PSYCH-CNVs: Copy number variations conferring risk of psychiatric disorders in children

This project is supported through Coordination Theme 1 (Health) of the European Community‘s FP7, Grant agreement number HEALTH-2007-2.2.1-10-223423

The recent technical improvements for the study of the cytogenetic basis of disease have led to the identification of many microdeletion and microduplication syndromes sometimes referred to as genomic disorders together with inversion polymorphisms and chromosomal translocations. Genomic rearrangements can lead to copy-number variation (CNV) affecting dosage-sensitive genes critical for normal development and can cause disorders representing a wide range of clinically distinct entities. Many of these CNVs affect the nervous system function and several neurodevelopmental, neurodegenerative, and psychiatric disorders are known to be caused by genomic rearrangements and CNVs. CNV may even account for a significant proportion of normal human variation including differences in cognitive, behavioural, and psychological features.

De novo copy number variants are seen more often than expected in autistic patients, and rare chromosomal aberrations are known to account for a small fraction of schizophrenia and bipolar disorder patients2-5. Recurrent spontaneous mutations at multiple sites across the genome may be a prime cause of these disorders, and the reduced fertility associated particularly with autism and schizophrenia may, through selection pressure, maintain these variants at very low frequency. CNVs are large enough to be identified using cost efficient genome-wide search techniques, such as oligonucleotide arrays. In contrast, rare DNA mutations might confer a large proportion of the overall genetic risk, but cannot be easily identified at the present time. The PsychCNVs consortium will apply oligonucleotide arrays for the large-scale interrogation of CNV variation in the human genome, focusing on people with Autism Spectrum Disorders (ASH) (ICED-10 autism, atypical autism and Asperger syndrome) and childhood and adolescent onset schizophrenia (DSM IV schizophrenia subtypes and schizoaffective disorder) and bipolar disorder (DSM IV BP1, BP2 and BPNOS) where CNVs are likely to be more common. This project follows on logically from our hypothesis-independent genome-wide SNP search for common variants, we now intend to systematically search for large, rare CNVs conferring high risk. The genetic risk conferred by CNVs will be estimated by genotyping a large sample of autistic patients and a large sample of childhood and adolescent onset psychosis cases as well as utilising available recourses. The large sample, 2,000 cases and 30,000 controls for each sample, insures power to detect rare variants with high penetrance and until low cost whole genome sequencing becomes available this approach offers the best current hope to identify causative genomic variants for these disorders.

We will be doing three primary analyses on each sample using data from the HumanCNV370 chip developed by Illumina in collaboration with deCODE genetics. Firstly, we will assess the 40,000 rare CNVs estimated to be in the frequency range from 0.0001-0.001, secondly we will search for association to the 5,000 common CNVs selected by deCODE to cover identifiable CNVs in the genome, and finally we will assess the 320,000 common SNPs on the chip. A two phase design will be applied to reduce the genotyping cost still maintaining most of the power. CNVs and SNPs associating with ASD or childhood and adolescence psychosis will be characterized and attempts made to prove causality. Proving a causal link between a variant and a psychiatric phenotype can present particular difficulties. Many of these can be traced to the complexity of the phenotypes themselves. At a basic level, psychiatric diseases involve disturbances in the biology of that most uniquely human and complex biological organ, the brain, but they manifest themselves not only as biological phenomena, but as perturbations of the mind. As a result, it may be difficult to generate animal models that meaningfully mimic or resemble psychiatric disease in man. Likewise, the difficulty in obtaining tissue samples and in culturing CNS cells hamper functional and expression analysis that might provide valuable information for proving causality. However, advances in behavioral phenotyping of animals such as rodents, for example using mouse models of social interaction or working/episodic-like memory, in combination with advanced genetic technology, mean that the consequences of knockouts on brain and behavior can be better investigated.