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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Genet. | doi: 10.3389/fgene.2019.01162

A Retrospective Analysis of Ten-Year Data Assessed the Diagnostic Accuracy and Efficacy of Cytogenomic Abnormalities in Current Prenatal and Pediatric Settings

 Hongyan Chai1, Autumn DiAdamo1, Brittany Grommisch1, Fang Xu2, Qinghua Zhou3,  Jiadi Wen1, Maurice Mahoney1, Allen Bale1,  James McGrath1, Michele Spencer-Manzon1,  Peining Li1* and  Hui Zhang1*
  • 1Department of Genetics, School of Medicine, Yale University, United States
  • 2PreventionGenetics, United States
  • 3Jinan University, China

Background: Array comparative genomic hybridization (aCGH), karyotyping and fluorescence in situ hybridization (FISH) analyses have been used in a clinical cytogenetic laboratory. A systematic analysis on diagnostic findings of cytogenomic abnormalities in current prenatal and pediatric settings provides approaches for future improvement.
Methods: A retrospective analysis was performed on abnormal findings by aCGH, karyotyping and FISH from 3,608 prenatal cases and 4,509 pediatric cases during 2008-2017. The diagnostic accuracy was evaluated by comparing the abnormality detection rate (ADR) and the relative frequency (RF) of different types of cytogenomic abnormalities between prenatal and pediatric cases. A linear regression correlation between known prevalence and ADR of genomic disorders was used to extrapolate the prevalence of other genomic disorders. The diagnostic efficacy was estimated as percentage of detected abnormal cases by expected abnormal cases from served population.
Results: The composite ADR for numerical chromosome abnormalities, structural chromosome abnormalities, recurrent genomic disorders, and sporadic pathogenic copy number variants (pCNVs) in prenatal cases were 13.03%, 1.77%, 1.69%, and 0.9%, respectively, and were 5.13%, 2.84%, 7.08%, and 2.69% in pediatric cases, respectively. The chromosomal abnormalities detected in prenatal cases (14.80%) was significantly higher than that of pediatric cases (7.97%) (p < 0.05), while the pCNVs detected in prenatal cases (2.59%) was significantly lower than that of pediatric cases (9.77%) (p < 0.05). The prevalence of recurrent genomic disorders and total pCNVs was estimated to be 1/396 and 1/291, respectively. Approximately 29% and 35% of cytogenomic abnormalities expected from the population served were detected in current prenatal and pediatric diagnostic practice, respectively.
Conclusion: For chromosomal abnormalities, effective detection of Down syndrome (DS) and Turner syndrome (TS) and under detection of sex chromosome numerical abnormalities in both prenatal and pediatric cases were noted. For pCNVs, under detection of pCNVs in prenatal cases and effective detection of DiGeorge syndrome (DGS) and variable efficacy in detecting other pCNVs in pediatric cases were noted. Extend aCGH analysis to more prenatal cases with fetal ultrasonographic anomalies, enhanced non-invasive prenatal (NIPT) testing screening for syndromic genomic disorders, and better clinical indications for pCNVs are approaches that could improve diagnostic yield of cytogenomic abnormalities.

Keywords: prenatal and pediatric diagnosis, Chromosomal abnormalities, recurrent genomic disorders, microdeletions and microduplications, pathogenic copy number variants (pCNVs), abnormality detection rate (ADR), relative frequency (RF), diagnostic accuracy and efficacy

Received: 21 Jul 2019; Accepted: 23 Oct 2019.

Copyright: © 2019 Chai, DiAdamo, Grommisch, Xu, Zhou, Wen, Mahoney, Bale, McGrath, Spencer-Manzon, Li and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. Peining Li, Department of Genetics, School of Medicine, Yale University, New Haven, 06520, Connecticut, United States, peining.li@yale.edu
Dr. Hui Zhang, Department of Genetics, School of Medicine, Yale University, New Haven, 06520, Connecticut, United States, hui.zhang@yale.edu