Exome sequencing supports a de novo mutational paradigm for schizophrenia

Department of Psychiatry, Columbia University, New York, New York, USA.
Nature Genetics (Impact Factor: 29.65). 08/2011; 43(9):864-8. DOI: 10.1038/ng.902
Source: PubMed

ABSTRACT Despite its high heritability, a large fraction of individuals with schizophrenia do not have a family history of the disease (sporadic cases). Here we examined the possibility that rare de novo protein-altering mutations contribute to the genetic component of schizophrenia by sequencing the exomes of 53 sporadic cases, 22 unaffected controls and their parents. We identified 40 de novo mutations in 27 cases affecting 40 genes, including a potentially disruptive mutation in DGCR2, a gene located in the schizophrenia-predisposing 22q11.2 microdeletion region. A comparison to rare inherited variants indicated that the identified de novo mutations show a large excess of non-synonymous changes in schizophrenia cases, as well as a greater potential to affect protein structure and function. Our analyses suggest a major role for de novo mutations in schizophrenia as well as a large mutational target, which together provide a plausible explanation for the high global incidence and persistence of the disease.

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Available from: Louw Roos, Jul 02, 2014
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    • "First, although we identified a risk eQTL SNP, we cannot rule out the possibility that it is co-inherited with other functional variants in IRF3. It should also be noted that there is the possibility of underlying rare variants that may create synthetic associations (Dickson et al., 2010) because rare missense mutations and copy number variations could increase risk for schizophrenia (Girard et al., 2011; Kirov, 2010; St Clair, 2009; Xu et al., 2011). Therefore , we could not identify the causative risk variant in this region unless further fine-grained analyses and functional assays are warranted. "
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    ABSTRACT: Schizophrenia is a brain disorder with high heritability. Recent studies have implicated genes involved in the immune response pathway in the pathogenesis of schizophrenia. Interferon regulatory factor 3 (IRF3), a virus-immune-related gene, activates the transcription of several interferon-induced genes, and functionally interacts with several schizophrenia susceptibility genes. To test whether IRF3 is a schizophrenia susceptibility gene, we analyzed the associations of its SNPs with schizophrenia in independent population samples as well as reported data from expression quantitative trait loci (eQTL) in healthy individuals. We observed multiple independent SNPs in IRF3 showing nominally significant associations with schizophrenia (P < 0.05); more intriguingly, a SNP (rs11880923), which is significantly correlated with IRF3 expression in independent samples (P < 0.05), is also consistently associated with schizophrenia across different cohorts and in combined samples (odds ratio = 1.075, Pmeta = 2.08 × 10(-5)), especially in Caucasians (odds ratio = 1.078, Pmeta = 2.46 × 10(-5)). These results suggested that IRF3 is likely a risk gene for schizophrenia, at least in Caucasians. Although the clinical associations of IRF3 with diagnosis did not achieve genome-wide level of statistical significance, the observed odds ratio is comparable with other susceptibility loci identified through large-scale genetic association studies on schizophrenia, which could be regarded simply as small but detectable effects. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Journal of Psychiatric Research 03/2015; 64. DOI:10.1016/j.jpsychires.2015.03.008 · 4.09 Impact Factor
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    • "Regarding the burden of protein-altering variants, some discrepancies exist among these studies. Indeed, Xu et al. (2011 & 2012) observed that individuals with SCZ exhibited a significantly higher ratio of non-synonymous-to-synonymous SNVs compared with controls, whereas Fromer et al. (2014) did not find any significant enrichment. "
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    ABSTRACT: Schizophrenia (SCZ) is a severe, debilitating mental illness which has a significant genetic component. The identification of genetic factors related to SCZ has been challenging and these factors remain largely unknown. To evaluate the contribution of de novo variants (DNVs) to SCZ, we sequenced the exomes of 53 individuals with sporadic SCZ and of their non-affected parents. We identified 49 DNVs, 18 of which were predicted to alter gene function, including 13 damaging missense mutations, 2 conserved splice site mutations, 2 nonsense mutations, and 1 frameshift deletion. The average number of exonic DNV per proband was 0.88, which corresponds to an exonic point mutation rate of 1.7×10−8 per nucleotide per generation. The non-synonymous-to-synonymous mutation ratio of 2.06 did not differ from neutral expectations. Overall, this study provides a list of 18 putative candidate genes for sporadic SCZ, and when combined with the results of similar reports, identifies a second proband carrying a non-synonymous DNV in the RGS12 gene.
    PLoS ONE 11/2014; DOI:10.1371/journal.pone.0112745 · 3.53 Impact Factor
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    • "In addition to large-scale structural variation, new sequencing methods are allowing a more detailed examination of the previously unknown genetic variation associated with psychiatric illness. Initial studies have concentrated on whole exome sequencing, selectively sequencing the coding regions of the genome, with some successes for ASD (Neale et al., 2012) and SCZ (Girard et al., 2011; Xu et al., 2011). Although greater numbers and further studies are required to solidify these early findings (Sullivan et al., 2012) there is hope that these sequencing techniques, particularly when applied to whole genomes, will fill some of the gaps in our understanding of the genetic risk of psychiatric illness. "
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    ABSTRACT: Rodent models are a key factor in the process of translating psychiatric genetics and genomics findings, allowing us to shed light on how risk-genes confer changes in neurobiology by merging different types of data across fields, from behavioural neuroscience to the burgeoning omics (e.g. genomics, epigenomics, proteomics, etc.). Moreover, they also provide an indispensable first step for drug discovery. However, recent evidence from both clinical and genetic studies highlights possible limitations in the current methods for classifying psychiatric illness, as both symptomology and underlying genetic risk are found to increasingly overlap across disorder diagnoses. Meanwhile, integration of data from animal models across disorders is currently limited. Here, we argue that behavioural neuroscience is in danger of missing informative data because of the practice of trying to ‘diagnose’ an animal model with a psychiatric illness. What is needed is a shift in emphasis, from seeking to ally an animal model to a specific disorder, to one focused on a more systematic assessment of the neurobiological and behavioural outcomes of any given genetic or environmental manipulation.
    European Journal of Neuroscience 05/2014; 39(11). DOI:10.1111/ejn.12607 · 3.67 Impact Factor
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