Antibody Microarray Analysis of Plasma Proteins for the Prediction of Histologic Chorioamnionitis in Women With Preterm Premature Rupture of Membranes
- Antibody Microarray Analysis of Plasma Proteins for the Prediction of Histologic Chorioamnionitis in Women With Preterm Premature Rupture of Membranes
- 이지은; Jeong Woo Park; Kyo Hoon Park; Yu Mi Kim; Se Jin Lee; Dong Huey Cheon
- Issue Date
- Reproductive sciences.
- VOL 26, NO 11-1484
- We aimed to identify maternal blood biomarkers predictive of histologic chorioamnionitis (HCA) in the plasma of women with preterm premature rupture of membranes (PPROM) and to determine whether the combination of these biomarkers with conventional clinical variables can improve the prediction of HCA. This retrospective cohort study included 82 consecutive women with PPROM (23-34 gestational weeks) who delivered within 96 hours of blood sampling. A membrane-based human antibody microarray was used to analyze the plasma proteome. The validation of 5 candidate biomarkers of interest was performed by enzyme-linked immunosorbent assay (ELISA) in the final cohort (n ¼ 82). Serum C-reactive protein (CRP) levels were measured at sampling. Seventy-nine molecules studied exhibited intergroup differences. Validation by ELISA confirmed higher levels of plasma matrix metalloproteinase-9 (MMP-9), interleukin-6 (IL-6), S100 A8/A9, and insulin-like growth factor-binding protein 1 (IGFBP-1), but not tissue inhibitor of metalloproteinase 1 (TIMP-1), in women with HCA than in women without HCA. Using a stepwise regression analysis, a combined prediction model was developed, which included the plasma MMP-9, serum CRP levels, and gestational age (area under the curve [AUC], 0.932). The AUC for this model was significantly greater than that for any
single variable included in the predictive model. Protein– antibody microarray technology can be useful in identifying plasma-based predictors for HCA. This study suggests that plasma MMP-9, IL-6, IGFBP-1, and S100 A8/A9 are important noninvasive predictors for HCA in women with PPROM and that the best predictive model, which combined these biomarkers with conventional clinical factors, can significantly improve the predictability for HCA.
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