Placental network differences among obstetric syndromes identified with an integrated multiomics approach

The placenta is essential for pregnancy, and its dysfunction can harm both mother and fetus. To better understand placental physiology and its disruption in disease, we employ a multiomics approach (transcriptomics, metabolomics, and proteomics) combined with clinical data and histopathology from 321 placentas across conditions: severe fetal growth restriction (FGR), FGR with hypertension (FGR + HDP), severe preeclampsia (PE), and spontaneous preterm delivery (PTD). Cellular deconvolution reveals FGR + HDP placentas have more extravillous trophoblasts than controls (p < 0.0001). After adjusting for fetal sex and gestational age, we build condition-specific interomics networks and detect communities (a.k.a. subnetworks). In a control community, miR-365a-3p is the most connected node, whereas in FGR + HDP placentas, it is hypoxia-induced miR-210-3p. From this community, we identify a signature containing mRNAs implicated in placental dysfunction (e.g. FLT1, FSTL3, HTRA4, LEP, and PHYHIP), which distinguishes FGR + HDP placentas from those with other conditions, illustrating the power of interomics in understanding obstetric syndromes.