Prenatal diagnosis of submicroscopic chromosomal aberrations in fetuses with congenital cystic adenomatoid malformation by chromosomal microarray analysis

Abstract

Objectives

To explore the copy number variations (CNVs) of fetal congenital cystic adenomatoid malformation (CCAM).

Methods

Fetuses with CCAM were investigated by karyotypes and chromosomal microarray analysis (CMA). The cases were classified as isolated or CCAM with additional structural anomalies. The pregnancy outcome and neonatal prognosis were reported after the follow-up investigation.

Results

The karyotypes of 43 fetuses were analyzed and no abnormal karyotype was detected. Thirty-seven cases were further tested using CMA. The CMA identified pathogenic CNVs in three fetuses with a pathogenic detection rate of 8.1%. Well-known microdeletion or microduplication syndromes, including RCAD syndrome, HNPP, and CMT1A were identified, among which HNPP and CMT1A were incidental findings. After excluding two incidental findings, there were no pathogenic CNVs in isolated CCAM. There were no significant differences in pathogenic CNVs between isolated CCAM and CCAM with additional structural anomalies (0%, 0/31 versus 16.7%, 1/6, p=.162). Nearly half of the patients (53.8%, 14/26) underwent surgery after birth with good postoperative recoveries while the remaining half patients were spontaneous regression or asymptomatic.

Conclusions

The results demonstrated the value of CMA in the prenatal diagnosis of CCAM. CCAM associated with other structural defects enhanced the frequency of pathogenic CNVs while isolated CCAM may not be associated with an increase in the prevalence of pathogenic CNVs. CCAMs have an overall good prognosis.

Keywords:

• Chromosomal microarray analysis
• congenital cystic adenomatoid malformation
• copy number variations
• prenatal diagnosis

Acknowledgments

We thank the patients and their family members for participating in this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by the National Natural Science Foundation of China [81771594, 81671474, and 81501267], Natural Science Foundation of Guangdong Province [2017A030313460], the Major Project of the Department of Science and Technology of Guangdong Province [2014B020213001 and 2013B022000005], the Major Project of the Department of Science and Technology of Guangzhou [2014Y2-00059, 201604020012, and 201704020108], the Municipal Healthcare Joint-Innovation Major Project of Guangzhou Phase III.