Abstract
By analyzing the exomes of 12,332 unrelated Swedish individuals, including 4,877 individuals affected with schizophrenia, in ways informed by exome sequences from 45,376 other individuals, we identified 244,246 coding-sequence and splice-site ultra-rare variants (URVs) that were unique to individual Swedes. We found that gene-disruptive and putatively protein-damaging URVs (but not synonymous URVs) were more abundant among individuals with schizophrenia than among controls (P = 1.3 × 10−10). This elevation of protein-compromising URVs was several times larger than an analogously elevated rate for de novo mutations, suggesting that most rare-variant effects on schizophrenia risk are inherited. Among individuals with schizophrenia, the elevated frequency of protein-compromising URVs was concentrated in brain-expressed genes, particularly in neuronally expressed genes; most of this elevation arose from large sets of genes whose RNAs have been found to interact with synaptically localized proteins. Our results suggest that synaptic dysfunction may mediate a large fraction of strong, individually rare genetic influences on schizophrenia risk.
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Acknowledgements
We thank C. Usher for comments on the manuscript and work on the figures. This study was supported by grants from the National Human Genome Research Institute (U54 HG003067, R01 HG006855 to S.A.M.), the National Institute of Mental Health (R01 MH077139 to P.F.S., R01 MH095034 to P.S., and RC2 MH089905 to S.M.P. and P.S.), the Stanley Center for Psychiatric Research, the Alexander and Margaret Stewart Trust, and the Sylvan C. Herman Foundation.
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G.G. and S.A.M. designed the analyses and wrote early drafts of the manuscript. G.G. performed the analyses. M.F. contributed to analyses of de novo mutated genes, D.M.R. and E.A.S. contributed with the specific design of the analyses. K.C. contributed with sample processing and data management. M.L., J.L.M., S.M.P., P.S., P.F.S. and C.M.H. contributed with sample and phenotype collection. All of the authors contributed to interpretation of the findings and revisions of the manuscript.
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Integrated supplementary information
Supplementary Figure 1 Missense damaging predictions as a function of allele frequency
Percentage of missense variants classified as damaging by eight different classifiers and a classifier consisting of the intersection of classifiers SIFT, PolyPhen-2 HDIV, PolyPhen-2 HVAR, LRT, Mutation Taster, Mutation Assessor, and PROVEAN as a function of minor allele count across 12,332 unrelated individuals from Sweden. Gray and black colors indicate, respectively, variants never observed and variants already observed in the ExAC cohort of 45,376 individuals.
Supplementary Figure 2 Correlations across ultra-rare variant types counts
Relationships between four separate types of coding-sequence and splice-site URV counts across 12,332 unrelated individuals from Sweden: (a) disruptive vs. damaging; (b) disruprive vs. missense non-damaging; (c) damaging vs. missense non-damaging; (d) disruptive vs. synonymous; (e) damaging vs. synonymous; (f) missense non-damaging vs synonymous. Black dots indicate individuals with less than or equal to 100 URVs detected, and red crosses indicate individuals with more than 100 URVs detected. Pearson correlation coefficients are indicated on the top left of each panel.
Supplementary Figure 3 Enrichment in schizophrenia cases across ultra-rare variant types
Observed enrichment in 4,877 schizophrenia cases compared to 6,203 controls for (a) URVs across all annotations, with non-coding including both intronic and untranslated region variants, (b) missense URVs classified as damaging by classifiers PolyPhen-2 HDIV, PolyPhen-2 HVAR, SIFT, LRT, PROVEAN, FATHMM, Mutation Taster, and Mutation Assessor, as well as missense damaging, in-frame indel, protein-protein-contact, splice-acceptor, splice-donor, stop-gained, and frameshift URVs. Enrichment and P values were computed using a linear regression model (left panels) and a logistic regression model (right panels) and correcting for covariates (a) with and (b) without the exclusion of URV individual count. Horizontal bars indicate 95% confidence intervals.
Supplementary Figure 4 Single gene burden tests for disruptive and damaging variants at different allele frequency thresholds
Quantile-quantile plots for burden tests for association with schizophrenia of all Ensembl genes for disruptive and damaging variants. Burden test for association was performed using SKAT software.
Supplementary Figure 5 Enrichment of dURVs in schizophrenia cases across selected gene sets stratified per variant types and cohorts
Burden of dURVs across selected gene sets analyzed in this study stratified across disruptive and damaging URVs (left panel) and across previously analyzed exomes and newly available exomes (right panel). Enrichment and P values were computed using a logistic regression model using exome-wide dURV count as a covariate to correct for average exome-wide burden (dot-dashed line). Horizontal bars indicate 95% confidence intervals.
Supplementary Figure 6 Enrichment of dURVs in schizophrenia cases across constrained and unconstrained genes
Burden of dURVs across loss-of-function intolerant (LoF-intolerant) genes, missense constrained genes and their complementary sets, stratified across disruptive and damaging URVs. Enrichment and P values were computed using a linear regression model (left panels) and a logistic regression model (right panels) and, contrary to most other analyses in this study, without using exome-wide dURV count to correct for average exome-wide burden. Horizontal bars indicate 95% confidence intervals. As LoF-intolerant and missense constrained genes were defined outside this study, different enrichments observed within and outside these gene sets cannot be attributed to differential false positive rates between cases and controls.
Supplementary Figure 7 Enrichment of dURVs in schizophrenia cases across gene sets from different tissues
Burden of dURVs across 27 tissue expression specific gene sets. Each gene set was generated selecting genes for which expression in a given tissue was at least 5 times the median expression across 27 different human organs and tissues ascertained from 95 individual. Enrichment and P values were computed using a logistic regression model using exome-wide dURV count as a covariate to correct for average exome-wide burden (dot-dashed line). Horizontal bars indicate 95% confidence intervals. Brain specific genes were significantly more enriched for dURVs in schizophrenia cases than the average gene.
Supplementary Figure 8 Enrichment of dURVs in schizophrenia cases across gene sets from different brain and neuronal cell types
Burden analysis for dURVs across genes defined from (a) 11 brain cell types and (b) 3 neuron cell types: excitatory pyramidal neurons (Exc), parvalbumin (PV)-expressing fast-spiking interneurons, vasoactive intestinal peptide (VIP)-expressing interneurons, both for expressed genes and cell-type specific genes. Brain cell type gene sets were generated selecting genes for which log-expression in a given cell type was 0.5 greater than the median log-expression across 11 central nervous system cell types ascertained from developing and mature mouse forebrain. Neuron cell type expressed gene sets were defined as those with more than 50 observed transcripts per million (TPM). Neuron cell type specific gene sets were defined as those observed more than 5 times the minimum expression across the 3 different cell types. Expression profiles for neurons were ascertained from nuclei isolated from adult (8–11 weeks) mouse neocortex. Enrichment and P values were computed using a logistic regression model using exome-wide dURV count as a covariate to correct for average exome-wide burden (dot-dashed line). Horizontal bars indicate 95% confidence intervals.
Supplementary Figure 9 Enrichment of dURVs in schizophrenia cases across different X linked intellectual disability gene sets
Burden analysis for dURVs across X linked intellectual disability (XLID) genes and developmental disorder genes. X linked ID genes correspond to the union of X linked ID sets of genes as defined from OMIM, GCC, and Chicago. Enrichment was computed separately for males, females, and both groups together. Enrichment and P values were computed using a logistic regression model using exome-wide dURV count as a covariate to correct for average exome-wide burden (dot-dashed line). Horizontal bars indicate 95% confidence intervals. Larger confidence intervals for males reflect the smaller number of variants observed in males due to carrying half as much X chromosome DNA.
Supplementary Figure 10 Average ultra-rare variant types count across sequencing waves
Average number of URVs detected in controls and in schizophrenia cases used in this analysis across several classes of variants and sequencing waves. Numbers of controls and cases within each wave is indicated in parentheses. Wave 1 is denoted in red as for this batch, accounting for approximately 1% of the whole cohort, an earlier version of the hybrid-capture procedure was used which captured approximately 10% less of the exome. Vertical bars indicate 95% confidence intervals.
Supplementary Figure 11 Duplicate and first degree relationship estimates across cohort
Estimates of percentage of genome shared IBD (PI_HAT) and percentage of genome shared IBD1 (Z1) among all pairs from 12,384 samples for which PI_HAT>.35. Estimates were generated with plink command “--genome full”.
Supplementary Figure 12 Ultra-rare variants counts relationships with population stratification
Covariates within the Swedish exome cohort: (a) ultra-rare SNP and indel counts across cohort 12,334 individuals; (b) distribution of birth year across cohort individuals; (c) relationship of cohort individuals (in black) with 1000 Genomes project phase 1 individuals with respect to the first two principal components with removed outliers (in red); (d) relationship of cohort individuals with respect to the two main Swedish principal components; (e) relationship between principal components tracking Finnish ancestry and URV count; (f) relationship between principal components tracking Northern-Southern Swedish ancestry and URV count. Black crosses indicate individuals with less than or equal to 100 URVs detected, and red crosses indicate individuals with more than 100 URVs detected.
Supplementary Figure 13 Gender estimates from genotypes
X chromosome inbreeding coefficient (F) and Y-chromosome non-missing genotype calls (YCOUNT) for the entire cohort of 12,384 samples. Male individuals inferred with 47,XXY karyotype (Klinefelter syndrome) are indicated in green and individuals with mismatching reported and genotyped sex are indicated as yellow crosses. Estimates were generated with plink command ′--check-sex ycount′.
Supplementary Figure 14 Manhattan plot for association with schizophrenia of common exome variants
Manhattan plot for association of exonic variants with schizophrenia phenotype using a logistic regression model with sex and first five principal components as covariates. Variants with P value less than 10-6 include variant rs281766 on chromosome 2 in the UTR5 of genes TYW5 and C2orf47, and seven variants in the MHC region around the HLA genes.
Supplementary Figure 15 Missense predictors comparisons for association with schizophrenia
P values for enrichment of missense URVs classified as damaging by all 256 possible predictors defined as the combination of damaging definitions from any subset of Polyphen2_HDIV, Polyphen2_HVAR, SIFT, LRT, PROVEAN, FATHMM, Mutation Taster, and Mutation Assessor algorithms. P values were computed using a linear regression model and correcting for covariates including total URV count. Predictors including FATHMM performed significantly worse than predictors excluding FATHMM while 25 predictors performed better than the predictor chosen for the analyses in this manuscript (bright red). Both predictors including all algorithms but FATHMM (bright red) and including LRT, MutationTaster, PolyPhen2 HDIV, PolyPhen2 HVAR, and SIFT (green) performed better than each predictor based on a single algorithm.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–15 and Supplementary Tables 1, 2 and 8 (PDF 2266 kb)
Supplementary Methods Checklist
(PDF 129 kb)
Supplementary Table 3
List of dURVs identified across 4,877 schizophernia cases and 6,203 controls. (XLSX 2968 kb)
Supplementary Table 4
List of studies to define genes hit by de novo CNVs (Fig. 5a). (XLSX 6 kb)
Supplementary Table 5
List of de novo CNVs previously found in individuals with schizophrenia, bipolar disorder, and autism (Fig. 5a). (XLSX 34 kb)
Supplementary Table 6
List of studies to define genes hit by de novo non-synonymous variants (Fig. 5b). (XLSX 6 kb)
Supplementary Table 7
List of de novo variants found in individuals with schizophrenia, autism, epilepsy, intellectual disability, congenital heart disease, and controls (Fig. 5b). (XLSX 4529 kb)
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Genovese, G., Fromer, M., Stahl, E. et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci 19, 1433–1441 (2016). https://doi.org/10.1038/nn.4402
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DOI: https://doi.org/10.1038/nn.4402
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