Evidence map›Paper›PMID 26817790›Full record

ArticleJAMA psychiatry2016

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

Andrea J Gonzalez-Mantilla, Andres Moreno-De-Luca, David H Ledbetter, Christa Lese Martin

Open access · bronzeAbstract read
In one paragraph

Article in JAMA psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 3 pooled it
16.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

83 citing papers in PubMed, 3 syntheses or guidelines pooled it, 152 citations in OpenAlex.

  1. Pooled it
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  6. Review
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  11. HiFiMAP: High-resolution fast identity-by-descent mapping test.medRxiv : the preprint server for health sciences · 2026
    Article
  12. Shared and distinct phenotypic profiles among neurodevelopmental disorder genes.medRxiv : the preprint server for health sciences · 2026
    Article
  13. Article
  14. Article
  15. Joint analysis ofNAR genomics and bioinformatics · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Review of autism spectrum disorder databases for the identification of candidate genes.Database : the journal of biological databases and curation · 2025
    Review
  20. DYRK1A roles in human neural progenitors.Frontiers in neuroscience · 2025
    Article

23 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Andrea J Gonzalez-MantillaAutism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania.
Andres Moreno-De-LucaAutism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania2Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania3Department of Radiology, Geisinger Health System, Danville, Pennsylvania.
David H LedbetterAutism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania2Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania.
Christa Lese MartinAutism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania2Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania.
Autism & Developmental Medicine Institute · USGeisinger Health System · US

Funding

GENE DOSAGE IMBALANCE IN NEURODEVELOPMENTAL DISORDERSR01MH074090 · NIMH · GEISINGER CLINIC · PI David H. Ledbetter, CHRISTA LESE MARTIN · 2005 to 2026
$13.5M
NIMH NIH HHS R01 MH074090NIMH NIH HHS R01MH074090
6 · The paper itself

Abstract

importanceDevelopmental 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.

objectivesTo 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.

resultsOur 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.

Indexed as

AllelesAttention Deficit Disorder with HyperactivityAutistic DisorderBipolar DisorderBrain DiseasesDevelopmental DisabilitiesGenetic Predisposition to DiseaseGenome, HumanGenomicsHumansPhenotype

Identifiers

PMID26817790
PMCPMC5333489
OpenAlexW2258597767

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.