SW-ARRAY: a dynamic programming solution for the identification of copy-number changes in genomic DNA using array comparative genome hybridization data

Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic applications. Here, we adapt the Smith–Waterman dynamic-programming algorithm to provide a sensitive and robust analytic approach (SW-ARRAY) for detecting copy-number changes in array CGH data. In a blind series of hybridizations to arrays consisting of the entire tiling path for the terminal 2 Mb of human chromosome 16p, the method identified all monosomies between 267 and 1567 kb with a high degree of statistical significance and accurately located the boundaries of deletions in the range 267–1052 kb. The approach is unique in offering both a nonparametric segmentation procedure and a nonparametric test of significance. It is scalable and well-suited to high resolution whole genome array CGH studies that use array probes derived from large insert clones as well as PCR products and oligonucleotides

Diagnosing idiopathic learning disability: a cost-effectiveness analysis of microarray technology in the National Health Service of the United Kingdom

Array based comparative genomic hybridisation (aCGH) is a powerful technique for detecting clinically relevant genome imbalance and can offer 40 to > 1000 times the resolution of karyotyping. Indeed, idiopathic learning disability (ILD) studies suggest that a genome-wide aCGH approach makes 10–15% more diagnoses involving genome imbalance than karyotyping. Despite this, aCGH has yet to be implemented as a routine NHS service. One significant obstacle is the perception that the technology is prohibitively expensive for most standard NHS clinical cytogenetics laboratories. To address this, we investigated the cost-effectiveness of aCGH versus standard cytogenetic analysis for diagnosing idiopathic learning disability (ILD) in the NHS. Cost data from four participating genetics centres were collected and analysed. In a single test comparison, the average cost of aCGH was £442 and the average cost of karyotyping was £117 with array costs contributing most to the cost difference. This difference was not a key barrier when the context of follow up diagnostic tests was considered. Indeed, in a hypothetical cohort of 100 ILD children, aCGH was found to cost less per diagnosis (£3,118) than a karyotyping and multi-telomere FISH approach (£4,957). We conclude that testing for genomic imbalances in ILD using microarray technology is likely to be cost-effective because long-term savings can be made regardless of a positive (diagnosis) or negative result. Earlier diagnoses save costs of additional diagnostic tests. Negative results are cost-effective in minimising follow-up test choice. The use of aCGH in routine clinical practice warrants serious consideration by healthcare providers

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

An inherited duplication at the gene p21 protein-activated Kinase 7 (PAK7) is a risk factor for psychosis

FUNDING Funding for this study was provided by the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z), the Wellcome Trust (072894/Z/03/Z, 090532/Z/09/Z and 075491/Z/04/B), NIMH grants (MH 41953 and MH083094) and Science Foundation Ireland (08/IN.1/B1916). We acknowledge use of the Trinity Biobank sample from the Irish Blood Transfusion Service; the Trinity Centre for High Performance Computing; British 1958 Birth Cohort DNA collection funded by the Medical Research Council (G0000934) and the Wellcome Trust (068545/Z/02) and of the UK National Blood Service controls funded by the Wellcome Trust. Chris Spencer is supported by a Wellcome Trust Career Development Fellowship (097364/Z/11/Z). Funding to pay the Open Access publication charges for this article was provided by the Wellcome Trust. ACKNOWLEDGEMENTS The authors sincerely thank all patients who contributed to this study and all staff who facilitated their involvement. We thank W. Bodmer and B. Winney for use of the People of the British Isles DNA collection, which was funded by the Wellcome Trust. We thank Akira Sawa and Koko Ishzuki for advice on the PAK7–DISC1 interaction experiment and Jan Korbel for discussions on mechanism of structural variation.Peer reviewedPublisher PD

The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism.

International audienceAlthough multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E-09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E-23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E-04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions

Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders.

International audienceRare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10(-5)) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10(-15), ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation

Functional impact of global rare copy number variation in autism spectrum disorders

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviors1. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability (ID)2. While ASDs are known to be highly heritable (~90%)3, the underlying genetic determinants are still largely unknown. Here, we analyzed the genome-wide characteristics of rare (<1% frequency) copy number variation (CNV) in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic CNVs (1.19 fold, P= 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P= 3.4×10−4). Among the CNVs, there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes like SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene-sets involved in cellular proliferation, projection and motility, and GTPase/Ras signaling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.Electronic supplementary materialThe online version of this article (doi:10.1007/s00439-011-1094-6) contains supplementary material, which is available to authorized users