ArticleNature genetics2025
Proteome-wide model for human disease genetics.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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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.
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.
Who cites it
19 citing papers in PubMed.
- Prediction of human missense variant effects from functional evidence.Nature genetics · 2026Article
- Molecular mechanisms of sudden unexplained death and recent updates on molecular autopsy strategies for forensic investigation.International journal of legal medicine · 2026Review
- Machine Learning, Large Language Models, and Multimodal AI for Diagnosing Pediatric Rare Diseases: Scoping Review.Journal of medical Internet research · 2026Article
- Review
- Prime Editing-Based Functional Characterization Supports a Likely Pathogenic Interpretation ofGenes · 2026Article
- Artificial intelligence for pediatric rare disease diagnosis: a multimethod study integrating published evidence and clinician interviews.BMC medical informatics and decision making · 2026Article
- Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.medRxiv : the preprint server for health sciences · 2026Article
- DeNovoSeer:a deep learning framework for pathogenicity prediction of De novo mutations.Briefings in bioinformatics · 2026Article
- Inference of elevated mutation rates and variant effects using 700k exomes.bioRxiv : the preprint server for biology · 2026Article
- Gene- and domain-aware calibration increases the clinical utility of variant effect predictors.Research square · 2026Article
- From variants to answers: The evolution of genetic counseling in IEI.Journal of human immunity · 2026Review
- Rare coding variant architecture and gene discovery from 130,000 sequenced cases of atrial fibrillation.Research square · 2026Article
- Integrating 730,947 exome sequences with clinical literature improves gene discovery.medRxiv : the preprint server for health sciences · 2026Article
- Massively parallel quantification of mutational impact on IAPP amyloid formation.Nature communications · 2026Article
- Long-read sequencing of families reveals increased germline and postzygotic mutation rates in repetitive DNA.Nature communications · 2026Article
- Disease- and gene-specific deep learning for pathogenicity prediction of rare missense variants in cancer predisposition genes.BioData mining · 2026Article
- Article
- Machine learning reveals hidden dimensions of functional similarity in proteins.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Expanded Carrier Screening: Current Evidence and Future Directions in the Era of Population Genomics.Genes · 2026Review
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10 authors.
Funding
Abstract
Missense variants remain a challenge in genetic interpretation owing to their subtle and context-dependent effects. Although current prediction models perform well in known disease genes, their scores are not calibrated across the proteome, limiting generalizability. To address this knowledge gap, we developed popEVE, a deep generative model combining evolutionary and human population data to estimate variant deleteriousness on a proteome-wide scale. popEVE achieves state-of-the-art performance without overestimating the burden of deleterious variants and identifies variants in 442 genes in a severe developmental disorder cohort, including 123 novel candidates. These genes are functionally similar to known disease genes, and their variants often localize to critical regions. Remarkably, popEVE can prioritize likely causal variants using only child exomes, enabling diagnosis even without parental sequencing. This work provides a generalizable framework for rare disease variant interpretation, especially in singleton cases, and demonstrates the utility of calibrated, evolution-informed scoring models for clinical genomics.
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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.