One in five pregnant women suffer from gestational complications, prevalently driven by placental malfunction. Using RNASeq, we analyzed differential placental gene expression in cases of normal gestation, late-onset preeclampsia (LO-PE), gestational diabetes (GD) and pregnancies ending with the birth of small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns (n = 8/group). In all groups, the highest expression was detected for small noncoding RNAs and genes specifically implicated in placental function and hormonal regulation. The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes. Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results. A limited number of transcription factors including LRF, SP1 and AP2 were identified as possible drivers of these changes. Notable differences were detected in differential expression signatures of LO-PE subtypes defined by the presence or absence of intrauterine growth restriction (IUGR). LO-PE with IUGR showed higher correlation with SGA and LO-PE without IUGR with LGA placentas. Whereas changes in placental transcriptome in SGA, LGA and GD cases were less prominent, the overall profiles of expressional disturbances overlapped among pregnancy complications providing support to shared placental responses. The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.

Recurrent miscarriage (RM) occurs in 1–3% of couples aiming at childbirth. Due to multifactorial etiology the clinical diagnosis of RM varies. The design of genetic/“omics” studies to identify genes and biological mechanisms involved in pathogenesis of RM has challenges as there are several options in defining the study subjects (female patient and/or couple with miscarriages, fetus/placenta) and controls. An ideal study would attempt a trio-design focusing on both partners as well as pregnancies of the couple. Application of genetic association studies focusing on pre-selected candidate genes with potential pathological effect in RM show limitations. Polymorphisms in ∼100 genes have been investigated and association with RM is often inconclusive or negative. Also, implication of prognostic molecular diagnostic tests in clinical practice exhibits uncertainties. Future directions in investigating biomolecular risk factors for RM rely on integrating alternative approaches (SNPs, copy number variations, gene/protein expression, epigenetic regulation) in studies of single genes as well as whole-genome analysis. This would be enhanced by collaborative network between research centers and RM clinics.

Very few studies have analyzed how the composition of mother’s microbiota affects the development of infant’s gut and oral microbiota during the first months of life. Here, microbiota present in the mothers’ gut, vagina, breast milk, oral cavity, and mammary areola were compared with the gut and oral microbiota of their infants over the first six months following birth. Samples were collected from the aforementioned body sites from seven mothers and nine infants at three different time points over a 6-month period. Each sample was analyzed with 16S rRNA gene sequencing. The gut microbiota of the infants harbored distinct microbial communities that had low similarity with the various maternal microbiota communities. In contrast, the oral microbiota of the infants exhibited high similarity with the microbiota of the mothers’ breast milk, mammary areola and mouth. These results demonstrate that constant contact between microbial communities increases their similarity. A majority of the operational taxonomic units in infant gut and oral microbiota were also shared with the mothers’ gut and oral communities, respectively. The disparity between the similarity and the proportion of the OTUs shared between infants’ and mothers’ gut microbiota might be related to lower diversity and therefore competition in infants’ gut microbiota.