Jacobine E. Buizer-Voskamp

Large recurrent microdeletions associated with schizophrenia.

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

Disruption of the neurexin 1 gene is associated with schizophrenia

Deletions within the neurexin 1 gene (NRXN1; 2p16.3) are associated with autism and have also been reported in two families with schizophrenia. We examined NRXN1, and the closely related NRXN2 and NRXN3 genes, for copy number variants (CNVs) in 2977 schizophrenia patients and 33 746 controls from seven European populations (Iceland, Finland, Norway, Germany, The Netherlands, Italy and UK) using microarray data. We found 66 deletions and 5 duplications in NRXN1, including a de novo deletion: 12 deletions and 2 duplications occurred in schizophrenia cases (0.47%) compared to 49 and 3 (0.15%) in controls. There was no common breakpoint and the CNVs varied from 18 to 420 kb. No CNVs were found in NRXN2 or NRXN3. We performed a Cochran-Mantel-Haenszel exact test to estimate association between all CNVs and schizophrenia (P = 0.13; OR = 1.73; 95% CI 0.81-3.50). Because the penetrance of NRXN1 CNVs may vary according to the level of functional impact on the gene, we next restricted the association analysis to CNVs that disrupt exons (0.24% of cases and 0.015% of controls). These were significantly associated with a high odds ratio (P = 0.0027; OR 8.97, 95% CI 1.8-51.9). We conclude that NRXN1 deletions affecting exons confer risk of schizophrenia.

Recurrent CNVs disrupt three candidate genes in schizophrenia patients

Schizophrenia is a severe psychiatric disease with complex etiology, affecting approximately 1% of the general population. Most genetics studies so far have focused on disease association with common genetic variation, such as single-nucleotide polymorphisms (SNPs), but it has recently become apparent that large-scale genomic copy-number variants (CNVs) are involved in disease development as well. To assess the role of rare CNVs in schizophrenia, we screened 54 patients with deficit schizophrenia using Affymetrixs GeneChip 250K SNP arrays. We identified 90 CNVs in total, 77 of which have been reported previously in unaffected control cohorts. Among the genes disrupted by the remaining rare CNVs are MYT1L, CTNND2, NRXN1, and ASTN2, genes that play an important role in neuronal functioning but--except for NRXN1--have not been associated with schizophrenia before. We studied the occurrence of CNVs at these four loci in an additional cohort of 752 patients and 706 normal controls from The Netherlands. We identified eight additional CNVs, of which the four that affect coding sequences were found only in the patient cohort. Our study supports a role for rare CNVs in schizophrenia susceptibility and identifies at least three candidate genes for this complex disorder.

Copy number variations of chromosome 16p13.1 region associated with schizophrenia

Deletions and reciprocal duplications of the chromosome 16p13.1 region have recently been reported in several cases of autism and mental retardation (MR). As genomic copy number variants found in these two disorders may also associate with schizophrenia, we examined 4345 schizophrenia patients and 35 079 controls from 8 European populations for duplications and deletions at the 16p13.1 locus, using microarray data. We found a threefold excess of duplications and deletions in schizophrenia cases compared with controls, with duplications present in 0.30% of cases versus 0.09% of controls (P=0.007) and deletions in 0.12 % of cases and 0.04% of controls (P>0.05). The region can be divided into three intervals defined by flanking low copy repeats. Duplications spanning intervals I and II showed the most significant (P=0.00010) association with schizophrenia. The age of onset in duplication and deletion carriers among cases ranged from 12 to 35 years, and the majority were males with a family history of psychiatric disorders. In a single Icelandic family, a duplication spanning intervals I and II was present in two cases of schizophrenia, and individual cases of alcoholism, attention deficit hyperactivity disorder and dyslexia. Candidate genes in the region include NTAN1 and NDE1. We conclude that duplications and perhaps also deletions of chromosome 16p13.1, previously reported to be associated with autism and MR, also confer risk of schizophrenia.

Genome Arrays for the Detection of Copy Number Variations in Idiopathic Mental Retardation, Idiopathic Generalized Epilepsy and Neuropsychiatric Disorders: Lessons for Diagnostic Workflow and Research

We review the contributions and limitations of genome-wide array-based identification of copy number variants (CNVs) in the clinical diagnostic evaluation of patients with mental retardation (MR) and other brain-related disorders. In unselected MR referrals a causative genomic gain or loss is detected in 14–18% of cases. Usually, such CNVs arise de novo, are not found in healthy subjects, and have a major impact on the phenotype by altering the dosage of multiple genes. This high diagnostic yield justifies array-based segmental aneuploidy screening as the initial genetic test in these patients. This also pertains to patients with autism (expected yield about 5–10% in nonsyndromic and 10–20% in syndromic patients) and schizophrenia (at least 5% yield). CNV studies in idiopathic generalized epilepsy, attention-deficit hyperactivity disorder, major depressive disorder and Tourette syndrome indicate that patients have, on average, a larger CNV burden as compared to controls. Collectively, the CNV studies suggest that a wide spectrum of disease-susceptibility variants exists, most of which are rare (<0.1%) and of variable and usually small effect. Notwithstanding, a rare CNV can have a major impact on the phenotype. Exome sequencing in MR and autism patients revealed de novo mutations in protein coding genes in 60 and 20% of cases, respectively. Therefore, it is likely that arrays will be supplanted by next-generation sequencing methods as the initial and perhaps ultimate diagnostic tool in patients with brain-related disorders, revealing both CNVs and mutations in a single test.

Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD.

A co-segregating microduplication of chromosome 15q11.2 pinpoints two risk genes for autism spectrum disorder.

High resolution genomic copy‐number analysis has shown that inherited and de novo copy‐number variations contribute significantly to autism pathology, and that identification of small chromosomal aberrations related to autism will expedite the discovery of risk genes involved. Here, we report a microduplication of chromosome 15q11.2, spanning only four genes, co‐segregating with autism in a Dutch pedigree, identified by SNP microarray analysis, and independently confirmed by FISH and MLPA analysis. Quantitative RT‐PCR analysis revealed over 70% increase in peripheral blood mRNA levels for the four genes present in the duplicated region in patients, and RNA in situ hybridization on mouse embryonic and adult brain sections revealed that two of the four genes, CYFIP1 and NIPA1, were highly expressed in the developing mouse brain. These findings point towards a contribution of microduplications at chromosome 15q11.2 to autism, and highlight CYFIP1 and NIPA1 as autism risk genes functioning in axonogenesis and synaptogenesis. Thereby, these findings further implicate defects in dosage‐sensitive molecular control of neuronal connectivity in autism. However, the prevalence of this microduplication in patient samples was statistically not significantly different from control samples (0.94% in patients vs. 0.42% controls, P = 0.247), which suggests that our findings should be interpreted with caution and indicates the need for studies that include large numbers of control subjects to ascertain the impact of these changes on a population scale.

Genetic Schizophrenia Risk Variants Jointly Modulate Total Brain and White Matter Volume

BACKGROUND Thousands of common single nucleotide polymorphisms (SNPs) are weakly associated with schizophrenia. It is likely that subsets of disease-associated SNPs are associated with distinct heritable disease-associated phenotypes. Therefore, we examined the shared genetic susceptibility modulating schizophrenia and brain volume. METHODS Odds ratios for genome-wide SNP data were calculated in the sample collected by the Psychiatric Genome-wide Association Study Consortium (8690 schizophrenia patients and 11,831 control subjects, excluding subjects from the present study). These were used to calculate individual polygenic schizophrenia (risk) scores in an independent sample of 152 schizophrenia patients and 142 healthy control subjects with available structural magnetic resonance imaging scans. RESULTS In the entire group, the polygenic schizophrenia score was significantly associated with total brain volume (R2 = .048, p = 1.6 × 10(-4)) and white matter volume (R2 = .051, p = 8.6 × 10(-5)) equally in patients and control subjects. The number of (independent) SNPs that substantially influenced both disease risk and white matter (n = 2020) was much smaller than the entire set of SNPs that modulated disease status (n = 14,751). From the set of 2020 SNPs, a group of 186 SNPs showed most evidence for association with white matter volume and an explorative functional analysis showed that these SNPs were located in genes with neuronal functions. CONCLUSIONS These results indicate that a relatively small subset of schizophrenia genetic risk variants is related to the (normal) development of white matter. This, in turn, suggests that disruptions in white matter growth increase the susceptibility to develop schizophrenia.

Genome-Wide Analysis Shows Increased Frequency of Copy Number Variation Deletions in Dutch Schizophrenia Patients

BACKGROUND Since 2008, multiple studies have reported on copy number variations (CNVs) in schizophrenia. However, many regions are unique events with minimal overlap between studies. This makes it difficult to gain a comprehensive overview of all CNVs involved in the etiology of schizophrenia. We performed a systematic CNV study on the basis of a homogeneous genome-wide dataset aiming at all CNVs ≥ 50 kilobase pair. We complemented this analysis with a review of cytogenetic and chromosomal abnormalities for schizophrenia reported in the literature with the purpose of combining classical genetic findings and our current understanding of genomic variation. METHODS We investigated 834 Dutch schizophrenia patients and 672 Dutch control subjects. The CNVs were included if they were detected by QuantiSNP (http://www.well.ox.ac.uk/QuantiSNP/) as well as PennCNV (http://www.neurogenome.org/cnv/penncnv/) and contain known protein coding genes. The integrated identification of CNV regions and cytogenetic loci indicates regions of interest (cytogenetic regions of interest [CROIs]). RESULTS In total, 2437 CNVs were identified with an average number of 2.1 CNVs/subject for both cases and control subjects. We observed significantly more deletions but not duplications in schizophrenia cases versus control subjects. The CNVs identified coincide with loci previously reported in the literature, confirming well-established schizophrenia CROIs 1q42 and 22q11.2 as well as indicating a potentially novel CROI on chromosome 5q35.1. CONCLUSIONS Chromosomal deletions are more prevalent in schizophrenia patients than in healthy subjects and therefore confer a risk factor for pathogenicity. The combination of our CNV data with previously reported cytogenetic abnormalities in schizophrenia provides an overview of potentially interesting regions for positional candidate genes.

Paternal age and psychiatric disorders: findings from a Dutch population registry.

BACKGROUND We measured the association between paternal age and schizophrenia (SCZ), autism spectrum disorders (ASD), major depressive disorder (MDD), and bipolar disorder (BPD) in the Dutch population. METHODS In total, 14231 patients and 56924 matched controls were collected and analyzed for an association with paternal age by logistic regression. RESULTS ASD is significantly associated with increased paternal age: Older fathers >40 years of age have a 3.3 times increased odds of having a child with ASD compared to young fathers <20 years of age. SCZ has significant associations for fathers aged >35 years (OR=1.27, 95% Confidence Interval: 1.05 and 1.53). For MDD, both younger and older fathers have increased odds. No association was found for BPD. CONCLUSIONS The effects of paternal age as a risk factor are different for ASD and SCZ on one hand, and the affective disorders on the other hand. Different types of association might indicate different biological or psychosocial mechanisms. Late paternity (associated with predispositions to psychiatric disorders) seems the most probable explanation for the association with paternal age.