Paired parental and product-of-conception genetic analysis for clinical management of recurrent pregnancy loss associated with chromosomal rearrangements

Abstract

The etiology of recurrent pregnancy loss (RPL) is complex, with embryonic chromosomal abnormalities being a significant genetic factor. However, genetic testing of miscarriage tissues alone may fail to identify parental carriers, leading to inaccurate recurrence risk assessment. Clarifying the parental origin of abnormal embryonic chromosomal segments is therefore a prerequisite for formulating precise reproductive management strategies. We conducted a longitudinal study of 13 families to document complete reproductive histories. To trace the origin of genetic variants and clarify the pathogenic etiology, we performed copy number variation sequencing (CNV-seq) on miscarriage tissues or amniotic fluid, alongside conventional karyotyping of peripheral blood samples from both partners. The cohort experienced 38 pregnancies resulting in only 5 healthy live births, with a pregnancy loss rate of 86.8%.Cytogenetic analysis confirmed that one partner in all 13 couples was a carrier of a chromosomal structural abnormality. Among the 13 miscarriage specimens available for testing, 10 were found to harbor unbalanced chromosomal rearrangements. The unbalanced chromosomal segments in these cases were derived from the corresponding parental balanced carrier. Three cases of miscarriage tissues suggested trisomy changes in the embryo. By integrating the data of parents and offspring, the source of the parents for unbalanced rearrangement was precisely defined, the cause was identified, and excessive examination of other factors was avoided. The detection of CNV-seq in abortion products combined with parental karyotypes is an effective strategy for the etiological diagnosis of recurrent miscarriage. This method can not only clarify the cause of this miscarriage, but also accurately identify high-risk carriers and provide them with targeted reproductive intervention suggestions, thereby optimizing clinical management.