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.

Placenta is a unique organ that serves its own function, and contributes to maternal gestational adaptation and fetal development. Coordination of its transcriptome to satisfy all the maternal-fetal needs across gestation is not fully understood. MicroRNAs are powerful transcriptome modulators capable to adjust rapidly the expression level and dynamics of large gene sets. This MiR-Seq based study presents a multi-omics investigation of the human placental miRNome and its synergy with the transcriptome. The analysis included 52 placentas representing three trimesters of normal pregnancy, and term cases of late-onset preeclampsia (LO-PE), gestational diabetes and affected fetal growth. Gestational-age dependent differential expression (FDR < 0.05) was detected for 319 of 417 tested miRNAs (76.5%). A shared list of target genes of dynamic miRNAs suggested their coordinated action. The most abundant miR-143-3p revealed as a marker for pregnancy progression. The data suggested critical, but distinct roles of placenta-specific imprinted C19MC and C14MC miRNA clusters. Paternally encoded primate-specific C19MC was highly transcribed during first trimester, potentially fine-tuning the early placental transcriptome in dosage-sensitive manner. Maternally encoded eutherian C14MC showed high expression until term, underlining its key contribution across gestation. A major shift in placental miRNome (16% miRNAs) was observed in LO-PE, but not in other term pregnancy complications. Notably, 13/38 upregulated miRNAs were transcribed from C19MC and only one from C14MC, whereas 11/28 downregulated miRNAs represented C14MC and none C19MC. miR-210-3p, miR-512-5p, miR-32-5p, miR-19a-3p, miR-590-3p, miR-379-5p were differentially expressed in LO-PE and cases of small-for-gestational-age newborns, supporting a shared etiology. Expression correlation analysis with the RNA-Seq data (16,567 genes) of the same samples clustered PE-linked miRNAs into five groups. Large notable clusters of miRNA–gene pairs showing directly and inversely correlated expression dynamics suggested potential functional relationships in both scenarios. The first genome-wide study of placental miR-eQTLs identified 66 placental SNVs associated with the expression of neighboring miRNAs, including PE-linked miRNAs miR-30a-5p, miR-210-3p, miR-490-3p and miR-518-5p. This study provided a rich catalog of miRNAs for further in-depth investigations of their individual and joint effect on placental transcriptome. Several highlighted miRNAs may serve as potential biomarkers for pregnancy monitoring and targets to prevent or treat gestational disorders.

The variant rs4769613 T/C within the enhancer element near FLT1 , an acknowledged gene in preeclampsia, was previously identified as a risk factor for preeclampsia in the genome-wide association study (GWAS) targeting placental genotypes. We aimed to test the robustness of this association in 2 Estonian cohorts. Both placental sample sets HAPPY PREGNANCY (Development of novel non-invasive biomarkers for fertility and healthy pregnancy; preeclampsia, n=44 versus nonpreeclampsia, n=1724) and REPROMETA (REPROgrammed fetal and/or maternal METAbolism; 52/277) exhibited suggestive association between rs4769613[C] variant and preeclampsia (logistic regression adjusted for gestational age and fetal sex, nominal P <0.05). Meta-analysis across 2 samples (96/2001) replicated the genome-wide association study outcome (Bonferroni corrected P =4×10 -3 ; odds ratio, 1.75 [95% CI, 1.23–2.49]). No association was detected with gestational diabetes mellitus, preterm birth, and newborn parameters. Also, neither maternal nor paternal rs4769613 genotypes predisposed to preeclampsia. The exact role of placental rs4769613 genotype in the preeclampsia pathogenesis is to be clarified as no effect was detected on maternal baseline serum sFlt-1 (soluble fms-related receptor tyrosine kinase 1) levels. However, when placental FLT1 gene expression and maternal serum sFlt-1 measurements were stratified by placental rs4769613 genotypes, significantly higher transcript and biomarker levels were detected in preeclampsia versus nonpreeclampsia cases in the CC- and CT- (Student t test, P ≤0.02), but not in the TT-genotype subgroup. We suggest that rs4769613 represents a conditional expression Quantitative Trait Locus, whereby only the enhancer with the C-allele reacts to promote the FLT1 expression in unfavorable placental conditions. The study highlighted that the placental FLT1 rs4769613 C-allele is a preeclampsia-specific risk factor. It may contribute to early identification of high-risk women, for example, when genotyped in the cffDNA available in maternal blood plasma.

Context and Objectives:The study represents the first comprehensive analysis of Stanniocalcin-1 (STC1) hormone in human pregnancy, assessing clinical, lifestyle, and genetic determinants of circulating STC1 at term.Design, Setting, and Participants:Participants included women with (n = 50) and without (n = 316) preeclampsia (PE) at delivery, recruited in the REPROgrammed fetal and/or maternal METAbolism (REPROMETA) study (2006–2011, Estonia). Genetic association analysis combined PE cases (n = 597) and controls (n = 623) from the REPROMETA and Finnish Genetics of Preeclampsia Consortium (2008–2011) studies.Main Outcome Measure(s):Maternal postpartum plasma STC1 was measured by ELISA (n = 366) and placental STC1 gene expression by TaqMan quantitative RT-PCR (n = 120). Genotyping was performed using Sequenom MassArray.Results:Significantly higher STC1 plasma level was measured for the PE (median, 1952 pg/mL; 1030–4284 pg/mL) compared with non-PE group (median, 1562 pg/mL; 423–3781 pg/mL; P = 3.7 × 10−4, Mann-Whitney U test). Statistical significance was enhanced after adjustment for cofactors (linear regression, P = 1.8 × 10−6). STC1 measurements were negatively correlated with maternal smoking. Prepregnancy body mass index had a positive correlation with STC1 only among PE patients (r = 0.45; P = .001). The strongest genetic association with hormone concentrations was detected for STC1 single nucleotide polymorphisms rs3758089 (C allele: minor allele frequency, 5%; linear regression: β = 249.2 pg/mL; P = .014) and rs12678447 (G allele: minor allele frequency, 7%; β = 147.0 pg/mL; P = .082). rs12678447 placental genotypes were significantly associated with STC1 gene expression (P = .014). The REPROMETA/Finnish Genetics of Preeclampsia Consortium meta-analysis suggested an increased risk to develop late-onset PE for the rs12678447 G allele carriers (P = .05; odds ratio = 1.38 [0.98–1.93]).Conclusions:Increased STC1 hormone represents a hallmark of late-onset PE. STC1 gene variants modulate placental gene expression and maternal hormone levels.

The knowledge of genetic variants shaping human placental transcriptome is limited and they are not cataloged in the Genotype-Tissue Expression project. So far, only one whole genome analysis of placental expression quantitative trait loci (eQTLs) has been published by Peng et al. (2017) with no external independent validation. We report the second study on the landscape of placental eQTLs. The study aimed to generate a high-confidence list of placental cis -eQTLs and to investigate their potential functional implications. Analysis of cis -eQTLs (±100 kbp from the gene) utilized 40 placental RNA sequencing and respective whole genome genotyping datasets. The identified 199 placental cis -eSNPs represented 88 independent eQTL signals (FDR < 5%). The most significant placental eQTLs (FDR < 10 -5 ) modulated the expression of ribosomal protein RPL9, transcription factor ZSCAN9 and aminopeptidase ERAP2. The analysis confirmed 50 eSNP-eGenes pairs reported by Peng et al. (2017) and thus, can be claimed as robust placental eQTL signals. The study identified also 13 novel placental eGenes. Among these, ZSCAN9 is modulated by several eSNPs (experimentally validated: rs1150707) that have been also shown to affect the methylation level of genes variably escaping X-chromosomal inactivation. The identified 63 placental eGenes exhibited mostly mixed or ubiquitous expression. Functional enrichment analysis highlighted 35 Gene Ontology categories with the top ranking pathways “ruffle membrane” (FDR = 1.81 × 10 -2 ) contributing to the formation of motile cell surface and “ATPase activity, coupled” (FDR = 2.88 × 10 -2 ), critical for the membrane transport. Placental eGenes were also significantly enriched in pathways implicated in development, signaling and immune function. However, this study was not able to confirm a significant overrepresentation of genome-wide association studies top hits among the placental eSNP and eGenes, reported by Peng et al. (2017) . The identified eSNPs were further analyzed in association with newborn and pregnancy traits. In the discovery step, a suggestive association was detected between the eQTL of ALPG (rs11678251) and reduced placental, newborn’s and infant’s weight. Meta-analysis across REPROMETA, HAPPY PREGNANCY, ALSPAC cohorts ( n = 6830) did not replicate these findings. In summary, the study emphasizes the role of genetic variation in driving the transcriptome profile of the human placenta and the importance to explore further its functional implications.