ArticleHuman mutation2017
A Cell Type-Specific Expression Signature Predicts Haploinsufficient Autism-Susceptibility Genes.
Article in Human mutation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 32 citations in OpenAlex.
- Age of machine learning: new trends in autism spectrum disorder prediction.Frontiers in microbiology · 2025Review
- Ranking and Combining Latent Structured Predictive Scores without Labeled Data.IISE transactions · 2024Article
- The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism.International journal of molecular sciences · 2024Review
- A network-based method for associating genes with autism spectrum disorder.Frontiers in bioinformatics · 2024Article
- VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants.Communications biology · 2023Article
- Prioritizing de novo autism risk variants with calibrated gene- and variant-scoring models.Human genetics · 2022Article
- DeepND: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders.Patterns (New York, N.Y.) · 2022Article
- "Guilt by association" is not competitive with genetic association for identifying autism risk genes.Scientific reports · 2021Article
- Rare variant analysis of 4241 pulmonary arterial hypertension cases from an international consortium implicates FBLN2, PDGFD, and rare de novo variants in PAH.Genome medicine · 2021Article
- Forecasting risk gene discovery in autism with machine learning and genome-scale data.Scientific reports · 2020Article
- Coupling of autism genes to tissue-wide expression and dysfunction of synapse, calcium signalling and transcriptional regulation.PloS one · 2020Article
- A Machine Learning Approach to Predicting Autism Risk Genes: Validation of Known Genes and Discovery of New Candidates.Frontiers in genetics · 2020Article
- A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases.Journal of integrative bioinformatics · 2019Review
- Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons.Translational psychiatry · 2018Article
- Systems biology in the central nervous system: a brief perspective on essential recent advancements.Current opinion in systems biology · 2017Article
- Secreted Reporter Assay Enables Quantitative and Longitudinal Monitoring of Neuronal Activity.eNeuroArticle
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
Abstract
Recent studies have identified many genes with rare de novo mutations in autism, but a limited number of these have been conclusively established as disease-susceptibility genes due to the lack of recurrence and confounding background mutations. Such extreme genetic heterogeneity severely limits recurrence-based statistical power even in studies with a large sample size. Here, we use cell-type specific expression profiles to differentiate mutations in autism patients from those in unaffected siblings. We report a gene expression signature in different neuronal cell types shared by genes with likely gene-disrupting (LGD) mutations in autism cases. This signature reflects haploinsufficiency of risk genes enriched in transcriptional and post-transcriptional regulators, with the strongest positive associations with specific types of neurons in different brain regions, including cortical neurons, cerebellar granule cells, and striatal medium spiny neurons. When used to prioritize genes with a single LGD mutation in cases, a D-score derived from the signature achieved a precision of 40% as compared with the 15% baseline with a minimal loss in sensitivity. An ensemble model combining D-score with mutation intolerance metrics from Exome Aggregation Consortium further improved the precision to 60%, resulting in 117 high-priority candidates. These prioritized lists can facilitate identification of additional autism-susceptibility genes.
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Registered trials
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.