ArticlePLoS genetics2013
Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes.
Article in PLoS genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers, 1 of them a synthesis that pooled it.
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Who cites it
184 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Rare coding variation provides insight into the genetic architecture and phenotypic context of autism.Nature genetics · 2022Pooled it
- Genetic architecture of postpartum psychosis: from common to rare genetic variation.Molecular psychiatry · 2026Article
- Monoallelic loss-of-function variants in ZNF536 are associated with a neurodevelopmental disorder with prominent behavioral features.American journal of human genetics · 2026Article
- Whole-exome sequencing in individuals with obsessive-compulsive disorder and chronic tic disorders identifies 36 large-effect risk genes.Nature neuroscience · 2026Article
- Rationale and Methods for the Prospective Genetic Risk Evaluation and Assessment (PROGRESS) in Autism Center at Columbia University.Pediatric research · 2026Article
- Genomic landscape of rare variants in a Chinese autism cohort and discovery of novel risk genes.Molecular psychiatry · 2026Article
- Advancing risk gene discovery across the allele frequency spectrum.HGG advances · 2026Review
- Article
- Identification of moderate effect size genes in autism spectrum disorder through a novel gene pairing approach.Communications biology · 2026Article
- Comprehensive analysis ofmedRxiv : the preprint server for health sciences · 2026Article
- Modeling rare coding variation on chromosome X provides insight into the genetics and differential sex prevalence of autism spectrum disorder.medRxiv : the preprint server for health sciences · 2026Article
- A framework to infer de novo exonic variants when parental genotypes are missing enhances association studies of autism.Bioinformatics (Oxford, England) · 2026Article
- Deleterious coding variation associated with autism is shared across ancestries.Nature medicine · 2026Article
- Black EquaLity in OCD NeuroGenomics (BELONG): Study Protocol.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2026Article
- The emerging role of gene therapy in autism spectrum disorder.Discover mental health · 2026Review
- Clinical,medRxiv : the preprint server for health sciences · 2026Article
- Genetic and Cortical Cell-Type Liability Architecture of Autism.Research square · 2026Article
- MIRAGE: A Bayesian statistical method for gene-level rare-variant analysis incorporating functional annotations.American journal of human genetics · 2026Article
- Gene4Denovo2: an updated platform for human de novo mutations discovery and interpretation.Nucleic acids research · 2026Article
- Rare coding variation in OCD implicates shared genes with other psychiatric disorders.medRxiv : the preprint server for health sciences · 2025Article
124 more citing papers are in PubMed but not listed here.
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13 authors.
Funding
Abstract
De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support.
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