Phenotypes of ultra-rare variant carriers benchmark variant effect scores
Shubhankar LondheiD, Eva HoltkampiD, George TsitsiridisiD, Anna StarovoitiD, Pedro Tomaz da SilvaiD, Johannes HingerliD, Hilary K. FinucaneiD, Julien GagneuriD
Abstract
Human genetics needs benchmarks for evaluating variant scores against observed phenotypic consequences. We therefore present UKBBGym, which evaluates coding and non-coding scores against plasma protein abundance and quantitative traits observed in carriers of ultra-rare variants in the UK Biobank. This design avoids ascertainment biases of clinical labels, potential physiological mismatch of experimental assays, and confounding pertaining to common-variant associations. UKBBGym recapitulates relative performance on pathogenicity prediction while enabling comparison across variant classes and molecular mechanisms. This shows that scores designed for coding and splicing variants correlate more strongly with protein abundance and quantitative traits than scores modelling transcriptional regulation. Moreover, experimental assays do not consistently outperform computational scores for predicting missense effects. Comparing captured to detectable variance indicates scope for improvement, particularly for indels and loss-of-function variants. Finally, for coding variants, UKBBGym can be reproduced from public summary statistics, providing an accessible population-phenotype benchmark complementary to clinical labels and experimental assays.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Surveying the contribution of rare variants to the genetic architecture of human disease through exome sequencing of 177,882 UK Biobank participants
Quanli Wang, Ryan S. Dhindsa, … AstraZeneca Genomics Initiative·bioRxiv·Dec 13, 2020
- Empowering rare variant burden-based gene-trait association studies via optimized computational predictor choice
Daniel R. Tabet, Da Kuang, … Frederick P. Roth·Genome biologyPeer-reviewed·Jul 1, 2024
- Gene identity, not variant effect, dominates ClinVar benchmarks of missense pathogenicity predictors
Saad Harrizi, Imane Nait Irahal, … Damien Arnoult·bioRxiv·Aug 24, 2026
- Assessing the pathogenicity, penetrance and expressivity of putative disease-causing variants in a population setting
Caroline Fiona Wright, Ben West, … Michael N. Weedon·The American Journal of Human GeneticsPeer-reviewed·Jan 18, 2019
- Mechanistic 5'UTR Variant Scoring Expands Rare Variant Discovery in the UK Biobank
Matthieu Chaldebas, Khoren Ponsin, … Aurélie Cobat·medRxiv·Sep 11, 2026
- Gene-based calibration of high-throughput functional assays for clinical variant classification
Daniel Zeiberg, Ross Stewart, … Predrag Radivojac A·bioRxiv·Apr 29, 2025