A Cross-Disorder Method to Identify Novel Candidate Genes for Developmental Brain Disorders.

Importance: Developmental brain disorders are a group of clinically and genetically heterogeneous disorders characterized by high heritability. Specific highly penetrant genetic causes can often be shared by a subset of individuals with different phenotypic features, and recent advances in genome sequencing have allowed the rapid and cost-effective identification of many of these pathogenic variants.

Objectives: To identify novel candidate genes for developmental brain disorders and provide additional evidence of previously implicated genes.

Data sources: The PubMed database was searched for studies published from March 28, 2003, through May 7, 2015, with large cohorts of individuals with developmental brain disorders.

Data extraction and synthesis: A tiered, multilevel data-integration approach was used, which intersects (1) whole-genome data from structural and sequence pathogenic loss-of-function (pLOF) variants, (2) phenotype data from 6 apparently distinct disorders (intellectual disability, autism, attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, and epilepsy), and (3) additional data from large-scale studies, smaller cohorts, and case reports focusing on specific candidate genes. All candidate genes were ranked into 4 tiers based on the strength of evidence as follows: tier 1, genes with 3 or more de novo pathogenic loss-of-function variants; tier 2, genes with 2 de novo pathogenic loss-of-function variants; tier 3, genes with 1 de novo pathogenic loss-of-function variant; and tier 4, genes with only inherited (or unknown inheritance) pathogenic loss-of-function variants.

Main outcomes and measures: Development of a comprehensive knowledge base of candidate genes related to developmental brain disorders. Genes were prioritized based on the inheritance pattern and total number of pathogenic loss-of-function variants identified amongst unrelated individuals with any one of six developmental brain disorders.

Study selection: A combination of phenotype-based and genotype-based literature review yielded 384 studies that used whole-genome or exome sequencing, chromosomal microarray analysis, and/or targeted sequencing to evaluate 1960 individuals with developmental brain disorders.

Results: Our initial phenotype-based literature review yielded 1911 individuals with pLOF variants involving 1034 genes from 118 studies. Filtering our results to genes with 2 or more pLOF variants identified in at least 2 unrelated individuals resulted in 241 genes from 1110 individuals. Of the 241 genes involved in brain disorders, 7 were novel high-confidence genes and 10 were novel putative candidate genes. Fifty-nine genes were ranked in tier 1, 44 in tier 2, 68 in tier 3, and 70 in tier 4. By transcending clinical diagnostic boundaries, the evidence level for 18 additional genes that were ranked 1 tier higher because of this cross-disorder approach was increased.

Conclusions and relevance: This approach increased the yield of gene discovery over what would be obtained if each disorder, type of genomic variant, and study design were analyzed independently. These results provide further support for shared genomic causes among apparently different disorders and demonstrate the clinical and genetic heterogeneity of developmental brain disorders.