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Cited by 1,058Genomic variations and chromosomal abnormalitiesSchizophrenia research and treatmentGenetic Associations and Epidemiology

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

Open access
Marshall, Christian R, Howrigan, Daniel P, Merico, Daniele, Thiruvahindrapuram, Bhooma, Wu, Wenting, Greer, Douglas S, Antaki, Danny, Shetty, Aniket +257 more·2017·Nature Genetics
DOI 10.1038/ng.3725PMC PMC5737772

Published version of a preprint

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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.

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Claims the paper makes

0 of 25 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    After removing nine previously implicated CNV loci, excess CNV burden in schizophrenia remained significantly enriched for genes affected (OR=1.11, P=1.3×10−7).

    “After removing nine previously implicated CNV loci (where reported p-values exceed our designated multiple testing threshold, Supplementary Table 1), excess CNV burden in SCZ remained significantly enriched (genes affected OR=1.11, p = 1.3×10−7, Figure 1b).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Supplementary Table 1

      Not checked in the free run.

  • Findingown data

    After excluding previously implicated loci, remaining loci with FDR < 0.05 in the gene-based burden test were NAHR enriched (6.03-fold, P=0.008) compared to a null distribution from randomizing genomic positions of associated genes.

    “after excluding loci that have been implicated in previous studies, the remaining loci with FDR < 0.05 in the gene-base burden test were NAHR enriched (6.03-fold, P=0.008; Supplementary Figure 7), when compared to a null distribution determined by randomizing the genomic positions of associated genes (Supplemental Note).”
    Quote in the paperSubstantial claim
  • Findingown data

    Suggestive support was found for eight additional candidate susceptibility and protective loci, predominantly CNVs mediated by non-allelic homologous recombination.

    “Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination.”
    Quote in the paperSubstantial claim
  • Findingown data

    The global CNV burden enrichment persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7×10−6).

    “which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6)”
    Quote in the paperSubstantial claim
  • Findingown data

    Deletions in schizophrenia are enriched within a highly connected network of synaptic proteins.

    “Our results provide strong evidence that deletions in SCZ are enriched within a highly connected network of synaptic proteins, consistent with previous studies 2, 6, 10, 28.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [2] Walsh, T. et al. Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia. Science 320, 539–543 (2008). source

      Not checked in the free run.

    • cites [6] Kirov, G. et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol. Psychiatry 17, 142–153 (2012). source

      Not checked in the free run.

    • cites [10] Pocklington, A.J. et al. Novel findings from CNVs implicate inhibitory and excitatory signaling complexes in schizophrenia. Neuron 86, 1203–1214 (2015). source

      Not checked in the free run.

  • May combine two claims. 31
  • Classified as probably not a substantial claim. 27

  • May combine two claims.

    Findingown data

    An additional eight loci met criteria for suggestive association, including six not previously reported in association with schizophrenia.

    “An additional eight loci meet criterion for suggestive association, including six that have not been reported previously in association with SCZ.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Eight loci attained genome-wide significance, including copy number losses at 1q21.1, 2p16.3 (NRXN1), 3q29, 15q13.3, 16p11.2 (distal) and 22q11.2, along with gains at 7q11.23 and 16p11.2 (proximal).

    “Eight loci attain genome-wide significance, including copy number losses at 1q21.1, 2p16.3 (NRXN1), 3q29, 15q13.3, 16p11.2 (distal) and 22q11.2 along with gains at 7q11.23 and 16p11.2 (proximal).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Duplications of distal Xq28 (regional P=3.6×10−4, OR=8.9) appear to confer risk for schizophrenia in both males and females, with the greatest effect size in males (P=0.01, OR=∞).

    “Notably, duplications of distal Xq28 (regional P = 3.6×10−4, OR = 8.9, Table 1 and Supplementary Figure 8) appear to confer risk for SCZ in both males and females, and the effect size was greatest in males (P = 0.01, OR = ∞).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Digital droplet PCR validation rates were 100% for gains of DMRT1, MAGEA11 and distal Xq28, losses of VPS13B, and gains and losses of ZNF92.

    “Validation rates of 100% were obtained for gains of DMRT1, MAGEA11 and distal Xq28, losses of VPS13B, and gains and losses of ZNF92 (Supplementary Table 5).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Supplementary Table 5

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Of 44 published findings, evidence was found for 8 loci at a false discovery rate of 5% and nominal support for an additional 17 loci at uncorrected p < 0.05.

    “Of 44 published findings from the recent literature, we find evidence for 8 loci at a false discovery rate of 5% and nominal support for an additional 17 loci (uncorrected p < 0.05, Supplementary Table 6).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Supplementary Table 6

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    After multiple-test correction at BH-FDR ≤ 10%, 15 gene-sets were enriched for rare loss burden in cases and 4 for rare gains, with no negative control sets among them.

    “After multiple test correction (Benjamini-Hochberg FDR ≤ 10%) 15 gene-sets were enriched for rare loss burden in cases and 4 for rare gains in cases, none of which are negative control sets (Figure 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Among all previously reported loci, 8 had BH-FDR q-value < 0.05, 13 had q-value < 0.1, and 25 of 42 were associated with schizophrenia at uncorrected p < .05.

    “8 loci have BH-FDR q-value < 0.05, 13 loci have BH-FDR q-value < 0.1, and 25 of the 42 loci were associated with SCZ at an uncorrected p < .05.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Prior to filtering, raw genotype calls were processed for 57,577 individuals, including 28,684 schizophrenia cases and 28,893 controls.

    “Prior to any filtering, we processed raw genotype calls for a total of 57,577 individuals, including 28,684 SCZ cases and 28,893 controls.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    CNV burden remained significantly enriched after removal of all reported loci from Supplementary Table 1, but the effect size was greatly reduced (OR=1.08) compared to the overall enrichment (OR=1.21).

    “CNV burden also remained significantly enriched after removal of all reported loci from Supplementary Table 1, but the effect-size was greatly reduced (OR = 1.08) compared to the enrichment overall (OR = 1.21).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Supplementary Table 1

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Losses in cases were significantly enriched for genes involved in nervous system or behavioral phenotypes in mouse but not for gene-sets related to other organ system phenotypes.

    “Losses in cases were also significantly enriched for genes involved in nervous system or behavioral phenotypes in mouse but not for gene-sets related to other organ system phenotypes (Figure 2c).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    Of five reciprocal deletions detected in this study, none were observed in males, consistent with hemizygous loss of distal Xq28 being associated with recessive embryonic lethality in males.

    “Of the five reciprocal deletions that were detected in this study, none were observed in males, consistent with hemizygous loss of distal Xq28 being associated with recessive embryonic lethality in males 24.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [24] El-Hattab, A.W. et al. Clinical characterization of int22h1/int22h2-mediated Xq28 duplication/deletion: new cases and literature review. BMC Med. Genet. 16, 12 (2015). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Four independent CNV loci surpassed genome-wide significance at the breakpoint level, all also identified in the gene-based test, including 15q13.2-13.3 and 22q11.21 deletions, 16p11.2 duplication, and 1q21.1 deletion and duplication.

    “Four independent CNV loci surpass genome-wide significance, all of which were also identified in the gene-based test, including the 15q13.2–13.3 and 22q11.21 deletions, 16p11.2 duplication, and 1q21.1 deletion and duplication.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Of the 15 gene-sets significant for losses, the majority were synaptic or other neuronal components (9 sets), with GO synaptic and ARC complex ranking first by statistical significance and effect size respectively.

    “Of the 15 sets significant for losses, the majority consisted of synaptic or other neuronal components (9 sets); in particular, “GO synaptic” (GO:0045202) and the activity-regulated cytoskeleton-associated protein complex, or “ARC complex”, rank first based on statistical significance and effect-size respectively (Figure 2a).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The validation rate at ZMYM5 was low (64%), so the association at this locus was not considered convincing.

    “We obtained a low validation rate at one locus, ZMYM5 (64%), and therefore do not consider the association at this locus convincing.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    By simulation, Pvalue_glm can be extremely over-conservative when very few gene-set counts differ from zero, while Pvalue_dev tends to be slightly under-conservative.

    “Please note that, by performing simple simulation analyses, we realized that Pvalue_glm can be extremely over-conservative in presence of very few gene-set counts different than 0, while Pvalue_dev tends to be slightly under-conservative.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Pvalue_glm is systematically over-conservative for gene analysis because smaller counts are typically available for single genes.

    “While the two p-values tend to agree well for gene-set analysis, Pvalue_glm is systematically over-conservative for gene analysis since smaller counts are typically available for single genes.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Multiple-testing correction using Benjamini-Hochberg false discovery rate was performed separately for each gene-set group and CNV type.

    “Multiple-testing correction (Benjamini-Hochberg False Discovery Rate, BH-FDR) was performed separately for each gene-set group and CNV type (gains, losses).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Multiple-testing thresholds for genome-wide significance were estimated from family-wise error rates drawn from permutation.

    “Multiple-testing thresholds for genome-wide significance were estimated from family-wise error rates drawn from permutation”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    The study used a centralized pipeline for systematic CNV calling across Affymetrix and Illumina platforms.

    “We developed a centralized pipeline for systematic calling of CNVs for Affymetrix and Illumina platforms.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    A consensus CNV call dataset was constructed by merging data at the sample level and further filtering calls.

    “We then constructed a consensus CNV call dataset by merging data at the sample level and further filtered calls to make a final dataset Supplementary Table 2.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Supplementary Table 2

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Many CNV loci strongly implicated in human disease are hotspots for non-allelic homologous recombination, a process usually mediated by flanking segmental duplications.

    “Many CNV loci that have been strongly implicated in human disease are hotspots for non-allelic homologous recombination (NAHR), a process which in most cases is mediated by flanking segmental duplications 21.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21] Lupski, J.R. Genomic disorders: structural features of the genome can lead to DNA rearrangements and human disease traits. Trends Genet. 14, 417–422 (1998). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Only CNV calls made by multiple algorithms were included.

    “Only CNV calls that were made using multiple algorithms were included in the call set.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A PGC schizophrenia GWAS identified 108 independent schizophrenia-associated loci.

    “as exemplified by a study by the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) which identified 108 independent schizophrenia associated loci 14.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    It is probable that some undiscovered rare alleles affecting schizophrenia risk confer protection, but larger sample sizes are needed to determine this unequivocally.

    “It is probable that some of the undiscovered rare alleles affecting risk for SCZ confer protection but larger sample sizes are needed to determine this unequivocally.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    It is likely that some earlier findings represent chance associations, as loci not supported by the data largely had weak original statistical evidence.

    “However, it is likely that some of the earlier findings represent chance associations; indeed, the loci that are not supported by our data consist largely of loci for which the original statistical evidence was weak (Supplementary Table 6).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Supplementary Table 6

      Not checked in the free run.

  • May combine two claims.

    Premisenone given

    All CNVs implicated in schizophrenia are rare in the population but confer significant risk, with odds ratios between 2 and 60.

    “All CNVs that have been implicated in SCZ are rare in the population, but confer significant risk (odds ratios 2–60).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Sample-level QC removed arrays with excessive probe variance or GC bias and samples with gender/ethnicity mismatches or aneuploidies.

    “Sample level QC filtering was performed by removing arrays with excessive probe variance or GC bias and removal of samples with mismatches in gender or ethnicity or chromosomal aneuploidies.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Gene-set burden analyses controlled for the total number of genes per subject spanned by rare CNVs to account for global enrichment.

    “we controlled for the total number of genes per subject spanned by rare CNVs to account for signal that merely reflects the global enrichment of CNV burden in cases 19.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [19] Raychaudhuri, S. et al. Accurately assessing the risk of schizophrenia conferred by rare copy-number variation affecting genes with brain function. PLoS Genet. 6, e1001097 (2010). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Duplications of distal Xq28 have been reported in association with developmental delay in both sexes.

    “Duplications of distal Xq28 have been reported in association with developmental delay in both sexes 23, 24.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [23] El-Hattab, A.W. et al. Int22h-1/int22h-2-mediated Xq28 rearrangements: intellectual disability associated with duplications and in utero male lethality with deletions. J. Med. Genet. 48, 840–850 (2011). source

      Not checked in the free run.

    • cites [24] El-Hattab, A.W. et al. Clinical characterization of int22h1/int22h2-mediated Xq28 duplication/deletion: new cases and literature review. BMC Med. Genet. 16, 12 (2015). source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    The CNV calling pipeline ran multiple callers in parallel and retained only CNV segments detected by all algorithms.

    “The pipeline included multiple CNV callers run in parallel.”
    • Also stated in: § Data processing and meta-analytic methods · plain
      “Only CNV segments that were detected by all algorithms were retained.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    CNV breakpoints in the study were estimated from genotyped SNPs around the true breakpoint and are limited by genotyping platform resolution and subject to error.

    “It is important, however, to note that CNV breakpoints in the current study are estimated from genotyped SNPs around the true breakpoint, and that these breakpoint estimates are limited by the resolution of the genotyping platform, and therefore subject to error.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductnone given

    The study is well-powered to detect CNVs of large effect occurring in >0.1% of cases but is underpowered to detect association to variants with modest effect sizes or ultra-rare variants regardless of effect size.

    “Our current study is well-powered to detect CNVs of large effect that occur in >0.1% of cases, but is underpowered to detect association to variants with modest effect sizes or to ultra-rare variants regardless of effect size.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A recent study demonstrated that the causal variants underlying the strongest common variant association in schizophrenia include duplications of Complement factor 4A.

    “a recent study has demonstrated that the causal variants underlying the strongest common variant association in SCZ include duplications of Complement factor 4A 35.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [35] Gymrek, M. et al. Abundant contribution of short tandem repeats to gene expression variation in humans. Nat. Genet. 48, 22–29 (2016). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Association analyses controlled for SNP-derived principal components, sex, genotyping platform and data quality metrics.

    “Analyses controlled for SNP-derived principal components, sex, genotyping platform and data quality metrics.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Microduplications of 22q11.2 appear to confer protection from schizophrenia but have been shown to increase risk for developmental delay and congenital anomalies in pediatric clinical populations.

    “For example, microduplications of 22q11.2 appear to confer protection from SCZ 26; however, such duplications have been shown to increase risk for developmental delay and a variety of congenital anomalies in pediatric clinical populations 27.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [26] Rees, E. et al. Evidence that duplications of 22q11.2 protect against schizophrenia. Mol. Psychiatry 19, 37–40 (2014). source

      Not checked in the free run.

    • cites [27] Van Campenhout, S. et al. Microduplication 22q11.2: a description of the clinical, developmental and behavioral characteristics during childhood. Genet. Couns. 23, 135–148 (2012).

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    Concordance of empirical and Z-score p-values is close to unity for tests with six or more CNV, while Z-score p-values are more conservative for tests with fewer than six CNV.

    “Concordance of the initial empirical and Z-score p-values are close to unity for association tests with six or more CNV, whereas Z-score p-values are more conservative among tests with less than six CNV.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Covariates included sex, genotyping platform, and ancestry principal components.

    “Covariates included sex, genotyping platform, and ancestry principal components derived from SNP genotypes on the same samples in a previous study1.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    An additional z-scoring correction was used to control for extreme values in the SCZ residual phenotype and to estimate two-sided empirical p-values for highly significant loci.

    “An additional z-scoring correction, explained below, is used to control for any extreme values in the SCZ residual phenotype and efficiently estimate two-sided empirical p-values for highly significant loci.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: When CNVs are extremely rare, carriers with extreme SCZ residual phenotype values can yield very significant p-values.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    To guard against power loss from covariate inclusion, a single degree of freedom Cochran-Mantel-Haenzel test stratified by genotyping platform was also run.

    “To ensure against the potential loss of power from the inclusion of covariates, we also ran a single degree of freedom Cochran-Mantel-Haenzel (CMH) test stratified by genotyping platform, with a 2 (CNV carrier status) × 2 (phenotype status) × N (genotyping platform) contingency matrix.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Burden and gene-set analyses included potential confounders as covariates in logistic regression.

    “In order to ensure the robustness of the analysis, burden and gene-set analyses included potential confounding variables as covariates in a logistic regression framework.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    Individuals failing companion PGC GWAS QC and unmatched samples were removed.

    “In order to minimize the impact of technical artifacts and potential confounds on CNV association results, we removed from the dataset individuals that did not pass QC filtering from the companion PGC GWAS study of schizophrenia 1 as well as well as case or control samples that could not be matched by array platform or reconciled by using a common set of probes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Among non-Affymetrix 6.0 datasets, LRRSD differed between cases and controls (t=-35.3, p<2e-16), with controls having a higher standardized mean (0.227) than cases (-0.199).

    “However, among non-Affymetrix 6.0 datasets, LRRSD showed significant differences between cases and controls (t=−35.3, p < 2e−16), with controls having a higher standardized mean LRRSD (0.227) than cases (−0.199).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    The Omni 2.5 array, with 28 cases and 10 controls, was excluded from figure presentation but included in all burden analyses with the total PGC sample.

    “Due to the small sample size of the Omni 2.5 array (28 cases and 10 controls), they were excluded from presentation in the figure, but are included in all burden analyses with the total PGC sample.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Variants at >=1% frequency in cases and controls combined were filtered out.

    “To make our final dataset of rare CNVs for all subsequent analysis we filtered out variants that were present at >= 1% (50% reciprocal overlap) frequency in cases and controls combined.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    The Z-score method provides an efficient way to estimate highly significant empirical p-values that would otherwise require hundreds of millions of permutations.

    “Furthermore, the Z-score method naturally provides an efficient manner to estimate highly significant empirical p-values that would involve hundreds of millions of permutations to achieve.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Included CNVs were >=20 kb and >=10 probes, with <50% overlap with polymorphic regions.

    “We included in the call set CNVs that were ≥20 kb and ≥10 probes in length and overlapped < 50% with regions tagged as copy number polymorphic on any other platform.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    For gene association analysis, the threshold was set to 12 counts for gains and 8 counts for losses, chosen by comparing BH-FDR to permutation-based FDR to limit FDR inflation (permuted FDR < 1.65 * BH-FDR at BH-FDR threshold = 5%) while maximizing power.

    “Only genes with at least a minimum number of subjects impacted by CNV were tested; this threshold was picked by comparing the BH-FDR to the permutation-based FDR and ensuring limited FDR inflation (permuted FDR < 1.65 * BH-FDR at BH-FDR threshold = 5%) while maximizing power. For gains the threshold was set to 12 counts, while for losses it was set to 8 counts.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    To determine the proportion of CNV burden risk attributable to loci not implicated in previous studies, all burden analyses were run after removing CNVs that overlapped previously implicated CNV boundaries by more than 10%.

    “In addition, to determine the proportion of CNV burden risk that is attributable to loci that have not been implicated in previous studies of SCZ, we ran all burden analyses after removing CNVs that overlapped previously implicated CNV boundaries by more than 10%.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    After post-processing QC, the retained dataset had 41,321 individuals (21,094 cases, 20,227 controls).

    “After the post-processing round of QC, we retained a dataset with a total of 41,321 individuals comprising 21,094 SCZ cases and 20,227 controls.”
    Quote in the paperSubstantial claim
49 of 49

  • The paper relies on this without support.

    Genome-wide investigation of the contribution of CNVs to schizophrenia risk has been hampered by limited sample sizes.

    “However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes.”

  • The paper relies on this without support.

    Limited statistical power from small samples is a significant obstacle in studies of rare and common genetic variation.

    “The limited statistical power provided by small samples is a significant obstacle in studies of rare and common genetic variation.”

  • The paper relies on this without support.

    There is a need for similarly large samples in studies of CNVs for psychiatric disorders.

    “Recognizing the need for similarly large samples in studies of CNVs for psychiatric disorders, we formed the PGC CNV Analysis Group.”

  • The paper relies on this without support.

    Extremely rare CNV events cannot surpass strict genome-wide correction.

    “While we understand that such rare events are unable to surpass strict genome-wide correction, we wanted to retain all tests to help delineate the potential fine-scale architecture within a single region of association.”

  • The paper relies on this without support.

    Many CNV metrics are auto-correlated because they measure similar patterns of variation in probe intensity.

    “Many CNV metrics are auto-correlated, as they measure similar patterns of variation in the probe intensity.”

  • The paper relies on this without support.

    The CMH test fails to address subtler biases that might generate false positives.

    “While the CMH test does not account for more subtle biases that could drive false positive signals, it is robust to signals driven by a single platform and allows for each CNV carrier to be treated equally.”

  • The paper relies on this without support.

    When CNVs are extremely rare, carriers with extreme SCZ residual phenotype values can yield very significant p-values.

    “For extremely rare CNV, however, CNV carriers at the extreme ends of the SCZ residual phenotype can produce highly significant p-values.”
7 of 7

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The 15q11.2 deletion is associated with schizophrenia (OR 1.8).

    “a mild enrichment of the deletion is observed in individuals with schizophrenia (OR 1.8),2”

    From Estimating the effect size of the 15Q11.2 BP1–BP2 deletion and its contribution to neurodevelopmental symptoms: recommendations for practice (2019) · cites this paper as [2]

    The Gene CNV association section reports a schizophrenia association for deletions at 15q13.3, not 15q11.2. Searches of our copy for 15q11.2 and an odds ratio of 1.8 found no passage establishing the claimed enrichment; the two loci cannot be treated as interchangeable. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

  • CNVs of large effect often disrupt hundreds of kilobases of the genome and multiple genes simultaneously, limiting ability to derive clear functional insights.

    “CNVs of large effect, on the other hand, often disrupt hundreds of kilobases of the genome and multiple genes simultaneously, limiting our ability to derive clear functional insights 7 .”

    From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [7]

  • Several rare recurrent copy number variants (CNVs) have been robustly associated with schizophrenia, as exemplified by dramatically higher rates of schizophrenia in 22q11.2 deletion carriers.

    “Several rare (MAF < 0.1%) recurrent copy number variants (CNVs) have also been robustly associated with schizophrenia, as exemplified by the dramatically higher rates of schizophrenia in 22q11.2deletion carriers 7,12 .”

    From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [7]

  • The genetic architecture of schizophrenia is composed of common variants of small effects, large CNVs with elevated frequencies driven by genomic instability, and URVs of large effect implicating individual genes.

    “Efforts in the past decade are beginning to generate a more comprehensive view of the genetic architecture for schizophrenia, composed of common variants of small effects, large CNVs with elevated frequencies driven by genomic instability, and now, URVs of large effect implicating individual genes (Figure 6A) 5,7 .”

    From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [7]

  • Large-effect CNVs often disrupt many genes simultaneously, limiting functional insights.

    “CNVs of large effect, on the other hand, often disrupt hundreds of kilobases of the genome and multiple genes simultaneously, limiting our ability to derive clear functional insights10.”

    From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [10]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

  • CNV count does not match the stated combined-sample frequency

    Minor

    A count of 80 among the stated 41,321 retained subjects is about 0.194%, not 0.4% of the combined sample.

    Reported 0.4 · recomputed 0.193606

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Authors
Marshall, C. R., Howrigan, D. P., Merico, D., Thiruvahindrapuram, B., Wu, W., Greer, D. S., Antaki, D., Shetty, A., Holmans, P. A., Pinto, D., Gujral, M., Brandler, W. M., Malhotra, D., Wang, Z., Fajarado, K. V. F., Maile, M. S., Ripke, S., Agartz, I., Albus, M., Alexander, M., Amin, F., Atkins, J., Bacanu, S. A., Belliveau, R. A., Bergen, S. E., Bertalan, M., Bevilacqua, E., Bigdeli, T. B., Black, D. W., Bruggeman, R., Buccola, N. G., Buckner, R. L., Bulik-Sullivan, B., Byerley, W., Cahn, W., Cai, G., Cairns, M. J., Campion, D., Cantor, R. M., Carr, V. J., Carrera, N., Catts, S. V., Chambert, K. D., Cheng, W., Cloninger, C. R., Cohen, D., Cormican, P., Craddock, N., Crespo-Facorro, B., Crowley, J. J., Curtis, D., Davidson, M., Davis, K. L., Degenhardt, F., Del Favero, J., DeLisi, L. E., Dikeos, D., Dinan, T., Djurovic, S., Donohoe, G., Drapeau, E., Duan, J., Dudbridge, F., Eichhammer, P., Eriksson, J., Escott-Price, V., Essioux, L., Fanous, A. H., Farh, K.-H., Farrell, M. S., Frank, J., Franke, L., Freedman, R., Freimer, N. B., Friedman, J. I., Forstner, A. J., Fromer, M., Genovese, G., Georgieva, L., Gershon, E. S., Giegling, I., Giusti-Rodríguez, P., Godard, S., Goldstein, J. I., Gratten, J., de Haan, L., Hamshere, M. L., Hansen, M., Hansen, T., Haroutunian, V., Hartmann, A. M., Henskens, F. A., Herms, S., Hirschhorn, J. N., Hoffmann, P., Hofman, A., Huang, H., Ikeda, M., Joa, I., Kähler, A. K., Kahn, R. S., Kalaydjieva, L., Karjalainen, J., Kavanagh, D., Keller, M. C., Kelly, B. J., Kennedy, J. L., Kim, Y., Knowles, J. A., Konte, B., Laurent, C., Lee, P., Lee, S. H., Legge, S. E., Lerer, B., Levy, D. L., Liang, K.-Y., Lieberman, J., Lönnqvist, J., Loughland, C. M., Magnusson, P. K. E., Maher, B. S., Maier, W., Mallet, J., Mattheisen, M., Mattingsdal, M., McCarley, R. W., McDonald, C., McIntosh, A. M., Meier, S., Meijer, C. J., Melle, I., Mesholam-Gately, R. I., Metspalu, A., Michie, P. T., Milani, L., Milanova, V., Mokrab, Y., Morris, D. W., Müller-Myhsok, B., Murphy, K. C., Murray, R. M., Myin-Germeys, I., Nenadic, I., Nertney, D. A., Nestadt, G., Nicodemus, K. K., Nisenbaum, L., Nordin, A., O'Callaghan, E., O'Dushlaine, C., Oh, S.-Y., Olincy, A., Olsen, L., O'Neill, F. A., Van Os, J., Pantelis, C., Papadimitriou, G. N., Parkhomenko, E., Pato, M. T., Paunio, T., Psychosis Endophenotypes International Consortium, Perkins, D. O., Pers, T. H., Pietiläinen, O., Pimm, J., Pocklington, A. J., Powell, J., Price, A., Pulver, A. E., Purcell, S. M., Quested, D., Rasmussen, H. B., Reichenberg, A., Reimers, M. A., Richards, A. L., Roffman, J. L., Roussos, P., Ruderfer, D. M., Salomaa, V., Sanders, A. R., Savitz, A., Schall, U., Schulze, T. G., Schwab, S. G., Scolnick, E. M., Scott, R. J., Seidman, L. J., Shi, J., Silverman, J. M., Smoller, J. W., Söderman, E., Spencer, C. C. A., Stahl, E. A., Strengman, E., Strohmaier, J., Stroup, T. S., Suvisaari, J., Svrakic, D. M., Szatkiewicz, J. P., Thirumalai, S., Tooney, P. A., Veijola, J., Visscher, P. M., Waddington, J., Walsh, D., Webb, B. T., Weiser, M., Wildenauer, D. B., Williams, N. M., Williams, S., Witt, S. H., Wolen, A. R., Wormley, B. K., Wray, N. R., Wu, J. Q., Zai, C. C., Adolfsson, R., Andreassen, O. A., Blackwood, D. H. R., Bramon, E., Buxbaum, J. D., Cichon, S., Collier, D. A., Corvin, A., Daly, M. J., Darvasi, A., Domenici, E., Esko, T., Gejman, P. V., Gill, M., Gurling, H., Hultman, C. M., Iwata, N., Jablensky, A. V., Jönsson, E. G., Kendler, K. S., Kirov, G., Knight, J., Levinson, D. F., Li, Q. S., McCarroll, S. A., McQuillin, A., Moran, J. L., Mowry, B. J., Nöthen, M. M., Ophoff, R. A., Owen, M. J., Palotie, A., Pato, C. N., Petryshen, T. L., Posthuma, D., Rietschel, M., Riley, B. P., Rujescu, D., Sklar, P., St Clair, D., Walters, J. T. R., Werge, T., Sullivan, P. F., O'Donovan, M. C., Scherer, S. W., Neale, B. M., Sebat, J., & CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium
Affiliations
  • Hospital for Sick Children (CA)
  • Broad Institute (US)
  • University of California San Diego (US)
  • Cardiff University (GB)
  • Icahn School of Medicine at Mount Sinai (US)
  • F. Hoffmann-La Roche AG (CH)
  • Division Technique de I'INSU (FR)
  • Stanford Medicine (US)
  • Hunter Medical Research Institute (AU)
  • Virginia Commonwealth University (US)
  • Mental Health Services (DK)
  • University of Iowa (US)
  • University Medical Center Groningen (NL)
  • Louisiana State University Health Sciences Center New Orleans (US)
  • Harvard University (US)
  • University of California, San Francisco (US)
  • University Medical Center Utrecht (NL)
  • Schizophrenia Research Institute (AU)
  • Inserm (FR)
  • University of California, Los Angeles (US)
  • UNSW Sydney (AU)
  • The University of Queensland (AU)
  • University of North Carolina at Chapel Hill (US)
  • Washington University in St. Louis (US)
  • Assistance Publique – Hôpitaux de Paris (FR)
  • Trinity College Dublin (IE)
  • Queen Mary University of London (GB)
  • Sheba Medical Center (IL)
  • University of Bonn (DE)
  • National and Kapodistrian University of Athens (GR)
  • Oslo University Hospital (NO)
  • Ollscoil na Gaillimhe – University of Galway (IE)
  • Endeavor Health (US)
  • London School of Hygiene & Tropical Medicine (GB)
  • University of Helsinki (FI)
  • University of Southern California (US)
  • University of Chicago (US)
  • Illumina (United States) (US)
  • James J. Peters VA Medical Center (US)
  • Fujita Health University (JP)
  • The University of Western Australia (AU)
  • Centre for Addiction and Mental Health (CA)
  • Johns Hopkins University (US)
  • Hadassah Medical Center (IL)
  • Karolinska Institutet (SE)
  • Centre National de la Recherche Scientifique (FR)
  • University of Oslo (NO)
  • Beth Israel Deaconess Medical Center (US)
  • Amsterdam UMC Location University of Amsterdam (NL)
  • Medical University of Sofia (BG)
  • Eli Lilly (United Kingdom) (GB)
  • University of Liverpool (GB)
  • Royal College of Surgeons in Ireland (IE)
  • King's College London (GB)
  • Lawrence Berkeley National Laboratory (US)
  • Umeå University (SE)
  • The University of Melbourne (AU)
  • Finnish Institute for Health and Welfare (FI)
  • University of Oxford (GB)
  • Janssen Research & Development (United States) (US)
  • Heidelberg University (DE)
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • Centre for Human Genetics (GB)
  • Berkshire Healthcare NHS Foundation Trust (GB)
  • Health Research Board (IE)
  • Hebrew University of Jerusalem (IL)
  • University College London (GB)
  • University of Copenhagen (DK)
  • Martin Luther University Halle-Wittenberg (DE)
  • University of Toronto (CA)
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2016-11-21
Volume
49
Issue
1
Pages
27-35
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/ng.3725
PMC
PMC5737772
OpenAlex
W2551102722
Semantic Scholar
e83f0cf7766e4642baff49bdaa3c424796ab3802
Cited by
1,058
References
39
Citations by year
2026: 75 · 2025: 83 · 2024: 109 · 2023: 95 · 2022: 131 · 2021: 121 · 2020: 146 · 2019: 133 · 2018: 99 · 2017: 64 · 2016: 2
FWCI
80.25
Type
journal article
Language
en
Update notices
Open access
Licence
Locations
  • Nature Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • UWA Profiles and Research Repository (UWA) (publishedVersion, other-oa)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, other-oa)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
  • Lancaster EPrints (Lancaster University) (acceptedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Cork Open Research Archive (University College Cork, Ireland) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Iris (University of Trento) (submittedVersion, other-oa)
  • Pure Amsterdam UMC (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • HAL (submittedVersion, other-oa)
  • ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) (submittedVersion, cc-by-nc-nd)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • Research Portal (Queen's University Belfast) (submittedVersion)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
  • VU Research Portal (submittedVersion, other-oa)
  • University of Galway Research Repository (submittedVersion, cc-by-nc)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
Funders
  • U.S. Department of Veterans Affairs
  • Massachusetts General Hospital
  • Strategiske Forskningsråd
  • Aarhus Universitet
  • Højteknologifonden
  • NHS Blood and Transplant
  • National Alliance for Research on Schizophrenia and Depression
  • Wellcome Trust
  • Pratt Foundation
  • Max-Planck-Förderstiftung
  • National Institute for Health and Care Research (NF-SI-0512-10110, PDA/02/06/016, RP-PG-0606-1049)
  • European Commission
  • Deutsche Forschungsgemeinschaft
  • ZonMw
  • Vrije Universiteit Amsterdam
  • Bundesministerium für Bildung und Forschung
  • Lundbeckfonden (R155-2014-1724)
  • Karolinska Institutet
  • Max-Planck-Gesellschaft
  • Alfried Krupp von Bohlen und Halbach-Stiftung
  • Norges Forskningsråd
  • H. Lundbeck A/S
  • Ramsay Health Care
  • Australian Schizophrenia Research Bank
  • National Institutes of Health
  • Seventh Framework Programme
  • Stanley Center for Psychiatric Research, Broad Institute
  • Medical Research Council (MR/L023784/2, MR/K004867/1, MR/P005748/1, MR/K013807/1, MR/L010305/1)
  • National Health and Medical Research Council
  • Strategic Research Council
  • National Institute of Mental Health (U01MH109539, U01MH109514, U01MH094411, R01MH077139, MH094421, U01MH109528, U01MH109536, U01MH094421, U01MH109501, R01MH085548, R01MH095034, MH077139, 62,63)
  • National Human Genome Research Institute
  • National Center for Research Resources
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
schizophrenia, copy number variation, genetic risk, CNV burden, 1q21.1, NRXN1, 15q13.3, 16p11.2, 22q11.2, non-allelic homologous recombination
MeSH terms
Female, Genetic Markers, Genotype, Humans, Male, Risk Factors, Schizophrenia, Case-Control Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Genetic Loci, DNA Copy Number Variations

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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