Derks E.M.,University Utrecht |
Derks E.M.,University of Amsterdam |
Ayub M.,Queens University |
Chambert K.,The Broad Institute of MIT and Harvard |
And 18 more authors.
American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics | Year: 2013
Background: Copy number variants (CNVs) have been shown to play a role in schizophrenia and intellectual disability. Methods: We compared the CNV burden in 66 patients with intellectual disability and no symptoms of psychosis (ID-only) with the burden in 64 patients with intellectual disability and schizophrenia (ID+SCZ). Samples were genotyped on three plates by the Broad Institute using the Affymetrix 6.0 array. Results: For CNVs larger than 100kb, there was no difference in the CNV burden of ID-only and ID+SCZ. In contrast, the number of duplications larger than 1Mb was increased in ID+SCZ compared to ID-only. We detected seven large duplications and two large deletions at chromosome 15q11.2 (18.5-20.1Mb) which were all present in patients with ID+SCZ. The involvement of this region in schizophrenia was confirmed in Scottish samples from the ISC study (N=2,114; 1,130 cases and 984 controls). Finally, one of the patients with schizophrenia and low IQ carrying a duplication at 15q11.2, is a member of a previously described pedigree with multiple cases of mild intellectual disability, schizophrenia, hearing impairment, retinitis pigmentosa and cataracts. DNA samples were available for 11 members of this family and the duplication was present in all 10 affected individuals and was absent in an unaffected individual. Conclusions: Duplications at 15q11.2 (18.5-20.1Mb) are highly prevalent in a severe group of patients characterized by intellectual disability and comorbid schizophrenia. It is also associated with a phenotype that includes schizophrenia, low IQ, hearing and visual impairments resembling the spectrum of symptoms described in "ciliopathies." © 2013 Wiley Periodicals, Inc. Source
Richards A.L.,University of Cardiff |
Jones L.,University of Cardiff |
Moskvina V.,University of Cardiff |
Kirov G.,University of Cardiff |
And 11 more authors.
Molecular Psychiatry | Year: 2012
It is widely thought that alleles that influence susceptibility to common diseases, including schizophrenia, will frequently do so through effects on gene expression. As only a small proportion of the genetic variance for schizophrenia has been attributed to specific loci, this remains an unproven hypothesis. The International Schizophrenia Consortium (ISC) recently reported a substantial polygenic contribution to that disorder, and that schizophrenia risk alleles are enriched among single-nucleotide polymorphisms (SNPs) selected for marginal evidence for association (P<0.5) from genome-wide association studies (GWAS). It follows that if schizophrenia susceptibility alleles are enriched for those that affect gene expression, those marginally associated SNPs, which are also expression quantitative trait loci (eQTLs), should carry more true association signals compared with SNPs that are not marginally associated. To test this, we identified marginally associated (P<0.5) SNPs from two of the largest available schizophrenia GWAS data sets. We assigned eQTL status to those SNPs based upon an eQTL data set derived from adult human brain. Using the polygenic score method of analysis reported by the ISC, we observed and replicated the observation that higher probability cis-eQTLs predicted schizophrenia better than those with a lower probability for being a cis-eQTL. Our data support the hypothesis that alleles conferring risk of schizophrenia are enriched among those that affect gene expression. Moreover, our data show that notwithstanding the likely developmental origin of schizophrenia, studies of adult brain tissue can, in principle, allow relevant susceptibility eQTLs to be identified. © 2012 Macmillan Publishers Limited All rights reserved. Source
Chen X.,Virginia Commonwealth University |
Lee G.,Virginia Commonwealth University |
Maher B.S.,Virginia Commonwealth University |
Fanous A.H.,Virginia Commonwealth University |
And 141 more authors.
Molecular Psychiatry | Year: 2011
We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611-rs10043986, r 2=0.008; rs10043986-rs4704591, r 2=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04-1.18, P=8.2 × 10 -4 and rs4704591, OR=1.07, 95% CI=1.03-1.11, P=3.0 × 10 -4). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03-1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02-1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted. © 2011 Macmillan Publishers Limited All rights reserved. Source
Evers K.,Catholic University of Leuven |
Noens I.,Catholic University of Leuven |
Noens I.,Psychiatric and Neurodevelopmental Genetics Unit |
Steyaert J.,Catholic University of Leuven |
And 2 more authors.
Research in Autism Spectrum Disorders | Year: 2011
Background: Children with an autism spectrum disorder (ASD) are known to have an atypical visual perception, with deficits in automatic Gestalt formation and an enhanced processing of visual details. In addition, they are sometimes found to have difficulties in emotion processing. Methods: In three experiments, we investigated whether 7-to-11-year old children with ASD were showing superiorities or deficits in matching tasks that required focusing on faces with an emotional expression. Throughout these experiments, we increased the complexity of the stimuli and tasks demands. Results and conclusions: In matching faces with emotional expressions, children with ASD were not able to show superior processing of details in any of the three experiments. They were able to compensate their inferior processing of emotions in some of the experiments (e.g., by using a slower, more sequential processing style). However, when stimulus complexity (e.g., dynamic facial expressions) or task demands (e.g., extracting and remembering the relevant stimulus dimension) increased, they were no longer able to do so, and they did show performance deficits. © 2011 Elsevier Ltd. All rights reserved. Source
Ruderfer D.M.,Psychiatric and Neurodevelopmental Genetics Unit |
Ruderfer D.M.,The Broad Institute of MIT and Harvard |
Korn J.,The Broad Institute of MIT and Harvard |
Purcell S.M.,Psychiatric and Neurodevelopmental Genetics Unit |
And 2 more authors.
Genome Medicine | Year: 2010
Genome-wide association studies have detected dozens of variants underlying complex diseases, although it is uncertain how often these discoveries will translate into clinically useful predictors. Here, to improve genetic risk prediction, we consider including phenotypic and genotypic information from related individuals. We develop and evaluate a family-based liability-threshold prediction model and apply it to a simulation of known Crohn's disease risk variants. We show that genotypes of a relative of known phenotype can be informative for an individual's disease risk, over and above the same locus genotyped in the individual. This approach can lead to better-calibrated estimates of disease risk, although the overall benefit for prediction is typically only very modest.© 2010 Ruderfer et al.; licensee BioMed Central Ltd. Source