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Mol Psychiatry. 2016 Feb;21(2):290-7. doi: 10.1038/mp.2015.40. Epub 2015 Apr 7.

Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database.

Li J1,2,3, Cai T4, Jiang Y2, Chen H2, He X5, Chen C3,6, Li X3, Shao Q2, Ran X2, Li Z2, Xia K3, Liu C3,6, Sun ZS1,2, Wu J1,2.

Author information

Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China.
Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, China.
State Key Laboratory of Medical Genetics, Central South University, Changsha, China.
Experimental Medicine Section, NIDCR/NIH, Bethesda, MD, USA.
Department of Human Genetics, University of Chicago, Chicago, IL, USA.
Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.


Currently, many studies on neuropsychiatric disorders have utilized massive trio-based whole-exome sequencing (WES) and whole-genome sequencing (WGS) to identify numerous de novo mutations (DNMs). Here, we retrieved 17,104 DNMs from 3555 trios across four neuropsychiatric disorders: autism spectrum disorder, epileptic encephalopathy, intellectual disability and schizophrenia, in addition to unaffected siblings (control), from 36 studies by WES/WGS. After eliminating non-exonic variants, we focused on 3334 exonic DNMs for evaluation of their association with these diseases. Our results revealed a higher prevalence of DNMs in the probands of all four disorders compared with the one in the controls (P<1.3 × 10(-7)). The elevated DNM frequency is dominated by loss-of-function/deleterious single-nucleotide variants and frameshift indels (that is, extreme mutations, P<4.5 × 10(-5)). With extensive annotation of these 'extreme' mutations, we prioritized 764 candidate genes in these four disorders. A combined analysis of Gene Ontology, microRNA targets and transcription factor targets revealed shared biological process and non-coding regulatory elements of candidate genes in the pathology of neuropsychiatric disorders. In addition, weighted gene co-expression network analysis of human laminar-specific neocortical expression data showed that candidate genes are convergent on eight shared modules with specific layer enrichment and biological process features. Furthermore, we identified that 53 candidate genes are associated with more than one disorder (P<0.000001), suggesting a possibly shared genetic etiology underlying these disorders. Particularly, DNMs of the SCN2A gene are frequently occurred across all four disorders. Finally, we constructed a freely available NPdenovo database, which provides a comprehensive catalog of the DNMs identified in neuropsychiatric disorders.

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