHS R01 ES018872
6 · The paper itself

Abstract

backgroundThe analysis of circulating microparticles in pregnancy is of revolutionary potential because it represents an in vivo biopsy of active gestational tissues.

objectiveWe hypothesized that circulating microparticle signaling will differ in pregnancies that experience spontaneous preterm birth from those delivering at term and that these differences will be evident many weeks in advance of clinical presentation. STUDY

designUtilizing plasma specimens obtained between 10 and 12 weeks' gestation as part of a prospectively collected birth cohort in which pregnancy outcomes are independently validated by 2 board-certified maternal-fetal medicine physicians, 25 singleton cases of spontaneous preterm birth ≤ 34 weeks were matched by maternal age, race, and gestational age of sampling (±2 weeks) with 50 uncomplicated term deliveries. Circulating microparticles from these first-trimester specimens were isolated and analyzed by multiple reaction monitoring mass spectrometry for potential protein biomarkers following previous studies. Markers with robust univariate performance in correlating spontaneous preterm birth were further evaluated for their biological relevance via a combined functional profiling/pathway analysis and for multivariate performance.

resultsAmong the 132 proteins evaluated, 62 demonstrated robust power of detecting spontaneous preterm birth in a bootstrap receiver-operating characteristic curve analysis at a false discovery rate of < 20% estimated via label permutation. Differential dependency network analysis identified spontaneous preterm birth-associated coexpression patterns linked to biological processes of inflammation, wound healing, and the coagulation cascade. Linear modeling of spontaneous preterm birth using a multiplex of the candidate biomarkers with a fixed sensitivity of 80% exhibited a specificity of 83% with median area under the curve of 0.89. These results indicate a strong potential of multivariate model development for informative risk stratification.

conclusionThis project has identified functional proteomic factors with associated biological processes that are already unique in their expression profiles at 10-12 weeks among women who go on to deliver spontaneously ≤ 34 weeks. These changes, with further validation, will allow the stratification of patients at risk of spontaneous preterm birth before clinical presentation.

Indexed as

Cell-Derived MicroparticlesAdultBiomarkersCase-Control StudiesChromatography, LiquidCohort StudiesFemaleHumansMass SpectrometryPregnancyPregnancy Trimester, FirstPremature BirthProteomicsRisk AssessmentROC CurveSensitivity and SpecificityBiomarkersdifferential dependency network analysisexosomesnested case/control studypregnancy

Identifiers

PMID26874302
PMCPMC4851565
OpenAlexW2259398297

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.