Pathogenic rare copy number variants in community-based schizophrenia suggest a potential role for clinical microarrays

Abstract

Individually rare, large copy number variants (CNVs) contribute to genetic vulnerability for schizophrenia. Unresolved questions remain, however, regarding the anticipated yield of clinical microarray testing in schizophrenia. Using high-resolution genome-wide microarrays and rigorous methods, we investigated rare CNVs in a prospectively recruited community-based cohort of 459 unrelated adults with schizophrenia and estimated the minimum prevalence of clinically significant CNVs that would be detectable on a clinical microarray. A blinded review by two independent clinical cytogenetic laboratory directors of all large (>500 kb) rare CNVs in cases and well-matched controls showed that those deemed to be clinically significant were highly enriched in schizophrenia (16.4-fold increase, P < 0.0001). In a single community catchment area, the prevalence of individuals with these CNVs was 8.1%. Rare 1.7 Mb CNVs at 2q13 were found to be significantly associated with schizophrenia for the first time, compared with the prevalence in 23 838 population-based controls (42.9-fold increase, P = 0.0002). Additional novel findings that will facilitate the future clinical interpretation of smaller CNVs in schizophrenia include: (i) a greater proportion of individuals with two or more rare exonic CNVs >10 kb in size (1.5-fold increase, P = 0.0109) in schizophrenia; (ii) the systematic discovery of new candidate genes for schizophrenia; and, (iii) functional gene enrichment mapping highlighting a differential impact in schizophrenia of rare exonic deletions involving diverse functions, including neurodevelopmental and synaptic processes (4.7-fold increase, P = 0.0060). These findings suggest consideration of a potential role for clinical microarray testing in schizophrenia, as is now the suggested standard of care for related developmental disorders like autism.

Figure 1.

Large, rare, clinically significant CNVs, absent in 2773 (population-based + OPGP) controls, at loci novel to schizophrenia (,–25). Solid and open bars represent gains (duplications) and losses (deletions), respectively. Genomic parameters are from NCBI Build 36. Only selected genes are shown (see Table 1 for details).

Figure 2.

A functional map of schizophrenia using results of the gene-set association analysis, displayed as a network of 70 gene sets (circles) related by mutual overlap (lines) using the Enrichment Map Cytoscape plugin (37). Circle size is proportional to the total number of ‘support’ genes in each gene set and line thickness represents the number of genes in common between two gene sets. Each support gene harbors a rare exonic loss CNV in one or more schizophrenia subjects but in no OPGP controls; only CNVs overlapping 15 or fewer genes were tested for gene-set association. Groups of functionally related gene sets are represented by the filled circles and respective labels; grey circles indicate gene sets not assigned to these 13 clusters. Three major functional groups are further highlighted by darker filled circles (blue, Synapse; pink, Nervous system development; red, Axonogenesis) with the respective 19 support genes for schizophrenia shown in color. We also list (in black) other genes in these three functional clusters that were overlapped by very rare loss or gain CNVs in subjects with schizophrenia (i.e., not in 2773 controls), and that have additional supportive data (see the text and Tables 1, 2 and 4). See Materials and Methods for more details.