Differential gene expression during placentation in pregnancies conceived with different fertility treatments compared with spontaneous pregnancies.
Lee B, Koeppel AF, Wang ET, Gonzalez TL, Sun T, Kroener L, Lin Y, Joshi NV, Ghadiali T, Turner SD, Rich SS, Farber CR, Rotter JI, Ida Chen YD, Goodarzi MO, Guller S, Harwood B, Serna TB, Williams J 3rd, Pisarska MD.Fertility and Sterility. 2019 Jan 2. pii: S0015-0282(18)32200-3. doi: 10.1016/j.fertnstert.2018.11.005.
Links
- PubMed ID: 30611556
- Fertility and Sterility journal article
Layman's summary
One big question in maternal-fetal health research is: how do fertility treatments affect the baby's health and biology? There's some mixed evidence that babies born with the help of fertility treatments may have lower birth weights (though we didn't find this), higher risk of pregnancy complications, and greater risk of metabolic issues later in life. Are these differences due to the parents' innate biology (whatever led to the infertility in the first place) or due to the medical treatments?
To help figure this out, we compared placenta tissue from ongoing pregnancies to see if there were RNA differences between three groups: spontaneous (no infertility), NIFT (non-IVF fertility treatments, e.g. medicine to help stimulate ovulation), and IVF pregnancies. We got RNA from placenta tissue leftover after a late first trimester test called "chorionic villus sampling" (CVS). It is a prenatal diagnostic test that takes a very small biopsy of the placenta to indirectly check the baby's genetics and make sure the pregnancy is healthy. Using CVS tissue gives us a unique opportunity to study first trimester gene expression in pregnancies that lead to live births.
Results and discussion: Only a few individual genes were significantly different between groups, probably because there was a lot of variability within the patient groups. This is good news since it means that gene expression in late first trimester was pretty similar among all patients. We next looked for trends in pathways (groups of genes). Many immune-related pathways were significantly different in IVF vs spontaneous pregnancies, and some also different in the NIFT vs spontaneous pregnancies. Our lab is continuing to study what this means for patients.
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.Abstract
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.
