Circulating microparticle proteins obtained in the late first trimester predict spontaneous preterm birth at less than 35 weeks' gestation: a panel validation with specific characterization by parity.

BACKGROUND: We have previously shown that protein biomarkers associated with circulating microparticles proteins (CMPs) obtained at the end of the first trimester may detect physiologic changes in maternal-fetal interaction such that the risk of spontaneous preterm delivery ≤35 weeks can be stratified.

OBJECTIVES: We present here a study extension and validation of the CMP protein multiplex concept using a larger sample set from a multicenter population that allows for model derivation in a training set and characterization in a separate testing set.

MATERIALS AND METHODS: Ethylenediaminetetraacetic acid (EDTA) plasma was obtained from 3 established biobanks (Seattle, Boston, and Pittsburgh). Samples were from patients at a median of 10-12 weeks' gestation, and the CMPs were isolated via size-exclusion chromatography followed by protein identification via targeted protein analysis using liquid chromatography-multiple reaction monitoring-mass (LC-MRM) spectrometry. A total of 87 women delivered at ≤35 weeks, and 174 women who delivered at term were matched by maternal age (±2 years) and gestational age at sample draw (±2 weeks). From our prior work, the CMP protein multiplex comprising F13A, FBLN1, IC1, ITIH2, and LCAT was selected for validation.

RESULTS: For delivery at ≤35 weeks, the receiver operating characteristic (ROC) curve for a panel of CMP proteins (F13A, FBLN1, IC1, ITIH2, and LCAT) revealed an associated area under the ROC curve (AUC) of 0.74 (95% CI, 0.63-0.81). A separate panel of markers (IC1, LCAT, TRFE, and ITIH4), which stratified risk among mothers with a parity of 0, showed an AUC of 0.77 (95% CI, 0.61-0.90).

CONCLUSION: We have identified a set of CMP proteins that provide, at 10-12 weeks gestation, a clinically useful AUC in an independent test population. Furthermore, we determined that parity is pertinent to the diagnostic testing performance of the biomarkers for risk stratification.