The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study

Abstract

Objective: Pregnancy is accompanied by dramatic physiological changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age and determine biological processes that are perturbed in normal pregnancy.

Study design: A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median, 5) were profiled to measure the abundance of 1125 proteins using multiplex assays. Linear mixed-effects models with polynomial splines were used to model protein abundance as a function of gestational age, and the significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having the following: (1) >1.5-fold change between 8 and 40 weeks of gestation; and (2) a false discovery rate-adjusted value of P < .1. Gene ontology enrichment analysis was used to identify biological processes overrepresented among the proteins that changed with advancing gestation.

Results: The following results were found: (1) Ten percent (112 of 1125) of the profiled proteins changed in abundance as a function of gestational age; (2) of the 1125 proteins analyzed, glypican-3, sialic acid-binding immunoglobulin-type lectin-6, placental growth factor, C-C motif-28, carbonic anhydrase 6, prolactin, interleukin-1 receptor 4, dual-specificity mitogen-activated protein kinase 4, and pregnancy-associated plasma protein-A had more than a 5-fold change in abundance across gestation (these 9 proteins are known to be involved in a wide range of both physiological and pathological processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc); and (3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis, and leukocyte migration (false discovery rate, 10%).

Conclusion: The plasma proteome of normal pregnancy demonstrates dramatic changes in both the magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy and the development of biomarkers to differentiate normal vs abnormal pregnancy and determine the response to interventions.

Keywords: C-C motif-28; aptamer; biomarker; carbonic anhydrase-6; dual-specificity mitogen-activated protein kinase kinase-4; glypican-3; high-throughput biology; interleukin-1 receptor 4; placental growth factor; pregnancy-associated plasma protein A; prolactin; proteins; sialic acid-binding immunoglobulin-type lectin-6.

Figure 1

Longitudinal profiles of placenta growth factor (left) and glypican-3 (right) in normal pregnancy. Protein abundance in (log, base 2, of) relative fluorescence units is shown for each of the 43 patients (grey lines). Mean protein abundance estimated by linear mixed-effects models with cubic splines (thick blue line) as well as median level (thick black line) and 10^th / 90^th centiles computed by quantile regression are also shown. Fold change (FC) is computed as the ratio in abundance between the highest and lowest value of the mean abundance over gestation.

Figure 2

Clustering of maternal plasma average protein profiles. The figure shows three clusters of proteins with increasing overall trends (increasing rate: n=21, constant rate: n=23, and decreasing rate: n=27) and three clusters with decreasing overall trends (increasing rate: n=8, constant rate: n=16, and increasing rate: n=17).

Figure 3

Maternal plasma average protein abundance for nine highest modulated proteins. The figure shows protein abundance in log (base 2) relative fluorescence units computed from linear mixed-effects models with cubic splines. Average profiles were shifted so that minimum expression corresponds to 0 for all preteins. Most changing nine proteins were (decreasing fold change order): Glypican-3, Siglec-6: Sialic acid-binding immunoglobulin-type lectins 6, PlGF: placental growth factor, CCL28: C-C motif 28, Carbonic anhydrase 6, PRL: Prolactin, IL-1 R4: Interleukin-1 receptor 4, MP2K4: Dual specificity mitogen-activated protein kinase kinase 4, PAPP-A: pregnancy-associated plasma protein A.

Figure 4

Protein-protein interaction network in normal pregnancy. Yellow circles represent proteins profiled that change with gestation while red circles represent proteins from the Human Protein Reference Database known to interact with these. The size of the circles is proportional with the number of interactions. Proto-oncogene tyrosine-protein kinase Src (SRCN1) and Tyrosine-protein kinase Fyn (FYN) had 260 and 196 interactions, respectively.