Abstract
Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin1,2. The extensive genetic heterogeneity of this disorder requires a genome-wide detection of all types of genetic variation. Microarray studies and, more recently, exome sequencing have demonstrated the importance of de novo copy number variations (CNVs) and single-nucleotide variations (SNVs) in ID, but the majority of cases remain undiagnosed3,4,5,6. Here we applied whole-genome sequencing to 50 patients with severe ID and their unaffected parents. All patients included had not received a molecular diagnosis after extensive genetic prescreening, including microarray-based CNV studies and exome sequencing. Notwithstanding this prescreening, 84 de novo SNVs affecting the coding region were identified, which showed a statistically significant enrichment of loss-of-function mutations as well as an enrichment for genes previously implicated in ID-related disorders. In addition, we identified eight de novo CNVs, including single-exon and intra-exonic deletions, as well as interchromosomal duplications. These CNVs affected known ID genes more frequently than expected. On the basis of diagnostic interpretation of all de novo variants, a conclusive genetic diagnosis was reached in 20 patients. Together with one compound heterozygous CNV causing disease in a recessive mode, this results in a diagnostic yield of 42% in this extensively studied cohort, and 62% as a cumulative estimate in an unselected cohort. These results suggest that de novo SNVs and CNVs affecting the coding region are a major cause of severe ID. Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.
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Data deposits
Data included in this manuscript have been deposited at the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home) under accession number EGAS00001000769.
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Acknowledgements
We thank R. Drmanac, K. Albers, J. Goeman, D. Lugtenberg and P. N. Robinson for useful discussions, and M. Steehouwer, P. de Vries and W. Nillesen for technical support. This work was in part financially supported by grants from the Netherlands Organization for Scientific Research (912-12-109 to J.A.V., A.S. and B.B.A.d.V., 916-14-043 to C.G., 916-12-095 to A.H., 907-00-365 to T.K. and SH-271-13 to C.G. and J.A.V.) and the European Research Council (ERC Starting grant DENOVO 281964 to J.A.V.).
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Authors and Affiliations
Contributions
Laboratory work: M.K., I.M.J., T.B., A.H., L.E.L.M.V. Clinical investigation: B.W.M.v.B., M.H.W., B.B.A.d.V., T.K., H.G.B. Data analysis: C.G., J.Y.H.-K., D.T.T., M.v.d.V., R.T. Generation of ID gene list: C.G., A.S., R.P., H.G.Y., T.K., L.E.L.M.V. Data interpretation: L.E.L.M.V., R.P., H.G.Y. Study design: J.A.V., H.G.B., R.L., R.K. Supervision of the study: H.G.B., L.E.L.M.V., J.A.V. Manuscript writing: C.G., J.Y.H.-K., H.G.B., L.E.L.M.V., J.A.V.
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R.L., R.K. and R.T. are employees of Complete Genomics Inc.
Extended data figures and tables
Extended Data Figure 1 Boxplots of rare missense burden in different gene sets.
Boxplots showing the difference in tolerance for rare missense variation in the general population. The vertical axis shows the distribution for each gene set of the number of rare (<1% in NHLBI Exome Sequencing Project) missense variants divided by the number of rare synonymous variants. From left to right the following gene sets are depicted: all 18,424 RefSeq genes, 170 loss-of-function tolerant genes from ref. 30, all 528 known ID genes (Supplementary Table 10), all 628 candidate ID genes (Supplementary Table 11), 9 known ID genes in which de novo mutations were identified in this study (Supplementary Table 8), and 10 candidate ID genes in which de novo mutations were identified in this study (Supplementary Table 8).
Extended Data Figure 2 Structural variant involving STAG1 (patient 40).
a–c, CNV identified using WGS in patient 40, including the STAG1 gene. a, Chromosome 3 profile (log2 test over reference (T/R) ratios) based on read-depth information for patient, father and mother. Black arrow points towards the de novo event in patient 40. b, Genic contents of deletion. Grey arrows show primers used to amplify the junction fragment. c, Details on the proximal and distal breakpoints, showing the ‘fragmented’ sequence at both ends. Breakpoints are provided in Extended Data Table 1.
Extended Data Figure 3 Structural variant involving SHANK3 (patient 5).
a–c, CNV identified using WGS in patient 5, including the SHANK3 gene. a, Detail of chromosome 22 profile (log2 T/R ratios) based on read-depth information for patient, father and mother. Red dots in top panel show ratios indicating the de novo deletion in patient 5. b, Genic content of the deletion. c, Sanger validation for the junction fragment. Dotted vertical line indicates the breakpoint with sequence on the left side originating from sequence proximal to SHANK3 and on the right side sequence that originates from sequence distal to ACR. Breakpoints are provided in Extended Data Table 1.
Extended Data Figure 4 Single-exon deletion involving SMC1A (patient 48).
a, Schematic depiction of the deletion identified in patient 48 involving a single exon of SMC1A. Pink horizontal bar highlights the exon that was deleted in the patient. b, Details at the genomic level of the deletion including exon 16, with Sanger sequence validation of the breakpoints. Junction is indicated by a black vertical dotted line. Breakpoints are provided in Extended Data Table 1.
Extended Data Figure 5 Intra-exonic deletion involving MECP2 (patient 18).
a, Schematic depiction of the deletion identified in patient 18, which is located within exon 4 of MECP2. Initial Sanger sequencing in a diagnostic setting could not validate the deletion as the primers used to amplify exon 4 removed the primer-binding sites (FW2 and RV1 respectively). Multiplex ligation probe amplification (MLPA) analysis for CNV detection showed normal results as the MLPA primer-binding sites were located just outside of the deleted region. b, Combining primers FW1 and RV2 amplified the junction fragment, clearly showing the deletion within exon 4. Of note, the background underneath the Sanger sequence is derived from the wild-type allele. Breakpoints are provided in Extended Data Table 1.
Extended Data Figure 6 Confirmation of mosaic mutations in PIAS1, HIVEP2 and KANSL2.
a–c, Approaches used to confirm the presence of mosaic mutations in PIAS1 (a), HIVEP2 (b) and KANSL2 (c). Images and read-depth information showing the base counts in the BAM files (left) indicated that the variants/wild-type allele were not in a 50%/50% distribution. Sanger sequencing (middle) then confirmed the variant to be present in the patient, and absent in the parents (data from parents not shown), again indicating that the mutation allele is underrepresented. Guided by these two observations, amplicon-based deep sequencing using Ion Torrent subsequently confirmed the mosaic state of the mutations (right). On the basis of deep sequencing, percentages of mosaicism for PIAS1, HIVEP2 and KANSL2 were estimated at 21%, 22% and 20%, respectively.
Extended Data Figure 7 Compound heterozygous structural variation affecting VPS13B (patient 12).
a, b, CNVs of VPS13B identified using WGS in patient 12. a, Schematic representation of VPS13B, with vertical bars indicating coding exons. In patient 12 two deletions were identified, one ∼122 kb in size which was inherited from his father, and another ∼2 kb in size, which was inherited from his mother and consisted only of a single exon. b, Both CNV junction fragments were subsequently validated using Sanger sequencing. Left, junction fragment from the paternally inherited deletion. Right, junction fragment from the maternally inherited deletion. Breakpoints are provided in Extended Data Table 1.
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This file contains Supplementary Methods, Supplementary Tables 1-15 and Supplementary References. (PDF 3010 kb)
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Gilissen, C., Hehir-Kwa, J., Thung, D. et al. Genome sequencing identifies major causes of severe intellectual disability. Nature 511, 344–347 (2014). https://doi.org/10.1038/nature13394
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DOI: https://doi.org/10.1038/nature13394
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