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Comparison of the diagnostic yield of aCGH and NGS across different neurodevelopmental disorders

ABSTRACT: Current recommendations for the genetic diagnosis of neurodevelopmental disorders (NDDs) do not include the use of next generation sequencing (NGS) and are still based on chromosomal microarrays, such as comparative genomic hybridization array (aCGH). The present study compares the diagnostic yield obtained by aCGH and clinical exome sequencing in NDD globally and its spectrum of disorders. To that end, 1412 patients clinically diagnosed with NDDs and studied with aCGH were classified into phenotype categories: Global developmental delay/intellectual disability (GDD/ID); autism spectrum disorder (ASD); and Other NDDs. These categories were further subclassified into subcategories, based on the most frequent accompanying signs and symptoms: isolated forms, forms with epilepsy; forms with micro or macrocephaly and syndromic forms. A subset of 245 patients of the 1412 were subjected to clinical exome sequencing. Diagnostic yield of aCGH and clinical exome sequencing, expressed as the number of solved cases, was compared for each phenotype category and subcategory. Clinical exome sequencing was superior than aCGH for all cases except for isolated ASD, with no cases solved by NGS. Globally, clinical exome sequencing solved 20% of cases (versus 5.7% by aCGH) and the diagnostic yield was highest for all forms of GDD/ID and lowest for Other NDDs (7.1% versus 1.4% by aCGH) and ASD (6.1% versus 3% by aCGH). In the majority of cases, diagnostic yield was higher in the phenotype subcategories than in the mother category. These results support the use of NGS as the first-tier test in the diagnostic algorithm of all NDDs followed by aCGH when necessary.

PROVIDER: EGAS00001004949 | EGA |

REPOSITORIES: EGA

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Project description:Background: Retinoblastoma (RB) is the most common malignant childhood tumor of the eye and results from inactivation of both alleles of the RB1 gene. Nowadays RB genetic diagnosis requires classical chromosome investigations, Multiplex Ligation-dependent Probe Amplification analysis (MLPA) and Sanger sequencing. Nevertheless, these techniques show some limitations. We report our experience on a cohort of RB patients using a combined approach of Next-Generation Sequencing (NGS) and RB1 custom array-Comparative Genomic Hybridization (aCGH). Methods: A total of 65 patients with retinoblastoma were studied: 29 cases of bilateral RB and 36 cases of unilateral RB. All patients were previously tested with conventional cytogenetics and MLPA techniques. Fifty-three samples were then analysed using NGS. Eleven cases were analysed by RB1 custom aCGH. One last case was studied only by classic cytogenetics. Finally, it has been tested, in a lab sensitivity assay, the capability of NGS to detect artificial mosaicism series in previously recognized samples prepared at 3 different mosaicism frequencies: 10%, 5%, 1%. Results: Of the 29 cases of bilateral RB, 28 resulted positive (96.5%) to the genetic investigation: 22 point mutations and 6 genomic rearrangements (four intragenic and two macrodeletion). A novel germline intragenic duplication, from exon18 to exon 23, was identified in a proband with bilateral RB. Of the 36 available cases of unilateral RB, 8 patients resulted positive (22%) to the genetic investigation: 3 patients showed point mutations while 5 carried large deletion. Finally, we successfully validated, in a lab sensitivity assay, the capability of NGS to accurately measure level of artificial mosaicism down to 1%. Conclusions: NGS and RB1-custom aCGH have demonstrated to be an effective combined approach in order to optimize the overall diagnostic procedures of RB. Custom aCGH is able to accurately detect genomic rearrangements allowing the characterization of their extension. NGS is extremely accurate in detecting single nucleotide variants, relatively simple to perform, cost savings and efficient and has confirmed a high sensitivity and accuracy in identifying low levels of artificial mosaicisms.

Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.

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Comparison of the diagnostic yield of aCGH and NGS across different neurodevelopmental disorders

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