Pervasive ancestry bias in variant effect predictors
Pathak, A. K.; Bora, N.; Badonyi, M.; Livesey, B. J.; SG10K_Health Consortium, ; Ngeow, J.; Marsh, J. A.
Show abstract
Variant effect predictors (VEPs) - computational tools that assess the potential impact of genetic variants - have become increasingly vital for clinical variant interpretation. Currently, most VEPs used in variant prioritisation have been trained on datasets of clinically curated or population-derived variants. These datasets, however, disproportionately represent individuals of European descent. We hypothesised that this bias may lead to unequal VEP performance across different populations. To test this, we evaluated the scoring patterns of 52 VEPs for missense variants across 14 ancestry groups. We observe striking disparities: some VEPs predict a markedly higher proportion of damaging variants in underrepresented populations, such as those of Malay descent, compared to individuals of European ancestry. In contrast, VEPs that do not rely on clinical or population data predict more consistent pathogenicity burdens across ancestry groups. Moreover, we could closely link these discrepancies across methods to biases in training data. Our findings underscore the urgent need to adopt tools that minimise ancestry bias to ensure fairer and more accurate variant effect prediction and genetic diagnoses for all populations.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of diverse feature set 96%
- A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project. 96%
- MetaRNN: Differentiating Rare Pathogenic and Rare Benign Missense SNVs and InDels Using Deep Learning 96%
Similar papers in this journal
- Inclusion of Variants Discovered from Diverse Populations Improves Polygenic Risk Score Transferability 95%
- Long-read genome sequencing for the diagnosis of neurodevelopmental disorders 95%
- Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations 94%
Similar papers in this journal
Similar papers in this journal
- The landscape of autosomal-recessive pathogenic variants in European populations reveals phenotype-specific effects 96%
- Identification of actionable genetic variants in 4,198 Scottish volunteers from the Viking Genes research cohort and implementation of return of results 96%
- Extracting and calibrating evidence of variant pathogenicity from population biobank data 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.