TLR3 expression by maternal and fetal cells at the maternal-fetal interface in normal and preeclamptic pregnancies.

Inflammation and oxidative stress at the maternal-fetal interface characterize the placental dysfunction that underlies the pregnancy disorder preeclampsia. Specialized fetal trophoblasts directly interact with leukocytes at both sites of the maternal-fetal interface; the uterine wall decidua; and the placenta. TLR3 has been implicated in the harmful inflammation at the maternal-fetal interface in preeclampsia, but the cellular involvement in the decidua and placenta has not been determined. This study aimed to characterize and quantify cell-specific TLR3 expression and function at the maternal-fetal interface in normal and preeclamptic pregnancies. TLR3 expression was assessed by immunohistochemistry and quantified by a novel image-based and cell-specific quantitation method. TLR3 was expressed at the maternal-fetal interface by all decidual and placental trophoblast types and by maternal and fetal leukocytes. Placental, but not decidual, TLR3 expression was significantly higher in preeclampsia compared to normal pregnancies. This increase was attributed to placental intravillous tissue and associated with both moderate and severe placental dysfunction. TLR3 pathway functionality in the decidua and placenta was confirmed by TLR3 ligand-induced cytokine response, but the TLR3 expression levels did not correlate between the two sites. In conclusion, functional TLR3 was broadly expressed by maternal and fetal cells at both sites of the maternal-fetal interface and the placental intravillous expression was increased in preeclampsia. This suggests TLR3-mediated inflammatory involvement with local regulation at both sites of the maternal-fetal interface in normal and preeclamptic pregnancies.

A transcriptional profile of the decidua in preeclampsia.

OBJECTIVE: We sought to obtain insight into possible mechanisms underlying preeclampsia using genomewide transcriptional profiling in decidua basalis. STUDY DESIGN: Genomewide transcriptional profiling was performed on decidua basalis tissue from preeclamptic (n = 37) and normal (n = 58) pregnancies. Differentially expressed genes were identified and merged into canonical pathways and networks. RESULTS: Of the 26,504 expressed transcripts detected, 455 were differentially expressed (P < .05; false discovery rate, P < .1). Both novel (ARL5B, SLITRK4) and previously reported preeclampsia-associated (PLA2G7, HMOX1) genes were identified. Pathway analysis revealed that tryptophan metabolism, endoplasmic reticulum stress, linoleic acid metabolism, notch signaling, fatty acid metabolism, arachidonic acid metabolism, and NRF2-mediated oxidative stress response were overrepresented canonical pathways. CONCLUSION: In the present study single genes, canonical pathways, and gene-gene networks that are likely to play an important role in the pathogenesis of preeclampsia have been identified. Future functional studies are needed to accomplish a greater understanding of the mechanisms involved.

Partial correlation network analyses to detect altered gene interactions in human disease: using preeclampsia as a model.

Differences in gene expression between cases and controls have been identified for a number of human diseases. However, the underlying mechanisms of transcriptional regulation remain largely unknown. Beyond comparisons of absolute or relative expression levels, disease states may be associated with alterations in the observed correlational patterns among sets of genes. Here we use partial correlation networks aiming to compare the transcriptional co-regulation for 222 genes that are differentially expressed in decidual tissues between preeclampsia (PE) cases and non-PE controls. Partial correlation coefficients (PCCs) have been calculated in cases (N = 37) and controls (N = 58) separately. For all PCCs, we tested if they were significant non-zero in the cases and controls separately. In addition, to examine if a given PCC is different between the cases and controls, we tested if the difference between two PCCs were significant non-zero. In the group with PE cases, only five PCCs were significant (FDR p value ≤ 0.05), of which none were significantly different from the PCCs in the controls. However, in the controls we identified a total of 56 statistically significant PCCs (FDR p value ≤ 0.05), of which 31 were also significantly different (FDR p value ≤ 0.05) from the PCCs in the PE cases. The identified partial correlation networks included genes that are potentially relevant for developing PE, including both known susceptibility genes (EGFL7, HES1) and novel candidate genes (CFH, NADSYN1, DBP, FIGLA). Our results might suggest that disturbed interactions, or higher order relationships between these genes play an important role in developing the disease.