Outcome of array CGH analysis for 255 subjects with intellectual disability and search for candidate genes using bioinformatics

Qiao, Ying; Harvard, Chansonette; Tyson, Christine; Li, Xudong; Fawcett, Chris; Pavlidis, Paul; Holden, J. J. A.; Sm, Lewis; Rajcan‐Separovic, Evica

doi:10.1007/s00439-010-0837-0

Cited by 23 publications

(16 citation statements)

References 70 publications

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“…In this study, of the 1354 individuals with ID/DD/MCA/autism analyzed using Agilent’s 44 K and 180 K oligonucleotide arrays, 176 patients (13.0%) were detected with pCNVs, chromosomal structural abnormalities and aneuploidies. This diagnostic yield is in consistent with the reported range of 12%-20% by several studies [5-13,24-26]. Of all the abnormal cases, the largest proportion (37.5%) belongs to recurrent genomic disorders and the other two significant groups are subtelomeric rearrangements (25.6%) and sporadic interstitial abnormalities (18.8%).…”

Section: Discussionsupporting

confidence: 91%

Cytogenomic mapping and bioinformatic mining reveal interacting brain expressed genes for intellectual disability

Schulz

et al. 2014

Mol Cytogenet

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BackgroundMicroarray analysis has been used as the first-tier genetic testing to detect chromosomal imbalances and copy number variants (CNVs) for pediatric patients with intellectual and developmental disabilities (ID/DD). To further investigate the candidate genes and underlying dosage-sensitive mechanisms related to ID, cytogenomic mapping of critical regions and bioinformatic mining of candidate brain-expressed genes (BEGs) and their functional interactions were performed. Critical regions of chromosomal imbalances and pathogenic CNVs were mapped by subtracting known benign CNVs from the Databases of Genomic Variants (DGV) and extracting smallest overlap regions with cases from DatabasE of Chromosomal Imbalance and Phenotype in Humans using Ensembl Resources (DECIPHER). BEGs from these critical regions were revealed by functional annotation using Database for Annotation, Visualization, and Integrated Discovery (DAVID) and by tissue expression pattern from Uniprot. Cross-region interrelations and functional networks of the BEGs were analyzed using Gene Relationships Across Implicated Loci (GRAIL) and Ingenuity Pathway Analysis (IPA).ResultsOf the 1,354 patients analyzed by oligonucleotide array comparative genomic hybridization (aCGH), pathogenic abnormalities were detected in 176 patients including genomic disorders in 66 patients (37.5%), subtelomeric rearrangements in 45 patients (25.6%), interstitial imbalances in 33 patients (18.8%), chromosomal structural rearrangements in 17 patients (9.7%) and aneuploidies in 15 patients (8.5%). Subtractive and extractive mapping defined 82 disjointed critical regions from the detected abnormalities. A total of 461 BEGs was generated from 73 disjointed critical regions. Enrichment of central nervous system specific genes in these regions was noted. The number of BEGs increased with the size of the regions. A list of 108 candidate BEGs with significant cross region interrelation was identified by GRAIL and five significant gene networks involving cell cycle, cell-to-cell signaling, cellular assembly, cell morphology, and gene expression regulations were denoted by IPA.ConclusionsThese results characterized ID related cross-region interrelations and multiple networks of candidate BEGs from the detected genomic imbalances. Further experimental study of these BEGs and their interactions will lead to a better understanding of dosage-sensitive mechanisms and modifying effects of human mental development.

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Section: Discussionsupporting

confidence: 91%

Cytogenomic mapping and bioinformatic mining reveal interacting brain expressed genes for intellectual disability

Schulz

et al. 2014

Mol Cytogenet

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“…24,25 Tag SNP selection and genotyping Eight Tag SNPs for XPO1 and three Tag SNPs in OTX1 and its flanking region (Supplementary Table 2) were selected based on Hapmap information, using the Applied Biosystems' SNP Browser (www.appliedbiosystems.com) and criteria as previously described. 26 Genotyping of the Tag SNPs was carried out using validated TaqMan SNP assays (Applied Biosystems) as previously described.…”

Section: Array Cghmentioning

confidence: 99%

2p15–p16.1 microdeletion syndrome: molecular characterization and association of the OTX1 and XPO1 genes with autism spectrum disorders

Malenfant

Reesor

et al. 2011

Eur J Hum Genet

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Reports of unrelated individuals with autism spectrum disorder (ASD) and similar clinical features having overlapping de novo interstitial deletions at 2p15-p16.1 suggest that this region harbors a gene(s) important to the development of autism. We molecularly characterized two such deletions, selecting two genes in this region, exportin 1 (XPO1) and orthodenticle homolog 1 (OTX1) for association studies in three North American cohorts (Autism Spectrum Disorder -Canadian American Research Consortium (ASD-CARC), New York, and Autism Genetic Resource Exchange (AGRE)) and one Italian cohort (Società Italiana per la Ricerca e la Formazione sull'Autismo (SIRFA)) of families with ASD. In XPO1, rs6735330 was associated with autism in all four cohorts (Po0.05), being significant in ASD-CARC cohorts (P-value following false discovery rate correction for multiple testing (P FDR )¼1.29Â10 À5 ), the AGRE cohort (P FDR ¼0.0011) and the combined families (P FDR ¼2.34Â10 À9 ). Similarly, in OTX1, rs2018650 and rs13000344 were associated with autism in ASD-CARC cohorts (P FDR ¼8.65Â10 À7 and 6.07Â10 5 , respectively), AGRE cohort (P FDR ¼0.0034 and 0.015, respectively) and the combined families (P FDR ¼2.34Â10 À9 and 0.00017, respectively); associations were marginal or insignificant in the New York and SIRFA cohorts. A significant association (P FDR ¼2.63Â10 À11 ) was found for the rs2018650G-rs13000344C haplotype. The above three SNPs were associated with severity of social interaction and verbal communication deficits and repetitive behaviors (P-values o0.01). No additional deletions were identified following screening of 798 ASD individuals. Our results indicate that deletion 2p15-p16.1 is not commonly associated with idiopathic ASD, but represents a novel contiguous gene syndrome associated with a constellation of phenotypic features (autism, intellectual disability, craniofacial/CNS dysmorphology), and that XPO1 and OXT1 may contribute to ASD in 2p15-p16.1 deletion cases and non-deletion cases of ASD mapping to this chromosome region.

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“…We show that a list of genes ordered by prevalence in GO (and other schemes that might be viewed as alternatives such as KEGG) performs comparably or better to real machine learning algorithms over many prediction tasks, despite lacking any specificity to the particular learning task. In another paper we provide anecdotal evidence that such effects are likely to be at play in disease candidate gene prioritization 6 . Further, node degree in many networks is correlated with the number of GO terms a gene has, so that much of the performance as evaluated with ROC curves can be explained by algorithms simply assigning all functions to high-degree nodes.…”

Section: Introductionmentioning

confidence: 99%

Progress and challenges in the computational prediction of gene function using networks

Pavlidis

Gillis

2012

F1000Res

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In this opinion piece, we attempt to unify recent arguments we have made that serious confounds affect the use of network data to predict and characterize gene function. The development of computational approaches to determine gene function is a major strand of computational genomics research. However, progress beyond using BLAST to transfer annotations has been surprisingly slow. We have previously argued that a large part of the reported success in using "guilt by association" in network data is due to the tendency of methods to simply assign new functions to already well-annotated genes. While such predictions will tend to be correct, they are generic; it is true, but not very helpful, that a gene with many functions is more likely to have any function. We have also presented evidence that much of the remaining performance in cross-validation cannot be usefully generalized to new predictions, making progressive improvement in analysis difficult to engineer. Here we summarize our findings about how these problems will affect network analysis, discuss some ongoing responses within the field to these issues, and consolidate some recommendations and speculation, which we hope will modestly increase the reliability and specificity of gene function prediction.

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Outcome of array CGH analysis for 255 subjects with intellectual disability and search for candidate genes using bioinformatics

Cited by 23 publications

References 70 publications

Cytogenomic mapping and bioinformatic mining reveal interacting brain expressed genes for intellectual disability

Cytogenomic mapping and bioinformatic mining reveal interacting brain expressed genes for intellectual disability

2p15–p16.1 microdeletion syndrome: molecular characterization and association of the OTX1 and XPO1 genes with autism spectrum disorders

Progress and challenges in the computational prediction of gene function using networks

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