Dataset Information

Analysis of Intellectual Disability Copy Number Variants for Association With Schizophrenia.

ABSTRACT: IMPORTANCE:At least 11 rare copy number variants (CNVs) have been shown to be major risk factors for schizophrenia (SZ). These CNVs also increase the risk for other neurodevelopmental disorders, such as intellectual disability. It is possible that additional intellectual disability-associated CNVs increase the risk for SZ but have not yet been implicated in SZ because of previous studies being underpowered. OBJECTIVE:To examine whether additional CNVs implicated in intellectual disability represent novel SZ risk loci. DESIGN, SETTING, AND PARTICIPANTS:We used single-nucleotide polymorphism (SNP) array data to evaluate a set of 51 CNVs implicated in intellectual disability (excluding the known SZ loci) in a large data set of patients with SZ and healthy persons serving as controls recruited in a variety of settings. We analyzed a new sample of 6934 individuals with SZ and 8751 controls and combined those data with previously published large data sets for a total of 20?403 cases of SZ and 26?628 controls. MAIN OUTCOMES AND MEASURES:Burden analysis of CNVs implicated in intellectual disability (excluding known SZ CNVs) for association with SZ. Association of individual intellectual disability CNV loci with SZ. RESULTS:Of data on the 20?403 cases (6151 [30.15%] female) and 26?628 controls (14?252 [53.52%] female), 51 intellectual disability CNVs were analyzed. Collectively, intellectual disability CNVs were significantly enriched for SZ (P?=?1.0?×?10-6; odds ratio [OR], 1.9 [95% CI, 1.46-2.49]). Of the 51 CNVs tested, 19 (37%) were more common in SZ cases; only 4 (8%) were more common in controls (no observations were made for the remaining 28 [55%] loci). One novel locus, deletion at 16p12.1, was significantly associated with SZ after correction for multiple testing (rate in SZ, 33 [0.16%]; rate in controls, 12 [0.05%]; corrected P?=?.017; OR, 3.3; 95% CI, 1.61-7.05), and 2 loci reached nominal levels of significance (deletions at 2q11.2: 6 [0.03%] vs 1 [0.004%]; OR, 9.3; 95% CI, 1.03-447.76; corrected P?>?.99; and duplications at 10q11.21q11.23: 5 [0.2%] vs 0 [0.03%]; OR, infinity; 95% CI, 1.26-infinity; corrected P?=?.71). Our new data set also provided independent support for the 11 SZ risk loci previously reported to be associated with the disorder and for the protective effect of 22q11.2 duplication. CONCLUSIONS AND RELEVANCE:A large proportion of CNV loci implicated in intellectual disability are risk factors for SZ, but the available sample size precludes statistical confirmation for additional individual loci.

SUBMITTER: Rees E

PROVIDER: S-EPMC5014093 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Analysis of Intellectual Disability Copy Number Variants for Association With Schizophrenia.

Rees Elliott E Kendall Kimberley K Pardiñas Antonio F AF Legge Sophie E SE Pocklington Andrew A Escott-Price Valentina V MacCabe James H JH Collier David A DA Holmans Peter P O'Donovan Michael C MC Owen Michael J MJ Walters James T R JTR Kirov George G

JAMA psychiatry 20160901 9

<h4>Importance</h4>At least 11 rare copy number variants (CNVs) have been shown to be major risk factors for schizophrenia (SZ). These CNVs also increase the risk for other neurodevelopmental disorders, such as intellectual disability. It is possible that additional intellectual disability-associated CNVs increase the risk for SZ but have not yet been implicated in SZ because of previous studies being underpowered.<h4>Objective</h4>To examine whether additional CNVs implicated in intellectual di ...[more]

PMID: 27602560

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Project description:BackgroundDNA copy number variants (CNVs) are found in 15% of subjects with ID but their association with phenotypic abnormalities has been predominantly studied in smaller cohorts of subjects with detailed yet non-systematically categorized phenotypes, or larger cohorts (thousands of cases) with smaller number of generalized phenotypes.MethodsWe evaluated the association of de novo, familial and common CNVs detected in 78 ID subjects with phenotypic abnormalities classified using the Winter-Baraitser Dysmorphology Database (WBDD) (formerly the London Dysmorphology Database). Terminology for 34 primary (coarse) and 169 secondary (fine) phenotype features were used to categorize the abnormal phenotypes and determine the prevalence of each phenotype in patients grouped by the type of CNV they had.ResultsIn our cohort more than 50% of cases had abnormalities in primary categories related to head (cranium, forehead, ears, eye globes, eye associated structures, nose) as well as hands and feet. The median number of primary and secondary abnormalities was 12 and 18 per subject, respectively, indicating that the cohort consisted of subjects with a high number of phenotypic abnormalities (median De Vries score for the cohort was 5). The prevalence of each phenotypic abnormality was comparable in patients with de novo or familial CNVs in comparison to those with only common CNVs, although a trend for increased frequency of cranial and forehead abnormalities was noted in subjects with rare de novo and familial CNVs. Two clusters of subjects were identified based on the prevalence of each fine phenotypic feature, with an average of 28.3 and 13.5 abnormal phenotypes/subject in the two clusters respectively (P?<?0.05).ConclusionsOur study is a rare example of using standardized, deep morphologic phenotype clustering with phenotype/CNV correlation in a cohort of subjects with ID. The composition of the cohort inevitably influences the phenotype/genotype association, and our studies show that the influence of the de novo CNVs on the phenotype is less obvious in cohorts consisting of subjects with a high number of phenotypic abnormalities. The outcome of phenotype/genotype analysis also depends on the choice of phenotypes assessed and standardized phenotyping is required to minimize variability.

Project description:Epilepsy is genetically complex but common brain disorder of the world affecting millions of people with almost of all age groups. Novel Copy number variations (CNVs) are considered as important reason for the numerous neurodevelopmental disorders along with intellectual disability and epilepsy. DNA array based studies contribute to explain a more severe clinical presentation of the disease but interoperation of many detected CNVs are still challenging.In order to study novel CNVs with epilepsy related genes in Saudi family with six affected and two normal individuals with several forms of epileptic seizures, intellectual disability (ID), and minor dysmorphism, we performed the high density whole genome Agilent sure print G3 Hmn CGH 2x 400 K array-CGH chips analysis. Our results showed de novo deletions, duplications and deletion plus duplication on differential chromosomal regions in the affected individuals that were not shown in the normal fathe and normal kids by using Agilent CytoGenomics 3.0.6.6 softwear. Copy number gain were observed in the chromosome 1, 16 and 22 with LCE3C, HPR, GSTT2, GSTTP2, DDT and DDTL genes respectively whereas the deletions observed in the chromosomal regions 8p23-p21 (4303127-4337759) and the potential gene in this region is CSMD1 (OMIM: 612279). Moreover, the array CGH results deletions and duplication were also validated by using primer design of deleted regions utilizing the flanked SNPs using simple PCR and also by using quantitative real time PCR.We found some of the de novo deletions and duplication in our study in Saudi family with intellectual disability and epilepsy. Our results suggest that array-CGH should be used as a first line of genetic test for epilepsy except there is a strong indication for a monogenic syndrome. The advanced high through put array-CGH technique used in this study aim to collect the data base and to identify new mechanisms describing epileptic disorder, may help to improve the clinical management of individual cases in decreasing the burden of epilepsy in Saudi Arabia.

Project description:BackgroundAutism spectrum disorders and schizophrenia have been associated with an overlapping set of copy number variant loci, but the nature and degree of overlap in copy number variants (deletions compared to duplications) between these two disorders remains unclear.MethodsWe systematically evaluated three lines of evidence: (1) the statistical bases for associations of autism spectrum disorders and schizophrenia with a set of the primary CNVs thus far investigated, from previous studies; (2) data from case series studies on the occurrence of these CNVs in autism spectrum disorders, especially among children, and (3) data on the extent to which the CNVs were associated with intellectual disability and developmental, speech, or language delays. We also conducted new analyses of existing data on these CNVs in autism by pooling data from seven case control studies.ResultsFour of the CNVs considered, dup 1q21.1, dup 15q11-q13, del 16p11.2, and dup 22q11.21, showed clear statistical evidence as autism risk factors, whereas eight CNVs, del 1q21.1, del 3q29, del 15q11.2, del 15q13.3, dup 16p11.2, dup 16p13.1, del 17p12, and del 22q11.21, were strongly statistically supported as risk factors for schizophrenia. Three of the CNVs, dup 1q21.1, dup 16p11.2, and dup 16p13.1, exhibited statistical support as risk factors for both autism and schizophrenia, although for each of these CNVs statistical significance was nominal for tests involving one of the two disorders. For the CNVs that were statistically associated with schizophrenia but were not statistically associated with autism, a notable number of children with the CNVs have been diagnosed with autism or ASD; children with these CNVs also demonstrate a high incidence of intellectual disability and developmental, speech, or language delays.ConclusionsThese findings suggest that although CNV loci notably overlap between autism and schizophrenia, the degree of strongly statistically supported overlap in specific CNVs at these loci remains limited. These analyses also suggest that relatively severe premorbidity to CNV-associated schizophrenia in children may sometimes be diagnosed as autism spectrum disorder.

Project description:BackgroundArray genomic hybridization is being used clinically to detect pathogenic copy number variants in children with intellectual disability and other birth defects. However, there is no agreement regarding the kind of array, the distribution of probes across the genome, or the resolution that is most appropriate for clinical use.ResultsWe performed 500 K Affymetrix GeneChip array genomic hybridization in 100 idiopathic intellectual disability trios, each comprised of a child with intellectual disability of unknown cause and both unaffected parents. We found pathogenic genomic imbalance in 16 of these 100 individuals with idiopathic intellectual disability. In comparison, we had found pathogenic genomic imbalance in 11 of 100 children with idiopathic intellectual disability in a previous cohort who had been studied by 100 K GeneChip array genomic hybridization. Among 54 intellectual disability trios selected from the previous cohort who were re-tested with 500 K GeneChip array genomic hybridization, we identified all 10 previously-detected pathogenic genomic alterations and at least one additional pathogenic copy number variant that had not been detected with 100 K GeneChip array genomic hybridization. Many benign copy number variants, including one that was de novo, were also detected with 500 K array genomic hybridization, but it was possible to distinguish the benign and pathogenic copy number variants with confidence in all but 3 (1.9%) of the 154 intellectual disability trios studied.ConclusionAffymetrix GeneChip 500 K array genomic hybridization detected pathogenic genomic imbalance in 10 of 10 patients with idiopathic developmental disability in whom 100 K GeneChip array genomic hybridization had found genomic imbalance, 1 of 44 patients in whom 100 K GeneChip array genomic hybridization had found no abnormality, and 16 of 100 patients who had not previously been tested. Effective clinical interpretation of these studies requires considerable skill and experience.

Dataset Information

Analysis of Intellectual Disability Copy Number Variants for Association With Schizophrenia.

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Analysis of Intellectual Disability Copy Number Variants for Association With Schizophrenia.

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