De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia.

A small number of rare, recurrent genomic copy number variants (CNVs) are known to substantially increase susceptibility to schizophrenia. As a consequence of the low fecundity in people with schizophrenia and other neurodevelopmental phenotypes to which these CNVs contribute, CNVs with large effects on risk are likely to be rapidly removed from the population by natural selection. Accordingly, such CNVs must frequently occur as recurrent de novo mutations. In a sample of 662 schizophrenia proband-parent trios, we found that rare de novo CNV mutations were significantly more frequent in cases (5.1% all cases, 5.5% family history negative) compared with 2.2% among 2623 controls, confirming the involvement of de novo CNVs in the pathogenesis of schizophrenia. Eight de novo CNVs occurred at four known schizophrenia loci (3q29, 15q11.2, 15q13.3 and 16p11.2). De novo CNVs of known pathogenic significance in other genomic disorders were also observed, including deletion at the TAR (thrombocytopenia absent radius) region on 1q21.1 and duplication at the WBS (Williams-Beuren syndrome) region at 7q11.23. Multiple de novos spanned genes encoding members of the DLG (discs large) family of membrane-associated guanylate kinases (MAGUKs) that are components of the postsynaptic density (PSD). Two de novos also affected EHMT1, a histone methyl transferase known to directly regulate DLG family members. Using a systems biology approach and merging novel CNV and proteomics data sets, systematic analysis of synaptic protein complexes showed that, compared with control CNVs, case de novos were significantly enriched for the PSD proteome (P=1.72 × 10⁻6. This was largely explained by enrichment for members of the N-methyl-D-aspartate receptor (NMDAR) (P=4.24 × 10⁻6) and neuronal activity-regulated cytoskeleton-associated protein (ARC) (P=3.78 × 10⁻8) postsynaptic signalling complexes. In an analysis of 18 492 subjects (7907 cases and 10 585 controls), case CNVs were enriched for members of the NMDAR complex (P=0.0015) but not ARC (P=0.14). Our data indicate that defects in NMDAR postsynaptic signalling and, possibly, ARC complexes, which are known to be important in synaptic plasticity and cognition, play a significant role in the pathogenesis of schizophrenia.

Standardized experiments in mutant mice reveal behavioural similarity on 129S5 and C57BL/6J backgrounds.

Behavioural analysis of mice carrying engineered mutations is widely used to identify roles of specific genes in components of the mammalian behavioural repertoire. The reproducibility and robustness of phenotypic measures has become a concern that undermines the use of mouse genetic models for translational studies. Contributing factors include low individual study power, non-standardized behavioural testing, failure to address confounds and differences in genetic background of mutant mice. We have examined the importance of these factors using a statistically robust approach applied to behavioural data obtained from three mouse mutations on 129S5 and C57BL/6J backgrounds generated in a standardized battery of five behavioural assays. The largest confounding effect was sampling variation, which partially masked the genetic background effect. Our observations suggest that strong interaction of mutation with genetic background in mice in innate and learned behaviours is not necessarily to be expected. We found composite measures of innate and learned behaviour were similarly impacted by mutations across backgrounds. We determined that, for frequently used group sizes, a single retest of a significant result conforming to the commonly used P < 0.05 threshold results in a reproducibility of 60% between identical experiments. Reproducibility was reduced in the presence of strain differences. We also identified a P-value threshold that maximized reproducibility of mutant phenotypes across strains. This study illustrates the value of standardized approaches for quantitative assessment of behavioural phenotypes and highlights approaches that may improve the translational value of mouse behavioural studies.

Impact of transposable elements on the evolution of mammalian gene regulation.

Transposable elements (TEs) are present in all organisms and nearly half of the human and mouse genome is derived from ancient transpositions. This fact alone suggests that TEs have played a major role in genome organization and evolution. Studies undertaken over the last two decades or so clearly show that TEs of various kinds have played an important role in organism evolution. Here we review the impact TEs have on the evolution of gene regulation and gene function with an emphasis on humans. Understanding the mechanisms resulting in genomic change is central to our understanding of gene regulation, genetic disease and genome evolution. Full comprehension of these biological processes is not possible without an in depth knowledge of how TEs impact upon the genome.

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders.

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations.

Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins.

Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence.

Genome variation and complexity in the autism spectrum.

A large international consortium reports in Nature on the diversity of genomic changes in families with autism spectrum disorders. Inherited and de novo mutations affecting many genes were discovered implicating disruption to postsynaptic and cellular signaling processes.