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Genome-wide microRNA expression analysis in human placenta reveals sex-specific patterns: an ENVIRONAGE birth cohort study.

Maria TsamouKaren VrijensCongrong WangEllen WinckelmansKristof Y NevenNarjes MadhloumTheo M de KokTim S Nawrot
Published in: Epigenetics (2020)
There is an increasing interest in microRNAs (miRNAs) as they are of utmost importance in gene regulation at the posttranscriptional level. Sex-related susceptibility for non-communicable diseases later in life could originate in early life. Until now, no data on sex-specific miRNA expression are available for the placenta. Therefore, we investigated the difference by sex of newborn's miRNA expression in human placental tissue. Within the ENVIRONAGE birth cohort, miRNA and mRNA expression profiling was performed in 60 placentae (50% boys) using Agilent (8 × 60 K) microarrays. The distribution of chromosome locations was studied and pathway analysis of the identified sex-specific miRNAs in the placenta was carried out. Of the total 2558 miRNAs on the array, 597 miRNAs were expressed in over 70% of the samples and were included for further analyses. A total of 142 miRNAs were significantly (FDR<0.05) associated with the newborn's sex. In newborn girls, 76 miRNAs had higher expression (hsa-miR-361-5p as most significant) and 66 miRNAs had lower expression (hsa-miR-4646-5p as most significant) than in newborn boys. In the same study population, placental differentially expressed genes by sex were also identified using a whole genome approach. The placental gene expression revealed 27 differentially expressed genes by comparing girls to boys. Ultimately, we studied the miRNA-RNA interactome and identified 14 miRNA-mRNA interactions as sex-specific. Sex differences in placental m(i)RNA expression may reveal sex-specific patterns already present during pregnancy, which may influence physiological conditions in early or later life. These molecular processes might play a role in sex-specific disease susceptibility in later life.
Keyphrases
  • genome wide
  • poor prognosis
  • gene expression
  • binding protein
  • dna methylation
  • endothelial cells
  • long non coding rna
  • genome wide identification
  • single cell
  • mass spectrometry
  • artificial intelligence