[80-OR]: Increased protein network connectivity in preeclampsia

Objectives The traditional approach to understand health and disease has relied on the analyses of individual genes or proteins. Yet, biological functions are the expression of integrated and interdependent networks. We examined the behavior of protein networks in peripheral blood of normal pregnant women and those with preeclampsia (PE). Methods A cross-sectional study was conducted to include: (1) normal pregnancy ( n  = 50); (2) early PE (delivered n  = 44); and (3) late PE ( n  = 43). Multiplex assay systems were used to measure proteins. Log transformed and normalized protein concentrations in normal pregnancies were modeled using locally weighted linear quantile regression. Protein abundance was represented as MOM. Differentially expressed proteins were retained to conduct a network analysis. Results (1) Eighty-six and 24 proteins were differentially expressed in early and late PE, respectively (fold >1.5 and adjusted p 4); (2) network analysis demonstrated a more coordinated protein activity in early PE with four distinct modules (Figure). These modules represented proteins involved in cell adhesion molecules, cytokine-cytokine receptor interaction; and coagulation cascade; and (3) the cyan module which was enriched in proteins involved in cell adhesion molecules pathway was present in early, but not in normal or late PE. Conclusions We report for the first time increased connectivity in protein–protein correlation networks in PE. We propose that characterizing the protein network structure and behavior provides insight into complex diseases. Figure Legend Protein correlation network in early preeclampsia. Four protein modules were identified (green, blue, gold, magenta). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Disclosures P. Chaemsaithong: None. R. Romero: None. A.L. Tarca: None. Z. Xu: None. M. Shaman: None. K. Lannaman: None. A.I. Ahmed: None. S.S. Hassan: None. L. Yeo: None. T. Chaiworapongsa: None.