Open AccessChromosomal microarray in postnatal diagnosis of congenital anomalies and neurodevelopmental disorders in Serbian patients
Author(s) -
Perovic Dijana,
Damnjanovic Tatjana,
Jekic Biljana,
DusanovicPjevic Marija,
Grk Milka,
Djuranovic Ana,
Rasic Milica,
Novakovic Ivana,
Maksimovic Nela
Publication year - 2022
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.24441
Subject(s) - copy number variation , intellectual disability , microarray , comparative genomic hybridization , phenotype , genetics , microarray analysis techniques , genetic heterogeneity , medicine , biology , bioinformatics , genome , gene , gene expression
Background Array‐based genomic analysis is a gold standard for the detection of copy number variations (CNVs) as an important source of benign as well as pathogenic variations in humans. The introduction of chromosomal microarray (CMA) has led to a significant leap in diagnostics of genetically caused congenital malformations and neurodevelopmental disorders, with an average diagnostic yield of 15%. Here, we present our experience from a single laboratory perspective in four years’ postnatal clinical CMA application. Methods DNA samples of 430 patients with congenital anomalies and/or neurodevelopmental disorders were analyzed by comparative genome hybridization using oligonucleotide‐based microarray platforms. Interpretation of detected CNVs was performed according to current guidelines. The detection rate (DR) of clinically significant findings (pathogenic/likely pathogenic CNVs) was calculated for the whole cohort and isolated or combined phenotypic categories. Results A total of 140 non‐benign CNVs were detected in 113/430 patients (26.5%). In 70 patients at least one CNV was considered clinically significant thus reaching a diagnostic yield of 16.3%. The more complex the phenotype, including developmental delay/intellectual disability (DD/ID) as a prevailing feature, the higher the DR of clinically significant CNVs is obtained. Isolated congenital anomalies had the lowest, while the “dysmorphism plus” category had the highest diagnostic yield. Conclusion In our study, CMA proved to be a very useful method in the diagnosis of genetically caused congenital anomalies and neurodevelopmental disorders. DD/ID and dysmorphism stand out as important phenotypic features that significantly increase the diagnostic yield of the analysis.