Detection of Clinically Relevant Copy Number Variations and Genes in a Bangladeshi Cohort of Neurodevelopmental Disorders

Abstract

Background: Copy number variations (CNVs) play a critical role into the pathogenesis of neurodevelopmental disorders (NDD) among children. In this study, we aim to identify clinically relevant CNVs, genes and their phenotypic characteristics in an ethnically underrepresented homogenous population of Bangladesh. Methods: We have conducted genome-wide chromosomal microarray analysis (CMA) for 212 NDD patients with male to female ratio of 2.2:1.0 to identify rare chromosomal abnormalities (deletion /duplication/ rearrangements). To identify candidate genes within the rare CNVs, multiple gene constraint metrics (i.e. “Critical-Exon Genes (CEGs)”) were applied to the population data. Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) was followed in a subset of 95 NDD patients to assess the severity of autism and all statistical tests were performed using R package. Results: In our cohort, the head circumference of males are significantly greater than females (p=0.0002). Of all samples assayed, 12.26% (26/212) and 47.17% (100/212) patients carried pathogenic and variant of uncertain significance (VOUS) CNVs, respectively. 2.83% (6/212) pathogenic CNVs are located at the subtelomeric regions. Further burden test identified females are significant carriers of pathogenic CNVs in comparison to males (OR=4.2; p=0.0007). ADOS-2 subset show severe social communication deficit (p=0.014) and overall ASD symptoms severity (p=0.026) among the patients carrying duplication CNV compared to the CNV negative group. Candidate gene analysis identified 153 unique CEGs in pathogenic CNVs and 31 in VOUS. Of the unique genes, 18 genes were found to be in smaller (<1 MB) focal CNVs and identified PSMC3 gene as a potential candidate gene for Autism Spectrum Disorder (ASD). Moreover, we hypothesized that KMT2B gene duplication might be associated with intellectual disability. Conclusion: Our results show the utility of CMA for precise genetic diagnosis and its integration into the diagnosis therapeutics and management of NDD patients.