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Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity

Abstract

We combined de novo mutation (DNM) data from 10,927 individuals with developmental delay and autism to identify 253 candidate neurodevelopmental disease genes with an excess of missense and/or likely gene-disruptive (LGD) mutations. Of these genes, 124 reach exome-wide significance (P < 5 × 10−7) for DNM. Intersecting these results with copy number variation (CNV) morbidity data shows an enrichment for genomic disorder regions (30/253, likelihood ratio (LR) +1.85, P = 0.0017). We identify genes with an excess of missense DNMs overlapping deletion syndromes (for example, KIF1A and the 2q37 deletion) as well as duplication syndromes, such as recurrent MAPK3 missense mutations within the chromosome 16p11.2 duplication, recurrent CHD4 missense DNMs in the 12p13 duplication region, and recurrent WDFY4 missense DNMs in the 10q11.23 duplication region. Network analyses of genes showing an excess of DNMs highlights functional networks, including cell-specific enrichments in the D1+ and D2+ spiny neurons of the striatum.

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Data availability

All variant data in this study are available to download from denovo-db v.1.5 (http://denovo-db.gs.washington.edu/). Human MTG single-nucleus RNA-seq data and clusters can be downloaded from the Allen Institute for Brain Science website at http://celltypes.brain-map.org/download.

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Acknowledgements

We wish to thank T. Turner and J. Shendure for helpful discussion and T. Brown for edits. This research was supported, in part, by the following: the Simons Foundation Autism Research Initiative (SFARI 303241) and US National Institutes of Health (NIH R01MH101221) to E.E.E. The J.D.D. laboratory is supported by a NARSAD Independent Investigator Award from the Brain and Behavior Research Foundation and NIH grant 5R01MH107515-03. We are grateful to all of the families at the participating Simons Simplex Collection (SSC) sites, as well as the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, R. Goin-Kochel, E. Hanson, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, K. Pelphrey, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, Z. Warren, E. Wijsman). E.E.E. is supported by the Howard Hughes Medical Institute.

Author information

B.P.C. and E.E.E. designed the study. B.P.C. performed the primary statistical data analysis. B.P.C., H.A.F.S., and M.R.G. curated DNMs and performed enrichment analyses. A.S. assisted with statistical analyses and interpretation. R.A.B. performed phenotype analysis. T.E.B. and E.S.L. performed the human expression analysis. A.M.L. and J.D.D. performed CSEA on cortex and assisted with additional CSEA and TSEA. F.H. performed the gene network analysis. B.P.C. and E.E.E. wrote the manuscript. All authors have read and approved the final version of the manuscript.

Competing interests

E.E.E. is on the scientific advisory board of DNAnexus, Inc.

Correspondence to Evan E. Eichler.

Integrated supplementary information

Supplementary Figure 1 Comparison of de novo variation rates in ASD and ID/DD.

a,b, The plots compare DNM rates for genes for patients from ASD (n = 5,624 independent samples) and ID/DD (n = 5,303 independent samples) studies included in our combined analysis. More than 75% of genes show DNM in both ASD and DD patients. We identify four LGD genes (ARID1B, ANDKRD11, KMT2A, DDX3X) (a) and one missense gene (KCNQ2) (b) that are biased for an ID/DD diagnosis at a q-value threshold of 0.1 (one-tailed Fisher’s exact test). Additional candidates for phenotypic bias at nominal significance (dashed lines at P = 0.05, one-tailed Fisher’s exact test) were also identified. Larger cohorts will be needed to confirm gene biases, especially with respect to ASD.

Supplementary Figure 2 CSEA identifies bias to specific brain regions.

Cell-specific enrichment analyses (CSEA) of the union set (n = 253 independent genes) highlight a strong bias to various developing parts of the brain (color corresponds to FDR-adjusted one-tailed Fisher’s exact test P values; shaded regions closer to the center of each hexagon indicate increasing tissue specificity). a, We observe enrichment for both classes of striatal medium spiny neurons for our gene set. This tissue has been previously implicated in autism and candidate neurodevelopmental genes (J. Neurosci 34, 1420–1431, 2014), and we now observe cell-specific enrichment among genes with a significant excess of DNM. b, Application of CSEA on n = 253 independent genes to the additional cell types profiled in Zeisel et al. (Science 347, 1138–1142, 2015) identifies pyramidal neurons in layer 5 of the cortex and hippocampus. Color corresponds to FDR-adjusted one-tailed Fisher’s exact test P values; shaded regions closer to the center of each hexagon indicate increasing tissue specificity.

Supplementary Figure 3 Pan-neuronal expression patterns of candidate NDD genes.

ac, Heatmaps demonstrating a broad pattern of inhibitory and excitatory neuronal expression (median log2 (CPM + 1)) in the NDD gene sets compared to control genes. The FWER union set shows even greater pan-neuronal-enriched expression than the larger union gene set. Rows represent individual genes and are ordered by the number of clusters with expression (median CPM > 1), and columns represent 41 inhibitory neuronal, 24 excitatory neuronal, and 6 glial clusters. df, Genes enriched for DNM are more broadly expressed in inhibitory (d) and excitatory (e) neurons, while genes enriched for LGD events specifically are enriched in glial expression (f). g, Comparison of control and test gene lists demonstrates similar maximum average expression (CPM) across cell types. h, Cell type specificity as measured by a beta marker score (Methods) is also similar for NDD and control genes.

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Fig. 1: De novo−enriched genes and their characteristics.
Fig. 2: Gene expression and protein-interaction networks.
Fig. 3: Expression in human cortical neurons.
Fig. 4: Estimation of gene discovery rates in future cohorts.
Fig. 5: Integration of de novo SNVs and CNV morbidity map.
Supplementary Figure 1: Comparison of de novo variation rates in ASD and ID/DD.
Supplementary Figure 2: CSEA identifies bias to specific brain regions.
Supplementary Figure 3: Pan-neuronal expression patterns of candidate NDD genes.