Equity in genome sequencing for rare disease diagnosis: a cross-sectional analysis of data from the UK 100,000 Genomes Project
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Background
Genome sequencing has improved rare disease diagnosis and is now part of routine clinical care in the National Health Service in England. Automated prioritisation pipelines narrow millions of variants per patient to a small subset for clinical review, a process that relies on allele frequency resources that do not fully represent human genetic diversity. We assessed ancestry-related differences in variant prioritisation and diagnostic outcomes in patients from the UK 100,000 Genomes Project.
Methods
We analysed 29,405 rare disease probands with genome sequencing and linked clinical outcomes data. We used multivariable regression to assess ancestry-related differences in prioritised variant counts and positive predictive value (PPV), as well as diagnostic yield and frequencies of recorded variants of uncertain significance (VUS). We also evaluated the use of ancestry-stratified allele frequency filters derived from an independent, diverse UK cohort (n = 31,814).
Results
Compared with the European group, the East African group had nearly three times more variants prioritised for clinical review (IRR 2·77, 95% CI 2·33–3·29). Other non-European groups also had significantly higher counts. Diagnostic yield was similar across ancestry groups after adjustment. PPV was lower in East African (OR 0·32, 0·22–0·46), West African (0·47, 0·39–0·57), South Asian (0·65, 0·58–0·73), and Middle Eastern (0·68, 0·54–0·86) groups. VUS frequency was highest in the East African group (OR 1·90, 1·17–3·10) and elevated in West African (1·35, 1·05–1·77) and South Asian (1·33, 1·15–1·59) groups. Applying ancestry-stratified allele-frequency filters removed 1·9% of prioritised variants overall—22·8% in the East African group—without loss of diagnostic sensitivity, including 29·5% of recorded VUS in this group.
Interpretation
Differences in PPV and VUS frequencies partly reflect limitations of current allele-frequency resources which use broad population groupings that mask within-group diversity. Increased representation of diverse ancestries in reference databases and better estimation of ancestry-appropriate allele frequencies will help reduce inefficiencies and improve equity in variant prioritisation for rare disease diagnosis.
