High-throughput mRNA sequencing of human placenta shows sex differences across gestation.

INTRODUCTION: Fetal sex affects fetal and maternal health outcomes in pregnancy, but this connection remains poorly understood. As the placenta is the route of fetomaternal communication and derives from the fetal genome, placental gene expression sex differences may explain these outcomes. OBJECTIVES: We utilized next generation sequencing to study the normal human placenta in both sexes in first and third trimester to generate a normative transcriptome based on sex and gestation. STUDY DESIGN: We analyzed 124 first trimester (T1, 59 female and 65 male) and 43 third trimester (T3, 18 female and 25 male) samples for sex differences within each trimester and sex-specific gestational differences. RESULTS: Placenta shows more significant sexual dimorphism in T1, with 94 T1 and 26 T3 differentially expressed genes (DEGs). The sex chromosomes contributed 60.6% of DEGs in T1 and 80.8% of DEGs in T3, excluding X/Y pseudoautosomal regions. There were 6 DEGs from the pseudoautosomal regions, only significant in T1 and all upregulated in males. The distribution of DEGs on the X chromosome suggests genes on Xp (the short arm) may be particularly important in placental sex differences. Dosage compensation analysis of X/Y homolog genes shows expression is primarily contributed by the X chromosome. In sex-specific analyses of first versus third trimester, there were 2815 DEGs common to both sexes upregulated in T1, and 3263 common DEGs upregulated in T3. There were 7 female-exclusive DEGs upregulated in T1, 15 female-exclusive DEGs upregulated in T3, 10 male-exclusive DEGs upregulated in T1, and 20 male-exclusive DEGs upregulated in T3. DISCUSSION: This is the largest cohort of placentas across gestation from healthy pregnancies defining the normative sex dimorphic gene expression and sex common, sex specific and sex exclusive gene expression across gestation. The first trimester has the most sexually dimorphic transcripts, and the majority were upregulated in females compared to males in both trimesters. The short arm of the X chromosome and the pseudoautosomal region is particularly critical in defining sex differences in the first trimester placenta. As pregnancy is a dynamic state, sex specific DEGs across gestation may contribute to sex dimorphic changes in overall outcomes.

A systematic review of genome-wide analyses of methylation changes associated with assisted reproductive technologies in various tissues.

IMPORTANCE: Because analytic technologies improve, increasing amounts of data on methylation differences between assisted reproductive technology (ART) and unassisted conceptions are available. However, various studies use different tissue types and different populations in their analyses, making data comparison and integration difficult. OBJECTIVE: To compare and integrate data on genome-wide analyses of methylation differences due to ART, allowing exposure of overarching themes. EVIDENCE REVIEW: All studies undertaking genome-wide analysis of human methylation differences due to ART or infertility in any tissue type across the lifespan were assessed for inclusion. FINDINGS: Seventeen studies were identified that met the inclusion criteria. One study assessed trophectoderm biopsies, 2 first-trimester placenta, 1 first-trimester fetal tissue, 2 term placenta, 7 cord blood, 3 newborn dried blood spots, 1 childhood buccal smears, 1 childhood peripheral blood, and 2 adult peripheral blood. Eleven studies compared tissues from in vitro fertilization (IVF) conceptions with those of unassisted conceptions, 4 compared intracytoplasmic sperm injection with unassisted conceptions, 4 compared non-IVF fertility treatment (NIFT) with unassisted conceptions, 4 compared NIFT with IVF, and 5 compared an infertile population (conceiving via various methods) with an unassisted presumably fertile population. In studies assessing placental tissue, 1 gene with potential methylation changes due to IVF when compared with unassisted conceptions was identified by 2 studies. In blood, 11 potential genes with methylation changes due to IVF compared with unassisted conceptions were identified by 2 studies, 1 of which was identified by 3 studies. Three potentially affected genes were identified by 2 studies involving blood between intracytoplasmic sperm injection and unassisted populations. There were no overlapping genes identified in any tissue type between NIFT and unassisted populations, between NIFT and IVF, or the infertility combined population when compared with the unassisted fertile population. CONCLUSIONS: Comparing studies is challenging due to differing variables between analyses. However, even in similar tissue types and populations, overlapping methylation changes are limited, suggesting that differences due to ART are minimal. RELEVANCE: Information from this systematic review is significant for providers and patients who provide and use ART to understand methylation risks that may be associated with the technology.