Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Abstract

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 (odds ratio (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 nonallelic homologous recombination.

Figure 1. CNV Burden

(A) Forest plot of CNV burden (measured here as genes affected by CNV), partitioned by genotyping platform, with the full PGC sample at the bottom. CNV burden is calculated by combining CNV gains and losses. Numbers of case and controls for each platform are listed, and “genes” denotes the mean number of genes affected by a CNV in controls. Burden tests use a logistic regression model predicting SCZ case/control status by CNV burden along with covariates (see methods). The odds ratio is the exponential of the logistic regression coefficient, and odds ratios above one predict increased SCZ risk. (B) CNV burden partitioned by CNV frequency. For reference, for autosomal CNVs, a CNV count of 41 in the sample corresponds to frequency of 0.1% in the full PGC sample. Using the same model as above, each CNV was placed into a single CNV frequency category based on a 50% reciprocal overlap with other CNVs. CNV gene burden with inclusion of all CNVs are shown in green, and burden excluding previously implicated CNV loci are shown in blue.

Figure 2. Gene-set Burden

Gene-set burden test results for rare losses (a, c) and gains (b, d); frames a–b display gene-sets for neuronal function, synaptic components, neurological and neurodevelopmental phenotypes in human; frames c–d display gene-sets for human homologs of mouse genes implicated in abnormal phenotypes (organized by organ systems); both are sorted by –log 10 of the logistic regression deviance test p-value multiplied by the beta coefficient sign, obtained for rare losses when including known loci. Gene-sets passing the 10% BH-FDR threshold are marked with “*”. Gene-sets representing brain expression patterns were omitted from the figure because only a few were significant (losses: 1, gains: 3).

Figure 3. Protein Interaction Network for Synaptic Genes

Synaptic and ARC-complex genes intersected by a rare loss in at least 4 case or control subjects and with genic burden Benjamini-Hochberg FDR <= 25% (red discs) were used to query GeneMANIA and retrieve additional protein interaction neighbors, resulting in a network of 136 synaptic genes. Genes are depicted as disks; disk centers are colored based on rare loss frequency (Freq.SZ and Freq.CT) being prevalent in cases or controls; disk borders are colored to mark (i) gene implication in human dominant or X-linked neurological or neurodevelopmental phenotype, (ii) de novo mutation (DeN) reported by Fromer et al. , split between LOF (frameshift, stop-gain, core splice site) and missense or amino acid insertion / deletion, (iii) implication in mouse neurobehavioral abnormality. Pre-synaptic adhesion molecules (NRXN1, NRXN3), post-synaptic scaffolds (DLG1, DLG2, DLGAP1, SHANK1, SHANK2) and glutamatergic ionotropic receptors (GRID1, GRID2, GRIN1, GRIA4) constitute a highly connected subnetwork with more losses in cases than controls.

Figure 4. Gene Based Manhattan Plot

Manhattan plot displaying the –log10 deviance p-value for (a) CNV losses and (b) CNV gains the gene-based test. P-value cutoffs corresponding to FWER < 0.05 and BH-FDR < 0.05 are highlighted in red and blue, respectively. Loci significant after multiple test correction are labeled.

Figure 5. Manhattan plot of breakpoint-level associations across the Neurexin-1 locus

The manhattan plot (for deletions) represents empirical P-values at each deletion breakpoint. CNV tracks display duplications (blue) and deletions (red) detected in cases and controls from the PGC SCZ dataset.