Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination.

We report the identification of a recurrent 520-kbp 16p12.1 microdeletion significantly associated with childhood developmental delay. The microdeletion was detected in 20/11,873 cases vs. 2/8,540 controls (p=0.0009, OR=7.2) and replicated in a second series of 22/9,254 cases vs. 6/6,299 controls (p=0.028, OR=2.5). Most deletions were inherited with carrier parents likely to manifest neuropsychiatric phenotypes (p=0.037, OR=6). Probands were more likely to carry an additional large CNV when compared to matched controls (10/42 cases, p=5.7×10-5, OR=6.65). Clinical features of cases with two mutations were distinct from and/or more severe than clinical features of patients carrying only the co-occurring mutation. Our data suggest a two-hit model in which the 16p12.1 microdeletion both predisposes to neuropsychiatric phenotypes as a single event and exacerbates neurodevelopmental phenotypes in association with other large deletions or duplications. Analysis of other microdeletions with variable expressivity suggests that this two-hit model may be more generally applicable to neuropsychiatric disease.

Recurrent microdeletions and microduplications of a 600 kb genomic region of chromosome 16p11.2 have been implicated in childhood-onset developmental disorders1-3. Here we report the strong association of 16p11.2 microduplications with schizophrenia in two large cohorts. In the primary sample, the microduplication was detected in 12/1906 (0.63%) cases and 1/3971 (0.03%) controls (P=1.2×10-5, OR=25.8). In the replication sample, the microduplication was detected in 9/2645 (0.34%) cases and 1/2420 (0.04%) controls (P=0.022, OR=8.3). For the series combined, microduplication of 16p11.2 was associated with 14.5-fold increased risk of schizophrenia (95% C.I. [3.3, 62]). A meta-analysis of multiple psychiatric disorders showed a significant association of the microduplication with schizophrenia, bipolar disorder and autism. The reciprocal microdeletion was associated only with autism and developmental disorders. Analysis of patient clinical data showed that head circumference was significantly larger in patients with the microdeletion compared with patients with the microduplication (P = 0.0007). Our results suggest that the microduplication of 16p11.2 confers substantial risk for schizophrenia and other psychiatric disorders, whereas the reciprocal microdeletion is associated with contrasting clinical features.

While it is known that rare copy-number variants (CNVs) contribute to risk for some neuropsychiatric disorders, the role of CNVs in bipolar disorder is unclear. Here, we reasoned that a contribution of CNVs to mood disorders might be most evident for de novo mutations. We performed a genome-wide analysis of de novo CNVs in a cohort of 788 trios. Diagnoses of offspring included bipolar disorder (n = 185), schizophrenia (n= 177), and healthy controls (n= 426). Frequencies of de novo CNVs were significantly higher in bipolar disorder as compared with controls (OR= 4.8 [1.4,16.0], p= 0.009). De novo CNVs were particularly enriched among cases with an age at onset younger than 18 (OR= 6.3 [1.7,22.6], p= 0.006). We also confirmed a significant enrichment of de novo CNVs in schizophrenia (OR= 5.0 [1.5,16.8], p= 0.007). Our results suggest that rare spontaneous mutations are an important contributor to risk for bipolar disorder and other major neuropsychiatric diseases.

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Rare copy number variants (CNVs) play a prominent role in the etiology of schizophrenia and other neuropsychiatric disorders1. Substantial risk for schizophrenia is conferred by large (>500 kb) CNVs at several loci, including microdeletions at 1q21.1 2, 3q29 3, 15q13.3 2 and 22q11.2 4 and microduplication at 16p11.2 5. However, these CNVs collectively account for a small fraction (2-4%) of cases, and the relevant genes and neurobiological mechanisms are not well understood. Here we performed a large two-stage genome-wide scan of rare CNVs and report the significant association of copy number gains at chromosome 7q36.3 with schizophrenia (P= 4.0×10-5, OR = 16.14 [3.06, ∞]). Microduplications with variable breakpoints occurred within a 362 kb region and were detected in 29 of 8,290 (0.35%) patients versus two of 7,431 (0.03%) controls in the combined sample (p-value= 5.7×10-7, odds ratio (OR) = 14.1 [3.5, 123.9]). All duplications overlapped or were located within 89 kb upstream of the vasoactive intestinal peptide receptor VIPR2. VIPR2 transcription and cyclic-AMP signaling were significantly increased in cultured lymphocytes from patients with microduplications of 7q36.3. These findings implicate altered VIP signaling in the pathogenesis of schizophrenia and suggest VIPR2 as a potential target for the development of novel antipsychotic drugs.

Recent studies have established an important role for rare genomic deletions and duplications in the etiology of schizophrenia. This research suggests that the genetic architecture of neuropsychiatric disorders includes a constellation of rare mutations in many different genes. Mutations that confer substantial risk for schizophrenia have been identified at several loci, most of which have also been implicated in other neurodevelopmental disorders, including autism. Genetic heterogeneity is a characteristic of schizophrenia; conversely, phenotypic heterogeneity is a characteristic of all schizophrenia-associated mutations. Both kinds of heterogeneity probably reflect the complexity of neurodevelopment. Research strategies must account for both genetic and clinical heterogeneity to identify the genes and pathways crucial for the development of neuropsychiatric disorders. A resurgence of the field of schizophrenia geneticsGenes play an important role in the etiology of schizophrenia, with a heritability estimated at 80% 1. Despite intensive effort to discover genetic risk factors for schizophrenia, causal variants have eluded definitive identification 2 -5. In the past, linkage studies were confounded by an under-appreciated degree of locus heterogeneity, yielding weak signals at many locations throughout the genome, the bulk of which did not replicate consistently across studies 6. Candidate gene-based analyses of common variants were also largely unsuccessful 2 -5 , 7. The first wave of genome-wide association studies produced variable results,8 -10 confounded by a lack of statistical power and the extremely small effect sizes of common risk alleles.In the past two years this trend has reversed. Studies by several groups have begun to shed new light on the genetics of schizophrenia. Recent findings have established that both rare mutations of large effect 11 -15 and common variants of modest effect 16 -19 contribute to genetic risk for schizophrenia. Collectively, these studies show that schizophrenia is characterized by much more genetic heterogeneity than was previously thought. The risk alleles that have been implicated include rare copy number variants (CNVs) and common haplotypes based on single nucleotide polymorphisms (SNPs). Mutations that confer risk are located throughout the genome and involve many different genes.* corresponding author: Jonathan Sebat, Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, sebat@cshl.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. What may represent the greatest change in our scientific un...