A Burden of Rare Copy Number Variants in Obsessive-Compulsive Disorder

Abstract

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from large, rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2,248 deeply phenotyped OCD cases and 3,608 unaffected controls from Sweden and Norway. We found that in general cases carry an elevated burden of large (>30kb, at least 15 probes) CNVs (OR=1.12, P=1.77×10^-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P=2.58×10^-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR=1.19, P=3.08×10^-4), particularly deletions impacting loss-of-function intolerant genes (pLI>0.995, OR=4.12, P=2.54×10^-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60×10^-3). In cases where sufficient clinical data were available (n=1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P<0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P=0.02). The results demonstrate a contribution of large, rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Keywords: CNV; OCD; Obsessive-Compulsive Disorder; copy number variant; genetic; genomic.

Figure 1

An overview of the study design and principal results from the analyses carried out. We have constructed a CNV case/control study using samples from Illumina GSA and its derivatives. We use extensive CNV call quality control to bring our CNV call rate down to around 0.6 per sample. Our principal results all point to a contribution to OCD genetic risk from large, rare CNVs, at a rate per sample of around 0.07 (95% CI 0.02–0.11, P=2.58×10⁻³).

Figure 2

CNV burden (deletions, duplications) partitioned by overlap with protein-coding genes. The odds ratio estimate for case status for each additional CNV (deletions in red, duplications in blue) is depicted with a dot while the 95% confidence interval for the estimate is depicted with bars. There is no evidence for case risk being conferred by CNVs that don’t overlap a protein-coding base (P>0.05 for both deletions and duplications). CNVs that confer OCD risk instead appear to overlap protein-coding regions, specifically those that code for genes that are loss-of-function intolerant (pLI>0.5).

Figure 3

Number of bases impacted by CNVs (deletions, duplications) partitioned by mammalian constraint score. The odds ratio estimate for case status for each additional kilobase impacted by CNVs (deletions in red, duplications in blue) is depicted with a dot while the 95% confidence interval for the estimate is depicted with bars. In general, each kilobase of DNA that is deleted increases OCD risk, in a manner where the risk conferred increases when the bases deleted are more constrained. This effect is not observed for duplications.

Figure 4

Lack of genome-significant CNV impacted loci in OCD cases versus controls likely due to low power. A) QQ plot for clumped gene-based test results specific for deletions. B) QQ plot for clumped gene-based test results specific for duplications. C) Results from permutation tests of CNV burden in recurrence in OCD cases relative to controls. D) Tests of association between neurodevelopmental disorder (NDD) CNV burden and OCD case status. Odds ratio for each additional CNV (deletions in red, duplications in blue) is depicted with a dot while the 95% confidence interval for the estimate is depicted with bars. All detectable duplication excess in cases appears to impact neurodevelopmental genes (n=664, from Fu et al. 2022, [27]) while the deletion excess in cases appears to impact both neurodevelopmental genes and unknown genes outside of this geneset.