In vitro fertilization outcomes after preimplantation genetic testing for chromosomal structural rearrangements comparing fluorescence in-situ hybridization, microarray comparative genomic hybridization, and next-generation sequencing

Chantal B Bartels; Reeva Makhijani; Prachi Godiwala; Alison Bartolucci; John C Nulsen; Daniel R Grow; Lawrence Engmann; Claudio A Benadiva

doi:10.1016/j.xfre.2020.09.011

In vitro fertilization outcomes after preimplantation genetic testing for chromosomal structural rearrangements comparing fluorescence in-situ hybridization, microarray comparative genomic hybridization, and next-generation sequencing

F S Rep. 2020 Sep 25;1(3):249-256. doi: 10.1016/j.xfre.2020.09.011. eCollection 2020 Dec.

Authors

Chantal B Bartels¹, Reeva Makhijani¹, Prachi Godiwala¹, Alison Bartolucci¹, John C Nulsen¹, Daniel R Grow¹, Lawrence Engmann¹, Claudio A Benadiva¹

Affiliation

¹ Center for Advanced Reproductive Services, Department of Obstetrics and Gynecology, University of Connecticut, Farmington, Connecticut.

Abstract

Objective: To compare in vitro fertilization (IVF) outcomes for preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) using various testing platforms.

Design: Retrospective cohort.

Setting: Large academic IVF center.

Patients: Fifty-one balanced translocation carriers undergoing IVF with PGT-SR who completed a total of 91 cycles, including 31 fluorescence in-situ hybridization (FISH), 24 microarray comparative genomic hybridization (aCGH), and 36 next-generation sequencing (NGS) testing cycles.

Interventions: PGT-SR.

Main outcome measures: Primary outcome of live-birth rate and secondary outcomes including implantation rate, clinical loss rate, and percentages of normal or balanced, unbalanced, and aneuploid embryos detected.

Results: There was no statistically significant difference in LBR, though there was a tendency toward a higher LBR for NGS testing (14 of 19, 73.7%) compared with FISH (8 of 18, 44.4%) and aCGH (10 of 20, 50.0%). The implantation rate was statistically significantly higher for NGS (16 of 20, 80.0%) compared with FISH (11 of 25, 44.0%) and aCGH (16 of 30, 53.3%). There was no statistically significant difference in clinical pregnancy losses. There was a lower percentage of normal or balanced embryos with FISH (12.5%) compared with aCGH (23.7%) and with NGS (20.7%).

Conclusions: This is the first report of PGT-SR outcomes for translocation carriers directly comparing PGT-SR using FISH, aCGH, and NGS. Our findings suggest an improvement in pregnancy outcomes parallel to the advancement in technology and are reassuring for continued use of NGS for this population.

Keywords: Chromosomal translocation; Robertsonian translocation; next generation sequencing; preimplantation genetic testing for structural rearrangements; reciprocal translocation.