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Differential gene expression during placentation in pregnancies conceived with different fertility treatments
Bora Lee1, Alex F Koeppel2, Erica T Wang3
1Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, California.
Objective:
To identify differences in the transcriptomic profiles during placentation from pregnancies conceived spontaneously vs. those with infertility using non-in vitro fertilization (IVF) fertility treatment (NIFT) or IVF.
Design:
Cohort study.
Setting:
Academic medical center.
Patient(S):
Women undergoing chorionic villus sampling at gestational age 11-13 weeks (n = 141), with pregnancies that were conceived spontaneously (n = 74), with NIFT (n = 33), or with IVF (n = 34), resulting in the delivery of viable offspring.
Intervention(S):
Collection of chorionic villus samples from women who conceived spontaneously, with NIFT, or with IVF for gene expression analysis using RNA sequencing.
Main Outcome Measure(S):
Baseline maternal, paternal, and fetal demographics, maternal medical conditions, pregnancy complications, and outcomes. Differential gene expression of first-trimester placenta.
Result(S):
There were few differences in the transcriptome of first-trimester placenta from NIFT, IVF, and spontaneous pregnancies. There was one protein-coding differentially expressed gene (DEG) between the spontaneous and infertility groups, CACNA1I, one protein-coding DEG between the spontaneous and IVF groups, CACNA1I, and five protein-coding DEGs between the NIFT and IVF groups, SLC18A2, CCL21, FXYD2, PAEP, and DNER.
Conclusion(S):
This is the first and largest study looking at transcriptomic profiles of first-trimester placenta demonstrating similar transcriptomic profiles in pregnancies conceived using NIFT or IVF and spontaneous conceptions. Gene expression differences found to be highest in the NIFT group suggest that the underlying infertility, in addition to treatment-related factors, may contribute to the observed gene expression profiles.
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