LDLR Variant Functional Scores and ACMG Evidence from Prime Editing Screening

5,184 LDLR coding variants were functionally assessed using an activity-normalized prime editing screening pipeline to measure their impact on LDL-cholesterol uptake. The dataset, created by Christopher Cassa and last updated in April 2026, contains functional scores, ACMG evidence scores, plasmid lists, and primer sequences as supplementary material for the linked preprint. The scores show concordance with LDL-C levels measured in UK Biobank participants and are calibrated to align with ACMG/AMP variant interpretation guidelines.

Use Cases

• Reclassifying rare LDLR variants of uncertain significance based on experimentally derived functional scores.
• Prioritizing variants for expert clinical review based on integrated ACMG evidence scores.
• Analyzing LDLR structure-function relationships, such as apolipoprotein binding interactions, based on broad variant coverage.
• Comparing variant effect measurements from prime editing with other screening methods like base editing or cDNA screens.
• Training or benchmarking computational models for predicting variant pathogenicity using functional evidence.

Strengths

• Covers 5,184 LDLR coding variants, providing broad genetic coverage.
• Functional scores are activity-normalized to account for variable editing efficiency, likely improving data reliability.
• Includes calibration to ACMG/AMP variant interpretation guidelines, enhancing clinical relevance.
• Data shows concordance with clinically observed LDL-C levels from UK Biobank participants.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific analytical tasks.

Provenance

Source

figshare

Collection Method

Activity-normalized prime editing screening pipeline paired with a genotypic outcome reporter.

Time Range

Experimental data collection timeframe is not specified.

Freshness

Last updated 2026-04-18 20:21:12; freshness should be verified.

Geography

Spatial coverage is not specified; data is likely from laboratory experiments.