4.6 Article

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

Journal

Publisher

MOSBY-ELSEVIER
DOI: 10.1016/j.ajog.2016.02.005

Keywords

differential dependency network analysis; exosomes; nested case/control study; pregnancy

Funding

  1. National Institute of Environmental Health Sciences, National Institutes of Health [R01ES018872]

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BACKGROUND: The analysis of circulating microparticles in pregnancy is of revolutionary potential because it represents an in vivo biopsy of active gestational tissues. OBJECTIVE: We 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 DESIGN: Utilizing 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 boardcertified 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. RESULTS: Among the 132 proteins evaluated, 62 demonstrated robust power of detecting spontaneous preterm birth in a bootstrap receiveroperating 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. CONCLUSION: This 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.

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