Cited by 142Genomics and Rare DiseasesGenetics and Neurodevelopmental DisordersGenomic variations and chromosomal abnormalities

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

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Gonzalez-Mantilla, Andrea J., Moreno-De-Luca, Andres, Ledbetter, David H., Martin, Christa Lese·2016·JAMA Psychiatry

Abstract

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.

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Crossref · 10.1001/jamapsychiatry.2015.2692

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  • Among 59 genes with at least 10 total probands with de novo pLOF variants in the DBD Genes Database, none are associated exclusively with ASD.

    “Among 59 genes for each of which there are at least 10 total probands with de novo pLOF variants in the database, none are associated exclusively with ASD (Figure 1).”

    From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [22]

  • For CHD8, SHANK3, and SCN2A, there are more individuals with ASD only than with ID only, but many have both ASD and ID, and for each of these genes there are more individuals with ID than without ID (ID rates 68%, 52%, and 62%, respectively).

    “For three genes, CHD8 [MIM: 610528], SHANK3 [MIM: 606230], and SCN2A [MIM: 182390], there are more individuals with ASD only than with ID only, but many have both ASD and ID, and for each of these genes, there are more individuals with ID than without ID (ID rates 68%, 52%, and 62% for CHD8, SHANK3, and SCN2A, respectively).”

    From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [22]

  • At the time it was accessed, the DBD Genes Database included 5,031 cases with loss-of-function variants in 553 genes based on information from 923 unique articles published between March 2003 and March 2019 that met curation criteria.

    “At the time it was accessed, the database included 5,031 cases with loss-of-function variants in 553 genes based on information from 923 unique articles published between March 2003 and March 2019 that met curation criteria.22”

    From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [22]

  • The DBD Genes Database integrates data from exome and genome sequencing, copy number array, and targeted gene studies with phenotype data for six clinically defined brain disorders to examine the phenotypes associated with de novo pathogenic loss-of-function variants.

    “For example, the Geisinger Developmental Brain Disorder Genes Database (DBD Genes Database) integrates data from exome and genome sequencing, copy number array, and targeted gene studies with phenotype data for six clinically defined brain disorders (including ASD and ID) to examine the phenotypes associated with de novo pathogenic loss-of-function (pLoF) variants (see Web Resources).22”

    From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [22]

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Authors
Gonzalez-Mantilla, A. J., Moreno-De-Luca, A., Ledbetter, D. H., & Martin, C. L.
Affiliations
  • Autism & Developmental Medicine Institute (US)
  • Autism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania2Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania3Department of Radiology, Geisinger Health System, Danville, Pennsylvania
Corresponding author
Martin, Christa Lese
Venue
JAMA Psychiatry
Published
2016-03-01
Volume
73
Issue
3
Pages
275
ISSN
2168-622X (ISSN-L)
OpenAlex
W2258597767
Cited by
139
References
32
Citations by year
2026: 14 · 2025: 12 · 2024: 10 · 2023: 6 · 2022: 14 · 2021: 21 · 2020: 12 · 2019: 21 · 2018: 7 · 2017: 10 · 2016: 12
FWCI
13.46
Type
journal article
Language
en
Open access
Locations
  • JAMA Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institute of Mental Health (R01MH074090)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Keywords
neurodevelopmental disorders, candidate genes, de novo mutations, intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, schizophrenia, bipolar disorder, epilepsy, gene prioritization, cross-disorder analysis, genetic heterogeneity, mode of inheritance, novel genes, phenotypic overlap, structural variants
MeSH terms
Alleles, Attention Deficit Disorder with Hyperactivity, Autistic Disorder, Bipolar Disorder, Brain Diseases, Developmental Disabilities, Humans, Phenotype, Genome, Human, Genetic Predisposition to Disease, Genomics

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