The uncertainty of copy number variants: pregnancy decisions and clinical follow-up

Prenatal diagnosis of polycystic renal diseases: diagnostic yield, novel disease-causing variants, and genotype-phenotype correlations

BACKGROUND

Polycystic renal disease is a frequent congenital anomaly of the kidneys, but research using chromosomal microarray analysis and exome sequencing in fetuses with polycystic renal disease remains sparse, with most studies focusing on the multisystem or genitourinary system.

OBJECTIVE

This study aimed to assess the detection rate of detectable genetic causes of fetal polycystic renal disease at different levels, novel disease-causing variants, and genotype-phenotype correlations.

STUDY DESIGN

This study included 220 fetal polycystic renal disease cases from January 2014 to June 2022. Cases were divided into the following 3 groups: isolated multicystic dysplastic kidneys, nonisolated multicystic dysplastic kidneys, and suspected polycystic kidney disease group. We reviewed data on maternal demographics, ultrasonographic results, chromosomal microarray analysis/exome sequencing results, and pregnancy outcomes.

RESULTS

In our cohort, chromosomal microarray analysis identified 19 (8.6%) fetuses carrying chromosomal abnormalities, and the most common copy number variation was 17q12 microdeletion (7/220; 3.2%). Furthermore, 94 families chose to perform trio-exome sequencing testing, and 21 fetuses (22.3%) were found to harbor pathogenic/likely pathogenic variants. There was a significant difference in the live birth rate among the 3 groups (91/130 vs 46/80 vs 1/10; P<.001). Among 138 live birth cases, 106 (78.5%) underwent postnatal ultrasound review, of which 95 (89.6%) had a consistent prenatal-postnatal ultrasound diagnosis.

CONCLUSION

For both isolated and nonisolated polycystic renal disease, our data showed high detection efficiency with both testing tools. The detection of novel pathogenic variants expands the known disease spectrum of polycystic renal disease-associated genes while enriching our understanding of the genotype-phenotype correlation. Therefore, we consider it feasible to perform chromosomal microarray analysis+exome sequencing testing in fetal polycystic renal disease. Moreover, prenatal-postnatal ultrasound concordance was greater, the live birth rate was higher, and prognosis was better when known genetic disorders were excluded, indicating that genetic testing results significantly influenced pregnancy decisions.

Chromosome Microarray Analysis and Exome Sequencing: Implementation in Prenatal Diagnosis of Fetuses with Digestive System Malformations

(1) Purpose: Retrospective back-to-back comparisons were performed to evaluate the accuracy, effectiveness, and incremental yield of chromosome microarray analysis (CMA) and exome sequencing (ES) analysis in fetuses with digestive system malformations (DSMs). (2) Methods: In total, 595 women with fetal DSMs who underwent prenatal diagnosis were enrolled. We analyzed the diagnostic yields of CMA and ES and evaluated pregnancy outcomes. Copy number variants (CNVs) were classified according to the American College of Medical Genetics and Genomics guidelines. (3) Results: Pathogenic CNVs were detected in 11/517 (2.12%) fetuses, and variants of unknown significance (VUS) were identified in 69 (13.35%) fetuses using CMA. ES detected 29 pathogenic/likely pathogenic variants in 23/143 (16.08%) fetuses and 26/143 (18.2%) VUS. In those with other ultrasound abnormalities, the detection rate of multiple system structural malformations was 41.2%, followed by skeletal (33.3%), cardiovascular (25.4%), and central nervous system (18.6%) malformations. Of the 391 surviving children, 40 (10.2%) exhibited varying degrees of mental retardation. (4) Conclusion: A correlation exists between DSMs and chromosomal abnormalities. When combined with other systemic abnormalities, the incidence of chromosomal abnormalities increases significantly. Patients with congenital DSM are at risk of developing neurodevelopmental disorders. Combined CMA and ES detection of fetal DSM has good clinical application potential.